[{"data":1,"prerenderedAt":8018},["ShallowReactive",2],{"navigation_docs":3,"learnalog_locale_counterpart__en_quant_01-research-data":1782,"-zh-quant-01-research-data":1783,"-zh-quant-01-research-data-surround":8013},[4,1038],{"title":5,"path":6,"stem":7,"children":8},"En","\u002Fen","en",[9,12,58,250,406,477,534,715,798,824,943],{"title":10,"path":6,"stem":11},"","en\u002Findex",{"title":13,"path":14,"stem":15,"children":16},"Research Skills and Academic Writing","\u002Fen\u002Facademic-writing","en\u002Facademic-writing\u002Findex",[17,18,22,26,30,34,38,42,46,50,54],{"title":13,"path":14,"stem":15},{"title":19,"path":20,"stem":21},"1. Research Questions, Scope, and Feasibility","\u002Fen\u002Facademic-writing\u002F01-research-questions-and-planning","en\u002Facademic-writing\u002F01-research-questions-and-planning",{"title":23,"path":24,"stem":25},"2. Search, Evaluate, and Read Evidence","\u002Fen\u002Facademic-writing\u002F02-reading-and-literature-matrix","en\u002Facademic-writing\u002F02-reading-and-literature-matrix",{"title":27,"path":28,"stem":29},"3. From Sources to Synthesis and Argument","\u002Fen\u002Facademic-writing\u002F03-arguments-outlines-and-paragraphs","en\u002Facademic-writing\u002F03-arguments-outlines-and-paragraphs",{"title":31,"path":32,"stem":33},"4. Literature Review and a Defensible Gap","\u002Fen\u002Facademic-writing\u002F04-writing-the-literature-review","en\u002Facademic-writing\u002F04-writing-the-literature-review",{"title":35,"path":36,"stem":37},"5. Research Design, Evidence, and Core Sections","\u002Fen\u002Facademic-writing\u002F05-core-sections-and-evidence","en\u002Facademic-writing\u002F05-core-sections-and-evidence",{"title":39,"path":40,"stem":41},"6. Citation, Paraphrasing, Integrity, and AI","\u002Fen\u002Facademic-writing\u002F06-citation-paraphrasing-and-integrity","en\u002Facademic-writing\u002F06-citation-paraphrasing-and-integrity",{"title":43,"path":44,"stem":45},"7. Revision, Review, and Submission","\u002Fen\u002Facademic-writing\u002F07-revision-style-and-submission","en\u002Facademic-writing\u002F07-revision-style-and-submission",{"title":47,"path":48,"stem":49},"8. Research Workbook","\u002Fen\u002Facademic-writing\u002F08-literature-review-checklist-and-template","en\u002Facademic-writing\u002F08-literature-review-checklist-and-template",{"title":51,"path":52,"stem":53},"9. Research Workflow and Tools","\u002Fen\u002Facademic-writing\u002F09-tools-for-academic-writing-and-literature-management","en\u002Facademic-writing\u002F09-tools-for-academic-writing-and-literature-management",{"title":55,"path":56,"stem":57},"10. Worked Project — From Question to Defensible Conclusion","\u002Fen\u002Facademic-writing\u002F10-worked-example-from-block-structure-to-question-chain","en\u002Facademic-writing\u002F10-worked-example-from-block-structure-to-question-chain",{"title":59,"path":60,"stem":61,"children":62,"page":249},"Accounting","\u002Fen\u002Faccounting","en\u002Faccounting",[63,69,87,93,193],{"title":64,"path":65,"stem":66,"children":67},"Accounting — From Evidence to Decisions","\u002Fen\u002Faccounting\u002F00-index","en\u002Faccounting\u002F00-index",[68],{"title":64,"path":65,"stem":66},{"title":70,"path":71,"stem":72,"children":73},"Accounting Appendix","\u002Fen\u002Faccounting\u002Fappendix","en\u002Faccounting\u002Fappendix\u002Findex",[74,75,79,83],{"title":70,"path":71,"stem":72},{"title":76,"path":77,"stem":78},"Worked Examples and Error Diagnosis","\u002Fen\u002Faccounting\u002Fappendix\u002F24-examples-pitfalls","en\u002Faccounting\u002Fappendix\u002F24-examples-pitfalls",{"title":80,"path":81,"stem":82},"Accounting Glossary","\u002Fen\u002Faccounting\u002Fappendix\u002F26-glossary","en\u002Faccounting\u002Fappendix\u002F26-glossary",{"title":84,"path":85,"stem":86},"Reading and Evidence Map","\u002Fen\u002Faccounting\u002Fappendix\u002F27-reading-map","en\u002Faccounting\u002Fappendix\u002F27-reading-map",{"title":88,"path":89,"stem":90,"children":91},"Northstar Record-to-Decision Capstone","\u002Fen\u002Faccounting\u002Fcapstone","en\u002Faccounting\u002Fcapstone\u002Findex",[92],{"title":88,"path":89,"stem":90},{"title":94,"path":95,"stem":96,"children":97},"Financial Accounting","\u002Fen\u002Faccounting\u002Ffinancial-accounting","en\u002Faccounting\u002Ffinancial-accounting\u002Findex",[98,99,117,131,165,179],{"title":94,"path":95,"stem":96},{"title":100,"path":101,"stem":102,"children":103},"1. Foundations","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations","en\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002Findex",[104,105,109,113],{"title":100,"path":101,"stem":102},{"title":106,"path":107,"stem":108},"Objectives and Qualitative Characteristics","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F01-objectives-qualitative-characteristics","en\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F01-objectives-qualitative-characteristics",{"title":110,"path":111,"stem":112},"Equation and Elements","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F02-equation-elements","en\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F02-equation-elements",{"title":114,"path":115,"stem":116},"Accrual Basis, Estimates and Periods","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F03-accounting-bases-principles","en\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F03-accounting-bases-principles",{"title":118,"path":119,"stem":120,"children":121},"2. Recording Transactions","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions","en\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002Findex",[122,123,127],{"title":118,"path":119,"stem":120},{"title":124,"path":125,"stem":126},"Double-Entry and Debit\u002FCredit","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002F04-double-entry-dr-cr","en\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002F04-double-entry-dr-cr",{"title":128,"path":129,"stem":130},"Accounting Cycle","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002F05-accounting-cycle","en\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002F05-accounting-cycle",{"title":132,"path":133,"stem":134,"children":135},"3. Measurement and Adjustments","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002Findex",[136,137,141,145,149,153,157,161],{"title":132,"path":133,"stem":134},{"title":138,"path":139,"stem":140},"Revenue Recognition","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F07-revenue-recognition","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F07-revenue-recognition",{"title":142,"path":143,"stem":144},"Inventory","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F08-inventory","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F08-inventory",{"title":146,"path":147,"stem":148},"Receivables and Expected Credit Losses","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F09-receivables","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F09-receivables",{"title":150,"path":151,"stem":152},"Property, Plant and Equipment","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F10-ppe","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F10-ppe",{"title":154,"path":155,"stem":156},"Intangible Assets","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F11-intangibles","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F11-intangibles",{"title":158,"path":159,"stem":160},"Leases","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F12-leases","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F12-leases",{"title":162,"path":163,"stem":164},"Current and Deferred Income Tax","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F13-income-tax","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F13-income-tax",{"title":166,"path":167,"stem":168,"children":169},"4. Reporting and Cash","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash","en\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002Findex",[170,171,175],{"title":166,"path":167,"stem":168},{"title":172,"path":173,"stem":174},"Linked Financial Statements","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002F06-financial-statements","en\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002F06-financial-statements",{"title":176,"path":177,"stem":178},"Cash, Reconciliation and Internal Control","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002F14-cash-control","en\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002F14-cash-control",{"title":180,"path":181,"stem":182,"children":183},"5. Analysis and Comparison","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison","en\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002Findex",[184,185,189],{"title":180,"path":181,"stem":182},{"title":186,"path":187,"stem":188},"Ratio Analysis","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F15-ratio-analysis","en\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F15-ratio-analysis",{"title":190,"path":191,"stem":192},"IFRS versus US GAAP","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F25-ifrs-gaap","en\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F25-ifrs-gaap",{"title":194,"path":195,"stem":196,"children":197},"Management Accounting","\u002Fen\u002Faccounting\u002Fmanagement-accounting","en\u002Faccounting\u002Fmanagement-accounting\u002Findex",[198,199,217,235],{"title":194,"path":195,"stem":196},{"title":200,"path":201,"stem":202,"children":203},"1. Cost Foundations","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations","en\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002Findex",[204,205,209,213],{"title":200,"path":201,"stem":202},{"title":206,"path":207,"stem":208},"Cost Concepts and Behaviour","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F16-cost-concepts","en\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F16-cost-concepts",{"title":210,"path":211,"stem":212},"Costing Systems","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F17-costing-systems","en\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F17-costing-systems",{"title":214,"path":215,"stem":216},"Variable and Absorption Costing","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F19-variable-vs-absorption","en\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F19-variable-vs-absorption",{"title":218,"path":219,"stem":220,"children":221},"2. Planning and Control","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control","en\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002Findex",[222,223,227,231],{"title":218,"path":219,"stem":220},{"title":224,"path":225,"stem":226},"Cost–Volume–Profit Analysis","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F18-cvp-analysis","en\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F18-cvp-analysis",{"title":228,"path":229,"stem":230},"Budgeting and Variance Analysis","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F20-budgeting-variances","en\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F20-budgeting-variances",{"title":232,"path":233,"stem":234},"Performance Measurement","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F21-performance-measurement","en\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F21-performance-measurement",{"title":236,"path":237,"stem":238,"children":239},"3. Decisions and Investment","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment","en\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002Findex",[240,241,245],{"title":236,"path":237,"stem":238},{"title":242,"path":243,"stem":244},"Short-Term Decisions","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002F22-short-term-decisions","en\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002F22-short-term-decisions",{"title":246,"path":247,"stem":248},"Capital Budgeting","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002F23-capital-budgeting","en\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002F23-capital-budgeting",false,{"title":251,"path":252,"stem":253,"children":254,"page":249},"Business Analytics","\u002Fen\u002Fbusiness-analytics","en\u002Fbusiness-analytics",[255,261,279,305,335,365,383,400],{"title":256,"path":257,"stem":258,"children":259},"Business Analytics — From Data to Defensible Action","\u002Fen\u002Fbusiness-analytics\u002F00-index","en\u002Fbusiness-analytics\u002F00-index",[260],{"title":256,"path":257,"stem":258},{"title":262,"path":263,"stem":264,"children":265},"0. Decision and Data Foundations","\u002Fen\u002Fbusiness-analytics\u002F00-intro","en\u002Fbusiness-analytics\u002F00-intro\u002Findex",[266,267,271,275],{"title":262,"path":263,"stem":264},{"title":268,"path":269,"stem":270},"Decision Framing","\u002Fen\u002Fbusiness-analytics\u002F00-intro\u002F01-decision-framing","en\u002Fbusiness-analytics\u002F00-intro\u002F01-decision-framing",{"title":272,"path":273,"stem":274},"Data Contracts","\u002Fen\u002Fbusiness-analytics\u002F00-intro\u002F02-data-contracts","en\u002Fbusiness-analytics\u002F00-intro\u002F02-data-contracts",{"title":276,"path":277,"stem":278},"Reproducible Analytics Workflow","\u002Fen\u002Fbusiness-analytics\u002F00-intro\u002F03-reproducible-workflow","en\u002Fbusiness-analytics\u002F00-intro\u002F03-reproducible-workflow",{"title":280,"path":281,"stem":282,"children":283},"1. Descriptive Analytics","\u002Fen\u002Fbusiness-analytics\u002F01-descriptive","en\u002Fbusiness-analytics\u002F01-descriptive\u002Findex",[284,285,289,293,297,301],{"title":280,"path":281,"stem":282},{"title":286,"path":287,"stem":288},"Distributions and Exploratory Data Analysis","\u002Fen\u002Fbusiness-analytics\u002F01-descriptive\u002F04-distributions-eda","en\u002Fbusiness-analytics\u002F01-descriptive\u002F04-distributions-eda",{"title":290,"path":291,"stem":292},"KPIs and Denominators","\u002Fen\u002Fbusiness-analytics\u002F01-descriptive\u002F05-kpis-denominators","en\u002Fbusiness-analytics\u002F01-descriptive\u002F05-kpis-denominators",{"title":294,"path":295,"stem":296},"Segments, Cohorts and Funnels","\u002Fen\u002Fbusiness-analytics\u002F01-descriptive\u002F06-segmentation-cohorts-funnels","en\u002Fbusiness-analytics\u002F01-descriptive\u002F06-segmentation-cohorts-funnels",{"title":298,"path":299,"stem":300},"Visual Evidence and Data Stories","\u002Fen\u002Fbusiness-analytics\u002F01-descriptive\u002F07-visualisation-story","en\u002Fbusiness-analytics\u002F01-descriptive\u002F07-visualisation-story",{"title":302,"path":303,"stem":304},"Experiments and Causal Boundaries","\u002Fen\u002Fbusiness-analytics\u002F01-descriptive\u002F08-experiments-causal-boundary","en\u002Fbusiness-analytics\u002F01-descriptive\u002F08-experiments-causal-boundary",{"title":306,"path":307,"stem":308,"children":309},"2. Predictive Analytics","\u002Fen\u002Fbusiness-analytics\u002F02-predictive","en\u002Fbusiness-analytics\u002F02-predictive\u002Findex",[310,311,315,319,323,327,331],{"title":306,"path":307,"stem":308},{"title":312,"path":313,"stem":314},"Validation, Baselines and Leakage","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F09-validation-leakage","en\u002Fbusiness-analytics\u002F02-predictive\u002F09-validation-leakage",{"title":316,"path":317,"stem":318},"Regression and Forecasting","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F10-regression-forecasting","en\u002Fbusiness-analytics\u002F02-predictive\u002F10-regression-forecasting",{"title":320,"path":321,"stem":322},"Classification and Calibration","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F11-classification-calibration","en\u002Fbusiness-analytics\u002F02-predictive\u002F11-classification-calibration",{"title":324,"path":325,"stem":326},"Trees and Ensembles","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F12-trees-ensembles","en\u002Fbusiness-analytics\u002F02-predictive\u002F12-trees-ensembles",{"title":328,"path":329,"stem":330},"Decision Metrics and Thresholds","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F13-decision-metrics-thresholds","en\u002Fbusiness-analytics\u002F02-predictive\u002F13-decision-metrics-thresholds",{"title":332,"path":333,"stem":334},"Explainability, Monitoring and Drift","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F14-explainability-drift","en\u002Fbusiness-analytics\u002F02-predictive\u002F14-explainability-drift",{"title":336,"path":337,"stem":338,"children":339},"3. Prescriptive Analytics","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive","en\u002Fbusiness-analytics\u002F03-prescriptive\u002Findex",[340,341,345,349,353,357,361],{"title":336,"path":337,"stem":338},{"title":342,"path":343,"stem":344},"Decision-Making under Uncertainty","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F15-decision-uncertainty","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F15-decision-uncertainty",{"title":346,"path":347,"stem":348},"Linear Optimisation","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F16-linear-optimization","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F16-linear-optimization",{"title":350,"path":351,"stem":352},"Inventory and Allocation","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F17-inventory-allocation","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F17-inventory-allocation",{"title":354,"path":355,"stem":356},"Queueing and Simulation","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F18-queueing-simulation","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F18-queueing-simulation",{"title":358,"path":359,"stem":360},"Pricing and Revenue Management","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F19-pricing-experimentation","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F19-pricing-experimentation",{"title":362,"path":363,"stem":364},"Causal Targeting and Policy Learning","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F20-causal-targeting","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F20-causal-targeting",{"title":366,"path":367,"stem":368,"children":369},"4. Deployment and Governance","\u002Fen\u002Fbusiness-analytics\u002F04-deployment","en\u002Fbusiness-analytics\u002F04-deployment\u002Findex",[370,371,375,379],{"title":366,"path":367,"stem":368},{"title":372,"path":373,"stem":374},"Data Products and Monitoring","\u002Fen\u002Fbusiness-analytics\u002F04-deployment\u002F21-data-products-monitoring","en\u002Fbusiness-analytics\u002F04-deployment\u002F21-data-products-monitoring",{"title":376,"path":377,"stem":378},"Governance, Fairness and Privacy","\u002Fen\u002Fbusiness-analytics\u002F04-deployment\u002F22-governance-fairness-privacy","en\u002Fbusiness-analytics\u002F04-deployment\u002F22-governance-fairness-privacy",{"title":380,"path":381,"stem":382},"Adoption and Business Value","\u002Fen\u002Fbusiness-analytics\u002F04-deployment\u002F23-adoption-value","en\u002Fbusiness-analytics\u002F04-deployment\u002F23-adoption-value",{"title":384,"path":385,"stem":386,"children":387},"Appendix and Revision Tools","\u002Fen\u002Fbusiness-analytics\u002Fappendix","en\u002Fbusiness-analytics\u002Fappendix\u002Findex",[388,389,393,397],{"title":384,"path":385,"stem":386},{"title":390,"path":391,"stem":392},"Formula and Decision Map","\u002Fen\u002Fbusiness-analytics\u002Fappendix\u002F24-formula-map","en\u002Fbusiness-analytics\u002Fappendix\u002F24-formula-map",{"title":394,"path":395,"stem":396},"Worked Examples and Pitfalls","\u002Fen\u002Fbusiness-analytics\u002Fappendix\u002F25-worked-examples-pitfalls","en\u002Fbusiness-analytics\u002Fappendix\u002F25-worked-examples-pitfalls",{"title":84,"path":398,"stem":399},"\u002Fen\u002Fbusiness-analytics\u002Fappendix\u002F26-reading-map","en\u002Fbusiness-analytics\u002Fappendix\u002F26-reading-map",{"title":401,"path":402,"stem":403,"children":404},"Capstone — The Evening Delivery Promise","\u002Fen\u002Fbusiness-analytics\u002Fcapstone","en\u002Fbusiness-analytics\u002Fcapstone\u002Findex",[405],{"title":401,"path":402,"stem":403},{"title":407,"path":408,"stem":409,"children":410,"page":249},"Financial Economic Time Series","\u002Fen\u002Ffinancial-economic-time-series","en\u002Ffinancial-economic-time-series",[411,417,423,429,435,441,447,453,459,465,471],{"title":412,"path":413,"stem":414,"children":415},"Financial and Economic Time Series — Course Guide","\u002Fen\u002Ffinancial-economic-time-series\u002F00-intro","en\u002Ffinancial-economic-time-series\u002F00-intro\u002Findex",[416],{"title":412,"path":413,"stem":414},{"title":418,"path":419,"stem":420,"children":421},"Three Versions of Time Series","\u002Fen\u002Ffinancial-economic-time-series\u002F01-bridge","en\u002Ffinancial-economic-time-series\u002F01-bridge\u002Findex",[422],{"title":418,"path":419,"stem":420},{"title":424,"path":425,"stem":426,"children":427},"Data, Clocks, and Transformations","\u002Fen\u002Ffinancial-economic-time-series\u002F02-data-transformations","en\u002Ffinancial-economic-time-series\u002F02-data-transformations\u002Findex",[428],{"title":424,"path":425,"stem":426},{"title":430,"path":431,"stem":432,"children":433},"Predictive Regressions and Persistent Predictors","\u002Fen\u002Ffinancial-economic-time-series\u002F03-predictive-regressions","en\u002Ffinancial-economic-time-series\u002F03-predictive-regressions\u002Findex",[434],{"title":430,"path":431,"stem":432},{"title":436,"path":437,"stem":438,"children":439},"Volatility, Tails, and Financial Risk","\u002Fen\u002Ffinancial-economic-time-series\u002F04-volatility-risk","en\u002Ffinancial-economic-time-series\u002F04-volatility-risk\u002Findex",[440],{"title":436,"path":437,"stem":438},{"title":442,"path":443,"stem":444,"children":445},"Unit Roots, Cointegration, and Error Correction","\u002Fen\u002Ffinancial-economic-time-series\u002F05-unit-roots-cointegration","en\u002Ffinancial-economic-time-series\u002F05-unit-roots-cointegration\u002Findex",[446],{"title":442,"path":443,"stem":444},{"title":448,"path":449,"stem":450,"children":451},"VAR, Structural Identification, and Local Projections","\u002Fen\u002Ffinancial-economic-time-series\u002F06-var-identification","en\u002Ffinancial-economic-time-series\u002F06-var-identification\u002Findex",[452],{"title":448,"path":449,"stem":450},{"title":454,"path":455,"stem":456,"children":457},"State Space, Mixed Frequency, and Nowcasting","\u002Fen\u002Ffinancial-economic-time-series\u002F07-state-space-nowcasting","en\u002Ffinancial-economic-time-series\u002F07-state-space-nowcasting\u002Findex",[458],{"title":454,"path":455,"stem":456},{"title":460,"path":461,"stem":462,"children":463},"Forecast Evaluation for Decisions","\u002Fen\u002Ffinancial-economic-time-series\u002F08-forecast-evaluation","en\u002Ffinancial-economic-time-series\u002F08-forecast-evaluation\u002Findex",[464],{"title":460,"path":461,"stem":462},{"title":466,"path":467,"stem":468,"children":469},"Integrated R Laboratory","\u002Fen\u002Ffinancial-economic-time-series\u002F09-r-laboratory","en\u002Ffinancial-economic-time-series\u002F09-r-laboratory\u002Findex",[470],{"title":466,"path":467,"stem":468},{"title":472,"path":473,"stem":474,"children":475},"Capstones, Data, and Reading Ladder","\u002Fen\u002Ffinancial-economic-time-series\u002F10-capstone-readings","en\u002Ffinancial-economic-time-series\u002F10-capstone-readings\u002Findex",[476],{"title":472,"path":473,"stem":474},{"title":478,"path":479,"stem":480,"children":481,"page":249},"Intro To Economics","\u002Fen\u002Fintro-to-economics","en\u002Fintro-to-economics",[482,486,490,494,498,502,506,510,514,518,522,526,530],{"title":483,"path":484,"stem":485},"Introduction to Economics — Decisions, Markets, and the Macroeconomy","\u002Fen\u002Fintro-to-economics\u002F00-intro","en\u002Fintro-to-economics\u002F00-intro",{"title":487,"path":488,"stem":489},"Chapter 1 — Choice, Opportunity Cost, and Trade","\u002Fen\u002Fintro-to-economics\u002F01-foundations","en\u002Fintro-to-economics\u002F01-foundations",{"title":491,"path":492,"stem":493},"Chapter 2 — Demand, Supply, Equilibrium, and Welfare","\u002Fen\u002Fintro-to-economics\u002F02-demand-and-supply","en\u002Fintro-to-economics\u002F02-demand-and-supply",{"title":495,"path":496,"stem":497},"Chapter 3 — Elasticity, Revenue, and Tax Incidence","\u002Fen\u002Fintro-to-economics\u002F03-elasticity","en\u002Fintro-to-economics\u002F03-elasticity",{"title":499,"path":500,"stem":501},"Chapter 4 — Firms, Market Power, and Market Failure","\u002Fen\u002Fintro-to-economics\u002F04-market-structures","en\u002Fintro-to-economics\u002F04-market-structures",{"title":503,"path":504,"stem":505},"Chapter 5 — GDP, Income, Wealth, and Welfare","\u002Fen\u002Fintro-to-economics\u002F05-gdp-and-wealth","en\u002Fintro-to-economics\u002F05-gdp-and-wealth",{"title":507,"path":508,"stem":509},"Chapter 6 — Inflation, Purchasing Power, and Labour Markets","\u002Fen\u002Fintro-to-economics\u002F06-inflation-and-unemployment","en\u002Fintro-to-economics\u002F06-inflation-and-unemployment",{"title":511,"path":512,"stem":513},"Chapter 7 — Productivity, Technology, and Economic Growth","\u002Fen\u002Fintro-to-economics\u002F07-economic-growth","en\u002Fintro-to-economics\u002F07-economic-growth",{"title":515,"path":516,"stem":517},"Chapter 8 — Money, Credit, and Banking","\u002Fen\u002Fintro-to-economics\u002F08-money-and-banking","en\u002Fintro-to-economics\u002F08-money-and-banking",{"title":519,"path":520,"stem":521},"Chapter 9 — Business Cycles, AD–AS, and Monetary Policy","\u002Fen\u002Fintro-to-economics\u002F09-monetary-policy-and-ad-as","en\u002Fintro-to-economics\u002F09-monetary-policy-and-ad-as",{"title":523,"path":524,"stem":525},"Chapter 10 — Fiscal Policy, Distribution, and Public Debt","\u002Fen\u002Fintro-to-economics\u002F10-fiscal-policy","en\u002Fintro-to-economics\u002F10-fiscal-policy",{"title":527,"path":528,"stem":529},"Chapter 11 — Trade, Capital Flows, and Exchange Rates","\u002Fen\u002Fintro-to-economics\u002F11-open-economy-and-exchange-rates","en\u002Fintro-to-economics\u002F11-open-economy-and-exchange-rates",{"title":531,"path":532,"stem":533},"Chapter 12 — Integrated Economic Analysis Studio","\u002Fen\u002Fintro-to-economics\u002F12-review-and-case-studies","en\u002Fintro-to-economics\u002F12-review-and-case-studies",{"title":535,"path":536,"stem":537,"children":538,"page":249},"Microeconometrics","\u002Fen\u002Fmicroeconometrics","en\u002Fmicroeconometrics",[539,557,563,581,603,629,651,673,691,709],{"title":540,"path":541,"stem":542,"children":543},"0. Causal Questions and Designs","\u002Fen\u002Fmicroeconometrics\u002F00-foundations","en\u002Fmicroeconometrics\u002F00-foundations\u002Findex",[544,545,549,553],{"title":540,"path":541,"stem":542},{"title":546,"path":547,"stem":548},"Causal Questions and Estimands","\u002Fen\u002Fmicroeconometrics\u002F00-foundations\u002F01-causal-question-estimands","en\u002Fmicroeconometrics\u002F00-foundations\u002F01-causal-question-estimands",{"title":550,"path":551,"stem":552},"Potential Outcomes and Experiments","\u002Fen\u002Fmicroeconometrics\u002F00-foundations\u002F02-potential-outcomes-experiments","en\u002Fmicroeconometrics\u002F00-foundations\u002F02-potential-outcomes-experiments",{"title":554,"path":555,"stem":556},"Causal Diagrams and Controls","\u002Fen\u002Fmicroeconometrics\u002F00-foundations\u002F03-dags-controls","en\u002Fmicroeconometrics\u002F00-foundations\u002F03-dags-controls",{"title":558,"path":559,"stem":560,"children":561},"Microeconometrics — Designing Credible Counterfactuals","\u002Fen\u002Fmicroeconometrics\u002F00-index","en\u002Fmicroeconometrics\u002F00-index",[562],{"title":558,"path":559,"stem":560},{"title":564,"path":565,"stem":566,"children":567},"1. Regression and Inference","\u002Fen\u002Fmicroeconometrics\u002F01-regression","en\u002Fmicroeconometrics\u002F01-regression\u002Findex",[568,569,573,577],{"title":564,"path":565,"stem":566},{"title":570,"path":571,"stem":572},"OLS as a Projection","\u002Fen\u002Fmicroeconometrics\u002F01-regression\u002F04-ols-projection","en\u002Fmicroeconometrics\u002F01-regression\u002F04-ols-projection",{"title":574,"path":575,"stem":576},"FWL, Selection and Controls","\u002Fen\u002Fmicroeconometrics\u002F01-regression\u002F05-fwl-selection-controls","en\u002Fmicroeconometrics\u002F01-regression\u002F05-fwl-selection-controls",{"title":578,"path":579,"stem":580},"Inference and Clustering","\u002Fen\u002Fmicroeconometrics\u002F01-regression\u002F06-inference-clustering","en\u002Fmicroeconometrics\u002F01-regression\u002F06-inference-clustering",{"title":582,"path":583,"stem":584,"children":585},"2. Instruments and Panel Data","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel","en\u002Fmicroeconometrics\u002F02-iv-panel\u002Findex",[586,587,591,595,599],{"title":582,"path":583,"stem":584},{"title":588,"path":589,"stem":590},"Instrumental Variables","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel\u002F07-iv-identification","en\u002Fmicroeconometrics\u002F02-iv-panel\u002F07-iv-identification",{"title":592,"path":593,"stem":594},"Weak Instruments and LATE","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel\u002F08-weak-iv-late","en\u002Fmicroeconometrics\u002F02-iv-panel\u002F08-weak-iv-late",{"title":596,"path":597,"stem":598},"Panel Fixed Effects","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel\u002F09-panel-fixed-effects","en\u002Fmicroeconometrics\u002F02-iv-panel\u002F09-panel-fixed-effects",{"title":600,"path":601,"stem":602},"Dynamic Panels and Limits","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel\u002F10-dynamic-panel","en\u002Fmicroeconometrics\u002F02-iv-panel\u002F10-dynamic-panel",{"title":604,"path":605,"stem":606,"children":607},"3. Policy Evaluation Designs","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs","en\u002Fmicroeconometrics\u002F03-policy-designs\u002Findex",[608,609,613,617,621,625],{"title":604,"path":605,"stem":606},{"title":610,"path":611,"stem":612},"Difference-in-Differences","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F11-did-core","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F11-did-core",{"title":614,"path":615,"stem":616},"Staggered DID and Event Studies","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F12-staggered-event-studies","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F12-staggered-event-studies",{"title":618,"path":619,"stem":620},"Regression Discontinuity","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F13-rdd","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F13-rdd",{"title":622,"path":623,"stem":624},"Matching, Weighting and Overlap","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F14-matching-weighting","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F14-matching-weighting",{"title":626,"path":627,"stem":628},"Synthetic Control","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F15-synthetic-control","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F15-synthetic-control",{"title":630,"path":631,"stem":632,"children":633},"Module 4 — Choice and Limited Outcomes","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002Findex",[634,635,639,643,647],{"title":630,"path":631,"stem":632},{"title":636,"path":637,"stem":638},"Binary Choice","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F16-binary-choice","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F16-binary-choice",{"title":640,"path":641,"stem":642},"Multinomial and Ordered Choice","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F17-multinomial-choice","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F17-multinomial-choice",{"title":644,"path":645,"stem":646},"Count Outcomes","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F18-count-outcomes","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F18-count-outcomes",{"title":648,"path":649,"stem":650},"Censoring, Truncation and Selection","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F19-censoring-selection","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F19-censoring-selection",{"title":652,"path":653,"stem":654,"children":655},"Module 5 — Modern Causal Analysis","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal","en\u002Fmicroeconometrics\u002F05-modern-causal\u002Findex",[656,657,661,665,669],{"title":652,"path":653,"stem":654},{"title":658,"path":659,"stem":660},"Double Machine Learning","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal\u002F20-dml","en\u002Fmicroeconometrics\u002F05-modern-causal\u002F20-dml",{"title":662,"path":663,"stem":664},"Heterogeneity and Policy Learning","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal\u002F21-heterogeneity-policy","en\u002Fmicroeconometrics\u002F05-modern-causal\u002F21-heterogeneity-policy",{"title":666,"path":667,"stem":668},"Sensitivity and Partial Identification","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal\u002F22-sensitivity-partial-id","en\u002Fmicroeconometrics\u002F05-modern-causal\u002F22-sensitivity-partial-id",{"title":670,"path":671,"stem":672},"External Validity and Transport","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal\u002F23-external-validity","en\u002Fmicroeconometrics\u002F05-modern-causal\u002F23-external-validity",{"title":674,"path":675,"stem":676,"children":677},"Module 6 — From Data to Auditable Evidence","\u002Fen\u002Fmicroeconometrics\u002F06-workflow","en\u002Fmicroeconometrics\u002F06-workflow\u002Findex",[678,679,683,687],{"title":674,"path":675,"stem":676},{"title":680,"path":681,"stem":682},"Data Provenance","\u002Fen\u002Fmicroeconometrics\u002F06-workflow\u002F24-data-provenance","en\u002Fmicroeconometrics\u002F06-workflow\u002F24-data-provenance",{"title":684,"path":685,"stem":686},"Reproducibility and Reporting","\u002Fen\u002Fmicroeconometrics\u002F06-workflow\u002F25-reproducibility-reporting","en\u002Fmicroeconometrics\u002F06-workflow\u002F25-reproducibility-reporting",{"title":688,"path":689,"stem":690},"Paper and Evidence Audit","\u002Fen\u002Fmicroeconometrics\u002F06-workflow\u002F26-paper-audit","en\u002Fmicroeconometrics\u002F06-workflow\u002F26-paper-audit",{"title":692,"path":693,"stem":694,"children":695},"Appendix — Revision and Evidence Map","\u002Fen\u002Fmicroeconometrics\u002Fappendix","en\u002Fmicroeconometrics\u002Fappendix\u002Findex",[696,697,701,705],{"title":692,"path":693,"stem":694},{"title":698,"path":699,"stem":700},"Formula and Design Map","\u002Fen\u002Fmicroeconometrics\u002Fappendix\u002F27-formula-design-map","en\u002Fmicroeconometrics\u002Fappendix\u002F27-formula-design-map",{"title":702,"path":703,"stem":704},"Ten Worked Microeconometric Pitfalls","\u002Fen\u002Fmicroeconometrics\u002Fappendix\u002F28-worked-pitfalls","en\u002Fmicroeconometrics\u002Fappendix\u002F28-worked-pitfalls",{"title":706,"path":707,"stem":708},"Reading and Software Map","\u002Fen\u002Fmicroeconometrics\u002Fappendix\u002F29-reading-software-map","en\u002Fmicroeconometrics\u002Fappendix\u002F29-reading-software-map",{"title":710,"path":711,"stem":712,"children":713},"Capstone — Should Northbridge Expand Pathways?","\u002Fen\u002Fmicroeconometrics\u002Fcapstone","en\u002Fmicroeconometrics\u002Fcapstone\u002Findex",[714],{"title":710,"path":711,"stem":712},{"title":716,"path":717,"stem":718,"children":719,"page":249},"Microeconomics","\u002Fen\u002Fmicroeconomics","en\u002Fmicroeconomics",[720,726,732,738,744,750,756,762,768,774,780,786,792],{"title":721,"path":722,"stem":723,"children":724},"Advanced Microeconomics — Course Guide","\u002Fen\u002Fmicroeconomics\u002F00-intro","en\u002Fmicroeconomics\u002F00-intro\u002Findex",[725],{"title":721,"path":722,"stem":723},{"title":727,"path":728,"stem":729,"children":730},"Module 1 — Choice, Duality, and Revealed Preference","\u002Fen\u002Fmicroeconomics\u002F01-fundations","en\u002Fmicroeconomics\u002F01-fundations\u002Findex",[731],{"title":727,"path":728,"stem":729},{"title":733,"path":734,"stem":735,"children":736},"Module 2 — Comparative Statics and Welfare Measurement","\u002Fen\u002Fmicroeconomics\u002F02-comparative-statics","en\u002Fmicroeconomics\u002F02-comparative-statics\u002Findex",[737],{"title":733,"path":734,"stem":735},{"title":739,"path":740,"stem":741,"children":742},"Module 3 — Choice under Risk and Insurance","\u002Fen\u002Fmicroeconomics\u002F03-uncertainty","en\u002Fmicroeconomics\u002F03-uncertainty\u002Findex",[743],{"title":739,"path":740,"stem":741},{"title":745,"path":746,"stem":747,"children":748},"Module 4 — General Equilibrium and Welfare","\u002Fen\u002Fmicroeconomics\u002F04-general-equilibrium","en\u002Fmicroeconomics\u002F04-general-equilibrium\u002Findex",[749],{"title":745,"path":746,"stem":747},{"title":751,"path":752,"stem":753,"children":754},"Module 5 — Static, Dynamic, and Repeated Games","\u002Fen\u002Fmicroeconomics\u002F05-game-theory","en\u002Fmicroeconomics\u002F05-game-theory\u002Findex",[755],{"title":751,"path":752,"stem":753},{"title":757,"path":758,"stem":759,"children":760},"Module 6 — Oligopoly, Entry, and Algorithmic Pricing","\u002Fen\u002Fmicroeconomics\u002F06-oligopoly","en\u002Fmicroeconomics\u002F06-oligopoly\u002Findex",[761],{"title":757,"path":758,"stem":759},{"title":763,"path":764,"stem":765,"children":766},"Module 7 — Information Economics and Contracts","\u002Fen\u002Fmicroeconomics\u002F07-information-economics","en\u002Fmicroeconomics\u002F07-information-economics\u002Findex",[767],{"title":763,"path":764,"stem":765},{"title":769,"path":770,"stem":771,"children":772},"Module 8 — Mechanism Design and Auctions","\u002Fen\u002Fmicroeconomics\u002F08-mechanism-design","en\u002Fmicroeconomics\u002F08-mechanism-design\u002Findex",[773],{"title":769,"path":770,"stem":771},{"title":775,"path":776,"stem":777,"children":778},"Module 9 — Behavioural and Experimental Microeconomics","\u002Fen\u002Fmicroeconomics\u002F09-behavioural-economics","en\u002Fmicroeconomics\u002F09-behavioural-economics\u002Findex",[779],{"title":775,"path":776,"stem":777},{"title":781,"path":782,"stem":783,"children":784},"Module 10 — Externalities, Public Goods, and Collective Action","\u002Fen\u002Fmicroeconomics\u002F10-externalities-public-goods","en\u002Fmicroeconomics\u002F10-externalities-public-goods\u002Findex",[785],{"title":781,"path":782,"stem":783},{"title":787,"path":788,"stem":789,"children":790},"Module 11 — Matching and Market Design","\u002Fen\u002Fmicroeconomics\u002F11-market-design","en\u002Fmicroeconomics\u002F11-market-design\u002Findex",[791],{"title":787,"path":788,"stem":789},{"title":793,"path":794,"stem":795,"children":796},"Module 12 — Integrated Microeconomic Design Studio","\u002Fen\u002Fmicroeconomics\u002F12-review","en\u002Fmicroeconomics\u002F12-review\u002Findex",[797],{"title":793,"path":794,"stem":795},{"title":799,"path":800,"stem":801,"children":802},"Playground","\u002Fen\u002Fplayground","en\u002Fplayground\u002Findex",[803,804,808,812,816,820],{"title":799,"path":800,"stem":801},{"title":805,"path":806,"stem":807},"Typst Plugin Playground","\u002Fen\u002Fplayground\u002F01-typstex","en\u002Fplayground\u002F01-typstex",{"title":809,"path":810,"stem":811},"Citation Plugin Test","\u002Fen\u002Fplayground\u002F02-citation","en\u002Fplayground\u002F02-citation",{"title":813,"path":814,"stem":815},"Pyodide Playground","\u002Fen\u002Fplayground\u002F03-pyodide","en\u002Fplayground\u002F03-pyodide",{"title":817,"path":818,"stem":819},"WebR Playground","\u002Fen\u002Fplayground\u002F04-webr","en\u002Fplayground\u002F04-webr",{"title":821,"path":822,"stem":823},"Chart.js 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文献综述的构建与写作","\u002Fzh\u002Facademic-writing\u002F04-writing-the-literature-review","zh\u002Facademic-writing\u002F04-writing-the-literature-review",{"title":1056,"path":1057,"stem":1058},"8. 文献综述清单与模板","\u002Fzh\u002Facademic-writing\u002F08-literature-review-checklist-and-template","zh\u002Facademic-writing\u002F08-literature-review-checklist-and-template",{"title":1060,"path":1061,"stem":1062},"10. 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策略全流程","\u002Fzh\u002Fquant\u002F09-case-study","zh\u002Fquant\u002F09-case-study",{"title":1779,"path":1780,"stem":1781},"量化投资文献与软件图谱","\u002Fzh\u002Fquant\u002F10-reading-software-map","zh\u002Fquant\u002F10-reading-software-map",null,{"id":1784,"title":1743,"body":1785,"description":8005,"extension":8006,"features":1782,"hero":1782,"layout":1782,"locale":1782,"meta":8007,"navigation":1782,"path":1744,"published":8010,"seo":8011,"stem":1745,"__hash__":8012},"docs\u002Fzh\u002Fquant\u002F01-research-data.md",{"type":1786,"value":1787,"toc":7968},"minimark",[1788,1791,1795,1798,1803,3827,3830,4215,4218,4223,4226,4230,4233,4268,4271,4282,4285,4289,4292,4303,4305,4313,4316,4320,4328,4330,4338,4342,4353,4355,4363,4367,4370,4412,4415,4421,4425,4431,4434,4449,4452,4456,4459,4470,4473,4764,4767,4771,4774,4794,4797,4805,4808,4824,4828,4831,4834,4842,4845,4849,4882,5826,5829,5837,5841,6289,6293,6296,6307,6310,6325,6329,6345,6349,6352,6363,6366,6414,6496,6815,6818,7067,7070,7074,7078,7081,7089,7092,7108,7112,7115,7123,7126,7137,7141,7144,7152,7155,7166,7177,7180,7184,7188,7191,7208,7212,7215,7229,7237,7241,7710,7716,7720,7723,7816,7822,7829,7833,7865,7869,7953,7957,7960,7962],[1789,1790,1743],"h1",{"id":1743},[1792,1793,1794],"p",{},"本章讨论量化策略的“地基”：数据。常说“Garbage in, garbage out”，如果数据本身质量不佳，后续再精巧的模型和策略也很难可靠。",[1792,1796,1797],{},"在后续章节中，我们会频繁用到“标的–时间”二维结构的数据。为方便引用，这里先给出一个简单的记号约定：",[1799,1800,1802],"h3",{"id":1801},"_0-一个简单的数据记号体系","0. 一个简单的数据记号体系",[1804,1805,1806,1924,2011,2176,2948,3595,3748],"ul",{},[1807,1808,1809,1810,1923],"li",{},"用 ",[1811,1812,1815,1858],"span",{"className":1813},[1814],"katex",[1811,1816,1819],{"className":1817},[1818],"katex-mathml",[1820,1821,1823],"math",{"xmlns":1822},"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML",[1824,1825,1826,1853],"semantics",{},[1827,1828,1829,1833,1837,1841,1845,1848,1850],"mrow",{},[1830,1831,1832],"mi",{},"i",[1834,1835,1836],"mo",{},"=",[1838,1839,1840],"mn",{},"1",[1834,1842,1844],{"separator":1843},"true",",",[1834,1846,1847],{},"…",[1834,1849,1844],{"separator":1843},[1830,1851,1852],{},"N",[1854,1855,1857],"annotation",{"encoding":1856},"application\u002Fx-tex","i=1,\\dots,N",[1811,1859,1862,1888],{"className":1860,"ariaHidden":1843},[1861],"katex-html",[1811,1863,1866,1871,1876,1881,1885],{"className":1864},[1865],"base",[1811,1867],{"className":1868,"style":1870},[1869],"strut","height:0.6595em;",[1811,1872,1832],{"className":1873},[1874,1875],"mord","mathnormal",[1811,1877],{"className":1878,"style":1880},[1879],"mspace","margin-right:0.2778em;",[1811,1882,1836],{"className":1883},[1884],"mrel",[1811,1886],{"className":1887,"style":1880},[1879],[1811,1889,1891,1895,1898,1902,1906,1910,1913,1916,1919],{"className":1890},[1865],[1811,1892],{"className":1893,"style":1894},[1869],"height:0.8778em;vertical-align:-0.1944em;",[1811,1896,1840],{"className":1897},[1874],[1811,1899,1844],{"className":1900},[1901],"mpunct",[1811,1903],{"className":1904,"style":1905},[1879],"margin-right:0.1667em;",[1811,1907,1847],{"className":1908},[1909],"minner",[1811,1911],{"className":1912,"style":1905},[1879],[1811,1914,1844],{"className":1915},[1901],[1811,1917],{"className":1918,"style":1905},[1879],[1811,1920,1852],{"className":1921,"style":1922},[1874,1875],"margin-right:0.109em;"," 表示资产（例如股票）；",[1807,1925,1809,1926,2010],{},[1811,1927,1929,1957],{"className":1928},[1814],[1811,1930,1932],{"className":1931},[1818],[1820,1933,1934],{"xmlns":1822},[1824,1935,1936,1954],{},[1827,1937,1938,1941,1943,1945,1947,1949,1951],{},[1830,1939,1940],{},"t",[1834,1942,1836],{},[1838,1944,1840],{},[1834,1946,1844],{"separator":1843},[1834,1948,1847],{},[1834,1950,1844],{"separator":1843},[1830,1952,1953],{},"T",[1854,1955,1956],{"encoding":1856},"t=1,\\dots,T",[1811,1958,1960,1979],{"className":1959,"ariaHidden":1843},[1861],[1811,1961,1963,1967,1970,1973,1976],{"className":1962},[1865],[1811,1964],{"className":1965,"style":1966},[1869],"height:0.6151em;",[1811,1968,1940],{"className":1969},[1874,1875],[1811,1971],{"className":1972,"style":1880},[1879],[1811,1974,1836],{"className":1975},[1884],[1811,1977],{"className":1978,"style":1880},[1879],[1811,1980,1982,1985,1988,1991,1994,1997,2000,2003,2006],{"className":1981},[1865],[1811,1983],{"className":1984,"style":1894},[1869],[1811,1986,1840],{"className":1987},[1874],[1811,1989,1844],{"className":1990},[1901],[1811,1992],{"className":1993,"style":1905},[1879],[1811,1995,1847],{"className":1996},[1909],[1811,1998],{"className":1999,"style":1905},[1879],[1811,2001,1844],{"className":2002},[1901],[1811,2004],{"className":2005,"style":1905},[1879],[1811,2007,1953],{"className":2008,"style":2009},[1874,1875],"margin-right:0.1389em;"," 表示离散时间（例如交易日，按照交易所日历排序）；",[1807,2012,2013,2117,2118,2146,2147,2175],{},[1811,2014,2016,2042],{"className":2015},[1814],[1811,2017,2019],{"className":2018},[1818],[1820,2020,2021],{"xmlns":1822},[1824,2022,2023,2039],{},[1827,2024,2025],{},[2026,2027,2028,2031],"msub",{},[1830,2029,2030],{},"P",[1827,2032,2033,2035,2037],{},[1830,2034,1832],{},[1834,2036,1844],{"separator":1843},[1830,2038,1940],{},[1854,2040,2041],{"encoding":1856},"P_{i,t}",[1811,2043,2045],{"className":2044,"ariaHidden":1843},[1861],[1811,2046,2048,2052],{"className":2047},[1865],[1811,2049],{"className":2050,"style":2051},[1869],"height:0.9694em;vertical-align:-0.2861em;",[1811,2053,2055,2058],{"className":2054},[1874],[1811,2056,2030],{"className":2057,"style":2009},[1874,1875],[1811,2059,2062],{"className":2060},[2061],"msupsub",[1811,2063,2067,2108],{"className":2064},[2065,2066],"vlist-t","vlist-t2",[1811,2068,2071,2103],{"className":2069},[2070],"vlist-r",[1811,2072,2076],{"className":2073,"style":2075},[2074],"vlist","height:0.3117em;",[1811,2077,2079,2084],{"style":2078},"top:-2.55em;margin-left:-0.1389em;margin-right:0.05em;",[1811,2080],{"className":2081,"style":2083},[2082],"pstrut","height:2.7em;",[1811,2085,2091],{"className":2086},[2087,2088,2089,2090],"sizing","reset-size6","size3","mtight",[1811,2092,2094,2097,2100],{"className":2093},[1874,2090],[1811,2095,1832],{"className":2096},[1874,1875,2090],[1811,2098,1844],{"className":2099},[1901,2090],[1811,2101,1940],{"className":2102},[1874,1875,2090],[1811,2104,2107],{"className":2105},[2106],"vlist-s","​",[1811,2109,2111],{"className":2110},[2070],[1811,2112,2115],{"className":2113,"style":2114},[2074],"height:0.2861em;",[1811,2116],{}," 表示第 ",[1811,2119,2121,2134],{"className":2120},[1814],[1811,2122,2124],{"className":2123},[1818],[1820,2125,2126],{"xmlns":1822},[1824,2127,2128,2132],{},[1827,2129,2130],{},[1830,2131,1832],{},[1854,2133,1832],{"encoding":1856},[1811,2135,2137],{"className":2136,"ariaHidden":1843},[1861],[1811,2138,2140,2143],{"className":2139},[1865],[1811,2141],{"className":2142,"style":1870},[1869],[1811,2144,1832],{"className":2145},[1874,1875]," 只资产在日期 ",[1811,2148,2150,2163],{"className":2149},[1814],[1811,2151,2153],{"className":2152},[1818],[1820,2154,2155],{"xmlns":1822},[1824,2156,2157,2161],{},[1827,2158,2159],{},[1830,2160,1940],{},[1854,2162,1940],{"encoding":1856},[1811,2164,2166],{"className":2165,"ariaHidden":1843},[1861],[1811,2167,2169,2172],{"className":2168},[1865],[1811,2170],{"className":2171,"style":1966},[1869],[1811,2173,1940],{"className":2174},[1874,1875]," 的收盘价；",[1807,2177,2178,2278,2279,2307,2308,2362,2363,2848,2851,2852,2947],{},[1811,2179,2181,2211],{"className":2180},[1814],[1811,2182,2184],{"className":2183},[1818],[1820,2185,2186],{"xmlns":1822},[1824,2187,2188,2208],{},[1827,2189,2190],{},[2026,2191,2192,2195],{},[1830,2193,2194],{},"R",[1827,2196,2197,2199,2201,2203,2206],{},[1830,2198,1832],{},[1834,2200,1844],{"separator":1843},[1830,2202,1940],{},[1834,2204,2205],{},"+",[1838,2207,1840],{},[1854,2209,2210],{"encoding":1856},"R_{i,t+1}",[1811,2212,2214],{"className":2213,"ariaHidden":1843},[1861],[1811,2215,2217,2220],{"className":2216},[1865],[1811,2218],{"className":2219,"style":2051},[1869],[1811,2221,2223,2227],{"className":2222},[1874],[1811,2224,2194],{"className":2225,"style":2226},[1874,1875],"margin-right:0.0077em;",[1811,2228,2230],{"className":2229},[2061],[1811,2231,2233,2270],{"className":2232},[2065,2066],[1811,2234,2236,2267],{"className":2235},[2070],[1811,2237,2239],{"className":2238,"style":2075},[2074],[1811,2240,2242,2245],{"style":2241},"top:-2.55em;margin-left:-0.0077em;margin-right:0.05em;",[1811,2243],{"className":2244,"style":2083},[2082],[1811,2246,2248],{"className":2247},[2087,2088,2089,2090],[1811,2249,2251,2254,2257,2260,2264],{"className":2250},[1874,2090],[1811,2252,1832],{"className":2253},[1874,1875,2090],[1811,2255,1844],{"className":2256},[1901,2090],[1811,2258,1940],{"className":2259},[1874,1875,2090],[1811,2261,2205],{"className":2262},[2263,2090],"mbin",[1811,2265,1840],{"className":2266},[1874,2090],[1811,2268,2107],{"className":2269},[2106],[1811,2271,2273],{"className":2272},[2070],[1811,2274,2276],{"className":2275,"style":2114},[2074],[1811,2277],{}," 表示从 ",[1811,2280,2282,2295],{"className":2281},[1814],[1811,2283,2285],{"className":2284},[1818],[1820,2286,2287],{"xmlns":1822},[1824,2288,2289,2293],{},[1827,2290,2291],{},[1830,2292,1940],{},[1854,2294,1940],{"encoding":1856},[1811,2296,2298],{"className":2297,"ariaHidden":1843},[1861],[1811,2299,2301,2304],{"className":2300},[1865],[1811,2302],{"className":2303,"style":1966},[1869],[1811,2305,1940],{"className":2306},[1874,1875]," 到 ",[1811,2309,2311,2329],{"className":2310},[1814],[1811,2312,2314],{"className":2313},[1818],[1820,2315,2316],{"xmlns":1822},[1824,2317,2318,2326],{},[1827,2319,2320,2322,2324],{},[1830,2321,1940],{},[1834,2323,2205],{},[1838,2325,1840],{},[1854,2327,2328],{"encoding":1856},"t+1",[1811,2330,2332,2352],{"className":2331,"ariaHidden":1843},[1861],[1811,2333,2335,2339,2342,2346,2349],{"className":2334},[1865],[1811,2336],{"className":2337,"style":2338},[1869],"height:0.6984em;vertical-align:-0.0833em;",[1811,2340,1940],{"className":2341},[1874,1875],[1811,2343],{"className":2344,"style":2345},[1879],"margin-right:0.2222em;",[1811,2347,2205],{"className":2348},[2263],[1811,2350],{"className":2351,"style":2345},[1879],[1811,2353,2355,2359],{"className":2354},[1865],[1811,2356],{"className":2357,"style":2358},[1869],"height:0.6444em;",[1811,2360,1840],{"className":2361},[1874]," 的简单收益率：",[1811,2364,2367],{"className":2365},[2366],"katex-display",[1811,2368,2370,2470],{"className":2369},[1814],[1811,2371,2373],{"className":2372},[1818],[1820,2374,2376],{"xmlns":1822,"display":2375},"block",[1824,2377,2378,2467],{},[1827,2379,2380,2396,2398,2465],{},[2026,2381,2382,2384],{},[1830,2383,2194],{},[1827,2385,2386,2388,2390,2392,2394],{},[1830,2387,1832],{},[1834,2389,1844],{"separator":1843},[1830,2391,1940],{},[1834,2393,2205],{},[1838,2395,1840],{},[1834,2397,1836],{},[2399,2400,2401,2453],"mfrac",{},[1827,2402,2403,2419,2422,2434,2436],{},[2026,2404,2405,2407],{},[1830,2406,2030],{},[1827,2408,2409,2411,2413,2415,2417],{},[1830,2410,1832],{},[1834,2412,1844],{"separator":1843},[1830,2414,1940],{},[1834,2416,2205],{},[1838,2418,1840],{},[1834,2420,2421],{},"−",[2026,2423,2424,2426],{},[1830,2425,2030],{},[1827,2427,2428,2430,2432],{},[1830,2429,1832],{},[1834,2431,1844],{"separator":1843},[1830,2433,1940],{},[1834,2435,2205],{},[2026,2437,2438,2441],{},[1830,2439,2440],{},"D",[1827,2442,2443,2445,2447,2449,2451],{},[1830,2444,1832],{},[1834,2446,1844],{"separator":1843},[1830,2448,1940],{},[1834,2450,2205],{},[1838,2452,1840],{},[2026,2454,2455,2457],{},[1830,2456,2030],{},[1827,2458,2459,2461,2463],{},[1830,2460,1832],{},[1834,2462,1844],{"separator":1843},[1830,2464,1940],{},[1834,2466,1844],{"separator":1843},[1854,2468,2469],{"encoding":1856},"R_{i,t+1} = \\frac{P_{i,t+1} - P_{i,t} + D_{i,t+1}}{P_{i,t}},",[1811,2471,2473,2543],{"className":2472,"ariaHidden":1843},[1861],[1811,2474,2476,2479,2534,2537,2540],{"className":2475},[1865],[1811,2477],{"className":2478,"style":2051},[1869],[1811,2480,2482,2485],{"className":2481},[1874],[1811,2483,2194],{"className":2484,"style":2226},[1874,1875],[1811,2486,2488],{"className":2487},[2061],[1811,2489,2491,2526],{"className":2490},[2065,2066],[1811,2492,2494,2523],{"className":2493},[2070],[1811,2495,2497],{"className":2496,"style":2075},[2074],[1811,2498,2499,2502],{"style":2241},[1811,2500],{"className":2501,"style":2083},[2082],[1811,2503,2505],{"className":2504},[2087,2088,2089,2090],[1811,2506,2508,2511,2514,2517,2520],{"className":2507},[1874,2090],[1811,2509,1832],{"className":2510},[1874,1875,2090],[1811,2512,1844],{"className":2513},[1901,2090],[1811,2515,1940],{"className":2516},[1874,1875,2090],[1811,2518,2205],{"className":2519},[2263,2090],[1811,2521,1840],{"className":2522},[1874,2090],[1811,2524,2107],{"className":2525},[2106],[1811,2527,2529],{"className":2528},[2070],[1811,2530,2532],{"className":2531,"style":2114},[2074],[1811,2533],{},[1811,2535],{"className":2536,"style":1880},[1879],[1811,2538,1836],{"className":2539},[1884],[1811,2541],{"className":2542,"style":1880},[1879],[1811,2544,2546,2550,2845],{"className":2545},[1865],[1811,2547],{"className":2548,"style":2549},[1869],"height:2.3324em;vertical-align:-0.9721em;",[1811,2551,2553,2558,2841],{"className":2552},[1874],[1811,2554],{"className":2555},[2556,2557],"mopen","nulldelimiter",[1811,2559,2561],{"className":2560},[2399],[1811,2562,2564,2832],{"className":2563},[2065,2066],[1811,2565,2567,2829],{"className":2566},[2070],[1811,2568,2571,2630,2641],{"className":2569,"style":2570},[2074],"height:1.3603em;",[1811,2572,2574,2578],{"style":2573},"top:-2.314em;",[1811,2575],{"className":2576,"style":2577},[2082],"height:3em;",[1811,2579,2581],{"className":2580},[1874],[1811,2582,2584,2587],{"className":2583},[1874],[1811,2585,2030],{"className":2586,"style":2009},[1874,1875],[1811,2588,2590],{"className":2589},[2061],[1811,2591,2593,2622],{"className":2592},[2065,2066],[1811,2594,2596,2619],{"className":2595},[2070],[1811,2597,2599],{"className":2598,"style":2075},[2074],[1811,2600,2601,2604],{"style":2078},[1811,2602],{"className":2603,"style":2083},[2082],[1811,2605,2607],{"className":2606},[2087,2088,2089,2090],[1811,2608,2610,2613,2616],{"className":2609},[1874,2090],[1811,2611,1832],{"className":2612},[1874,1875,2090],[1811,2614,1844],{"className":2615},[1901,2090],[1811,2617,1940],{"className":2618},[1874,1875,2090],[1811,2620,2107],{"className":2621},[2106],[1811,2623,2625],{"className":2624},[2070],[1811,2626,2628],{"className":2627,"style":2114},[2074],[1811,2629],{},[1811,2631,2633,2636],{"style":2632},"top:-3.23em;",[1811,2634],{"className":2635,"style":2577},[2082],[1811,2637],{"className":2638,"style":2640},[2639],"frac-line","border-bottom-width:0.04em;",[1811,2642,2644,2647],{"style":2643},"top:-3.677em;",[1811,2645],{"className":2646,"style":2577},[2082],[1811,2648,2650,2705,2708,2711,2714,2763,2766,2769,2772],{"className":2649},[1874],[1811,2651,2653,2656],{"className":2652},[1874],[1811,2654,2030],{"className":2655,"style":2009},[1874,1875],[1811,2657,2659],{"className":2658},[2061],[1811,2660,2662,2697],{"className":2661},[2065,2066],[1811,2663,2665,2694],{"className":2664},[2070],[1811,2666,2668],{"className":2667,"style":2075},[2074],[1811,2669,2670,2673],{"style":2078},[1811,2671],{"className":2672,"style":2083},[2082],[1811,2674,2676],{"className":2675},[2087,2088,2089,2090],[1811,2677,2679,2682,2685,2688,2691],{"className":2678},[1874,2090],[1811,2680,1832],{"className":2681},[1874,1875,2090],[1811,2683,1844],{"className":2684},[1901,2090],[1811,2686,1940],{"className":2687},[1874,1875,2090],[1811,2689,2205],{"className":2690},[2263,2090],[1811,2692,1840],{"className":2693},[1874,2090],[1811,2695,2107],{"className":2696},[2106],[1811,2698,2700],{"className":2699},[2070],[1811,2701,2703],{"className":2702,"style":2114},[2074],[1811,2704],{},[1811,2706],{"className":2707,"style":2345},[1879],[1811,2709,2421],{"className":2710},[2263],[1811,2712],{"className":2713,"style":2345},[1879],[1811,2715,2717,2720],{"className":2716},[1874],[1811,2718,2030],{"className":2719,"style":2009},[1874,1875],[1811,2721,2723],{"className":2722},[2061],[1811,2724,2726,2755],{"className":2725},[2065,2066],[1811,2727,2729,2752],{"className":2728},[2070],[1811,2730,2732],{"className":2731,"style":2075},[2074],[1811,2733,2734,2737],{"style":2078},[1811,2735],{"className":2736,"style":2083},[2082],[1811,2738,2740],{"className":2739},[2087,2088,2089,2090],[1811,2741,2743,2746,2749],{"className":2742},[1874,2090],[1811,2744,1832],{"className":2745},[1874,1875,2090],[1811,2747,1844],{"className":2748},[1901,2090],[1811,2750,1940],{"className":2751},[1874,1875,2090],[1811,2753,2107],{"className":2754},[2106],[1811,2756,2758],{"className":2757},[2070],[1811,2759,2761],{"className":2760,"style":2114},[2074],[1811,2762],{},[1811,2764],{"className":2765,"style":2345},[1879],[1811,2767,2205],{"className":2768},[2263],[1811,2770],{"className":2771,"style":2345},[1879],[1811,2773,2775,2779],{"className":2774},[1874],[1811,2776,2440],{"className":2777,"style":2778},[1874,1875],"margin-right:0.0278em;",[1811,2780,2782],{"className":2781},[2061],[1811,2783,2785,2821],{"className":2784},[2065,2066],[1811,2786,2788,2818],{"className":2787},[2070],[1811,2789,2791],{"className":2790,"style":2075},[2074],[1811,2792,2794,2797],{"style":2793},"top:-2.55em;margin-left:-0.0278em;margin-right:0.05em;",[1811,2795],{"className":2796,"style":2083},[2082],[1811,2798,2800],{"className":2799},[2087,2088,2089,2090],[1811,2801,2803,2806,2809,2812,2815],{"className":2802},[1874,2090],[1811,2804,1832],{"className":2805},[1874,1875,2090],[1811,2807,1844],{"className":2808},[1901,2090],[1811,2810,1940],{"className":2811},[1874,1875,2090],[1811,2813,2205],{"className":2814},[2263,2090],[1811,2816,1840],{"className":2817},[1874,2090],[1811,2819,2107],{"className":2820},[2106],[1811,2822,2824],{"className":2823},[2070],[1811,2825,2827],{"className":2826,"style":2114},[2074],[1811,2828],{},[1811,2830,2107],{"className":2831},[2106],[1811,2833,2835],{"className":2834},[2070],[1811,2836,2839],{"className":2837,"style":2838},[2074],"height:0.9721em;",[1811,2840],{},[1811,2842],{"className":2843},[2844,2557],"mclose",[1811,2846,1844],{"className":2847},[1901],[2849,2850],"br",{},"其中 ",[1811,2853,2855,2883],{"className":2854},[1814],[1811,2856,2858],{"className":2857},[1818],[1820,2859,2860],{"xmlns":1822},[1824,2861,2862,2880],{},[1827,2863,2864],{},[2026,2865,2866,2868],{},[1830,2867,2440],{},[1827,2869,2870,2872,2874,2876,2878],{},[1830,2871,1832],{},[1834,2873,1844],{"separator":1843},[1830,2875,1940],{},[1834,2877,2205],{},[1838,2879,1840],{},[1854,2881,2882],{"encoding":1856},"D_{i,t+1}",[1811,2884,2886],{"className":2885,"ariaHidden":1843},[1861],[1811,2887,2889,2892],{"className":2888},[1865],[1811,2890],{"className":2891,"style":2051},[1869],[1811,2893,2895,2898],{"className":2894},[1874],[1811,2896,2440],{"className":2897,"style":2778},[1874,1875],[1811,2899,2901],{"className":2900},[2061],[1811,2902,2904,2939],{"className":2903},[2065,2066],[1811,2905,2907,2936],{"className":2906},[2070],[1811,2908,2910],{"className":2909,"style":2075},[2074],[1811,2911,2912,2915],{"style":2793},[1811,2913],{"className":2914,"style":2083},[2082],[1811,2916,2918],{"className":2917},[2087,2088,2089,2090],[1811,2919,2921,2924,2927,2930,2933],{"className":2920},[1874,2090],[1811,2922,1832],{"className":2923},[1874,1875,2090],[1811,2925,1844],{"className":2926},[1901,2090],[1811,2928,1940],{"className":2929},[1874,1875,2090],[1811,2931,2205],{"className":2932},[2263,2090],[1811,2934,1840],{"className":2935},[1874,2090],[1811,2937,2107],{"className":2938},[2106],[1811,2940,2942],{"className":2941},[2070],[1811,2943,2945],{"className":2944,"style":2114},[2074],[1811,2946],{}," 是期间分红（若无则为 0）；",[1807,2949,2950,3047,3048,3297,3299,3300,3408,3409,3594],{},[1811,2951,2953,2982],{"className":2952},[1814],[1811,2954,2956],{"className":2955},[1818],[1820,2957,2958],{"xmlns":1822},[1824,2959,2960,2979],{},[1827,2961,2962],{},[2026,2963,2964,2967],{},[1830,2965,2966],{},"r",[1827,2968,2969,2971,2973,2975,2977],{},[1830,2970,1832],{},[1834,2972,1844],{"separator":1843},[1830,2974,1940],{},[1834,2976,2205],{},[1838,2978,1840],{},[1854,2980,2981],{"encoding":1856},"r_{i,t+1}",[1811,2983,2985],{"className":2984,"ariaHidden":1843},[1861],[1811,2986,2988,2992],{"className":2987},[1865],[1811,2989],{"className":2990,"style":2991},[1869],"height:0.7167em;vertical-align:-0.2861em;",[1811,2993,2995,2998],{"className":2994},[1874],[1811,2996,2966],{"className":2997,"style":2778},[1874,1875],[1811,2999,3001],{"className":3000},[2061],[1811,3002,3004,3039],{"className":3003},[2065,2066],[1811,3005,3007,3036],{"className":3006},[2070],[1811,3008,3010],{"className":3009,"style":2075},[2074],[1811,3011,3012,3015],{"style":2793},[1811,3013],{"className":3014,"style":2083},[2082],[1811,3016,3018],{"className":3017},[2087,2088,2089,2090],[1811,3019,3021,3024,3027,3030,3033],{"className":3020},[1874,2090],[1811,3022,1832],{"className":3023},[1874,1875,2090],[1811,3025,1844],{"className":3026},[1901,2090],[1811,3028,1940],{"className":3029},[1874,1875,2090],[1811,3031,2205],{"className":3032},[2263,2090],[1811,3034,1840],{"className":3035},[1874,2090],[1811,3037,2107],{"className":3038},[2106],[1811,3040,3042],{"className":3041},[2070],[1811,3043,3045],{"className":3044,"style":2114},[2074],[1811,3046],{}," 表示对应的对数收益率：",[1811,3049,3051],{"className":3050},[2366],[1811,3052,3054,3120],{"className":3053},[1814],[1811,3055,3057],{"className":3056},[1818],[1820,3058,3059],{"xmlns":1822,"display":2375},[1824,3060,3061,3117],{},[1827,3062,3063,3079,3081,3084,3087,3092,3094,3096,3112,3115],{},[2026,3064,3065,3067],{},[1830,3066,2966],{},[1827,3068,3069,3071,3073,3075,3077],{},[1830,3070,1832],{},[1834,3072,1844],{"separator":1843},[1830,3074,1940],{},[1834,3076,2205],{},[1838,3078,1840],{},[1834,3080,1836],{},[1830,3082,3083],{},"ln",[1834,3085,3086],{},"⁡",[1834,3088,3091],{"fence":3089,"stretchy":1843,"minsize":3090,"maxsize":3090},"false","1.2em","(",[1838,3093,1840],{},[1834,3095,2205],{},[2026,3097,3098,3100],{},[1830,3099,2194],{},[1827,3101,3102,3104,3106,3108,3110],{},[1830,3103,1832],{},[1834,3105,1844],{"separator":1843},[1830,3107,1940],{},[1834,3109,2205],{},[1838,3111,1840],{},[1834,3113,3114],{"fence":3089,"stretchy":1843,"minsize":3090,"maxsize":3090},")",[1834,3116,1844],{"separator":1843},[1854,3118,3119],{"encoding":1856},"r_{i,t+1} = \\ln\\big(1 + R_{i,t+1}\\big),",[1811,3121,3123,3193,3227],{"className":3122,"ariaHidden":1843},[1861],[1811,3124,3126,3129,3184,3187,3190],{"className":3125},[1865],[1811,3127],{"className":3128,"style":2991},[1869],[1811,3130,3132,3135],{"className":3131},[1874],[1811,3133,2966],{"className":3134,"style":2778},[1874,1875],[1811,3136,3138],{"className":3137},[2061],[1811,3139,3141,3176],{"className":3140},[2065,2066],[1811,3142,3144,3173],{"className":3143},[2070],[1811,3145,3147],{"className":3146,"style":2075},[2074],[1811,3148,3149,3152],{"style":2793},[1811,3150],{"className":3151,"style":2083},[2082],[1811,3153,3155],{"className":3154},[2087,2088,2089,2090],[1811,3156,3158,3161,3164,3167,3170],{"className":3157},[1874,2090],[1811,3159,1832],{"className":3160},[1874,1875,2090],[1811,3162,1844],{"className":3163},[1901,2090],[1811,3165,1940],{"className":3166},[1874,1875,2090],[1811,3168,2205],{"className":3169},[2263,2090],[1811,3171,1840],{"className":3172},[1874,2090],[1811,3174,2107],{"className":3175},[2106],[1811,3177,3179],{"className":3178},[2070],[1811,3180,3182],{"className":3181,"style":2114},[2074],[1811,3183],{},[1811,3185],{"className":3186,"style":1880},[1879],[1811,3188,1836],{"className":3189},[1884],[1811,3191],{"className":3192,"style":1880},[1879],[1811,3194,3196,3200,3204,3207,3215,3218,3221,3224],{"className":3195},[1865],[1811,3197],{"className":3198,"style":3199},[1869],"height:1.2em;vertical-align:-0.35em;",[1811,3201,3083],{"className":3202},[3203],"mop",[1811,3205],{"className":3206,"style":1905},[1879],[1811,3208,3210],{"className":3209},[1874],[1811,3211,3091],{"className":3212},[3213,3214],"delimsizing","size1",[1811,3216,1840],{"className":3217},[1874],[1811,3219],{"className":3220,"style":2345},[1879],[1811,3222,2205],{"className":3223},[2263],[1811,3225],{"className":3226,"style":2345},[1879],[1811,3228,3230,3233,3288,3294],{"className":3229},[1865],[1811,3231],{"className":3232,"style":3199},[1869],[1811,3234,3236,3239],{"className":3235},[1874],[1811,3237,2194],{"className":3238,"style":2226},[1874,1875],[1811,3240,3242],{"className":3241},[2061],[1811,3243,3245,3280],{"className":3244},[2065,2066],[1811,3246,3248,3277],{"className":3247},[2070],[1811,3249,3251],{"className":3250,"style":2075},[2074],[1811,3252,3253,3256],{"style":2241},[1811,3254],{"className":3255,"style":2083},[2082],[1811,3257,3259],{"className":3258},[2087,2088,2089,2090],[1811,3260,3262,3265,3268,3271,3274],{"className":3261},[1874,2090],[1811,3263,1832],{"className":3264},[1874,1875,2090],[1811,3266,1844],{"className":3267},[1901,2090],[1811,3269,1940],{"className":3270},[1874,1875,2090],[1811,3272,2205],{"className":3273},[2263,2090],[1811,3275,1840],{"className":3276},[1874,2090],[1811,3278,2107],{"className":3279},[2106],[1811,3281,3283],{"className":3282},[2070],[1811,3284,3286],{"className":3285,"style":2114},[2074],[1811,3287],{},[1811,3289,3291],{"className":3290},[1874],[1811,3292,3114],{"className":3293},[3213,3214],[1811,3295,1844],{"className":3296},[1901],[2849,3298],{},"在 ",[1811,3301,3303,3337],{"className":3302},[1814],[1811,3304,3306],{"className":3305},[1818],[1820,3307,3308],{"xmlns":1822},[1824,3309,3310,3334],{},[1827,3311,3312,3316,3332],{},[1830,3313,3315],{"mathvariant":3314},"normal","∣",[2026,3317,3318,3320],{},[1830,3319,2194],{},[1827,3321,3322,3324,3326,3328,3330],{},[1830,3323,1832],{},[1834,3325,1844],{"separator":1843},[1830,3327,1940],{},[1834,3329,2205],{},[1838,3331,1840],{},[1830,3333,3315],{"mathvariant":3314},[1854,3335,3336],{"encoding":1856},"|R_{i,t+1}|",[1811,3338,3340],{"className":3339,"ariaHidden":1843},[1861],[1811,3341,3343,3347,3350,3405],{"className":3342},[1865],[1811,3344],{"className":3345,"style":3346},[1869],"height:1.0361em;vertical-align:-0.2861em;",[1811,3348,3315],{"className":3349},[1874],[1811,3351,3353,3356],{"className":3352},[1874],[1811,3354,2194],{"className":3355,"style":2226},[1874,1875],[1811,3357,3359],{"className":3358},[2061],[1811,3360,3362,3397],{"className":3361},[2065,2066],[1811,3363,3365,3394],{"className":3364},[2070],[1811,3366,3368],{"className":3367,"style":2075},[2074],[1811,3369,3370,3373],{"style":2241},[1811,3371],{"className":3372,"style":2083},[2082],[1811,3374,3376],{"className":3375},[2087,2088,2089,2090],[1811,3377,3379,3382,3385,3388,3391],{"className":3378},[1874,2090],[1811,3380,1832],{"className":3381},[1874,1875,2090],[1811,3383,1844],{"className":3384},[1901,2090],[1811,3386,1940],{"className":3387},[1874,1875,2090],[1811,3389,2205],{"className":3390},[2263,2090],[1811,3392,1840],{"className":3393},[1874,2090],[1811,3395,2107],{"className":3396},[2106],[1811,3398,3400],{"className":3399},[2070],[1811,3401,3403],{"className":3402,"style":2114},[2074],[1811,3404],{},[1811,3406,3315],{"className":3407},[1874]," 较小的情况下有近似关系 ",[1811,3410,3412,3459],{"className":3411},[1814],[1811,3413,3415],{"className":3414},[1818],[1820,3416,3417],{"xmlns":1822},[1824,3418,3419,3456],{},[1827,3420,3421,3437,3440],{},[2026,3422,3423,3425],{},[1830,3424,2966],{},[1827,3426,3427,3429,3431,3433,3435],{},[1830,3428,1832],{},[1834,3430,1844],{"separator":1843},[1830,3432,1940],{},[1834,3434,2205],{},[1838,3436,1840],{},[1834,3438,3439],{},"≈",[2026,3441,3442,3444],{},[1830,3443,2194],{},[1827,3445,3446,3448,3450,3452,3454],{},[1830,3447,1832],{},[1834,3449,1844],{"separator":1843},[1830,3451,1940],{},[1834,3453,2205],{},[1838,3455,1840],{},[1854,3457,3458],{"encoding":1856},"r_{i,t+1} \\approx R_{i,t+1}",[1811,3460,3462,3533],{"className":3461,"ariaHidden":1843},[1861],[1811,3463,3465,3469,3524,3527,3530],{"className":3464},[1865],[1811,3466],{"className":3467,"style":3468},[1869],"height:0.7692em;vertical-align:-0.2861em;",[1811,3470,3472,3475],{"className":3471},[1874],[1811,3473,2966],{"className":3474,"style":2778},[1874,1875],[1811,3476,3478],{"className":3477},[2061],[1811,3479,3481,3516],{"className":3480},[2065,2066],[1811,3482,3484,3513],{"className":3483},[2070],[1811,3485,3487],{"className":3486,"style":2075},[2074],[1811,3488,3489,3492],{"style":2793},[1811,3490],{"className":3491,"style":2083},[2082],[1811,3493,3495],{"className":3494},[2087,2088,2089,2090],[1811,3496,3498,3501,3504,3507,3510],{"className":3497},[1874,2090],[1811,3499,1832],{"className":3500},[1874,1875,2090],[1811,3502,1844],{"className":3503},[1901,2090],[1811,3505,1940],{"className":3506},[1874,1875,2090],[1811,3508,2205],{"className":3509},[2263,2090],[1811,3511,1840],{"className":3512},[1874,2090],[1811,3514,2107],{"className":3515},[2106],[1811,3517,3519],{"className":3518},[2070],[1811,3520,3522],{"className":3521,"style":2114},[2074],[1811,3523],{},[1811,3525],{"className":3526,"style":1880},[1879],[1811,3528,3439],{"className":3529},[1884],[1811,3531],{"className":3532,"style":1880},[1879],[1811,3534,3536,3539],{"className":3535},[1865],[1811,3537],{"className":3538,"style":2051},[1869],[1811,3540,3542,3545],{"className":3541},[1874],[1811,3543,2194],{"className":3544,"style":2226},[1874,1875],[1811,3546,3548],{"className":3547},[2061],[1811,3549,3551,3586],{"className":3550},[2065,2066],[1811,3552,3554,3583],{"className":3553},[2070],[1811,3555,3557],{"className":3556,"style":2075},[2074],[1811,3558,3559,3562],{"style":2241},[1811,3560],{"className":3561,"style":2083},[2082],[1811,3563,3565],{"className":3564},[2087,2088,2089,2090],[1811,3566,3568,3571,3574,3577,3580],{"className":3567},[1874,2090],[1811,3569,1832],{"className":3570},[1874,1875,2090],[1811,3572,1844],{"className":3573},[1901,2090],[1811,3575,1940],{"className":3576},[1874,1875,2090],[1811,3578,2205],{"className":3579},[2263,2090],[1811,3581,1840],{"className":3582},[1874,2090],[1811,3584,2107],{"className":3585},[2106],[1811,3587,3589],{"className":3588},[2070],[1811,3590,3592],{"className":3591,"style":2114},[2074],[1811,3593],{},"；",[1807,3596,3597,2117,3685,3713,3714,3742,3743,3747],{},[1811,3598,3600,3625],{"className":3599},[1814],[1811,3601,3603],{"className":3602},[1818],[1820,3604,3605],{"xmlns":1822},[1824,3606,3607,3622],{},[1827,3608,3609],{},[2026,3610,3611,3614],{},[1830,3612,3613],{},"X",[1827,3615,3616,3618,3620],{},[1830,3617,1832],{},[1834,3619,1844],{"separator":1843},[1830,3621,1940],{},[1854,3623,3624],{"encoding":1856},"X_{i,t}",[1811,3626,3628],{"className":3627,"ariaHidden":1843},[1861],[1811,3629,3631,3634],{"className":3630},[1865],[1811,3632],{"className":3633,"style":2051},[1869],[1811,3635,3637,3641],{"className":3636},[1874],[1811,3638,3613],{"className":3639,"style":3640},[1874,1875],"margin-right:0.0785em;",[1811,3642,3644],{"className":3643},[2061],[1811,3645,3647,3677],{"className":3646},[2065,2066],[1811,3648,3650,3674],{"className":3649},[2070],[1811,3651,3653],{"className":3652,"style":2075},[2074],[1811,3654,3656,3659],{"style":3655},"top:-2.55em;margin-left:-0.0785em;margin-right:0.05em;",[1811,3657],{"className":3658,"style":2083},[2082],[1811,3660,3662],{"className":3661},[2087,2088,2089,2090],[1811,3663,3665,3668,3671],{"className":3664},[1874,2090],[1811,3666,1832],{"className":3667},[1874,1875,2090],[1811,3669,1844],{"className":3670},[1901,2090],[1811,3672,1940],{"className":3673},[1874,1875,2090],[1811,3675,2107],{"className":3676},[2106],[1811,3678,3680],{"className":3679},[2070],[1811,3681,3683],{"className":3682,"style":2114},[2074],[1811,3684],{},[1811,3686,3688,3701],{"className":3687},[1814],[1811,3689,3691],{"className":3690},[1818],[1820,3692,3693],{"xmlns":1822},[1824,3694,3695,3699],{},[1827,3696,3697],{},[1830,3698,1832],{},[1854,3700,1832],{"encoding":1856},[1811,3702,3704],{"className":3703,"ariaHidden":1843},[1861],[1811,3705,3707,3710],{"className":3706},[1865],[1811,3708],{"className":3709,"style":1870},[1869],[1811,3711,1832],{"className":3712},[1874,1875]," 只资产在 ",[1811,3715,3717,3730],{"className":3716},[1814],[1811,3718,3720],{"className":3719},[1818],[1820,3721,3722],{"xmlns":1822},[1824,3723,3724,3728],{},[1827,3725,3726],{},[1830,3727,1940],{},[1854,3729,1940],{"encoding":1856},[1811,3731,3733],{"className":3732,"ariaHidden":1843},[1861],[1811,3734,3736,3739],{"className":3735},[1865],[1811,3737],{"className":3738,"style":1966},[1869],[1811,3740,1940],{"className":3741},[1874,1875]," 期的某个",[3744,3745,3746],"strong",{},"特征\u002F因子","（例如市盈率、动量等），通常通过原始数据计算得到；",[1807,3749,3750,3826],{},[1811,3751,3753,3772],{"className":3752},[1814],[1811,3754,3756],{"className":3755},[1818],[1820,3757,3758],{"xmlns":1822},[1824,3759,3760,3769],{},[1827,3761,3762],{},[2026,3763,3764,3767],{},[1830,3765,3766],{},"Z",[1830,3768,1940],{},[1854,3770,3771],{"encoding":1856},"Z_t",[1811,3773,3775],{"className":3774,"ariaHidden":1843},[1861],[1811,3776,3778,3782],{"className":3777},[1865],[1811,3779],{"className":3780,"style":3781},[1869],"height:0.8333em;vertical-align:-0.15em;",[1811,3783,3785,3789],{"className":3784},[1874],[1811,3786,3766],{"className":3787,"style":3788},[1874,1875],"margin-right:0.0715em;",[1811,3790,3792],{"className":3791},[2061],[1811,3793,3795,3817],{"className":3794},[2065,2066],[1811,3796,3798,3814],{"className":3797},[2070],[1811,3799,3802],{"className":3800,"style":3801},[2074],"height:0.2806em;",[1811,3803,3805,3808],{"style":3804},"top:-2.55em;margin-left:-0.0715em;margin-right:0.05em;",[1811,3806],{"className":3807,"style":2083},[2082],[1811,3809,3811],{"className":3810},[2087,2088,2089,2090],[1811,3812,1940],{"className":3813},[1874,1875,2090],[1811,3815,2107],{"className":3816},[2106],[1811,3818,3820],{"className":3819},[2070],[1811,3821,3824],{"className":3822,"style":3823},[2074],"height:0.15em;",[1811,3825],{}," 表示与时间相关但与单个资产无关的宏观或市场状态变量（如市场收益、宏观指数等）。",[1792,3828,3829],{},"从数据结构角度，可以把量化研究的数据视作一个“面板”（panel）：",[1811,3831,3833],{"className":3832},[2366],[1811,3834,3836,3934],{"className":3835},[1814],[1811,3837,3839],{"className":3838},[1818],[1820,3840,3841],{"xmlns":1822,"display":2375},[1824,3842,3843,3931],{},[1827,3844,3845,3848,3850,3866,3868,3880,3882,3888,3890,3928],{},[1834,3846,3847],{"fence":3089,"stretchy":1843,"minsize":3090,"maxsize":3090},"{",[1834,3849,3091],{"stretchy":3089},[2026,3851,3852,3854],{},[1830,3853,2194],{},[1827,3855,3856,3858,3860,3862,3864],{},[1830,3857,1832],{},[1834,3859,1844],{"separator":1843},[1830,3861,1940],{},[1834,3863,2205],{},[1838,3865,1840],{},[1834,3867,1844],{"separator":1843},[2026,3869,3870,3872],{},[1830,3871,3613],{},[1827,3873,3874,3876,3878],{},[1830,3875,1832],{},[1834,3877,1844],{"separator":1843},[1830,3879,1940],{},[1834,3881,1844],{"separator":1843},[2026,3883,3884,3886],{},[1830,3885,3766],{},[1830,3887,1940],{},[1834,3889,3114],{"stretchy":3089},[3891,3892,3893,3896,3912],"msubsup",{},[1834,3894,3895],{"fence":3089,"stretchy":1843,"minsize":3090,"maxsize":3090},"}",[1827,3897,3898,3900,3902,3904,3906,3908,3910],{},[1830,3899,1832],{},[1834,3901,1836],{},[1838,3903,1840],{},[1834,3905,1844],{"separator":1843},[1834,3907,1847],{},[1834,3909,1844],{"separator":1843},[1830,3911,1852],{},[1827,3913,3914,3916,3918,3920,3922,3924,3926],{},[1830,3915,1940],{},[1834,3917,1836],{},[1838,3919,1840],{},[1834,3921,1844],{"separator":1843},[1834,3923,1847],{},[1834,3925,1844],{"separator":1843},[1830,3927,1953],{},[1830,3929,3930],{"mathvariant":3314},".",[1854,3932,3933],{"encoding":1856},"\\big\\{(R_{i,t+1}, X_{i,t}, Z_t)\\big\\}_{i=1,\\dots,N}^{t=1,\\dots,T}.",[1811,3935,3937],{"className":3936,"ariaHidden":1843},[1861],[1811,3938,3940,3944,3950,3953,4008,4011,4014,4063,4066,4069,4109,4112,4212],{"className":3939},[1865],[1811,3941],{"className":3942,"style":3943},[1869],"height:1.617em;vertical-align:-0.5358em;",[1811,3945,3947],{"className":3946},[1874],[1811,3948,3847],{"className":3949},[3213,3214],[1811,3951,3091],{"className":3952},[2556],[1811,3954,3956,3959],{"className":3955},[1874],[1811,3957,2194],{"className":3958,"style":2226},[1874,1875],[1811,3960,3962],{"className":3961},[2061],[1811,3963,3965,4000],{"className":3964},[2065,2066],[1811,3966,3968,3997],{"className":3967},[2070],[1811,3969,3971],{"className":3970,"style":2075},[2074],[1811,3972,3973,3976],{"style":2241},[1811,3974],{"className":3975,"style":2083},[2082],[1811,3977,3979],{"className":3978},[2087,2088,2089,2090],[1811,3980,3982,3985,3988,3991,3994],{"className":3981},[1874,2090],[1811,3983,1832],{"className":3984},[1874,1875,2090],[1811,3986,1844],{"className":3987},[1901,2090],[1811,3989,1940],{"className":3990},[1874,1875,2090],[1811,3992,2205],{"className":3993},[2263,2090],[1811,3995,1840],{"className":3996},[1874,2090],[1811,3998,2107],{"className":3999},[2106],[1811,4001,4003],{"className":4002},[2070],[1811,4004,4006],{"className":4005,"style":2114},[2074],[1811,4007],{},[1811,4009,1844],{"className":4010},[1901],[1811,4012],{"className":4013,"style":1905},[1879],[1811,4015,4017,4020],{"className":4016},[1874],[1811,4018,3613],{"className":4019,"style":3640},[1874,1875],[1811,4021,4023],{"className":4022},[2061],[1811,4024,4026,4055],{"className":4025},[2065,2066],[1811,4027,4029,4052],{"className":4028},[2070],[1811,4030,4032],{"className":4031,"style":2075},[2074],[1811,4033,4034,4037],{"style":3655},[1811,4035],{"className":4036,"style":2083},[2082],[1811,4038,4040],{"className":4039},[2087,2088,2089,2090],[1811,4041,4043,4046,4049],{"className":4042},[1874,2090],[1811,4044,1832],{"className":4045},[1874,1875,2090],[1811,4047,1844],{"className":4048},[1901,2090],[1811,4050,1940],{"className":4051},[1874,1875,2090],[1811,4053,2107],{"className":4054},[2106],[1811,4056,4058],{"className":4057},[2070],[1811,4059,4061],{"className":4060,"style":2114},[2074],[1811,4062],{},[1811,4064,1844],{"className":4065},[1901],[1811,4067],{"className":4068,"style":1905},[1879],[1811,4070,4072,4075],{"className":4071},[1874],[1811,4073,3766],{"className":4074,"style":3788},[1874,1875],[1811,4076,4078],{"className":4077},[2061],[1811,4079,4081,4101],{"className":4080},[2065,2066],[1811,4082,4084,4098],{"className":4083},[2070],[1811,4085,4087],{"className":4086,"style":3801},[2074],[1811,4088,4089,4092],{"style":3804},[1811,4090],{"className":4091,"style":2083},[2082],[1811,4093,4095],{"className":4094},[2087,2088,2089,2090],[1811,4096,1940],{"className":4097},[1874,1875,2090],[1811,4099,2107],{"className":4100},[2106],[1811,4102,4104],{"className":4103},[2070],[1811,4105,4107],{"className":4106,"style":3823},[2074],[1811,4108],{},[1811,4110,3114],{"className":4111},[2844],[1811,4113,4115,4121],{"className":4114},[1874],[1811,4116,4118],{"className":4117},[1874],[1811,4119,3895],{"className":4120},[3213,3214],[1811,4122,4124],{"className":4123},[2061],[1811,4125,4127,4203],{"className":4126},[2065,2066],[1811,4128,4130,4200],{"className":4129},[2070],[1811,4131,4134,4167],{"className":4132,"style":4133},[2074],"height:1.0812em;",[1811,4135,4137,4140],{"style":4136},"top:-2.3003em;margin-right:0.05em;",[1811,4138],{"className":4139,"style":2083},[2082],[1811,4141,4143],{"className":4142},[2087,2088,2089,2090],[1811,4144,4146,4149,4152,4155,4158,4161,4164],{"className":4145},[1874,2090],[1811,4147,1832],{"className":4148},[1874,1875,2090],[1811,4150,1836],{"className":4151},[1884,2090],[1811,4153,1840],{"className":4154},[1874,2090],[1811,4156,1844],{"className":4157},[1901,2090],[1811,4159,1847],{"className":4160},[1909,2090],[1811,4162,1844],{"className":4163},[1901,2090],[1811,4165,1852],{"className":4166,"style":1922},[1874,1875,2090],[1811,4168,4170,4173],{"style":4169},"top:-3.3029em;margin-right:0.05em;",[1811,4171],{"className":4172,"style":2083},[2082],[1811,4174,4176],{"className":4175},[2087,2088,2089,2090],[1811,4177,4179,4182,4185,4188,4191,4194,4197],{"className":4178},[1874,2090],[1811,4180,1940],{"className":4181},[1874,1875,2090],[1811,4183,1836],{"className":4184},[1884,2090],[1811,4186,1840],{"className":4187},[1874,2090],[1811,4189,1844],{"className":4190},[1901,2090],[1811,4192,1847],{"className":4193},[1909,2090],[1811,4195,1844],{"className":4196},[1901,2090],[1811,4198,1953],{"className":4199,"style":2009},[1874,1875,2090],[1811,4201,2107],{"className":4202},[2106],[1811,4204,4206],{"className":4205},[2070],[1811,4207,4210],{"className":4208,"style":4209},[2074],"height:0.5358em;",[1811,4211],{},[1811,4213,3930],{"className":4214},[1874],[1792,4216,4217],{},"在后续的因子检验和计量部分，我们会基于这一面板形式做横截面回归、面板回归等分析。",[4219,4220,4222],"h2",{"id":4221},"_1-量化投资中常见的数据类型","1. 量化投资中常见的数据类型",[1792,4224,4225],{},"从资产类别和来源角度，大致可以分为以下几类：",[1799,4227,4229],{"id":4228},"_11-市场数据","1.1 市场数据",[1792,4231,4232],{},"描述资产在各种市场上的价格和成交特征：",[1804,4234,4235,4241,4255],{},[1807,4236,4237,4240],{},[3744,4238,4239],{},"日度行情数据","：开盘价、最高价、最低价、收盘价（OHLC）、成交量、成交额等。",[1807,4242,4243,4246,4247],{},[3744,4244,4245],{},"高频\u002F分笔数据","：\n",[1804,4248,4249,4252],{},[1807,4250,4251],{},"逐笔成交（每一笔成交的时间、价格、成交量、方向等）；",[1807,4253,4254],{},"分钟\u002F秒级 bar（1m、5m 等）。",[1807,4256,4257,4246,4260],{},[3744,4258,4259],{},"盘口数据（Level 1\u002FLevel 2）",[1804,4261,4262,4265],{},[1807,4263,4264],{},"L1：最优买一\u002F卖一价和量；",[1807,4266,4267],{},"L2：多档买卖盘，反映盘口深度与订单簿结构。",[1792,4269,4270],{},"用于：",[1804,4272,4273,4276,4279],{},[1807,4274,4275],{},"价格序列构造收益率、波动率等；",[1807,4277,4278],{},"分析成交行为、流动性情况；",[1807,4280,4281],{},"对高频策略尤为重要。",[1792,4283,4284],{},"在学术研究中，日度及更高频的市场数据常被用于刻画收益的“风格化事实（stylized facts）”，例如厚尾分布、波动聚集和长记忆等，典型文献包括 Cont (2001) 对金融时间序列经验特征的综述，以及 Tsay (2010) 对金融时间序列模型的系统总结。",[1799,4286,4288],{"id":4287},"_12-基本面与财务数据","1.2 基本面与财务数据",[1792,4290,4291],{},"反映公司或资产发行主体的经营状况与财务健康程度，例如：",[1804,4293,4294,4297,4300],{},[1807,4295,4296],{},"资产负债表、利润表、现金流量表；",[1807,4298,4299],{},"各类财务指标：ROE、ROA、毛利率、负债率等；",[1807,4301,4302],{},"分红、回购、再融资等信息。",[1792,4304,4270],{},[1804,4306,4307,4310],{},[1807,4308,4309],{},"构建估值因子（PE、PB、EV\u002FEBITDA 等）；",[1807,4311,4312],{},"构建质量因子（盈利能力、稳健性等）。",[1792,4314,4315],{},"在资产定价文献中，财务与账面价值类变量经常出现在多因子模型中，例如 Fama and French (1993, 2015) 提出的账面市值比（B\u002FM）、盈利能力和投资风格因子。量化研究中常用这些变量构建价值因子、质量因子，并与经典因子保持口径一致以方便对比。",[1799,4317,4319],{"id":4318},"_13-衍生品与利率相关数据","1.3 衍生品与利率相关数据",[1804,4321,4322,4325],{},[1807,4323,4324],{},"期货、期权、互换等衍生品的行情和持仓情况；",[1807,4326,4327],{},"利率曲线、信用利差等。",[1792,4329,4270],{},[1804,4331,4332,4335],{},[1807,4333,4334],{},"对冲与套利策略；",[1807,4336,4337],{},"利率\u002F信用风险建模。",[1799,4339,4341],{"id":4340},"_14-宏观与另类数据alternative-data","1.4 宏观与另类数据（Alternative Data）",[1804,4343,4344,4347,4350],{},[1807,4345,4346],{},"宏观指标：GDP、通胀率、失业率、PMI 等；",[1807,4348,4349],{},"行业高频指标：电力负荷、运量、在线搜索指数等；",[1807,4351,4352],{},"新闻、公告、舆情相关文本数据。",[1792,4354,4270],{},[1804,4356,4357,4360],{},[1807,4358,4359],{},"自上而下宏观\u002F资产配置策略；",[1807,4361,4362],{},"事件驱动、情绪因子构建等。",[4219,4364,4366],{"id":4365},"_2-数据来源与获取方式","2. 数据来源与获取方式",[1792,4368,4369],{},"不同机构会有不同的数据获取渠道，一般包括：",[1804,4371,4372,4382,4392,4402],{},[1807,4373,4374,4246,4377],{},[3744,4375,4376],{},"交易所\u002F官方渠道",[1804,4378,4379],{},[1807,4380,4381],{},"直接获取历史和实时行情数据（通常需要付费授权）；",[1807,4383,4384,4246,4387],{},[3744,4385,4386],{},"数据供应商",[1804,4388,4389],{},[1807,4390,4391],{},"聚合多家交易所和市场的数据，提供统一接口；",[1807,4393,4394,4246,4397],{},[3744,4395,4396],{},"公开数据",[1804,4398,4399],{},[1807,4400,4401],{},"例如监管机构披露数据、上市公司公告等；",[1807,4403,4404,4246,4407],{},[3744,4405,4406],{},"自建采集",[1804,4408,4409],{},[1807,4410,4411],{},"对新闻网站、企业网站等进行爬取（需遵守相关法律和网站使用条款）。",[1792,4413,4414],{},"在教学与研究环境中，更多使用公开或教学用数据集；在生产环境中，一般使用商业数据源，并配合内部数据清洗标准。",[4416,4417,4418],"blockquote",{},[1792,4419,4420],{},"注意：本笔记只讨论数据类别与处理方法，不会涉及具体商业数据商的数据结构或接口细节，以避免版权问题。",[4219,4422,4424],{"id":4423},"_3-数据清洗的核心目标","3. 数据清洗的核心目标",[1792,4426,4427,4428],{},"数据清洗的目标不是“修正所有问题”，而是：",[3744,4429,4430],{},"尽量减少系统性偏差和明显错误，使数据适合用来建模和回测。",[1792,4432,4433],{},"典型工作包括：",[4435,4436,4437,4440,4443,4446],"ol",{},[1807,4438,4439],{},"识别并处理缺失值；",[1807,4441,4442],{},"处理异常值和极端值；",[1807,4444,4445],{},"时间对齐与重采样；",[1807,4447,4448],{},"检查并避免常见偏差（幸存者偏差、前视偏差等）。",[1792,4450,4451],{},"下面分别展开。",[4219,4453,4455],{"id":4454},"_4-缺失值处理","4. 缺失值处理",[1792,4457,4458],{},"在表格化数据中，缺失值几乎是不可避免的，例如：",[1804,4460,4461,4464,4467],{},[1807,4462,4463],{},"某些财务指标在部分年份\u002F季度未披露；",[1807,4465,4466],{},"某些股票在早期或停牌期间没有价格数据；",[1807,4468,4469],{},"新上市公司历史数据较少。",[1792,4471,4472],{},"常见处理方式：",[4435,4474,4475,4488,4734,4751],{},[1807,4476,4477,4480],{},[3744,4478,4479],{},"删除含缺失值的样本",[1804,4481,4482,4485],{},[1807,4483,4484],{},"适用场景：缺失比例极小，且删除后不会改变样本结构；",[1807,4486,4487],{},"风险：如果缺失具有系统性（例如财务状况不佳的公司更易延迟披露），简单删除会引入偏差。",[1807,4489,4490,4493],{},[3744,4491,4492],{},"前值填充（Forward Fill）",[1804,4494,4495,4728,4731],{},[1807,4496,4497,4498],{},"对时间序列数据常用：\n",[1804,4499,4500],{},[1807,4501,4502,4503,4576,4577,3594],{},"若 ",[1811,4504,4506,4525],{"className":4505},[1814],[1811,4507,4509],{"className":4508},[1818],[1820,4510,4511],{"xmlns":1822},[1824,4512,4513,4522],{},[1827,4514,4515],{},[2026,4516,4517,4520],{},[1830,4518,4519],{},"x",[1830,4521,1940],{},[1854,4523,4524],{"encoding":1856},"x_t",[1811,4526,4528],{"className":4527,"ariaHidden":1843},[1861],[1811,4529,4531,4535],{"className":4530},[1865],[1811,4532],{"className":4533,"style":4534},[1869],"height:0.5806em;vertical-align:-0.15em;",[1811,4536,4538,4541],{"className":4537},[1874],[1811,4539,4519],{"className":4540},[1874,1875],[1811,4542,4544],{"className":4543},[2061],[1811,4545,4547,4568],{"className":4546},[2065,2066],[1811,4548,4550,4565],{"className":4549},[2070],[1811,4551,4553],{"className":4552,"style":3801},[2074],[1811,4554,4556,4559],{"style":4555},"top:-2.55em;margin-left:0em;margin-right:0.05em;",[1811,4557],{"className":4558,"style":2083},[2082],[1811,4560,4562],{"className":4561},[2087,2088,2089,2090],[1811,4563,1940],{"className":4564},[1874,1875,2090],[1811,4566,2107],{"className":4567},[2106],[1811,4569,4571],{"className":4570},[2070],[1811,4572,4574],{"className":4573,"style":3823},[2074],[1811,4575],{}," 缺失，则令 ",[1811,4578,4580,4612],{"className":4579},[1814],[1811,4581,4583],{"className":4582},[1818],[1820,4584,4585],{"xmlns":1822},[1824,4586,4587,4609],{},[1827,4588,4589,4595,4597],{},[2026,4590,4591,4593],{},[1830,4592,4519],{},[1830,4594,1940],{},[1834,4596,1836],{},[2026,4598,4599,4601],{},[1830,4600,4519],{},[1827,4602,4603,4605,4607],{},[1830,4604,1940],{},[1834,4606,2421],{},[1838,4608,1840],{},[1854,4610,4611],{"encoding":1856},"x_t = x_{t-1}",[1811,4613,4615,4670],{"className":4614,"ariaHidden":1843},[1861],[1811,4616,4618,4621,4661,4664,4667],{"className":4617},[1865],[1811,4619],{"className":4620,"style":4534},[1869],[1811,4622,4624,4627],{"className":4623},[1874],[1811,4625,4519],{"className":4626},[1874,1875],[1811,4628,4630],{"className":4629},[2061],[1811,4631,4633,4653],{"className":4632},[2065,2066],[1811,4634,4636,4650],{"className":4635},[2070],[1811,4637,4639],{"className":4638,"style":3801},[2074],[1811,4640,4641,4644],{"style":4555},[1811,4642],{"className":4643,"style":2083},[2082],[1811,4645,4647],{"className":4646},[2087,2088,2089,2090],[1811,4648,1940],{"className":4649},[1874,1875,2090],[1811,4651,2107],{"className":4652},[2106],[1811,4654,4656],{"className":4655},[2070],[1811,4657,4659],{"className":4658,"style":3823},[2074],[1811,4660],{},[1811,4662],{"className":4663,"style":1880},[1879],[1811,4665,1836],{"className":4666},[1884],[1811,4668],{"className":4669,"style":1880},[1879],[1811,4671,4673,4677],{"className":4672},[1865],[1811,4674],{"className":4675,"style":4676},[1869],"height:0.6389em;vertical-align:-0.2083em;",[1811,4678,4680,4683],{"className":4679},[1874],[1811,4681,4519],{"className":4682},[1874,1875],[1811,4684,4686],{"className":4685},[2061],[1811,4687,4689,4719],{"className":4688},[2065,2066],[1811,4690,4692,4716],{"className":4691},[2070],[1811,4693,4696],{"className":4694,"style":4695},[2074],"height:0.3011em;",[1811,4697,4698,4701],{"style":4555},[1811,4699],{"className":4700,"style":2083},[2082],[1811,4702,4704],{"className":4703},[2087,2088,2089,2090],[1811,4705,4707,4710,4713],{"className":4706},[1874,2090],[1811,4708,1940],{"className":4709},[1874,1875,2090],[1811,4711,2421],{"className":4712},[2263,2090],[1811,4714,1840],{"className":4715},[1874,2090],[1811,4717,2107],{"className":4718},[2106],[1811,4720,4722],{"className":4721},[2070],[1811,4723,4726],{"className":4724,"style":4725},[2074],"height:0.2083em;",[1811,4727],{},[1807,4729,4730],{},"适用：价格、持仓等连续性质较强的指标；",[1807,4732,4733],{},"不适用：变化突发、跳跃明显的指标（如一次性利润）。",[1807,4735,4736,4739],{},[3744,4737,4738],{},"插值（Interpolation）",[1804,4740,4741,4744],{},[1807,4742,4743],{},"线性插值、样条插值等；",[1807,4745,4746,4747,4750],{},"在金融时间序列中需谨慎使用，避免",[3744,4748,4749],{},"制造不存在的中间状态","。",[1807,4752,4753,4756],{},[3744,4754,4755],{},"用分组统计量填充",[1804,4757,4758,4761],{},[1807,4759,4760],{},"按行业、市值等分组，用组内均值或中位数替代缺失值；",[1807,4762,4763],{},"适合构建截面因子时保持横截面平衡，但会影响因子的真实分布。",[1792,4765,4766],{},"在实际量化研究中，经常会结合多种方法：例如先判断缺失原因，对小比例随机缺失使用简单方法，对系统性缺失则单独建模或做样本剔除。",[1799,4768,4770],{"id":4769},"_41-从缺失机制角度看缺失值","4.1 从缺失机制角度看缺失值",[1792,4772,4773],{},"在统计学中（Rubin, 1976），常用以下三类机制刻画缺失数据：",[1804,4775,4776,4782,4788],{},[1807,4777,4778,4781],{},[3744,4779,4780],{},"完全随机缺失（MCAR）","：缺失与观测值和未观测值都无关；",[1807,4783,4784,4787],{},[3744,4785,4786],{},"条件随机缺失（MAR）","：在给定已观测变量的条件下，缺失与未观测值无关；",[1807,4789,4790,4793],{},[3744,4791,4792],{},"非随机缺失（MNAR）","：缺失机制依赖于未观测的真实值本身。",[1792,4795,4796],{},"在量化场景中，许多缺失并非 MCAR：",[1804,4798,4799,4802],{},[1807,4800,4801],{},"财报延迟披露或不披露，往往与公司经营状况、风险状况有关，更接近 MNAR；",[1807,4803,4804],{},"某些市值\u002F行业的股票更易长期停牌，价格和成交量缺失可能与流动性风险高度相关。",[1792,4806,4807],{},"因此：",[1804,4809,4810,4813],{},[1807,4811,4812],{},"对于占比极小、近似 MCAR 的缺失，简单删除或用组内统计量填充通常问题不大；",[1807,4814,4815,4816],{},"对于明显具有结构性的缺失，更合理的做法是：\n",[1804,4817,4818,4821],{},[1807,4819,4820],{},"将“可交易性\u002F是否有数据”本身视作一个特征，显式纳入策略设计；",[1807,4822,4823],{},"或在样本划定时就剔除长期缺失和持续停牌的资产，并在文档中说明这一筛选规则。",[4219,4825,4827],{"id":4826},"_5-异常值与极端值处理","5. 异常值与极端值处理",[1792,4829,4830],{},"由于录入错误、拆分复权错误、交易异常等原因，数据中可能出现非常大的“尖刺”。",[1792,4832,4833],{},"例如：",[1804,4835,4836,4839],{},[1807,4837,4838],{},"某日价格被记录为 10000，而前后价格均在 10 左右；",[1807,4840,4841],{},"成交量突然比历史平均高出几百倍。",[1792,4843,4844],{},"常见处理方法：",[1799,4846,4848],{"id":4847},"_51-winsorization去极值","5.1 Winsorization（去极值）",[1792,4850,4851,4852,4881],{},"对某个指标 ",[1811,4853,4855,4868],{"className":4854},[1814],[1811,4856,4858],{"className":4857},[1818],[1820,4859,4860],{"xmlns":1822},[1824,4861,4862,4866],{},[1827,4863,4864],{},[1830,4865,4519],{},[1854,4867,4519],{"encoding":1856},[1811,4869,4871],{"className":4870,"ariaHidden":1843},[1861],[1811,4872,4874,4878],{"className":4873},[1865],[1811,4875],{"className":4876,"style":4877},[1869],"height:0.4306em;",[1811,4879,4519],{"className":4880},[1874,1875],"，在横截面或时间序列上，将极端分位数缩回到阈值，例如：",[1804,4883,4884,5035],{},[1807,4885,4886,4887,3594],{},"计算 1% 和 99% 分位数，记为 ",[1811,4888,4890,4927],{"className":4889},[1814],[1811,4891,4893],{"className":4892},[1818],[1820,4894,4895],{"xmlns":1822},[1824,4896,4897,4924],{},[1827,4898,4899,4911,4913],{},[2026,4900,4901,4904],{},[1830,4902,4903],{},"q",[1827,4905,4906,4908],{},[1838,4907,1840],{},[1830,4909,4910],{"mathvariant":3314},"%",[1834,4912,1844],{"separator":1843},[2026,4914,4915,4917],{},[1830,4916,4903],{},[1827,4918,4919,4922],{},[1838,4920,4921],{},"99",[1830,4923,4910],{"mathvariant":3314},[1854,4925,4926],{"encoding":1856},"q_{1\\%}, q_{99\\%}",[1811,4928,4930],{"className":4929,"ariaHidden":1843},[1861],[1811,4931,4933,4937,4985,4988,4991],{"className":4932},[1865],[1811,4934],{"className":4935,"style":4936},[1869],"height:0.6497em;vertical-align:-0.2191em;",[1811,4938,4940,4944],{"className":4939},[1874],[1811,4941,4903],{"className":4942,"style":4943},[1874,1875],"margin-right:0.0359em;",[1811,4945,4947],{"className":4946},[2061],[1811,4948,4950,4976],{"className":4949},[2065,2066],[1811,4951,4953,4973],{"className":4952},[2070],[1811,4954,4957],{"className":4955,"style":4956},[2074],"height:0.3448em;",[1811,4958,4960,4963],{"style":4959},"top:-2.5198em;margin-left:-0.0359em;margin-right:0.05em;",[1811,4961],{"className":4962,"style":2083},[2082],[1811,4964,4966],{"className":4965},[2087,2088,2089,2090],[1811,4967,4969],{"className":4968},[1874,2090],[1811,4970,4972],{"className":4971},[1874,2090],"1%",[1811,4974,2107],{"className":4975},[2106],[1811,4977,4979],{"className":4978},[2070],[1811,4980,4983],{"className":4981,"style":4982},[2074],"height:0.2191em;",[1811,4984],{},[1811,4986,1844],{"className":4987},[1901],[1811,4989],{"className":4990,"style":1905},[1879],[1811,4992,4994,4997],{"className":4993},[1874],[1811,4995,4903],{"className":4996,"style":4943},[1874,1875],[1811,4998,5000],{"className":4999},[2061],[1811,5001,5003,5027],{"className":5002},[2065,2066],[1811,5004,5006,5024],{"className":5005},[2070],[1811,5007,5009],{"className":5008,"style":4956},[2074],[1811,5010,5011,5014],{"style":4959},[1811,5012],{"className":5013,"style":2083},[2082],[1811,5015,5017],{"className":5016},[2087,2088,2089,2090],[1811,5018,5020],{"className":5019},[1874,2090],[1811,5021,5023],{"className":5022},[1874,2090],"99%",[1811,5025,2107],{"className":5026},[2106],[1811,5028,5030],{"className":5029},[2070],[1811,5031,5033],{"className":5032,"style":4982},[2074],[1811,5034],{},[1807,5036,5037,5038],{},"对所有样本：\n",[1811,5039,5041],{"className":5040},[2366],[1811,5042,5044,5196],{"className":5043},[1814],[1811,5045,5047],{"className":5046},[1818],[1820,5048,5049],{"xmlns":1822,"display":2375},[1824,5050,5051,5193],{},[1827,5052,5053,5063,5065],{},[3891,5054,5055,5057,5059],{},[1830,5056,4519],{},[1830,5058,1832],{},[1834,5060,5062],{"mathvariant":3314,"lspace":5061,"rspace":5061},"0em","′",[1834,5064,1836],{},[1827,5066,5067,5069],{},[1834,5068,3847],{"fence":1843},[5070,5071,5075,5124,5169],"mtable",{"rowspacing":5072,"columnalign":5073,"columnspacing":5074},"0.36em","left left","1em",[5076,5077,5078,5099],"mtr",{},[5079,5080,5081],"mtd",{},[5082,5083,5085],"mstyle",{"scriptlevel":5084,"displaystyle":3089},"0",[1827,5086,5087,5097],{},[2026,5088,5089,5091],{},[1830,5090,4903],{},[1827,5092,5093,5095],{},[1838,5094,1840],{},[1830,5096,4910],{"mathvariant":3314},[1834,5098,1844],{"separator":1843},[5079,5100,5101],{},[5082,5102,5103],{"scriptlevel":5084,"displaystyle":3089},[1827,5104,5105,5111,5114],{},[2026,5106,5107,5109],{},[1830,5108,4519],{},[1830,5110,1832],{},[1834,5112,5113],{},"\u003C",[2026,5115,5116,5118],{},[1830,5117,4903],{},[1827,5119,5120,5122],{},[1838,5121,1840],{},[1830,5123,4910],{"mathvariant":3314},[5076,5125,5126,5144],{},[5079,5127,5128],{},[5082,5129,5130],{"scriptlevel":5084,"displaystyle":3089},[1827,5131,5132,5142],{},[2026,5133,5134,5136],{},[1830,5135,4903],{},[1827,5137,5138,5140],{},[1838,5139,4921],{},[1830,5141,4910],{"mathvariant":3314},[1834,5143,1844],{"separator":1843},[5079,5145,5146],{},[5082,5147,5148],{"scriptlevel":5084,"displaystyle":3089},[1827,5149,5150,5156,5159],{},[2026,5151,5152,5154],{},[1830,5153,4519],{},[1830,5155,1832],{},[1834,5157,5158],{},">",[2026,5160,5161,5163],{},[1830,5162,4903],{},[1827,5164,5165,5167],{},[1838,5166,4921],{},[1830,5168,4910],{"mathvariant":3314},[5076,5170,5171,5185],{},[5079,5172,5173],{},[5082,5174,5175],{"scriptlevel":5084,"displaystyle":3089},[1827,5176,5177,5183],{},[2026,5178,5179,5181],{},[1830,5180,4519],{},[1830,5182,1832],{},[1834,5184,1844],{"separator":1843},[5079,5186,5187],{},[5082,5188,5189],{"scriptlevel":5084,"displaystyle":3089},[5190,5191,5192],"mtext",{},"otherwise",[1854,5194,5195],{"encoding":1856},"x'_i =\n\\begin{cases}\nq_{1\\%}, & x_i \u003C q_{1\\%} \\\\\nq_{99\\%}, & x_i > q_{99\\%} \\\\\nx_i, & \\text{otherwise}\n\\end{cases}",[1811,5197,5199,5273],{"className":5198,"ariaHidden":1843},[1861],[1811,5200,5202,5206,5264,5267,5270],{"className":5201},[1865],[1811,5203],{"className":5204,"style":5205},[1869],"height:1.0489em;vertical-align:-0.247em;",[1811,5207,5209,5212],{"className":5208},[1874],[1811,5210,4519],{"className":5211},[1874,1875],[1811,5213,5215],{"className":5214},[2061],[1811,5216,5218,5255],{"className":5217},[2065,2066],[1811,5219,5221,5252],{"className":5220},[2070],[1811,5222,5225,5237],{"className":5223,"style":5224},[2074],"height:0.8019em;",[1811,5226,5228,5231],{"style":5227},"top:-2.453em;margin-left:0em;margin-right:0.05em;",[1811,5229],{"className":5230,"style":2083},[2082],[1811,5232,5234],{"className":5233},[2087,2088,2089,2090],[1811,5235,1832],{"className":5236},[1874,1875,2090],[1811,5238,5240,5243],{"style":5239},"top:-3.113em;margin-right:0.05em;",[1811,5241],{"className":5242,"style":2083},[2082],[1811,5244,5246],{"className":5245},[2087,2088,2089,2090],[1811,5247,5249],{"className":5248},[1874,2090],[1811,5250,5062],{"className":5251},[1874,2090],[1811,5253,2107],{"className":5254},[2106],[1811,5256,5258],{"className":5257},[2070],[1811,5259,5262],{"className":5260,"style":5261},[2074],"height:0.247em;",[1811,5263],{},[1811,5265],{"className":5266,"style":1880},[1879],[1811,5268,1836],{"className":5269},[1884],[1811,5271],{"className":5272,"style":1880},[1879],[1811,5274,5276,5280],{"className":5275},[1865],[1811,5277],{"className":5278,"style":5279},[1869],"height:4.32em;vertical-align:-1.91em;",[1811,5281,5283,5385,5823],{"className":5282},[1909],[1811,5284,5286],{"className":5285},[2556],[1811,5287,5290],{"className":5288},[3213,5289],"mult",[1811,5291,5293,5376],{"className":5292},[2065,2066],[1811,5294,5296,5373],{"className":5295},[2070],[1811,5297,5300,5315,5337,5349,5361],{"className":5298,"style":5299},[2074],"height:2.35em;",[1811,5301,5303,5307],{"style":5302},"top:-2.2em;",[1811,5304],{"className":5305,"style":5306},[2082],"height:3.15em;",[1811,5308,5312],{"className":5309},[5310,5311],"delimsizinginner","delim-size4",[1811,5313,5314],{},"⎩",[1811,5316,5318,5321],{"style":5317},"top:-2.192em;",[1811,5319],{"className":5320,"style":5306},[2082],[1811,5322,5324],{"style":5323},"height:0.316em;width:0.8889em;",[5325,5326,5333],"svg",{"xmlns":5327,"width":5328,"height":5329,"style":5330,"viewBox":5331,"preserveAspectRatio":5332},"http:\u002F\u002Fwww.w3.org\u002F2000\u002Fsvg","0.8889em","0.316em","width:0.8889em","0 0 888.89 316","xMinYMin",[5334,5335],"path",{"d":5336},"M384 0 H504 V316 H384z M384 0 H504 V316 H384z",[1811,5338,5340,5343],{"style":5339},"top:-3.15em;",[1811,5341],{"className":5342,"style":5306},[2082],[1811,5344,5346],{"className":5345},[5310,5311],[1811,5347,5348],{},"⎨",[1811,5350,5352,5355],{"style":5351},"top:-4.292em;",[1811,5353],{"className":5354,"style":5306},[2082],[1811,5356,5357],{"style":5323},[5325,5358,5359],{"xmlns":5327,"width":5328,"height":5329,"style":5330,"viewBox":5331,"preserveAspectRatio":5332},[5334,5360],{"d":5336},[1811,5362,5364,5367],{"style":5363},"top:-4.6em;",[1811,5365],{"className":5366,"style":5306},[2082],[1811,5368,5370],{"className":5369},[5310,5311],[1811,5371,5372],{},"⎧",[1811,5374,2107],{"className":5375},[2106],[1811,5377,5379],{"className":5378},[2070],[1811,5380,5383],{"className":5381,"style":5382},[2074],"height:1.85em;",[1811,5384],{},[1811,5386,5388],{"className":5387},[1874],[1811,5389,5391,5580,5585],{"className":5390},[5070],[1811,5392,5395],{"className":5393},[5394],"col-align-l",[1811,5396,5398,5571],{"className":5397},[2065,2066],[1811,5399,5401,5568],{"className":5400},[2070],[1811,5402,5405,5461,5516],{"className":5403,"style":5404},[2074],"height:2.41em;",[1811,5406,5408,5412],{"style":5407},"top:-4.41em;",[1811,5409],{"className":5410,"style":5411},[2082],"height:3.008em;",[1811,5413,5415,5458],{"className":5414},[1874],[1811,5416,5418,5421],{"className":5417},[1874],[1811,5419,4903],{"className":5420,"style":4943},[1874,1875],[1811,5422,5424],{"className":5423},[2061],[1811,5425,5427,5450],{"className":5426},[2065,2066],[1811,5428,5430,5447],{"className":5429},[2070],[1811,5431,5433],{"className":5432,"style":4956},[2074],[1811,5434,5435,5438],{"style":4959},[1811,5436],{"className":5437,"style":2083},[2082],[1811,5439,5441],{"className":5440},[2087,2088,2089,2090],[1811,5442,5444],{"className":5443},[1874,2090],[1811,5445,4972],{"className":5446},[1874,2090],[1811,5448,2107],{"className":5449},[2106],[1811,5451,5453],{"className":5452},[2070],[1811,5454,5456],{"className":5455,"style":4982},[2074],[1811,5457],{},[1811,5459,1844],{"className":5460},[1901],[1811,5462,5464,5467],{"style":5463},"top:-2.97em;",[1811,5465],{"className":5466,"style":5411},[2082],[1811,5468,5470,5513],{"className":5469},[1874],[1811,5471,5473,5476],{"className":5472},[1874],[1811,5474,4903],{"className":5475,"style":4943},[1874,1875],[1811,5477,5479],{"className":5478},[2061],[1811,5480,5482,5505],{"className":5481},[2065,2066],[1811,5483,5485,5502],{"className":5484},[2070],[1811,5486,5488],{"className":5487,"style":4956},[2074],[1811,5489,5490,5493],{"style":4959},[1811,5491],{"className":5492,"style":2083},[2082],[1811,5494,5496],{"className":5495},[2087,2088,2089,2090],[1811,5497,5499],{"className":5498},[1874,2090],[1811,5500,5023],{"className":5501},[1874,2090],[1811,5503,2107],{"className":5504},[2106],[1811,5506,5508],{"className":5507},[2070],[1811,5509,5511],{"className":5510,"style":4982},[2074],[1811,5512],{},[1811,5514,1844],{"className":5515},[1901],[1811,5517,5519,5522],{"style":5518},"top:-1.53em;",[1811,5520],{"className":5521,"style":5411},[2082],[1811,5523,5525,5565],{"className":5524},[1874],[1811,5526,5528,5531],{"className":5527},[1874],[1811,5529,4519],{"className":5530},[1874,1875],[1811,5532,5534],{"className":5533},[2061],[1811,5535,5537,5557],{"className":5536},[2065,2066],[1811,5538,5540,5554],{"className":5539},[2070],[1811,5541,5543],{"className":5542,"style":2075},[2074],[1811,5544,5545,5548],{"style":4555},[1811,5546],{"className":5547,"style":2083},[2082],[1811,5549,5551],{"className":5550},[2087,2088,2089,2090],[1811,5552,1832],{"className":5553},[1874,1875,2090],[1811,5555,2107],{"className":5556},[2106],[1811,5558,5560],{"className":5559},[2070],[1811,5561,5563],{"className":5562,"style":3823},[2074],[1811,5564],{},[1811,5566,1844],{"className":5567},[1901],[1811,5569,2107],{"className":5570},[2106],[1811,5572,5574],{"className":5573},[2070],[1811,5575,5578],{"className":5576,"style":5577},[2074],"height:1.91em;",[1811,5579],{},[1811,5581],{"className":5582,"style":5584},[5583],"arraycolsep","width:1em;",[1811,5586,5588],{"className":5587},[5394],[1811,5589,5591,5815],{"className":5590},[2065,2066],[1811,5592,5594,5812],{"className":5593},[2070],[1811,5595,5597,5697,5797],{"className":5596,"style":5404},[2074],[1811,5598,5599,5602],{"style":5407},[1811,5600],{"className":5601,"style":5411},[2082],[1811,5603,5605,5645,5648,5651,5654],{"className":5604},[1874],[1811,5606,5608,5611],{"className":5607},[1874],[1811,5609,4519],{"className":5610},[1874,1875],[1811,5612,5614],{"className":5613},[2061],[1811,5615,5617,5637],{"className":5616},[2065,2066],[1811,5618,5620,5634],{"className":5619},[2070],[1811,5621,5623],{"className":5622,"style":2075},[2074],[1811,5624,5625,5628],{"style":4555},[1811,5626],{"className":5627,"style":2083},[2082],[1811,5629,5631],{"className":5630},[2087,2088,2089,2090],[1811,5632,1832],{"className":5633},[1874,1875,2090],[1811,5635,2107],{"className":5636},[2106],[1811,5638,5640],{"className":5639},[2070],[1811,5641,5643],{"className":5642,"style":3823},[2074],[1811,5644],{},[1811,5646],{"className":5647,"style":1880},[1879],[1811,5649,5113],{"className":5650},[1884],[1811,5652],{"className":5653,"style":1880},[1879],[1811,5655,5657,5660],{"className":5656},[1874],[1811,5658,4903],{"className":5659,"style":4943},[1874,1875],[1811,5661,5663],{"className":5662},[2061],[1811,5664,5666,5689],{"className":5665},[2065,2066],[1811,5667,5669,5686],{"className":5668},[2070],[1811,5670,5672],{"className":5671,"style":4956},[2074],[1811,5673,5674,5677],{"style":4959},[1811,5675],{"className":5676,"style":2083},[2082],[1811,5678,5680],{"className":5679},[2087,2088,2089,2090],[1811,5681,5683],{"className":5682},[1874,2090],[1811,5684,4972],{"className":5685},[1874,2090],[1811,5687,2107],{"className":5688},[2106],[1811,5690,5692],{"className":5691},[2070],[1811,5693,5695],{"className":5694,"style":4982},[2074],[1811,5696],{},[1811,5698,5699,5702],{"style":5463},[1811,5700],{"className":5701,"style":5411},[2082],[1811,5703,5705,5745,5748,5751,5754],{"className":5704},[1874],[1811,5706,5708,5711],{"className":5707},[1874],[1811,5709,4519],{"className":5710},[1874,1875],[1811,5712,5714],{"className":5713},[2061],[1811,5715,5717,5737],{"className":5716},[2065,2066],[1811,5718,5720,5734],{"className":5719},[2070],[1811,5721,5723],{"className":5722,"style":2075},[2074],[1811,5724,5725,5728],{"style":4555},[1811,5726],{"className":5727,"style":2083},[2082],[1811,5729,5731],{"className":5730},[2087,2088,2089,2090],[1811,5732,1832],{"className":5733},[1874,1875,2090],[1811,5735,2107],{"className":5736},[2106],[1811,5738,5740],{"className":5739},[2070],[1811,5741,5743],{"className":5742,"style":3823},[2074],[1811,5744],{},[1811,5746],{"className":5747,"style":1880},[1879],[1811,5749,5158],{"className":5750},[1884],[1811,5752],{"className":5753,"style":1880},[1879],[1811,5755,5757,5760],{"className":5756},[1874],[1811,5758,4903],{"className":5759,"style":4943},[1874,1875],[1811,5761,5763],{"className":5762},[2061],[1811,5764,5766,5789],{"className":5765},[2065,2066],[1811,5767,5769,5786],{"className":5768},[2070],[1811,5770,5772],{"className":5771,"style":4956},[2074],[1811,5773,5774,5777],{"style":4959},[1811,5775],{"className":5776,"style":2083},[2082],[1811,5778,5780],{"className":5779},[2087,2088,2089,2090],[1811,5781,5783],{"className":5782},[1874,2090],[1811,5784,5023],{"className":5785},[1874,2090],[1811,5787,2107],{"className":5788},[2106],[1811,5790,5792],{"className":5791},[2070],[1811,5793,5795],{"className":5794,"style":4982},[2074],[1811,5796],{},[1811,5798,5799,5802],{"style":5518},[1811,5800],{"className":5801,"style":5411},[2082],[1811,5803,5805],{"className":5804},[1874],[1811,5806,5809],{"className":5807},[1874,5808],"text",[1811,5810,5192],{"className":5811},[1874],[1811,5813,2107],{"className":5814},[2106],[1811,5816,5818],{"className":5817},[2070],[1811,5819,5821],{"className":5820,"style":5577},[2074],[1811,5822],{},[1811,5824],{"className":5825},[2844,2557],[1792,5827,5828],{},"好处：",[1804,5830,5831,5834],{},[1807,5832,5833],{},"降低极端数据对均值、方差等统计量的影响；",[1807,5835,5836],{},"对回归、协方差估计更加稳定。",[1799,5838,5840],{"id":5839},"_52-标准差截断","5.2 标准差截断",[1804,5842,5843,6286],{},[1807,5844,5845,5846,6202,6203,6255,6256,6285],{},"假设某变量近似服从正态分布，若 ",[1811,5847,5849,5903],{"className":5848},[1814],[1811,5850,5852],{"className":5851},[1818],[1820,5853,5854],{"xmlns":1822},[1824,5855,5856,5900],{},[1827,5857,5858,5860,5867,5869,5871,5895,5897],{},[1830,5859,3315],{"mathvariant":3314},[2026,5861,5862,5865],{},[1830,5863,5864],{},"z",[1830,5866,1832],{},[1830,5868,3315],{"mathvariant":3314},[1834,5870,1836],{},[1827,5872,5873,5875,5893],{},[1834,5874,3315],{"fence":1843},[2399,5876,5877,5890],{},[1827,5878,5879,5885,5887],{},[2026,5880,5881,5883],{},[1830,5882,4519],{},[1830,5884,1832],{},[1834,5886,2421],{},[1830,5888,5889],{},"μ",[1830,5891,5892],{},"σ",[1834,5894,3315],{"fence":1843},[1834,5896,5158],{},[1830,5898,5899],{},"k",[1854,5901,5902],{"encoding":1856},"|z_i| = \\left|\\frac{x_i-\\mu}{\\sigma}\\right| > k",[1811,5904,5906,5970,6191],{"className":5905,"ariaHidden":1843},[1861],[1811,5907,5909,5913,5916,5958,5961,5964,5967],{"className":5908},[1865],[1811,5910],{"className":5911,"style":5912},[1869],"height:1em;vertical-align:-0.25em;",[1811,5914,3315],{"className":5915},[1874],[1811,5917,5919,5923],{"className":5918},[1874],[1811,5920,5864],{"className":5921,"style":5922},[1874,1875],"margin-right:0.044em;",[1811,5924,5926],{"className":5925},[2061],[1811,5927,5929,5950],{"className":5928},[2065,2066],[1811,5930,5932,5947],{"className":5931},[2070],[1811,5933,5935],{"className":5934,"style":2075},[2074],[1811,5936,5938,5941],{"style":5937},"top:-2.55em;margin-left:-0.044em;margin-right:0.05em;",[1811,5939],{"className":5940,"style":2083},[2082],[1811,5942,5944],{"className":5943},[2087,2088,2089,2090],[1811,5945,1832],{"className":5946},[1874,1875,2090],[1811,5948,2107],{"className":5949},[2106],[1811,5951,5953],{"className":5952},[2070],[1811,5954,5956],{"className":5955,"style":3823},[2074],[1811,5957],{},[1811,5959,3315],{"className":5960},[1874],[1811,5962],{"className":5963,"style":1880},[1879],[1811,5965,1836],{"className":5966},[1884],[1811,5968],{"className":5969,"style":1880},[1879],[1811,5971,5973,5977,6182,6185,6188],{"className":5972},[1865],[1811,5974],{"className":5975,"style":5976},[1869],"height:1.2044em;vertical-align:-0.35em;",[1811,5978,5980,6025,6145],{"className":5979},[1909],[1811,5981,5983],{"className":5982},[2556],[1811,5984,5986],{"className":5985},[3213,5289],[1811,5987,5989,6016],{"className":5988},[2065,2066],[1811,5990,5992,6013],{"className":5991},[2070],[1811,5993,5996],{"className":5994,"style":5995},[2074],"height:0.85em;",[1811,5997,5999,6003],{"style":5998},"top:-2.85em;",[1811,6000],{"className":6001,"style":6002},[2082],"height:3.2em;",[1811,6004,6006],{"style":6005},"width:0.333em;height:1.2em;",[5325,6007,6010],{"xmlns":5327,"width":6008,"height":3090,"viewBox":6009},"0.333em","0 0 333 1200",[5334,6011],{"d":6012},"M145 15 v585 v0 v585 c2.667,10,9.667,15,21,15\nc10,0,16.667,-5,20,-15 v-585 v0 v-585 c-2.667,-10,-9.667,-15,-21,-15\nc-10,0,-16.667,5,-20,15z M188 15 H145 v585 v0 v585 h43z",[1811,6014,2107],{"className":6015},[2106],[1811,6017,6019],{"className":6018},[2070],[1811,6020,6023],{"className":6021,"style":6022},[2074],"height:0.35em;",[1811,6024],{},[1811,6026,6028,6031,6142],{"className":6027},[1874],[1811,6029],{"className":6030},[2556,2557],[1811,6032,6034],{"className":6033},[2399],[1811,6035,6037,6133],{"className":6036},[2065,2066],[1811,6038,6040,6130],{"className":6039},[2070],[1811,6041,6044,6059,6067],{"className":6042,"style":6043},[2074],"height:0.8544em;",[1811,6045,6047,6050],{"style":6046},"top:-2.655em;",[1811,6048],{"className":6049,"style":2577},[2082],[1811,6051,6053],{"className":6052},[2087,2088,2089,2090],[1811,6054,6056],{"className":6055},[1874,2090],[1811,6057,5892],{"className":6058,"style":4943},[1874,1875,2090],[1811,6060,6061,6064],{"style":2632},[1811,6062],{"className":6063,"style":2577},[2082],[1811,6065],{"className":6066,"style":2640},[2639],[1811,6068,6070,6073],{"style":6069},"top:-3.4461em;",[1811,6071],{"className":6072,"style":2577},[2082],[1811,6074,6076],{"className":6075},[2087,2088,2089,2090],[1811,6077,6079,6124,6127],{"className":6078},[1874,2090],[1811,6080,6082,6085],{"className":6081},[1874,2090],[1811,6083,4519],{"className":6084},[1874,1875,2090],[1811,6086,6088],{"className":6087},[2061],[1811,6089,6091,6115],{"className":6090},[2065,2066],[1811,6092,6094,6112],{"className":6093},[2070],[1811,6095,6098],{"className":6096,"style":6097},[2074],"height:0.3281em;",[1811,6099,6101,6105],{"style":6100},"top:-2.357em;margin-left:0em;margin-right:0.0714em;",[1811,6102],{"className":6103,"style":6104},[2082],"height:2.5em;",[1811,6106,6109],{"className":6107},[2087,6108,3214,2090],"reset-size3",[1811,6110,1832],{"className":6111},[1874,1875,2090],[1811,6113,2107],{"className":6114},[2106],[1811,6116,6118],{"className":6117},[2070],[1811,6119,6122],{"className":6120,"style":6121},[2074],"height:0.143em;",[1811,6123],{},[1811,6125,2421],{"className":6126},[2263,2090],[1811,6128,5889],{"className":6129},[1874,1875,2090],[1811,6131,2107],{"className":6132},[2106],[1811,6134,6136],{"className":6135},[2070],[1811,6137,6140],{"className":6138,"style":6139},[2074],"height:0.345em;",[1811,6141],{},[1811,6143],{"className":6144},[2844,2557],[1811,6146,6148],{"className":6147},[2844],[1811,6149,6151],{"className":6150},[3213,5289],[1811,6152,6154,6174],{"className":6153},[2065,2066],[1811,6155,6157,6171],{"className":6156},[2070],[1811,6158,6160],{"className":6159,"style":5995},[2074],[1811,6161,6162,6165],{"style":5998},[1811,6163],{"className":6164,"style":6002},[2082],[1811,6166,6167],{"style":6005},[5325,6168,6169],{"xmlns":5327,"width":6008,"height":3090,"viewBox":6009},[5334,6170],{"d":6012},[1811,6172,2107],{"className":6173},[2106],[1811,6175,6177],{"className":6176},[2070],[1811,6178,6180],{"className":6179,"style":6022},[2074],[1811,6181],{},[1811,6183],{"className":6184,"style":1880},[1879],[1811,6186,5158],{"className":6187},[1884],[1811,6189],{"className":6190,"style":1880},[1879],[1811,6192,6194,6198],{"className":6193},[1865],[1811,6195],{"className":6196,"style":6197},[1869],"height:0.6944em;",[1811,6199,5899],{"className":6200,"style":6201},[1874,1875],"margin-right:0.0315em;","，则认为是异常值（典型 ",[1811,6204,6206,6225],{"className":6205},[1814],[1811,6207,6209],{"className":6208},[1818],[1820,6210,6211],{"xmlns":1822},[1824,6212,6213,6222],{},[1827,6214,6215,6217,6219],{},[1830,6216,5899],{},[1834,6218,1836],{},[1838,6220,6221],{},"3",[1854,6223,6224],{"encoding":1856},"k=3",[1811,6226,6228,6246],{"className":6227,"ariaHidden":1843},[1861],[1811,6229,6231,6234,6237,6240,6243],{"className":6230},[1865],[1811,6232],{"className":6233,"style":6197},[1869],[1811,6235,5899],{"className":6236,"style":6201},[1874,1875],[1811,6238],{"className":6239,"style":1880},[1879],[1811,6241,1836],{"className":6242},[1884],[1811,6244],{"className":6245,"style":1880},[1879],[1811,6247,6249,6252],{"className":6248},[1865],[1811,6250],{"className":6251,"style":2358},[1869],[1811,6253,6221],{"className":6254},[1874]," 或 ",[1811,6257,6259,6273],{"className":6258},[1814],[1811,6260,6262],{"className":6261},[1818],[1820,6263,6264],{"xmlns":1822},[1824,6265,6266,6271],{},[1827,6267,6268],{},[1838,6269,6270],{},"4",[1854,6272,6270],{"encoding":1856},[1811,6274,6276],{"className":6275,"ariaHidden":1843},[1861],[1811,6277,6279,6282],{"className":6278},[1865],[1811,6280],{"className":6281,"style":2358},[1869],[1811,6283,6270],{"className":6284},[1874],"）。",[1807,6287,6288],{},"类似于 winsorization，也可以把超出部分缩回到边界，或直接标记为异常。",[1799,6290,6292],{"id":6291},"_53-稳健统计视角与厚尾分布","5.3 稳健统计视角与厚尾分布",[1792,6294,6295],{},"大量实证研究表明，金融收益序列往往表现出：",[1804,6297,6298,6301,6304],{},[1807,6299,6300],{},"厚尾（heavy tails）：极端收益出现的频率远高于正态分布预期；",[1807,6302,6303],{},"非对称性（skewness）：收益分布呈显著偏度；",[1807,6305,6306],{},"波动聚集（volatility clustering）：大波动往往伴随后续一段时间的大波动。",[1792,6308,6309],{},"这意味着：",[1804,6311,6312,6315,6322],{},[1807,6313,6314],{},"依赖均值和方差的传统统计量在小样本和极端行情下并不稳健；",[1807,6316,6317,6318,6321],{},"实务中常配合",[3744,6319,6320],{},"稳健统计量","（如中位数、分位数、MAD）和基于分位数的截断方法；",[1807,6323,6324],{},"在风险建模中，使用 t 分布、偏态 t 分布或其他厚尾分布来拟合收益的尾部行为会更合理（见 Cont, 2001；Tsay, 2010）。",[1799,6326,6328],{"id":6327},"_53-业务规则与人工检查","5.3 业务规则与人工检查",[1804,6330,6331,6342],{},[1807,6332,6333,6334],{},"某些异常值可以通过业务知识直接判定：\n",[1804,6335,6336,6339],{},[1807,6337,6338],{},"如某股票价格低于最小价格单位；",[1807,6340,6341],{},"某些日期为停牌状态，价格和成交量应为特定模式；",[1807,6343,6344],{},"对于关键策略往往需要配合人工抽样检查，以避免黑箱处理带来隐患。",[4219,6346,6348],{"id":6347},"_6-时间对齐与重采样","6. 时间对齐与重采样",[1792,6350,6351],{},"不同数据源的频率和时间戳可能不一致，例如：",[1804,6353,6354,6357,6360],{},[1807,6355,6356],{},"分钟级价格 vs 日度财务数据；",[1807,6358,6359],{},"不同市场的交易时间不同；",[1807,6361,6362],{},"宏观数据按月\u002F季度更新。",[1792,6364,6365],{},"处理思路：",[4435,6367,6368,6382,6404],{},[1807,6369,6370,6373,6374],{},[3744,6371,6372],{},"统一时间频率","：",[1804,6375,6376,6379],{},[1807,6377,6378],{},"将高频数据聚合到低频（例如：分钟 → 日度 OHLC）；",[1807,6380,6381],{},"对日度数据，可按交易所日历对齐，处理非交易日（节假日）。",[1807,6383,6384,6373,6387],{},[3744,6385,6386],{},"对齐不同来源的数据",[1804,6388,6389],{},[1807,6390,6391,6392,6395,6396],{},"按“",[3744,6393,6394],{},"可获得时点","”对齐，避免使用未来信息：\n",[1804,6397,6398,6401],{},[1807,6399,6400],{},"财报数据往往在披露日之后才能使用；",[1807,6402,6403],{},"宏观数据公布有滞后。",[1807,6405,6406,6373,6409],{},[3744,6407,6408],{},"考虑时区与夏令时问题",[1804,6410,6411],{},[1807,6412,6413],{},"对跨市场策略，需统一到 UTC 或某一标准时区。",[1792,6415,6416,6417,6420,6421,6373],{},"从计量的角度看，避免前视偏差的关键在于明确",[3744,6418,6419],{},"信息集"," ",[1811,6422,6424,6444],{"className":6423},[1814],[1811,6425,6427],{"className":6426},[1818],[1820,6428,6429],{"xmlns":1822},[1824,6430,6431,6441],{},[1827,6432,6433],{},[2026,6434,6435,6439],{},[1830,6436,6438],{"mathvariant":6437},"script","F",[1830,6440,1940],{},[1854,6442,6443],{"encoding":1856},"\\mathcal{F}_t",[1811,6445,6447],{"className":6446,"ariaHidden":1843},[1861],[1811,6448,6450,6453],{"className":6449},[1865],[1811,6451],{"className":6452,"style":3781},[1869],[1811,6454,6456,6461],{"className":6455},[1874],[1811,6457,6438],{"className":6458,"style":6460},[1874,6459],"mathcal","margin-right:0.0993em;",[1811,6462,6464],{"className":6463},[2061],[1811,6465,6467,6488],{"className":6466},[2065,2066],[1811,6468,6470,6485],{"className":6469},[2070],[1811,6471,6473],{"className":6472,"style":3801},[2074],[1811,6474,6476,6479],{"style":6475},"top:-2.55em;margin-left:-0.0993em;margin-right:0.05em;",[1811,6477],{"className":6478,"style":2083},[2082],[1811,6480,6482],{"className":6481},[2087,2088,2089,2090],[1811,6483,1940],{"className":6484},[1874,1875,2090],[1811,6486,2107],{"className":6487},[2106],[1811,6489,6491],{"className":6490},[2070],[1811,6492,6494],{"className":6493,"style":3823},[2074],[1811,6495],{},[1804,6497,6498,6599],{},[1807,6499,6500,6569,6570,6598],{},[1811,6501,6503,6520],{"className":6502},[1814],[1811,6504,6506],{"className":6505},[1818],[1820,6507,6508],{"xmlns":1822},[1824,6509,6510,6518],{},[1827,6511,6512],{},[2026,6513,6514,6516],{},[1830,6515,6438],{"mathvariant":6437},[1830,6517,1940],{},[1854,6519,6443],{"encoding":1856},[1811,6521,6523],{"className":6522,"ariaHidden":1843},[1861],[1811,6524,6526,6529],{"className":6525},[1865],[1811,6527],{"className":6528,"style":3781},[1869],[1811,6530,6532,6535],{"className":6531},[1874],[1811,6533,6438],{"className":6534,"style":6460},[1874,6459],[1811,6536,6538],{"className":6537},[2061],[1811,6539,6541,6561],{"className":6540},[2065,2066],[1811,6542,6544,6558],{"className":6543},[2070],[1811,6545,6547],{"className":6546,"style":3801},[2074],[1811,6548,6549,6552],{"style":6475},[1811,6550],{"className":6551,"style":2083},[2082],[1811,6553,6555],{"className":6554},[2087,2088,2089,2090],[1811,6556,1940],{"className":6557},[1874,1875,2090],[1811,6559,2107],{"className":6560},[2106],[1811,6562,6564],{"className":6563},[2070],[1811,6565,6567],{"className":6566,"style":3823},[2074],[1811,6568],{}," 表示在时刻 ",[1811,6571,6573,6586],{"className":6572},[1814],[1811,6574,6576],{"className":6575},[1818],[1820,6577,6578],{"xmlns":1822},[1824,6579,6580,6584],{},[1827,6581,6582],{},[1830,6583,1940],{},[1854,6585,1940],{"encoding":1856},[1811,6587,6589],{"className":6588,"ariaHidden":1843},[1861],[1811,6590,6592,6595],{"className":6591},[1865],[1811,6593],{"className":6594,"style":1966},[1869],[1811,6596,1940],{"className":6597},[1874,1875]," 决策前，研究者\u002F投资者能够观察到的所有变量；",[1807,6600,6601,6602,6630,6631,6715,6716,6785,6786,6814],{},"任一在 ",[1811,6603,6605,6618],{"className":6604},[1814],[1811,6606,6608],{"className":6607},[1818],[1820,6609,6610],{"xmlns":1822},[1824,6611,6612,6616],{},[1827,6613,6614],{},[1830,6615,1940],{},[1854,6617,1940],{"encoding":1856},[1811,6619,6621],{"className":6620,"ariaHidden":1843},[1861],[1811,6622,6624,6627],{"className":6623},[1865],[1811,6625],{"className":6626,"style":1966},[1869],[1811,6628,1940],{"className":6629},[1874,1875]," 期使用的因子 ",[1811,6632,6634,6657],{"className":6633},[1814],[1811,6635,6637],{"className":6636},[1818],[1820,6638,6639],{"xmlns":1822},[1824,6640,6641,6655],{},[1827,6642,6643],{},[2026,6644,6645,6647],{},[1830,6646,3613],{},[1827,6648,6649,6651,6653],{},[1830,6650,1832],{},[1834,6652,1844],{"separator":1843},[1830,6654,1940],{},[1854,6656,3624],{"encoding":1856},[1811,6658,6660],{"className":6659,"ariaHidden":1843},[1861],[1811,6661,6663,6666],{"className":6662},[1865],[1811,6664],{"className":6665,"style":2051},[1869],[1811,6667,6669,6672],{"className":6668},[1874],[1811,6670,3613],{"className":6671,"style":3640},[1874,1875],[1811,6673,6675],{"className":6674},[2061],[1811,6676,6678,6707],{"className":6677},[2065,2066],[1811,6679,6681,6704],{"className":6680},[2070],[1811,6682,6684],{"className":6683,"style":2075},[2074],[1811,6685,6686,6689],{"style":3655},[1811,6687],{"className":6688,"style":2083},[2082],[1811,6690,6692],{"className":6691},[2087,2088,2089,2090],[1811,6693,6695,6698,6701],{"className":6694},[1874,2090],[1811,6696,1832],{"className":6697},[1874,1875,2090],[1811,6699,1844],{"className":6700},[1901,2090],[1811,6702,1940],{"className":6703},[1874,1875,2090],[1811,6705,2107],{"className":6706},[2106],[1811,6708,6710],{"className":6709},[2070],[1811,6711,6713],{"className":6712,"style":2114},[2074],[1811,6714],{},"，都应当是 ",[1811,6717,6719,6736],{"className":6718},[1814],[1811,6720,6722],{"className":6721},[1818],[1820,6723,6724],{"xmlns":1822},[1824,6725,6726,6734],{},[1827,6727,6728],{},[2026,6729,6730,6732],{},[1830,6731,6438],{"mathvariant":6437},[1830,6733,1940],{},[1854,6735,6443],{"encoding":1856},[1811,6737,6739],{"className":6738,"ariaHidden":1843},[1861],[1811,6740,6742,6745],{"className":6741},[1865],[1811,6743],{"className":6744,"style":3781},[1869],[1811,6746,6748,6751],{"className":6747},[1874],[1811,6749,6438],{"className":6750,"style":6460},[1874,6459],[1811,6752,6754],{"className":6753},[2061],[1811,6755,6757,6777],{"className":6756},[2065,2066],[1811,6758,6760,6774],{"className":6759},[2070],[1811,6761,6763],{"className":6762,"style":3801},[2074],[1811,6764,6765,6768],{"style":6475},[1811,6766],{"className":6767,"style":2083},[2082],[1811,6769,6771],{"className":6770},[2087,2088,2089,2090],[1811,6772,1940],{"className":6773},[1874,1875,2090],[1811,6775,2107],{"className":6776},[2106],[1811,6778,6780],{"className":6779},[2070],[1811,6781,6783],{"className":6782,"style":3823},[2074],[1811,6784],{}," 可测的，不能依赖于 ",[1811,6787,6789,6802],{"className":6788},[1814],[1811,6790,6792],{"className":6791},[1818],[1820,6793,6794],{"xmlns":1822},[1824,6795,6796,6800],{},[1827,6797,6798],{},[1830,6799,1940],{},[1854,6801,1940],{"encoding":1856},[1811,6803,6805],{"className":6804,"ariaHidden":1843},[1861],[1811,6806,6808,6811],{"className":6807},[1865],[1811,6809],{"className":6810,"style":1966},[1869],[1811,6812,1940],{"className":6813},[1874,1875]," 之后才会公布的信息。",[1792,6816,6817],{},"对于存在公布滞后的数据（如财报、宏观数据等），常用做法包括：",[1804,6819,6820,6983],{},[1807,6821,6822,6823,6892,6893,6982],{},"为每一条记录引入“可用日期” ",[1811,6824,6826,6846],{"className":6825},[1814],[1811,6827,6829],{"className":6828},[1818],[1820,6830,6831],{"xmlns":1822},[1824,6832,6833,6843],{},[1827,6834,6835],{},[6836,6837,6838,6840],"msup",{},[1830,6839,1940],{},[5190,6841,6842],{},"avail",[1854,6844,6845],{"encoding":1856},"t^{\\text{avail}}",[1811,6847,6849],{"className":6848,"ariaHidden":1843},[1861],[1811,6850,6852,6856],{"className":6851},[1865],[1811,6853],{"className":6854,"style":6855},[1869],"height:0.8491em;",[1811,6857,6859,6862],{"className":6858},[1874],[1811,6860,1940],{"className":6861},[1874,1875],[1811,6863,6865],{"className":6864},[2061],[1811,6866,6868],{"className":6867},[2065],[1811,6869,6871],{"className":6870},[2070],[1811,6872,6874],{"className":6873,"style":6855},[2074],[1811,6875,6877,6880],{"style":6876},"top:-3.063em;margin-right:0.05em;",[1811,6878],{"className":6879,"style":2083},[2082],[1811,6881,6883],{"className":6882},[2087,2088,2089,2090],[1811,6884,6886],{"className":6885},[1874,2090],[1811,6887,6889],{"className":6888},[1874,5808,2090],[1811,6890,6842],{"className":6891},[1874,2090],"，在回测中只允许使用满足 ",[1811,6894,6896,6919],{"className":6895},[1814],[1811,6897,6899],{"className":6898},[1818],[1820,6900,6901],{"xmlns":1822},[1824,6902,6903,6916],{},[1827,6904,6905,6911,6914],{},[6836,6906,6907,6909],{},[1830,6908,1940],{},[5190,6910,6842],{},[1834,6912,6913],{},"≤",[1830,6915,1940],{},[1854,6917,6918],{"encoding":1856},"t^{\\text{avail}} \\le t",[1811,6920,6922,6973],{"className":6921,"ariaHidden":1843},[1861],[1811,6923,6925,6929,6964,6967,6970],{"className":6924},[1865],[1811,6926],{"className":6927,"style":6928},[1869],"height:0.9851em;vertical-align:-0.136em;",[1811,6930,6932,6935],{"className":6931},[1874],[1811,6933,1940],{"className":6934},[1874,1875],[1811,6936,6938],{"className":6937},[2061],[1811,6939,6941],{"className":6940},[2065],[1811,6942,6944],{"className":6943},[2070],[1811,6945,6947],{"className":6946,"style":6855},[2074],[1811,6948,6949,6952],{"style":6876},[1811,6950],{"className":6951,"style":2083},[2082],[1811,6953,6955],{"className":6954},[2087,2088,2089,2090],[1811,6956,6958],{"className":6957},[1874,2090],[1811,6959,6961],{"className":6960},[1874,5808,2090],[1811,6962,6842],{"className":6963},[1874,2090],[1811,6965],{"className":6966,"style":1880},[1879],[1811,6968,6913],{"className":6969},[1884],[1811,6971],{"className":6972,"style":1880},[1879],[1811,6974,6976,6979],{"className":6975},[1865],[1811,6977],{"className":6978,"style":1966},[1869],[1811,6980,1940],{"className":6981},[1874,1875]," 的观测；",[1807,6984,6985,6986,7014,7015,7066],{},"或者引入固定滞后窗口，例如在 ",[1811,6987,6989,7002],{"className":6988},[1814],[1811,6990,6992],{"className":6991},[1818],[1820,6993,6994],{"xmlns":1822},[1824,6995,6996,7000],{},[1827,6997,6998],{},[1830,6999,1940],{},[1854,7001,1940],{"encoding":1856},[1811,7003,7005],{"className":7004,"ariaHidden":1843},[1861],[1811,7006,7008,7011],{"className":7007},[1865],[1811,7009],{"className":7010,"style":1966},[1869],[1811,7012,1940],{"className":7013},[1874,1875]," 期使用的是上一财年在 ",[1811,7016,7018,7036],{"className":7017},[1814],[1811,7019,7021],{"className":7020},[1818],[1820,7022,7023],{"xmlns":1822},[1824,7024,7025,7033],{},[1827,7026,7027,7029,7031],{},[1830,7028,1940],{},[1834,7030,2421],{},[1838,7032,1840],{},[1854,7034,7035],{"encoding":1856},"t-1",[1811,7037,7039,7057],{"className":7038,"ariaHidden":1843},[1861],[1811,7040,7042,7045,7048,7051,7054],{"className":7041},[1865],[1811,7043],{"className":7044,"style":2338},[1869],[1811,7046,1940],{"className":7047},[1874,1875],[1811,7049],{"className":7050,"style":2345},[1879],[1811,7052,2421],{"className":7053},[2263],[1811,7055],{"className":7056,"style":2345},[1879],[1811,7058,7060,7063],{"className":7059},[1865],[1811,7061],{"className":7062,"style":2358},[1869],[1811,7064,1840],{"className":7065},[1874]," 或更早已经披露的财务数据。",[1792,7068,7069],{},"关于公告日和交易日错配的系统处理方式，可参考 Campbell, Lo and MacKinlay (1997) 中对事件研究（event study）和公告效应的讨论。",[4219,7071,7073],{"id":7072},"_7-常见数据偏差与坑","7. 常见数据偏差与“坑”",[1799,7075,7077],{"id":7076},"_71-幸存者偏差survivorship-bias","7.1 幸存者偏差（Survivorship Bias）",[1792,7079,7080],{},"只使用当前仍在交易的资产（例如当前成分股），忽略已经退市\u002F破产\u002F剔除的历史资产，会导致：",[1804,7082,7083,7086],{},[1807,7084,7085],{},"对历史收益率估计过于乐观；",[1807,7087,7088],{},"对风险估计偏低。",[1792,7090,7091],{},"解决方向：",[1804,7093,7094,7105],{},[1807,7095,7096,7097,7100,7101,7104],{},"尽量使用",[3744,7098,7099],{},"当期成分","和",[3744,7102,7103],{},"历史成分变更记录","重构投资标的池；",[1807,7106,7107],{},"保留已经退市或长期停牌的资产记录。",[1799,7109,7111],{"id":7110},"_72-前视偏差look-ahead-bias","7.2 前视偏差（Look-ahead Bias）",[1792,7113,7114],{},"在回测中不小心使用了未来才会可见的数据：",[1804,7116,7117,7120],{},[1807,7118,7119],{},"例如用财报公布日之后才知道的数据去构建公布日前的因子；",[1807,7121,7122],{},"用当日收盘价构建需要在收盘前决策的信号。",[1792,7124,7125],{},"避免方法：",[1804,7127,7128,7134],{},[1807,7129,7130,7131,3594],{},"明确每个数据字段的",[3744,7132,7133],{},"可用时间（timestamp of availability）",[1807,7135,7136],{},"回测框架中强制按照“可见信息集”进行计算。",[1799,7138,7140],{"id":7139},"_73-数据挖掘偏差data-snooping","7.3 数据挖掘偏差（Data Snooping）",[1792,7142,7143],{},"在同一份数据上尝试大量策略和参数组合，很容易找到“看起来性能很好”的策略，但这些表现很可能只是随机噪声。表现为：",[1804,7145,7146,7149],{},[1807,7147,7148],{},"样本内夏普极高；",[1807,7150,7151],{},"样本外迅速失效。",[1792,7153,7154],{},"缓解方法包括：",[1804,7156,7157,7160,7163],{},[1807,7158,7159],{},"严格划分训练、验证、测试集；",[1807,7161,7162],{},"使用交叉验证、滚动窗口等方法；",[1807,7164,7165],{},"对策略数量和复杂度保持约束，并使用统计检验（如白检验、SPA 检验等）评估显著性（在本系列后续章节中会提到）。",[1792,7167,7168,7169,7172,7173,7176],{},"在更形式化的框架里，White (2000) 提出的 ",[3744,7170,7171],{},"Reality Check"," 和 Hansen (2005) 提出的 ",[3744,7174,7175],{},"Superior Predictive Ability (SPA)"," 检验，都试图回答这样一个问题：在同时比较大量候选策略时，样本中表现最好的那个策略，其超额收益是否在统计上显著优于基准，而不是数据挖掘的产物。本系列在“计量方法”章节会给出这些方法更直观的介绍。",[7178,7179],"hr",{},[4219,7181,7183],{"id":7182},"_8-自学手册把原始数据整理成研究面板","8. 自学手册：把原始数据整理成研究面板",[1799,7185,7187],{"id":7186},"_81-学习目标","8.1 学习目标",[1792,7189,7190],{},"学完本章后，你应当能够：",[4435,7192,7193,7196,7199,7202,7205],{},[1807,7194,7195],{},"区分市场数据、基本面数据、宏观数据和另类数据的用途；",[1807,7197,7198],{},"说明为什么每个字段都需要记录“数据日期”和“可用日期”；",[1807,7200,7201],{},"为一个股票多因子研究项目设计最小可用的数据字典；",[1807,7203,7204],{},"判断缺失值、异常值、幸存者偏差和前视偏差会怎样污染回测；",[1807,7206,7207],{},"把清洗规则写成可复查、可复现的研究记录。",[1799,7209,7211],{"id":7210},"_82-研究场景","8.2 研究场景",[1792,7213,7214],{},"假设你加入一个股票量化团队，第一项任务是验证“盈利能力改善的股票未来一个月收益更高”。你拿到了日度价格、成交量、行业分类和季度财报数据。研究经理不会先问模型，而会先问：",[1804,7216,7217,7220,7223,7226],{},[1807,7218,7219],{},"每只股票在每个调仓日是否真实可交易？",[1807,7221,7222],{},"当天使用的财报字段在当时是否已经披露？",[1807,7224,7225],{},"缺失财报和停牌股票是被删除、填充，还是单独标记？",[1807,7227,7228],{},"任何人能否用相同数据版本复现你的研究面板？",[1792,7230,7231,7232,7236],{},"这就是本章的核心场景：在研究开始前，先构造一个可信的 ",[7233,7234,7235],"code",{},"asset-date"," 面板。",[1799,7238,7240],{"id":7239},"_83-定义与工作流逻辑","8.3 定义与工作流逻辑",[7242,7243,7244,7260],"table",{},[7245,7246,7247],"thead",{},[7248,7249,7250,7254,7257],"tr",{},[7251,7252,7253],"th",{},"步骤",[7251,7255,7256],{},"关键问题",[7251,7258,7259],{},"典型产出",[7261,7262,7263,7346,7357,7444,7455,7699],"tbody",{},[7248,7264,7265,7269,7272],{},[7266,7267,7268],"td",{},"1. 定义样本宇宙",[7266,7270,7271],{},"哪些资产在每个日期属于可研究、可交易范围？",[7266,7273,7274,7275],{},"历史股票池 ",[1811,7276,7278,7297],{"className":7277},[1814],[1811,7279,7281],{"className":7280},[1818],[1820,7282,7283],{"xmlns":1822},[1824,7284,7285,7294],{},[1827,7286,7287],{},[2026,7288,7289,7292],{},[1830,7290,7291],{"mathvariant":6437},"U",[1830,7293,1940],{},[1854,7295,7296],{"encoding":1856},"\\mathcal{U}_t",[1811,7298,7300],{"className":7299,"ariaHidden":1843},[1861],[1811,7301,7303,7306],{"className":7302},[1865],[1811,7304],{"className":7305,"style":3781},[1869],[1811,7307,7309,7312],{"className":7308},[1874],[1811,7310,7291],{"className":7311,"style":6460},[1874,6459],[1811,7313,7315],{"className":7314},[2061],[1811,7316,7318,7338],{"className":7317},[2065,2066],[1811,7319,7321,7335],{"className":7320},[2070],[1811,7322,7324],{"className":7323,"style":3801},[2074],[1811,7325,7326,7329],{"style":6475},[1811,7327],{"className":7328,"style":2083},[2082],[1811,7330,7332],{"className":7331},[2087,2088,2089,2090],[1811,7333,1940],{"className":7334},[1874,1875,2090],[1811,7336,2107],{"className":7337},[2106],[1811,7339,7341],{"className":7340},[2070],[1811,7342,7344],{"className":7343,"style":3823},[2074],[1811,7345],{},[7248,7347,7348,7351,7354],{},[7266,7349,7350],{},"2. 标准化原始字段",[7266,7352,7353],{},"价格、成交量、财报字段的单位和口径是否一致？",[7266,7355,7356],{},"数据字典",[7248,7358,7359,7362,7435],{},[7266,7360,7361],{},"3. 标记可用日期",[7266,7363,7364,7365,7434],{},"信息什么时候真正进入 ",[1811,7366,7368,7385],{"className":7367},[1814],[1811,7369,7371],{"className":7370},[1818],[1820,7372,7373],{"xmlns":1822},[1824,7374,7375,7383],{},[1827,7376,7377],{},[2026,7378,7379,7381],{},[1830,7380,6438],{"mathvariant":6437},[1830,7382,1940],{},[1854,7384,6443],{"encoding":1856},[1811,7386,7388],{"className":7387,"ariaHidden":1843},[1861],[1811,7389,7391,7394],{"className":7390},[1865],[1811,7392],{"className":7393,"style":3781},[1869],[1811,7395,7397,7400],{"className":7396},[1874],[1811,7398,6438],{"className":7399,"style":6460},[1874,6459],[1811,7401,7403],{"className":7402},[2061],[1811,7404,7406,7426],{"className":7405},[2065,2066],[1811,7407,7409,7423],{"className":7408},[2070],[1811,7410,7412],{"className":7411,"style":3801},[2074],[1811,7413,7414,7417],{"style":6475},[1811,7415],{"className":7416,"style":2083},[2082],[1811,7418,7420],{"className":7419},[2087,2088,2089,2090],[1811,7421,1940],{"className":7422},[1874,1875,2090],[1811,7424,2107],{"className":7425},[2106],[1811,7427,7429],{"className":7428},[2070],[1811,7430,7432],{"className":7431,"style":3823},[2074],[1811,7433],{},"？",[7266,7436,7437,7440,7441],{},[7233,7438,7439],{},"as_of_date"," \u002F ",[7233,7442,7443],{},"available_date",[7248,7445,7446,7449,7452],{},[7266,7447,7448],{},"4. 清洗缺失与异常",[7266,7450,7451],{},"缺失是否有业务含义？极端值是真实事件还是错误？",[7266,7453,7454],{},"清洗日志",[7248,7456,7457,7460,7463],{},[7266,7458,7459],{},"5. 构造研究面板",[7266,7461,7462],{},"收益、特征和宏观状态是否按同一时间轴对齐？",[7266,7464,7465],{},[1811,7466,7468,7526],{"className":7467},[1814],[1811,7469,7471],{"className":7470},[1818],[1820,7472,7473],{"xmlns":1822},[1824,7474,7475,7523],{},[1827,7476,7477,7479,7481,7497,7499,7511,7513,7519,7521],{},[1834,7478,3847],{"stretchy":3089},[1834,7480,3091],{"stretchy":3089},[2026,7482,7483,7485],{},[1830,7484,2194],{},[1827,7486,7487,7489,7491,7493,7495],{},[1830,7488,1832],{},[1834,7490,1844],{"separator":1843},[1830,7492,1940],{},[1834,7494,2205],{},[1838,7496,1840],{},[1834,7498,1844],{"separator":1843},[2026,7500,7501,7503],{},[1830,7502,3613],{},[1827,7504,7505,7507,7509],{},[1830,7506,1832],{},[1834,7508,1844],{"separator":1843},[1830,7510,1940],{},[1834,7512,1844],{"separator":1843},[2026,7514,7515,7517],{},[1830,7516,3766],{},[1830,7518,1940],{},[1834,7520,3114],{"stretchy":3089},[1834,7522,3895],{"stretchy":3089},[1854,7524,7525],{"encoding":1856},"\\{(R_{i,t+1},X_{i,t},Z_t)\\}",[1811,7527,7529],{"className":7528,"ariaHidden":1843},[1861],[1811,7530,7532,7535,7539,7594,7597,7600,7649,7652,7655,7695],{"className":7531},[1865],[1811,7533],{"className":7534,"style":3346},[1869],[1811,7536,7538],{"className":7537},[2556],"{(",[1811,7540,7542,7545],{"className":7541},[1874],[1811,7543,2194],{"className":7544,"style":2226},[1874,1875],[1811,7546,7548],{"className":7547},[2061],[1811,7549,7551,7586],{"className":7550},[2065,2066],[1811,7552,7554,7583],{"className":7553},[2070],[1811,7555,7557],{"className":7556,"style":2075},[2074],[1811,7558,7559,7562],{"style":2241},[1811,7560],{"className":7561,"style":2083},[2082],[1811,7563,7565],{"className":7564},[2087,2088,2089,2090],[1811,7566,7568,7571,7574,7577,7580],{"className":7567},[1874,2090],[1811,7569,1832],{"className":7570},[1874,1875,2090],[1811,7572,1844],{"className":7573},[1901,2090],[1811,7575,1940],{"className":7576},[1874,1875,2090],[1811,7578,2205],{"className":7579},[2263,2090],[1811,7581,1840],{"className":7582},[1874,2090],[1811,7584,2107],{"className":7585},[2106],[1811,7587,7589],{"className":7588},[2070],[1811,7590,7592],{"className":7591,"style":2114},[2074],[1811,7593],{},[1811,7595,1844],{"className":7596},[1901],[1811,7598],{"className":7599,"style":1905},[1879],[1811,7601,7603,7606],{"className":7602},[1874],[1811,7604,3613],{"className":7605,"style":3640},[1874,1875],[1811,7607,7609],{"className":7608},[2061],[1811,7610,7612,7641],{"className":7611},[2065,2066],[1811,7613,7615,7638],{"className":7614},[2070],[1811,7616,7618],{"className":7617,"style":2075},[2074],[1811,7619,7620,7623],{"style":3655},[1811,7621],{"className":7622,"style":2083},[2082],[1811,7624,7626],{"className":7625},[2087,2088,2089,2090],[1811,7627,7629,7632,7635],{"className":7628},[1874,2090],[1811,7630,1832],{"className":7631},[1874,1875,2090],[1811,7633,1844],{"className":7634},[1901,2090],[1811,7636,1940],{"className":7637},[1874,1875,2090],[1811,7639,2107],{"className":7640},[2106],[1811,7642,7644],{"className":7643},[2070],[1811,7645,7647],{"className":7646,"style":2114},[2074],[1811,7648],{},[1811,7650,1844],{"className":7651},[1901],[1811,7653],{"className":7654,"style":1905},[1879],[1811,7656,7658,7661],{"className":7657},[1874],[1811,7659,3766],{"className":7660,"style":3788},[1874,1875],[1811,7662,7664],{"className":7663},[2061],[1811,7665,7667,7687],{"className":7666},[2065,2066],[1811,7668,7670,7684],{"className":7669},[2070],[1811,7671,7673],{"className":7672,"style":3801},[2074],[1811,7674,7675,7678],{"style":3804},[1811,7676],{"className":7677,"style":2083},[2082],[1811,7679,7681],{"className":7680},[2087,2088,2089,2090],[1811,7682,1940],{"className":7683},[1874,1875,2090],[1811,7685,2107],{"className":7686},[2106],[1811,7688,7690],{"className":7689},[2070],[1811,7691,7693],{"className":7692,"style":3823},[2074],[1811,7694],{},[1811,7696,7698],{"className":7697},[2844],")}",[7248,7700,7701,7704,7707],{},[7266,7702,7703],{},"6. 做偏差审计",[7266,7705,7706],{},"是否引入幸存者偏差、前视偏差或数据挖掘偏差？",[7266,7708,7709],{},"数据审计清单",[1792,7711,7712,7713],{},"一个实用原则是：",[3744,7714,7715],{},"凡是会影响交易决策的字段，都必须能回答“它在当时是否可见”。",[1799,7717,7719],{"id":7718},"_84-迷你案例季度-roe-因子的可用日期","8.4 迷你案例：季度 ROE 因子的可用日期",[1792,7721,7722],{},"你要在每月末用最新 ROE 构建质量因子。某公司 2023Q4 财报的报告期结束日是 2023-12-31，但披露日是 2024-03-28。正确做法是：",[4435,7724,7725,7735,7738,7810,7813],{},[1807,7726,7727,7728,7731,7732,3594],{},"在数据表中保留 ",[7233,7729,7730],{},"period_end = 2023-12-31"," 和 ",[7233,7733,7734],{},"available_date = 2024-03-28",[1807,7736,7737],{},"2024-01-31 和 2024-02-29 调仓时不能使用该 ROE；",[1807,7739,7740,7741,3594],{},"只有当调仓日不早于 2024-03-28，且交易系统在决策前已经收到数据时，才允许纳入 ",[1811,7742,7744,7761],{"className":7743},[1814],[1811,7745,7747],{"className":7746},[1818],[1820,7748,7749],{"xmlns":1822},[1824,7750,7751,7759],{},[1827,7752,7753],{},[2026,7754,7755,7757],{},[1830,7756,6438],{"mathvariant":6437},[1830,7758,1940],{},[1854,7760,6443],{"encoding":1856},[1811,7762,7764],{"className":7763,"ariaHidden":1843},[1861],[1811,7765,7767,7770],{"className":7766},[1865],[1811,7768],{"className":7769,"style":3781},[1869],[1811,7771,7773,7776],{"className":7772},[1874],[1811,7774,6438],{"className":7775,"style":6460},[1874,6459],[1811,7777,7779],{"className":7778},[2061],[1811,7780,7782,7802],{"className":7781},[2065,2066],[1811,7783,7785,7799],{"className":7784},[2070],[1811,7786,7788],{"className":7787,"style":3801},[2074],[1811,7789,7790,7793],{"style":6475},[1811,7791],{"className":7792,"style":2083},[2082],[1811,7794,7796],{"className":7795},[2087,2088,2089,2090],[1811,7797,1940],{"className":7798},[1874,1875,2090],[1811,7800,2107],{"className":7801},[2106],[1811,7803,7805],{"className":7804},[2070],[1811,7806,7808],{"className":7807,"style":3823},[2074],[1811,7809],{},[1807,7811,7812],{},"若月末调仓发生在 2024-03-29，可使用该 ROE；若调仓发生在披露日前，则只能使用上一期已披露 ROE；",[1807,7814,7815],{},"在研究记录中说明这一滞后规则，并在回测代码中统一执行。",[7817,7818],"pyodide",{"code64":7819,"layout":7820,"locale":7,"title":7821},"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","vertical","按 available_date 重建当时可见财报",[1792,7823,7824,7825,7828],{},"前两次调仓只能看到 2023Q3 的 12%；3 月 29 日才可使用 2023Q4 的 18%。若直接按 ",[7233,7826,7827],{},"period"," 合并，前两个月会被未来信息污染。",[1799,7830,7832],{"id":7831},"_85-常见错误与研究陷阱","8.5 常见错误与研究陷阱",[1804,7834,7835,7841,7847,7853,7859],{},[1807,7836,7837,7840],{},[3744,7838,7839],{},"用报告期替代可用日期","：把 2023Q4 财报当作 2023-12-31 已知，会直接产生前视偏差。",[1807,7842,7843,7846],{},[3744,7844,7845],{},"只保留当前股票池","：历史中退市、并购、长期停牌的股票消失，会抬高收益、压低风险。",[1807,7848,7849,7852],{},[3744,7850,7851],{},"过度填充缺失值","：把长期缺失的财务指标用行业中位数填满，可能掩盖“披露质量差”这一风险信号。",[1807,7854,7855,7858],{},[3744,7856,7857],{},"把异常收益全删掉","：极端值既可能是录入错误，也可能是真实危机事件。先标记、抽样核查，再决定处理方式。",[1807,7860,7861,7864],{},[3744,7862,7863],{},"清洗规则写在临时代码里","：没有数据版本和清洗日志，后续因子失效时无法判断是策略问题还是数据问题。",[1799,7866,7868],{"id":7867},"_86-自测题与答案提示","8.6 自测题与答案提示",[4435,7870,7871,7944,7947,7950],{},[1807,7872,7873,7874,7943],{},"为什么财报数据要同时记录报告期结束日和实际披露日？\n答案提示：报告期描述经济归属，披露日决定信息何时进入 ",[1811,7875,7877,7894],{"className":7876},[1814],[1811,7878,7880],{"className":7879},[1818],[1820,7881,7882],{"xmlns":1822},[1824,7883,7884,7892],{},[1827,7885,7886],{},[2026,7887,7888,7890],{},[1830,7889,6438],{"mathvariant":6437},[1830,7891,1940],{},[1854,7893,6443],{"encoding":1856},[1811,7895,7897],{"className":7896,"ariaHidden":1843},[1861],[1811,7898,7900,7903],{"className":7899},[1865],[1811,7901],{"className":7902,"style":3781},[1869],[1811,7904,7906,7909],{"className":7905},[1874],[1811,7907,6438],{"className":7908,"style":6460},[1874,6459],[1811,7910,7912],{"className":7911},[2061],[1811,7913,7915,7935],{"className":7914},[2065,2066],[1811,7916,7918,7932],{"className":7917},[2070],[1811,7919,7921],{"className":7920,"style":3801},[2074],[1811,7922,7923,7926],{"style":6475},[1811,7924],{"className":7925,"style":2083},[2082],[1811,7927,7929],{"className":7928},[2087,2088,2089,2090],[1811,7930,1940],{"className":7931},[1874,1875,2090],[1811,7933,2107],{"className":7934},[2106],[1811,7936,7938],{"className":7937},[2070],[1811,7939,7941],{"className":7940,"style":3823},[2074],[1811,7942],{},"；两者混用会造成前视偏差。",[1807,7945,7946],{},"如果某股票在样本期后半段退市，回测中应如何处理？\n答案提示：应保留退市前历史和退市事件处理规则，不能因为当前不可交易就从历史样本中删除。",[1807,7948,7949],{},"分位数去极值和删除极端值有什么区别？\n答案提示：去极值保留样本但压缩尾部影响；删除会改变样本构成，若极端值具有系统性会引入选择偏差。",[1807,7951,7952],{},"哪些迹象说明缺失值可能不是 MCAR？\n答案提示：缺失集中在小市值、亏损、停牌或特定行业公司；缺失本身与风险和收益有关。",[1799,7954,7956],{"id":7955},"_87-小结与过渡","8.7 小结与过渡",[1792,7958,7959],{},"数据章节的核心不是“把表填满”，而是建立一个能抵御偏差的研究面板：样本宇宙要按历史还原，字段要按可用日期对齐，清洗规则要可追溯。下一章会在这个面板之上构建因子与交易信号；如果数据地基不稳，后续任何 IC、分组收益和回测指标都会失去可信度。",[7178,7961],{},[1792,7963,7964,7965,7967],{},"下一章将基于清洗后的数据，介绍如何从原始数据中构建",[3744,7966,1747],{},"，并进行初步有效性检验。",{"title":10,"searchDepth":7969,"depth":7969,"links":7970},2,[7971,7973,7979,7980,7981,7984,7990,7991,7996],{"id":1801,"depth":7972,"text":1802},3,{"id":4221,"depth":7969,"text":4222,"children":7974},[7975,7976,7977,7978],{"id":4228,"depth":7972,"text":4229},{"id":4287,"depth":7972,"text":4288},{"id":4318,"depth":7972,"text":4319},{"id":4340,"depth":7972,"text":4341},{"id":4365,"depth":7969,"text":4366},{"id":4423,"depth":7969,"text":4424},{"id":4454,"depth":7969,"text":4455,"children":7982},[7983],{"id":4769,"depth":7972,"text":4770},{"id":4826,"depth":7969,"text":4827,"children":7985},[7986,7987,7988,7989],{"id":4847,"depth":7972,"text":4848},{"id":5839,"depth":7972,"text":5840},{"id":6291,"depth":7972,"text":6292},{"id":6327,"depth":7972,"text":6328},{"id":6347,"depth":7969,"text":6348},{"id":7072,"depth":7969,"text":7073,"children":7992},[7993,7994,7995],{"id":7076,"depth":7972,"text":7077},{"id":7110,"depth":7972,"text":7111},{"id":7139,"depth":7972,"text":7140},{"id":7182,"depth":7969,"text":7183,"children":7997},[7998,7999,8000,8001,8002,8003,8004],{"id":7186,"depth":7972,"text":7187},{"id":7210,"depth":7972,"text":7211},{"id":7239,"depth":7972,"text":7240},{"id":7718,"depth":7972,"text":7719},{"id":7831,"depth":7972,"text":7832},{"id":7867,"depth":7972,"text":7868},{"id":7955,"depth":7972,"text":7956},"构造 point-in-time 研究面板，审计价格、财务、另类数据的可用时点、版本和偏差。","md",{"sidebar":8008},{"order":8009},1,true,{"title":1743,"description":8005},"Qpau6SsZ9_uRGt6RWAjFK0BQZOrMRH1X3mH_l3_PcHo",[8014,8016],{"title":1737,"path":1738,"stem":1739,"description":8015,"children":-1},"一门以时点数据、样本外证据、交易成本和可复现研究为主线的量化投资课程。",{"title":1747,"path":1748,"stem":1749,"description":8017,"children":-1},"从经济假设构造、标准化、中性化并验证横截面因子和可交易信号。",1785754758667]