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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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",[1805,2038,2040,2059],{"className":2039},[1808],[1805,2041,2043],{"className":2042},[1812],[1814,2044,2045],{"xmlns":1816},[1818,2046,2047,2056],{},[1821,2048,2049],{},[1864,2050,2051,2054],{},[1824,2052,2053],{},"Y",[1824,2055,1826],{},[1828,2057,2058],{"encoding":1830},"Y_t",[1805,2060,2062],{"className":2061,"ariaHidden":1835},[1834],[1805,2063,2065,2068],{"className":2064},[1839],[1805,2066],{"className":2067,"style":1893},[1843],[1805,2069,2071,2075],{"className":2070},[1848],[1805,2072,2053],{"className":2073,"style":2074},[1848,1849],"margin-right:0.2222em;",[1805,2076,2078],{"className":2077},[1904],[1805,2079,2081,2102],{"className":2080},[1908,1909],[1805,2082,2084,2099],{"className":2083},[1913],[1805,2085,2087],{"className":2086,"style":2012},[1917],[1805,2088,2090,2093],{"style":2089},"top:-2.55em;margin-left:-0.2222em;margin-right:0.05em;",[1805,2091],{"className":2092,"style":1926},[1925],[1805,2094,2096],{"className":2095},[1930,1931,1932,1933],[1805,2097,1826],{"className":2098},[1848,1849,1933],[1805,2100,1951],{"className":2101},[1950],[1805,2103,2105],{"className":2104},[1913],[1805,2106,2108],{"className":2107,"style":1958},[1917],[1805,2109],{},"（成交、收益、风险等）。用符号表示就是一个策略–环境闭环：",[1805,2112,2115],{"className":2113},[2114],"katex-display",[1805,2116,2118,2220],{"className":2117},[1808],[1805,2119,2121],{"className":2120},[1812],[1814,2122,2124],{"xmlns":1816,"display":2123},"block",[1818,2125,2126,2217],{},[1821,2127,2128,2134,2137,2145,2149,2161,2164,2177,2180,2182,2186,2192,2194,2198,2200,2206,2209,2213,2215],{},[1864,2129,2130,2132],{},[1824,2131,1978],{},[1824,2133,1826],{},[1876,2135,2136],{},"=",[1864,2138,2139,2142],{},[1824,2140,2141],{},"π",[1824,2143,2144],{},"θ",[1876,2146,2148],{"stretchy":2147},"false","(",[1864,2150,2151,2153],{},[1824,2152,1868],{},[1821,2154,2155,2157,2159],{},[1872,2156,1874],{},[1876,2158,1878],{},[1824,2160,1826],{},[1876,2162,2163],{"separator":1835},",",[1864,2165,2166,2169],{},[1824,2167,2168],{},"Z",[1821,2170,2171,2173,2175],{},[1872,2172,1874],{},[1876,2174,1878],{},[1824,2176,1826],{},[1876,2178,2179],{"stretchy":2147},")",[1876,2181,2163],{"separator":1835},[2183,2184],"mspace",{"width":2185},"2em",[1864,2187,2188,2190],{},[1824,2189,2053],{},[1824,2191,1826],{},[1876,2193,2136],{},[1824,2195,2197],{"mathvariant":2196},"script","M",[1876,2199,2148],{"stretchy":2147},[1864,2201,2202,2204],{},[1824,2203,1978],{},[1824,2205,1826],{},[1876,2207,2208],{"separator":1835},";",[2210,2211,2212],"mtext",{},"market",[1876,2214,2179],{"stretchy":2147},[1876,2216,2163],{"separator":1835},[1828,2218,2219],{"encoding":1830},"u_t = \\pi_\\theta(X_{0:t}, Z_{0:t}), \\qquad Y_t = \\mathcal{M}(u_t; \\text{market}),",[1805,2221,2223,2279,2505],{"className":2222,"ariaHidden":1835},[1834],[1805,2224,2226,2229,2269,2273,2276],{"className":2225},[1839],[1805,2227],{"className":2228,"style":1993},[1843],[1805,2230,2232,2235],{"className":2231},[1848],[1805,2233,1978],{"className":2234},[1848,1849],[1805,2236,2238],{"className":2237},[1904],[1805,2239,2241,2261],{"className":2240},[1908,1909],[1805,2242,2244,2258],{"className":2243},[1913],[1805,2245,2247],{"className":2246,"style":2012},[1917],[1805,2248,2249,2252],{"style":2015},[1805,2250],{"className":2251,"style":1926},[1925],[1805,2253,2255],{"className":2254},[1930,1931,1932,1933],[1805,2256,1826],{"className":2257},[1848,1849,1933],[1805,2259,1951],{"className":2260},[1950],[1805,2262,2264],{"className":2263},[1913],[1805,2265,2267],{"className":2266,"style":1958},[1917],[1805,2268],{},[1805,2270],{"className":2271,"style":2272},[2183],"margin-right:0.2778em;",[1805,2274,2136],{"className":2275},[1943],[1805,2277],{"className":2278,"style":2272},[2183],[1805,2280,2282,2286,2330,2334,2383,2387,2391,2442,2446,2449,2453,2456,2496,2499,2502],{"className":2281},[1839],[1805,2283],{"className":2284,"style":2285},[1843],"height:1em;vertical-align:-0.25em;",[1805,2287,2289,2293],{"className":2288},[1848],[1805,2290,2141],{"className":2291,"style":2292},[1848,1849],"margin-right:0.0359em;",[1805,2294,2296],{"className":2295},[1904],[1805,2297,2299,2322],{"className":2298},[1908,1909],[1805,2300,2302,2319],{"className":2301},[1913],[1805,2303,2306],{"className":2304,"style":2305},[1917],"height:0.3361em;",[1805,2307,2309,2312],{"style":2308},"top:-2.55em;margin-left:-0.0359em;margin-right:0.05em;",[1805,2310],{"className":2311,"style":1926},[1925],[1805,2313,2315],{"className":2314},[1930,1931,1932,1933],[1805,2316,2144],{"className":2317,"style":2318},[1848,1849,1933],"margin-right:0.0278em;",[1805,2320,1951],{"className":2321},[1950],[1805,2323,2325],{"className":2324},[1913],[1805,2326,2328],{"className":2327,"style":1958},[1917],[1805,2329],{},[1805,2331,2148],{"className":2332},[2333],"mopen",[1805,2335,2337,2340],{"className":2336},[1848],[1805,2338,1868],{"className":2339,"style":1900},[1848,1849],[1805,2341,2343],{"className":2342},[1904],[1805,2344,2346,2375],{"className":2345},[1908,1909],[1805,2347,2349,2372],{"className":2348},[1913],[1805,2350,2352],{"className":2351,"style":1918},[1917],[1805,2353,2354,2357],{"style":1921},[1805,2355],{"className":2356,"style":1926},[1925],[1805,2358,2360],{"className":2359},[1930,1931,1932,1933],[1805,2361,2363,2366,2369],{"className":2362},[1848,1933],[1805,2364,1874],{"className":2365},[1848,1933],[1805,2367,1878],{"className":2368},[1943,1933],[1805,2370,1826],{"className":2371},[1848,1849,1933],[1805,2373,1951],{"className":2374},[1950],[1805,2376,2378],{"className":2377},[1913],[1805,2379,2381],{"className":2380,"style":1958},[1917],[1805,2382],{},[1805,2384,2163],{"className":2385},[2386],"mpunct",[1805,2388],{"className":2389,"style":2390},[2183],"margin-right:0.1667em;",[1805,2392,2394,2398],{"className":2393},[1848],[1805,2395,2168],{"className":2396,"style":2397},[1848,1849],"margin-right:0.0715em;",[1805,2399,2401],{"className":2400},[1904],[1805,2402,2404,2434],{"className":2403},[1908,1909],[1805,2405,2407,2431],{"className":2406},[1913],[1805,2408,2410],{"className":2409,"style":1918},[1917],[1805,2411,2413,2416],{"style":2412},"top:-2.55em;margin-left:-0.0715em;margin-right:0.05em;",[1805,2414],{"className":2415,"style":1926},[1925],[1805,2417,2419],{"className":2418},[1930,1931,1932,1933],[1805,2420,2422,2425,2428],{"className":2421},[1848,1933],[1805,2423,1874],{"className":2424},[1848,1933],[1805,2426,1878],{"className":2427},[1943,1933],[1805,2429,1826],{"className":2430},[1848,1849,1933],[1805,2432,1951],{"className":2433},[1950],[1805,2435,2437],{"className":2436},[1913],[1805,2438,2440],{"className":2439,"style":1958},[1917],[1805,2441],{},[1805,2443,2179],{"className":2444},[2445],"mclose",[1805,2447,2163],{"className":2448},[2386],[1805,2450],{"className":2451,"style":2452},[2183],"margin-right:2em;",[1805,2454],{"className":2455,"style":2390},[2183],[1805,2457,2459,2462],{"className":2458},[1848],[1805,2460,2053],{"className":2461,"style":2074},[1848,1849],[1805,2463,2465],{"className":2464},[1904],[1805,2466,2468,2488],{"className":2467},[1908,1909],[1805,2469,2471,2485],{"className":2470},[1913],[1805,2472,2474],{"className":2473,"style":2012},[1917],[1805,2475,2476,2479],{"style":2089},[1805,2477],{"className":2478,"style":1926},[1925],[1805,2480,2482],{"className":2481},[1930,1931,1932,1933],[1805,2483,1826],{"className":2484},[1848,1849,1933],[1805,2486,1951],{"className":2487},[1950],[1805,2489,2491],{"className":2490},[1913],[1805,2492,2494],{"className":2493,"style":1958},[1917],[1805,2495],{},[1805,2497],{"className":2498,"style":2272},[2183],[1805,2500,2136],{"className":2501},[1943],[1805,2503],{"className":2504,"style":2272},[2183],[1805,2506,2508,2511,2515,2518,2558,2561,256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是由研究平台训练出来、在生产系统中运行的“策略 + 风控 + 执行”组合映射，",[1805,2652,2654,2672],{"className":2653},[1808],[1805,2655,2657],{"className":2656},[1812],[1814,2658,2659],{"xmlns":1816},[1818,2660,2661,2669],{},[1821,2662,2663],{},[1864,2664,2665,2667],{},[1824,2666,2168],{},[1824,2668,1826],{},[1828,2670,2671],{"encoding":1830},"Z_t",[1805,2673,2675],{"className":2674,"ariaHidden":1835},[1834],[1805,2676,2678,2681],{"className":2677},[1839],[1805,2679],{"className":2680,"style":1893},[1843],[1805,2682,2684,2687],{"className":2683},[1848],[1805,2685,2168],{"className":2686,"style":2397},[1848,1849],[1805,2688,2690],{"className":2689},[1904],[1805,2691,2693,2713],{"className":2692},[1908,1909],[1805,2694,2696,2710],{"className":2695},[1913],[1805,2697,2699],{"className":2698,"style":2012},[1917],[1805,2700,2701,2704],{"style":2412},[1805,2702],{"className":2703,"style":1926},[1925],[1805,2705,2707],{"className":2706},[1930,1931,1932,1933],[1805,2708,1826],{"className":2709},[1848,1849,1933],[1805,2711,1951],{"className":2712},[1950],[1805,2714,2716],{"className":2715},[1913],[1805,2717,2719],{"className":2718,"style":1958},[1917],[1805,2720],{}," 代表内部状态（如风控限额、系统负载）。",[1793,2723,2724,2725,2795,2796,2865,2866,2896,2897,2979],{},"本章的目标，是把前几章的理论和统计工具放在这样一个工程系统的框架下去理解：数据平台决定 ",[1805,2726,2728,2746],{"className":2727},[1808],[1805,2729,2731],{"className":2730},[1812],[1814,2732,2733],{"xmlns":1816},[1818,2734,2735,2743],{},[1821,2736,2737],{},[1864,2738,2739,2741],{},[1824,2740,1868],{},[1824,2742,1826],{},[1828,2744,2745],{"encoding":1830},"X_t",[1805,2747,2749],{"className":2748,"ariaHidden":1835},[1834],[1805,2750,2752,2755],{"className":2751},[1839],[1805,2753],{"className":2754,"style":1893},[1843],[1805,2756,2758,2761],{"className":2757},[1848],[1805,2759,1868],{"className":2760,"style":1900},[1848,1849],[1805,2762,2764],{"className":2763},[1904],[1805,2765,2767,2787],{"className":2766},[1908,1909],[1805,2768,2770,2784],{"className":2769},[1913],[1805,2771,2773],{"className":2772,"style":2012},[1917],[1805,2774,2775,2778],{"style":1921},[1805,2776],{"className":2777,"style":1926},[1925],[1805,2779,2781],{"className":2780},[1930,1931,1932,1933],[1805,2782,1826],{"className":2783},[1848,1849,1933],[1805,2785,1951],{"className":2786},[1950],[1805,2788,2790],{"className":2789},[1913],[1805,2791,2793],{"className":2792,"style":1958},[1917],[1805,2794],{}," 的质量和可用性，研究平台决定 ",[1805,2797,2799,2816],{"className":2798},[1808],[1805,2800,2802],{"className":2801},[1812],[1814,2803,2804],{"xmlns":1816},[1818,2805,2806,2814],{},[1821,2807,2808],{},[1864,2809,2810,2812],{},[1824,2811,2141],{},[1824,2813,2144],{},[1828,2815,2600],{"encoding":1830},[1805,2817,2819],{"className":2818,"ariaHidden":1835},[1834],[1805,2820,2822,2825],{"className":2821},[1839],[1805,2823],{"className":2824,"style":1993},[1843],[1805,2826,2828,2831],{"className":2827},[1848],[1805,2829,2141],{"className":2830,"style":2292},[1848,1849],[1805,2832,2834],{"className":2833},[1904],[1805,2835,2837,2857],{"className":2836},[1908,1909],[1805,2838,2840,2854],{"className":2839},[1913],[1805,2841,2843],{"className":2842,"style":2305},[1917],[1805,2844,2845,2848],{"style":2308},[1805,2846],{"className":2847,"style":1926},[1925],[1805,2849,2851],{"className":2850},[1930,1931,1932,1933],[1805,2852,2144],{"className":2853,"style":2318},[1848,1849,1933],[1805,2855,1951],{"className":2856},[1950],[1805,2858,2860],{"className":2859},[1913],[1805,2861,2863],{"className":2862,"style":1958},[1917],[1805,2864],{}," 的形式与参数，交易与执行系统决定 ",[1805,2867,2869,2883],{"className":2868},[1808],[1805,2870,2872],{"className":2871},[1812],[1814,2873,2874],{"xmlns":1816},[1818,2875,2876,2880],{},[1821,2877,2878],{},[1824,2879,2197],{"mathvariant":2196},[1828,2881,2882],{"encoding":1830},"\\mathcal{M}",[1805,2884,2886],{"className":2885,"ariaHidden":1835},[1834],[1805,2887,2889,2893],{"className":2888},[1839],[1805,2890],{"className":2891,"style":2892},[1843],"height:0.6833em;",[1805,2894,2197],{"className":2895},[1848,2514]," 的延迟和成本，风险与监控系统则把 ",[1805,2898,2900,2924],{"className":2899},[1808],[1805,2901,2903],{"className":2902},[1812],[1814,2904,2905],{"xmlns":1816},[1818,2906,2907,2921],{},[1821,2908,2909,2912,2918],{},[1876,2910,2911],{"stretchy":2147},"{",[1864,2913,2914,2916],{},[1824,2915,2053],{},[1824,2917,1826],{},[1876,2919,2920],{"stretchy":2147},"}",[1828,2922,2923],{"encoding":1830},"\\{Y_t\\}",[1805,2925,2927],{"className":2926,"ariaHidden":1835},[1834],[1805,2928,2930,2933,2936,2976],{"className":2929},[1839],[1805,2931],{"className":2932,"style":2285},[1843],[1805,2934,2911],{"className":2935},[2333],[1805,2937,2939,2942],{"className":2938},[1848],[1805,2940,2053],{"className":2941,"style":2074},[1848,1849],[1805,2943,2945],{"className":2944},[1904],[1805,2946,2948,2968],{"className":2947},[1908,1909],[1805,2949,2951,2965],{"className":2950},[1913],[1805,2952,2954],{"className":2953,"style":2012},[1917],[1805,2955,2956,2959],{"style":2089},[1805,2957],{"className":2958,"style":1926},[1925],[1805,2960,2962],{"className":2961},[1930,1931,1932,1933],[1805,2963,1826],{"className":2964},[1848,1849,1933],[1805,2966,1951],{"className":2967},[1950],[1805,2969,2971],{"className":2970},[1913],[1805,2972,2974],{"className":2973,"style":1958},[1917],[1805,2975],{},[1805,2977,2920],{"className":2978},[2445]," 变成可解释和可预警的指标序列。",[2981,2982,2984],"h2",{"id":2983},"_1-典型系统组成","1. 典型系统组成",[1793,2986,2987],{},"一个相对完整的量化平台通常包括以下子系统，可以抽象成一个有向无环图（DAG）：节点是不同子系统，边是数据与任务的依赖关系：",[2989,2990,2991,3004,3014,3024,3034],"ol",{},[2992,2993,2994,2997,2998],"li",{},[1800,2995,2996],{},"数据平台（Data Platform）","：\n",[2999,3000,3001],"ul",{},[2992,3002,3003],{},"负责数据采集、清洗、存储与服务；",[2992,3005,3006,2997,3009],{},[1800,3007,3008],{},"研究平台（Research Platform）",[2999,3010,3011],{},[2992,3012,3013],{},"提供回测框架、因子库、统计工具等；",[2992,3015,3016,2997,3019],{},[1800,3017,3018],{},"交易与执行系统（Trading & Execution System）",[2999,3020,3021],{},[2992,3022,3023],{},"负责策略信号的接收、订单生成与下单、成交回报处理；",[2992,3025,3026,2997,3029],{},[1800,3027,3028],{},"风险与监控系统（Risk & Monitoring）",[2999,3030,3031],{},[2992,3032,3033],{},"实时监控风险指标、策略表现与系统健康状态；",[2992,3035,3036,2997,3039],{},[1800,3037,3038],{},"调度与任务编排（Scheduling & Orchestration）",[2999,3040,3041],{},[2992,3042,3043],{},"管理批处理任务（夜间回测、报表生成）与实时任务（行情处理、策略计算）。",[1793,3045,3046],{},"不同机构在实现细节和技术选型上差异很大，但上述功能模块在概念上是类似的。形式化一点可以写成：",[1805,3048,3050],{"className":3049},[2114],[1805,3051,3053,3099],{"className":3052},[1808],[1805,3054,3056],{"className":3055},[1812],[1814,3057,3058],{"xmlns":1816,"display":2123},[1818,3059,3060,3096],{},[1821,3061,3062,3065,3067,3069,3072,3074,3077,3079,3082,3084,3087,3089,3092,3094],{},[2210,3063,3064],{},"Platform",[1876,3066,2136],{},[1876,3068,2148],{"stretchy":2147},[1824,3070,3071],{"mathvariant":2196},"D",[1876,3073,2163],{"separator":1835},[1824,3075,3076],{"mathvariant":2196},"R",[1876,3078,2163],{"separator":1835},[1824,3080,3081],{"mathvariant":2196},"T",[1876,3083,2163],{"separator":1835},[1824,3085,3086],{"mathvariant":2196},"K",[1876,3088,2163],{"separator":1835},[1824,3090,3091],{"mathvariant":2196},"S",[1876,3093,2179],{"stretchy":2147},[1876,3095,2163],{"separator":1835},[1828,3097,3098],{"encoding":1830},"\\text{Platform} = (\\mathcal{D}, \\mathcal{R}, \\mathcal{T}, \\mathcal{K}, \\mathcal{S}),",[1805,3100,3102,3124],{"className":3101,"ariaHidden":1835},[1834],[1805,3103,3105,3109,3115,3118,3121],{"className":3104},[1839],[1805,3106],{"className":3107,"style":3108},[1843],"height:0.6944em;",[1805,3110,3112],{"className":3111},[1848,2567],[1805,3113,3064],{"className":3114},[1848],[1805,3116],{"className":3117,"style":2272},[2183],[1805,3119,2136],{"className":3120},[1943],[1805,3122],{"className":3123,"style":2272},[2183],[1805,3125,3127,3130,3133,3136,3139,3142,3145,3148,3151,3155,3158,3161,3165,3168,3171,3175,3178],{"className":3126},[1839],[1805,3128],{"className":3129,"style":2285},[1843],[1805,3131,2148],{"className":3132},[2333],[1805,3134,3071],{"className":3135,"style":2318},[1848,2514],[1805,3137,2163],{"className":3138},[2386],[1805,3140],{"className":3141,"style":2390},[2183],[1805,3143,3076],{"className":3144},[1848,2514],[1805,3146,2163],{"className":3147},[2386],[1805,3149],{"className":3150,"style":2390},[2183],[1805,3152,3081],{"className":3153,"style":3154},[1848,2514],"margin-right:0.2542em;",[1805,3156,2163],{"className":3157},[2386],[1805,3159],{"className":3160,"style":2390},[2183],[1805,3162,3086],{"className":3163,"style":3164},[1848,2514],"margin-right:0.0144em;",[1805,3166,2163],{"className":3167},[2386],[1805,3169],{"className":3170,"style":2390},[2183],[1805,3172,3091],{"className":3173,"style":3174},[1848,2514],"margin-right:0.075em;",[1805,3176,2179],{"className":3177},[2445],[1805,3179,2163],{"className":3180},[2386],[1793,3182,2579,3183,3212,3213,3242,3243,3272,3273,3302,3303,3332],{},[1805,3184,3186,3200],{"className":3185},[1808],[1805,3187,3189],{"className":3188},[1812],[1814,3190,3191],{"xmlns":1816},[1818,3192,3193,3197],{},[1821,3194,3195],{},[1824,3196,3071],{"mathvariant":2196},[1828,3198,3199],{"encoding":1830},"\\mathcal{D}",[1805,3201,3203],{"className":3202,"ariaHidden":1835},[1834],[1805,3204,3206,3209],{"className":3205},[1839],[1805,3207],{"className":3208,"style":2892},[1843],[1805,3210,3071],{"className":3211,"style":2318},[1848,2514]," 是数据平台，",[1805,3214,3216,3230],{"className":3215},[1808],[1805,3217,3219],{"className":3218},[1812],[1814,3220,3221],{"xmlns":1816},[1818,3222,3223,3227],{},[1821,3224,3225],{},[1824,3226,3076],{"mathvariant":2196},[1828,3228,3229],{"encoding":1830},"\\mathcal{R}",[1805,3231,3233],{"className":3232,"ariaHidden":1835},[1834],[1805,3234,3236,3239],{"className":3235},[1839],[1805,3237],{"className":3238,"style":2892},[1843],[1805,3240,3076],{"className":3241},[1848,2514]," 是研究平台（research）、",[1805,3244,3246,3260],{"className":3245},[1808],[1805,3247,3249],{"className":3248},[1812],[1814,3250,3251],{"xmlns":1816},[1818,3252,3253,3257],{},[1821,3254,3255],{},[1824,3256,3081],{"mathvariant":2196},[1828,3258,3259],{"encoding":1830},"\\mathcal{T}",[1805,3261,3263],{"className":3262,"ariaHidden":1835},[1834],[1805,3264,3266,3269],{"className":3265},[1839],[1805,3267],{"className":3268,"style":2892},[1843],[1805,3270,3081],{"className":3271,"style":3154},[1848,2514]," 是交易与执行系统（trading）、",[1805,3274,3276,3290],{"className":3275},[1808],[1805,3277,3279],{"className":3278},[1812],[1814,3280,3281],{"xmlns":1816},[1818,3282,3283,3287],{},[1821,3284,3285],{},[1824,3286,3086],{"mathvariant":2196},[1828,3288,3289],{"encoding":1830},"\\mathcal{K}",[1805,3291,3293],{"className":3292,"ariaHidden":1835},[1834],[1805,3294,3296,3299],{"className":3295},[1839],[1805,3297],{"className":3298,"style":2892},[1843],[1805,3300,3086],{"className":3301,"style":3164},[1848,2514]," 是风险与监控（risk & monitoring）、",[1805,3304,3306,3320],{"className":3305},[1808],[1805,3307,3309],{"className":3308},[1812],[1814,3310,3311],{"xmlns":1816},[1818,3312,3313,3317],{},[1821,3314,3315],{},[1824,3316,3091],{"mathvariant":2196},[1828,3318,3319],{"encoding":1830},"\\mathcal{S}",[1805,3321,3323],{"className":3322,"ariaHidden":1835},[1834],[1805,3324,3326,3329],{"className":3325},[1839],[1805,3327],{"className":3328,"style":2892},[1843],[1805,3330,3091],{"className":3331,"style":3174},[1848,2514]," 是调度与任务编排（scheduling）。后续各节依次拆解这些组件。",[2981,3334,3336],{"id":3335},"_2-数据平台从原始数据到可回测数据","2. 数据平台：从原始数据到“可回测数据”",[3338,3339,3341],"h3",{"id":3340},"_21-数据分层","2.1 数据分层",[1793,3343,3344],{},"为了支持研究与生产的双重需求，一个常见的做法是将数据平台分层，并显式区分数据转换算子：",[2989,3346,3347,3431,3511],{},[2992,3348,3349,3352,3353,3422,3423],{},[1800,3350,3351],{},"Raw 层","（",[1805,3354,3356,3376],{"className":3355},[1808],[1805,3357,3359],{"className":3358},[1812],[1814,3360,3361],{"xmlns":1816},[1818,3362,3363,3373],{},[1821,3364,3365],{},[3366,3367,3368,3370],"msup",{},[1824,3369,3071],{"mathvariant":2196},[2210,3371,3372],{},"raw",[1828,3374,3375],{"encoding":1830},"\\mathcal{D}^{\\text{raw}}",[1805,3377,3379],{"className":3378,"ariaHidden":1835},[1834],[1805,3380,3382,3385],{"className":3381},[1839],[1805,3383],{"className":3384,"style":2892},[1843],[1805,3386,3388,3391],{"className":3387},[1848],[1805,3389,3071],{"className":3390,"style":2318},[1848,2514],[1805,3392,3394],{"className":3393},[1904],[1805,3395,3397],{"className":3396},[1908],[1805,3398,3400],{"className":3399},[1913],[1805,3401,3404],{"className":3402,"style":3403},[1917],"height:0.6644em;",[1805,3405,3407,3410],{"style":3406},"top:-3.063em;margin-right:0.05em;",[1805,3408],{"className":3409,"style":1926},[1925],[1805,3411,3413],{"className":3412},[1930,1931,1932,1933],[1805,3414,3416],{"className":3415},[1848,1933],[1805,3417,3419],{"className":3418},[1848,2567,1933],[1805,3420,3372],{"className":3421},[1848,1933],"）：\n",[2999,3424,3425,3428],{},[2992,3426,3427],{},"基本不做处理地存储从交易所、数据商、内部系统等获取的原始数据；",[2992,3429,3430],{},"保留原始时间戳、字段和格式，便于追溯和重新清洗。",[2992,3432,3433,3352,3436,3422,3503],{},[1800,3434,3435],{},"Clean 层",[1805,3437,3439,3458],{"className":3438},[1808],[1805,3440,3442],{"className":3441},[1812],[1814,3443,3444],{"xmlns":1816},[1818,3445,3446,3455],{},[1821,3447,3448],{},[3366,3449,3450,3452],{},[1824,3451,3071],{"mathvariant":2196},[2210,3453,3454],{},"clean",[1828,3456,3457],{"encoding":1830},"\\mathcal{D}^{\\text{clean}}",[1805,3459,3461],{"className":3460,"ariaHidden":1835},[1834],[1805,3462,3464,3468],{"className":3463},[1839],[1805,3465],{"className":3466,"style":3467},[1843],"height:0.8491em;",[1805,3469,3471,3474],{"className":3470},[1848],[1805,3472,3071],{"className":3473,"style":2318},[1848,2514],[1805,3475,3477],{"className":3476},[1904],[1805,3478,3480],{"className":3479},[1908],[1805,3481,3483],{"className":3482},[1913],[1805,3484,3486],{"className":3485,"style":3467},[1917],[1805,3487,3488,3491],{"style":3406},[1805,3489],{"className":3490,"style":1926},[1925],[1805,3492,3494],{"className":3493},[1930,1931,1932,1933],[1805,3495,3497],{"className":3496},[1848,1933],[1805,3498,3500],{"className":3499},[1848,2567,1933],[1805,3501,3454],{"className":3502},[1848,1933],[2999,3504,3505,3508],{},[2992,3506,3507],{},"进行字段标准化、缺失值处理、异常值过滤等；",[2992,3509,3510],{},"对不同数据源的数据进行对齐和合并。",[2992,3512,3513,3352,3516,3422,3582],{},[1800,3514,3515],{},"Feature\u002FFactor 层",[1805,3517,3519,3538],{"className":3518},[1808],[1805,3520,3522],{"className":3521},[1812],[1814,3523,3524],{"xmlns":1816},[1818,3525,3526,3535],{},[1821,3527,3528],{},[3366,3529,3530,3532],{},[1824,3531,3071],{"mathvariant":2196},[2210,3533,3534],{},"factor",[1828,3536,3537],{"encoding":1830},"\\mathcal{D}^{\\text{factor}}",[1805,3539,3541],{"className":3540,"ariaHidden":1835},[1834],[1805,3542,3544,3547],{"className":3543},[1839],[1805,3545],{"className":3546,"style":3467},[1843],[1805,3548,3550,3553],{"className":3549},[1848],[1805,3551,3071],{"className":3552,"style":2318},[1848,2514],[1805,3554,3556],{"className":3555},[1904],[1805,3557,3559],{"className":3558},[1908],[1805,3560,3562],{"className":3561},[1913],[1805,3563,3565],{"className":3564,"style":3467},[1917],[1805,3566,3567,3570],{"style":3406},[1805,3568],{"className":3569,"style":1926},[1925],[1805,3571,3573],{"className":3572},[1930,1931,1932,1933],[1805,3574,3576],{"className":3575},[1848,1933],[1805,3577,3579],{"className":3578},[1848,2567,1933],[1805,3580,3534],{"className":3581},[1848,1933],[2999,3583,3584,3587],{},[2992,3585,3586],{},"在 Clean 数据基础上构建因子和特征；",[2992,3588,3589],{},"形成可直接用于回测和建模的“研究数据集”。",[1793,3591,3592],{},"在记号上，可以把清洗和因子构建视为两个确定性算子：",[1805,3594,3596],{"className":3595},[2114],[1805,3597,3599,3667],{"className":3598},[1808],[1805,3600,3602],{"className":3601},[1812],[1814,3603,3604],{"xmlns":1816,"display":2123},[1818,3605,3606,3664],{},[1821,3607,3608,3614,3616,3622,3624,3630,3632,3634,3636,3642,3644,3650,3652,3658,3660],{},[3366,3609,3610,3612],{},[1824,3611,3071],{"mathvariant":2196},[2210,3613,3454],{},[1876,3615,2136],{},[1864,3617,3618,3620],{},[1824,3619,3081],{},[2210,3621,3454],{},[1876,3623,2148],{"stretchy":2147},[3366,3625,3626,3628],{},[1824,3627,3071],{"mathvariant":2196},[2210,3629,3372],{},[1876,3631,2179],{"stretchy":2147},[1876,3633,2163],{"separator":1835},[2183,3635],{"width":2185},[3366,3637,3638,3640],{},[1824,3639,3071],{"mathvariant":2196},[2210,3641,3534],{},[1876,3643,2136],{},[1864,3645,3646,3648],{},[1824,3647,3081],{},[2210,3649,3534],{},[1876,3651,2148],{"stretchy":2147},[3366,3653,3654,3656],{},[1824,3655,3071],{"mathvariant":2196},[2210,3657,3454],{},[1876,3659,2179],{"stretchy":2147},[1824,3661,3663],{"mathvariant":3662},"normal",".",[1828,3665,3666],{"encoding":1830},"\\mathcal{D}^{\\text{clean}} = T_{\\text{clean}}(\\mathcal{D}^{\\text{raw}}), \\qquad\n\\mathcal{D}^{\\text{factor}} = T_{\\text{factor}}(\\mathcal{D}^{\\text{clean}}).",[1805,3668,3670,3722,3872],{"className":3669,"ariaHidden":1835},[1834],[1805,3671,3673,3677,3713,3716,3719],{"className":3672},[1839],[1805,3674],{"className":3675,"style":3676},[1843],"height:0.8991em;",[1805,3678,3680,3683],{"className":3679},[1848],[1805,3681,3071],{"className":3682,"style":2318},[1848,2514],[1805,3684,3686],{"className":3685},[1904],[1805,3687,3689],{"className":3688},[1908],[1805,3690,3692],{"className":3691},[1913],[1805,3693,3695],{"className":3694,"style":3676},[1917],[1805,3696,3698,3701],{"style":3697},"top:-3.113em;margin-right:0.05em;",[1805,3699],{"className":3700,"style":1926},[1925],[1805,3702,3704],{"className":3703},[1930,1931,1932,1933],[1805,3705,3707],{"className":3706},[1848,1933],[1805,3708,3710],{"className":3709},[1848,2567,1933],[1805,3711,3454],{"className":3712},[1848,1933],[1805,3714],{"className":3715,"style":2272},[2183],[1805,3717,2136],{"className":3718},[1943],[1805,3720],{"className":3721,"style":2272},[2183],[1805,3723,3725,3729,3777,3780,3816,3819,3822,3825,3828,3863,3866,3869],{"className":3724},[1839],[1805,3726],{"className":3727,"style":3728},[1843],"height:1.1491em;vertical-align:-0.25em;",[1805,3730,3732,3736],{"className":3731},[1848],[1805,3733,3081],{"className":3734,"style":3735},[1848,1849],"margin-right:0.1389em;",[1805,3737,3739],{"className":3738},[1904],[1805,3740,3742,3769],{"className":3741},[1908,1909],[1805,3743,3745,3766],{"className":3744},[1913],[1805,3746,3748],{"className":3747,"style":2305},[1917],[1805,3749,3751,3754],{"style":3750},"top:-2.55em;margin-left:-0.1389em;margin-right:0.05em;",[1805,3752],{"className":3753,"style":1926},[1925],[1805,3755,3757],{"className":3756},[1930,1931,1932,1933],[1805,3758,3760],{"className":3759},[1848,1933],[1805,3761,3763],{"className":3762},[1848,2567,1933],[1805,3764,3454],{"className":3765},[1848,1933],[1805,3767,1951],{"className":3768},[1950],[1805,3770,3772],{"className":3771},[1913],[1805,3773,3775],{"className":3774,"style":1958},[1917],[1805,3776],{},[1805,3778,2148],{"className":3779},[2333],[1805,3781,3783,3786],{"className":3782},[1848],[1805,3784,3071],{"className":3785,"style":2318},[1848,2514],[1805,3787,3789],{"className":3788},[1904],[1805,3790,3792],{"className":3791},[1908],[1805,3793,3795],{"className":3794},[1913],[1805,3796,3799],{"className":3797,"style":3798},[1917],"height:0.7144em;",[1805,3800,3801,3804],{"style":3697},[1805,3802],{"className":3803,"style":1926},[1925],[1805,3805,3807],{"className":3806},[1930,1931,1932,1933],[1805,3808,3810],{"className":3809},[1848,1933],[1805,3811,3813],{"className":3812},[1848,2567,1933],[1805,3814,3372],{"className":3815},[1848,1933],[1805,3817,2179],{"className":3818},[2445],[1805,3820,2163],{"className":3821},[2386],[1805,3823],{"className":3824,"style":2452},[2183],[1805,3826],{"className":3827,"style":2390},[2183],[1805,3829,3831,3834],{"className":3830},[1848],[1805,3832,3071],{"className":3833,"style":2318},[1848,2514],[1805,3835,3837],{"className":3836},[1904],[1805,3838,3840],{"className":3839},[1908],[1805,3841,3843],{"className":3842},[1913],[1805,3844,3846],{"className":3845,"style":3676},[1917],[1805,3847,3848,3851],{"style":3697},[1805,3849],{"className":3850,"style":1926},[1925],[1805,3852,3854],{"className":3853},[1930,1931,1932,1933],[1805,3855,3857],{"className":3856},[1848,1933],[1805,3858,3860],{"className":3859},[1848,2567,1933],[1805,3861,3534],{"className":3862},[1848,1933],[1805,3864],{"className":3865,"style":2272},[2183],[1805,3867,2136],{"className":3868},[1943],[1805,3870],{"className":3871,"style":2272},[2183],[1805,3873,3875,3878,3924,3927,3962,3965],{"className":3874},[1839],[1805,3876],{"className":3877,"style":3728},[1843],[1805,3879,3881,3884],{"className":3880},[1848],[1805,3882,3081],{"className":3883,"style":3735},[1848,1849],[1805,3885,3887],{"className":3886},[1904],[1805,3888,3890,3916],{"className":3889},[1908,1909],[1805,3891,3893,3913],{"className":3892},[1913],[1805,3894,3896],{"className":3895,"style":2305},[1917],[1805,3897,3898,3901],{"style":3750},[1805,3899],{"className":3900,"style":1926},[1925],[1805,3902,3904],{"className":3903},[1930,1931,1932,1933],[1805,3905,3907],{"className":3906},[1848,1933],[1805,3908,3910],{"className":3909},[1848,2567,1933],[1805,3911,3534],{"className":3912},[1848,1933],[1805,3914,1951],{"className":3915},[1950],[1805,3917,3919],{"className":3918},[1913],[1805,3920,3922],{"className":3921,"style":1958},[1917],[1805,3923],{},[1805,3925,2148],{"className":3926},[2333],[1805,3928,3930,3933],{"className":3929},[1848],[1805,3931,3071],{"className":3932,"style":2318},[1848,2514],[1805,3934,3936],{"className":3935},[1904],[1805,3937,3939],{"className":3938},[1908],[1805,3940,3942],{"className":3941},[1913],[1805,3943,3945],{"className":3944,"style":3676},[1917],[1805,3946,3947,3950],{"style":3697},[1805,3948],{"className":3949,"style":1926},[1925],[1805,3951,3953],{"className":3952},[1930,1931,1932,1933],[1805,3954,3956],{"className":3955},[1848,1933],[1805,3957,3959],{"className":3958},[1848,2567,1933],[1805,3960,3454],{"className":3961},[1848,1933],[1805,3963,2179],{"className":3964},[2445],[1805,3966,3663],{"className":3967},[1848],[1793,3969,3970],{},"在工程上，可以使用列式存储（如 Parquet）或时序数据库，以优化 I\u002FO 性能和压缩效率。这种分层 + 显式转换算子的设计有利于**数据血缘（data lineage）**追踪：一条因子时间序列可以被精确追溯到对应的原始数据版本和清洗规则。",[3338,3972,3974],{"id":3973},"_22-数据版本与可重复性","2.2 数据版本与可重复性",[1793,3976,3977],{},"为了保证回测结果可重复，需要对数据版本进行管理：",[2999,3979,3980,4183,4186],{},[2992,3981,3982,3983,4182],{},"对每一次清洗和修正记录版本号（例如 ",[1805,3984,3986,4021],{"className":3985},[1808],[1805,3987,3989],{"className":3988},[1812],[1814,3990,3991],{"xmlns":1816},[1818,3992,3993,4018],{},[1821,3994,3995,4002,4004,4010,4012],{},[1864,3996,3997,4000],{},[1824,3998,3999],{},"v",[2210,4001,3372],{},[1876,4003,2163],{"separator":1835},[1864,4005,4006,4008],{},[1824,4007,3999],{},[2210,4009,3454],{},[1876,4011,2163],{"separator":1835},[1864,4013,4014,4016],{},[1824,4015,3999],{},[2210,4017,3534],{},[1828,4019,4020],{"encoding":1830},"v_{\\text{raw}}, v_{\\text{clean}}, v_{\\text{factor}}",[1805,4022,4024],{"className":4023,"ariaHidden":1835},[1834],[1805,4025,4027,4031,4078,4081,4084,4130,4133,4136],{"className":4026},[1839],[1805,4028],{"className":4029,"style":4030},[1843],"height:0.625em;vertical-align:-0.1944em;",[1805,4032,4034,4037],{"className":4033},[1848],[1805,4035,3999],{"className":4036,"style":2292},[1848,1849],[1805,4038,4040],{"className":4039},[1904],[1805,4041,4043,4070],{"className":4042},[1908,1909],[1805,4044,4046,4067],{"className":4045},[1913],[1805,4047,4050],{"className":4048,"style":4049},[1917],"height:0.1514em;",[1805,4051,4052,4055],{"style":2308},[1805,4053],{"className":4054,"style":1926},[1925],[1805,4056,4058],{"className":4057},[1930,1931,1932,1933],[1805,4059,4061],{"className":4060},[1848,1933],[1805,4062,4064],{"className":4063},[1848,2567,1933],[1805,4065,3372],{"className":4066},[1848,1933],[1805,4068,1951],{"className":4069},[1950],[1805,4071,4073],{"className":4072},[1913],[1805,4074,4076],{"className":4075,"style":1958},[1917],[1805,4077],{},[1805,4079,2163],{"className":4080},[2386],[1805,4082],{"className":4083,"style":2390},[2183],[1805,4085,4087,4090],{"className":4086},[1848],[1805,4088,3999],{"className":4089,"style":2292},[1848,1849],[1805,4091,4093],{"className":4092},[1904],[1805,4094,4096,4122],{"className":4095},[1908,1909],[1805,4097,4099,4119],{"className":4098},[1913],[1805,4100,4102],{"className":4101,"style":2305},[1917],[1805,4103,4104,4107],{"style":2308},[1805,4105],{"className":4106,"style":1926},[1925],[1805,4108,4110],{"className":4109},[1930,1931,1932,1933],[1805,4111,4113],{"className":4112},[1848,1933],[1805,4114,4116],{"className":4115},[1848,2567,1933],[1805,4117,3454],{"className":4118},[1848,1933],[1805,4120,1951],{"className":4121},[1950],[1805,4123,4125],{"className":4124},[1913],[1805,4126,4128],{"className":4127,"style":1958},[1917],[1805,4129],{},[1805,4131,2163],{"className":4132},[2386],[1805,4134],{"className":4135,"style":2390},[2183],[1805,4137,4139,4142],{"className":4138},[1848],[1805,4140,3999],{"className":4141,"style":2292},[1848,1849],[1805,4143,4145],{"className":4144},[1904],[1805,4146,4148,4174],{"className":4147},[1908,1909],[1805,4149,4151,4171],{"className":4150},[1913],[1805,4152,4154],{"className":4153,"style":2305},[1917],[1805,4155,4156,4159],{"style":2308},[1805,4157],{"className":4158,"style":1926},[1925],[1805,4160,4162],{"className":4161},[1930,1931,1932,1933],[1805,4163,4165],{"className":4164},[1848,1933],[1805,4166,4168],{"className":4167},[1848,2567,1933],[1805,4169,3534],{"className":4170},[1848,1933],[1805,4172,1951],{"className":4173},[1950],[1805,4175,4177],{"className":4176},[1913],[1805,4178,4180],{"className":4179,"style":1958},[1917],[1805,4181],{},"）；",[2992,4184,4185],{},"在回测任务中记录使用的数据版本；",[2992,4187,4188],{},"对重要策略，保留当时使用的数据快照。",[1793,4190,4191],{},"从形式上看，一个回测结果可以写成：",[1805,4193,4195],{"className":4194},[2114],[1805,4196,4198,4240],{"className":4197},[1808],[1805,4199,4201],{"className":4200},[1812],[1814,4202,4203],{"xmlns":1816,"display":2123},[1818,4204,4205,4237],{},[1821,4206,4207,4210,4212,4215,4218,4224,4226,4228,4230,4233,4235],{},[2210,4208,4209],{},"BacktestResult",[1876,4211,2136],{},[1824,4213,4214],{"mathvariant":2196},"B",[1876,4216,2148],{"fence":2147,"stretchy":1835,"minsize":4217,"maxsize":4217},"1.2em",[3366,4219,4220,4222],{},[1824,4221,3071],{"mathvariant":2196},[2210,4223,3534],{},[1876,4225,2208],{"separator":1835},[1824,4227,2144],{},[1876,4229,2163],{"separator":1835},[1824,4231,4232],{},"ϕ",[1876,4234,2179],{"fence":2147,"stretchy":1835,"minsize":4217,"maxsize":4217},[1876,4236,2163],{"separator":1835},[1828,4238,4239],{"encoding":1830},"\\text{BacktestResult} = \\mathcal{B}\\big(\\mathcal{D}^{\\text{factor}}; \\theta, \\phi\\big),",[1805,4241,4243,4264],{"className":4242,"ariaHidden":1835},[1834],[1805,4244,4246,4249,4255,4258,4261],{"className":4245},[1839],[1805,4247],{"className":4248,"style":3108},[1843],[1805,4250,4252],{"className":4251},[1848,2567],[1805,4253,4209],{"className":4254},[1848],[1805,4256],{"className":4257,"style":2272},[2183],[1805,4259,2136],{"className":4260},[1943],[1805,4262],{"className":4263,"style":2272},[2183],[1805,4265,4267,4271,4275,4283,4318,4321,4324,4327,4330,4333,4336,4342],{"className":4266},[1839],[1805,4268],{"className":4269,"style":4270},[1843],"height:1.2491em;vertical-align:-0.35em;",[1805,4272,4214],{"className":4273,"style":4274},[1848,2514],"margin-right:0.0304em;",[1805,4276,4278],{"className":4277},[1848],[1805,4279,2148],{"className":4280},[4281,4282],"delimsizing","size1",[1805,4284,4286,4289],{"className":4285},[1848],[1805,4287,3071],{"className":4288,"style":2318},[1848,2514],[1805,4290,4292],{"className":4291},[1904],[1805,4293,4295],{"className":4294},[1908],[1805,4296,4298],{"className":4297},[1913],[1805,4299,4301],{"className":4300,"style":3676},[1917],[1805,4302,4303,4306],{"style":3697},[1805,4304],{"className":4305,"style":1926},[1925],[1805,4307,4309],{"className":4308},[1930,1931,1932,1933],[1805,4310,4312],{"className":4311},[1848,1933],[1805,4313,4315],{"className":4314},[1848,2567,1933],[1805,4316,3534],{"className":4317},[1848,1933],[1805,4319,2208],{"className":4320},[2386],[1805,4322],{"className":4323,"style":2390},[2183],[1805,4325,2144],{"className":4326,"style":2318},[1848,1849],[1805,4328,2163],{"className":4329},[2386],[1805,4331],{"className":4332,"style":2390},[2183],[1805,4334,4232],{"className":4335},[1848,1849],[1805,4337,4339],{"className":4338},[1848],[1805,4340,2179],{"className":4341},[4281,4282],[1805,4343,2163],{"className":4344},[2386],[1793,4346,2579,4347,4376,4377,4407,4408,4640],{},[1805,4348,4350,4364],{"className":4349},[1808],[1805,4351,4353],{"className":4352},[1812],[1814,4354,4355],{"xmlns":1816},[1818,4356,4357,4361],{},[1821,4358,4359],{},[1824,4360,2144],{},[1828,4362,4363],{"encoding":1830},"\\theta",[1805,4365,4367],{"className":4366,"ariaHidden":1835},[1834],[1805,4368,4370,4373],{"className":4369},[1839],[1805,4371],{"className":4372,"style":3108},[1843],[1805,4374,2144],{"className":4375,"style":2318},[1848,1849]," 是策略参数（如因子权重、打分阈值），",[1805,4378,4380,4394],{"className":4379},[1808],[1805,4381,4383],{"className":4382},[1812],[1814,4384,4385],{"xmlns":1816},[1818,4386,4387,4391],{},[1821,4388,4389],{},[1824,4390,4232],{},[1828,4392,4393],{"encoding":1830},"\\phi",[1805,4395,4397],{"className":4396,"ariaHidden":1835},[1834],[1805,4398,4400,4404],{"className":4399},[1839],[1805,4401],{"className":4402,"style":4403},[1843],"height:0.8889em;vertical-align:-0.1944em;",[1805,4405,4232],{"className":4406},[1848,1849]," 是成本模型与约束参数（参见第 03、04、05 章）。只要锁定 ",[1805,4409,4411,4457],{"className":4410},[1808],[1805,4412,4414],{"className":4413},[1812],[1814,4415,4416],{"xmlns":1816},[1818,4417,4418,4454],{},[1821,4419,4420,4422,4428,4430,4436,4438,4444,4446,4448,4450,4452],{},[1876,4421,2148],{"stretchy":2147},[1864,4423,4424,4426],{},[1824,4425,3999],{},[2210,4427,3372],{},[1876,4429,2163],{"separator":1835},[1864,4431,4432,4434],{},[1824,4433,3999],{},[2210,4435,3454],{},[1876,4437,2163],{"separator":1835},[1864,4439,4440,4442],{},[1824,4441,3999],{},[2210,4443,3534],{},[1876,4445,2163],{"separator":1835},[1824,4447,2144],{},[1876,4449,2163],{"separator":1835},[1824,4451,4232],{},[1876,4453,2179],{"stretchy":2147},[1828,4455,4456],{"encoding":1830},"(v_{\\text{raw}}, v_{\\text{clean}}, v_{\\text{factor}}, \\theta, \\phi)",[1805,4458,4460],{"className":4459,"ariaHidden":1835},[1834],[1805,4461,4463,4466,4469,4515,4518,4521,4567,4570,4573,4619,4622,4625,4628,4631,4634,4637],{"className":4462},[1839],[1805,4464],{"className":4465,"style":2285},[1843],[1805,4467,2148],{"className":4468},[2333],[1805,4470,4472,4475],{"className":4471},[1848],[1805,4473,3999],{"className":4474,"style":2292},[1848,1849],[1805,4476,4478],{"className":4477},[1904],[1805,4479,4481,4507],{"className":4480},[1908,1909],[1805,4482,4484,4504],{"className":4483},[1913],[1805,4485,4487],{"className":4486,"style":4049},[1917],[1805,4488,4489,4492],{"style":2308},[1805,4490],{"className":4491,"style":1926},[1925],[1805,4493,4495],{"className":4494},[1930,1931,1932,1933],[1805,4496,4498],{"className":4497},[1848,1933],[1805,4499,4501],{"className":4500},[1848,2567,1933],[1805,4502,3372],{"className":4503},[1848,1933],[1805,4505,1951],{"className":4506},[1950],[1805,4508,4510],{"className":4509},[1913],[1805,4511,4513],{"className":4512,"style":1958},[1917],[1805,4514],{},[1805,4516,2163],{"className":4517},[2386],[1805,4519],{"className":4520,"style":2390},[2183],[1805,4522,4524,4527],{"className":4523},[1848],[1805,4525,3999],{"className":4526,"style":2292},[1848,1849],[1805,4528,4530],{"className":4529},[1904],[1805,4531,4533,4559],{"className":4532},[1908,1909],[1805,4534,4536,4556],{"className":4535},[1913],[1805,4537,4539],{"className":4538,"style":2305},[1917],[1805,4540,4541,4544],{"style":2308},[1805,4542],{"className":4543,"style":1926},[1925],[1805,4545,4547],{"className":4546},[1930,1931,1932,1933],[1805,4548,4550],{"className":4549},[1848,1933],[1805,4551,4553],{"className":4552},[1848,2567,1933],[1805,4554,3454],{"className":4555},[1848,1933],[1805,4557,1951],{"className":4558},[1950],[1805,4560,4562],{"className":4561},[1913],[1805,4563,4565],{"className":4564,"style":1958},[1917],[1805,4566],{},[1805,4568,2163],{"className":4569},[2386],[1805,4571],{"className":4572,"style":2390},[2183],[1805,4574,4576,4579],{"className":4575},[1848],[1805,4577,3999],{"className":4578,"style":2292},[1848,1849],[1805,4580,4582],{"className":4581},[1904],[1805,4583,4585,4611],{"className":4584},[1908,1909],[1805,4586,4588,4608],{"className":4587},[1913],[1805,4589,4591],{"className":4590,"style":2305},[1917],[1805,4592,4593,4596],{"style":2308},[1805,4594],{"className":4595,"style":1926},[1925],[1805,4597,4599],{"className":4598},[1930,1931,1932,1933],[1805,4600,4602],{"className":4601},[1848,1933],[1805,4603,4605],{"className":4604},[1848,2567,1933],[1805,4606,3534],{"className":4607},[1848,1933],[1805,4609,1951],{"className":4610},[1950],[1805,4612,4614],{"className":4613},[1913],[1805,4615,4617],{"className":4616,"style":1958},[1917],[1805,4618],{},[1805,4620,2163],{"className":4621},[2386],[1805,4623],{"className":4624,"style":2390},[2183],[1805,4626,2144],{"className":4627,"style":2318},[1848,1849],[1805,4629,2163],{"className":4630},[2386],[1805,4632],{"className":4633,"style":2390},[2183],[1805,4635,4232],{"className":4636},[1848,1849],[1805,4638,2179],{"className":4639},[2445],"，回测结果理论上应当是可复现的。这有点类似“数据的 Git”，在业界被称为 Data Version Control（DVC）或 data lineage 管理。",[2981,4642,4644],{"id":4643},"_3-回测与研究平台","3. 回测与研究平台",[3338,4646,4648],{"id":4647},"_31-回测框架的关键设计点","3.1 回测框架的关键设计点",[1793,4650,4651,4652,4655,4656,4659],{},"一个好的回测框架，需要在",[1800,4653,4654],{},"灵活性","和",[1800,4657,4658],{},"严格性","之间平衡。从理论上可以把回测框架抽象为一个“理想回测算子”：",[1805,4661,4663],{"className":4662},[2114],[1805,4664,4666,4737],{"className":4665},[1808],[1805,4667,4669],{"className":4668},[1812],[1814,4670,4671],{"xmlns":1816,"display":2123},[1818,4672,4673,4734],{},[1821,4674,4675,4677,4679,4681,4683,4685,4687,4689,4692,4694,4696,4698,4701,4703,4716,4732],{},[1824,4676,4214],{"mathvariant":2196},[1876,4678,1878],{},[1876,4680,2148],{"stretchy":2147},[1824,4682,3071],{"mathvariant":2196},[1876,4684,2163],{"separator":1835},[1824,4686,2141],{},[1876,4688,2163],{"separator":1835},[1824,4690,4691],{"mathvariant":2196},"C",[1876,4693,2163],{"separator":1835},[1824,4695,3076],{"mathvariant":2196},[1876,4697,2179],{"stretchy":2147},[1876,4699,4700],{},"↦",[1876,4702,2911],{"stretchy":2147},[1864,4704,4705,4708],{},[1824,4706,4707],{},"r",[1821,4709,4710,4712,4714],{},[1824,4711,1793],{},[1876,4713,2163],{"separator":1835},[1824,4715,1826],{},[4717,4718,4719,4721,4730],"msubsup",{},[1876,4720,2920],{"stretchy":2147},[1821,4722,4723,4725,4727],{},[1824,4724,1826],{},[1876,4726,2136],{},[1872,4728,4729],{},"1",[1824,4731,3081],{},[1876,4733,2163],{"separator":1835},[1828,4735,4736],{"encoding":1830},"\\mathcal{B} : (\\mathcal{D}, \\pi, \\mathcal{C}, \\mathcal{R}) \\mapsto \\{r_{p,t}\\}_{t=1}^T,",[1805,4738,4740,4758,4810],{"className":4739,"ariaHidden":1835},[1834],[1805,4741,4743,4746,4749,4752,4755],{"className":4742},[1839],[1805,4744],{"className":4745,"style":2892},[1843],[1805,4747,4214],{"className":4748,"style":4274},[1848,2514],[1805,4750],{"className":4751,"style":2272},[2183],[1805,4753,1878],{"className":4754},[1943],[1805,4756],{"className":4757,"style":2272},[2183],[1805,4759,4761,4764,4767,4770,4773,4776,4779,4782,4785,4789,4792,4795,4798,4801,4804,4807],{"className":4760},[1839],[1805,4762],{"className":4763,"style":2285},[1843],[1805,4765,2148],{"className":4766},[2333],[1805,4768,3071],{"className":4769,"style":2318},[1848,2514],[1805,4771,2163],{"className":4772},[2386],[1805,4774],{"className":4775,"style":2390},[2183],[1805,4777,2141],{"className":4778,"style":2292},[1848,1849],[1805,4780,2163],{"className":4781},[2386],[1805,4783],{"className":4784,"style":2390},[2183],[1805,4786,4691],{"className":4787,"style":4788},[1848,2514],"margin-right:0.0583em;",[1805,4790,2163],{"className":4791},[2386],[1805,4793],{"className":4794,"style":2390},[2183],[1805,4796,3076],{"className":4797},[1848,2514],[1805,4799,2179],{"className":4800},[2445],[1805,4802],{"className":4803,"style":2272},[2183],[1805,4805,4700],{"className":4806},[1943],[1805,4808],{"className":4809,"style":2272},[2183],[1805,4811,4813,4817,4820,4871,4934],{"className":4812},[1839],[1805,4814],{"className":4815,"style":4816},[1843],"height:1.1774em;vertical-align:-0.2861em;",[1805,4818,2911],{"className":4819},[2333],[1805,4821,4823,4826],{"className":4822},[1848],[1805,4824,4707],{"className":4825,"style":2318},[1848,1849],[1805,4827,4829],{"className":4828},[1904],[1805,4830,4832,4862],{"className":4831},[1908,1909],[1805,4833,4835,4859],{"className":4834},[1913],[1805,4836,4838],{"className":4837,"style":2012},[1917],[1805,4839,4841,4844],{"style":4840},"top:-2.55em;margin-left:-0.0278em;margin-right:0.05em;",[1805,4842],{"className":4843,"style":1926},[1925],[1805,4845,4847],{"className":4846},[1930,1931,1932,1933],[1805,4848,4850,4853,4856],{"className":4849},[1848,1933],[1805,4851,1793],{"className":4852},[1848,1849,1933],[1805,4854,2163],{"className":4855},[2386,1933],[1805,4857,1826],{"className":4858},[1848,1849,1933],[1805,4860,1951],{"className":4861},[1950],[1805,4863,4865],{"className":4864},[1913],[1805,4866,4869],{"className":4867,"style":4868},[1917],"height:0.2861em;",[1805,4870],{},[1805,4872,4874,4877],{"className":4873},[2445],[1805,4875,2920],{"className":4876},[2445],[1805,4878,4880],{"className":4879},[1904],[1805,4881,4883,4925],{"className":4882},[1908,1909],[1805,4884,4886,4922],{"className":4885},[1913],[1805,4887,4890,4911],{"className":4888,"style":4889},[1917],"height:0.8913em;",[1805,4891,4893,4896],{"style":4892},"top:-2.453em;margin-left:0em;margin-right:0.05em;",[1805,4894],{"className":4895,"style":1926},[1925],[1805,4897,4899],{"className":4898},[1930,1931,1932,1933],[1805,4900,4902,4905,4908],{"className":4901},[1848,1933],[1805,4903,1826],{"className":4904},[1848,1849,1933],[1805,4906,2136],{"className":4907},[1943,1933],[1805,4909,4729],{"className":4910},[1848,1933],[1805,4912,4913,4916],{"style":3697},[1805,4914],{"className":4915,"style":1926},[1925],[1805,4917,4919],{"className":4918},[1930,1931,1932,1933],[1805,4920,3081],{"className":4921,"style":3735},[1848,1849,1933],[1805,4923,1951],{"className":4924},[1950],[1805,4926,4928],{"className":4927},[1913],[1805,4929,4932],{"className":4930,"style":4931},[1917],"height:0.247em;",[1805,4933],{},[1805,4935,2163],{"className":4936},[2386],[1793,4938,4939],{},"其中：",[2999,4941,4942,4973,5325,5357],{},[2992,4943,4944,4972],{},[1805,4945,4947,4960],{"className":4946},[1808],[1805,4948,4950],{"className":4949},[1812],[1814,4951,4952],{"xmlns":1816},[1818,4953,4954,4958],{},[1821,4955,4956],{},[1824,4957,3071],{"mathvariant":2196},[1828,4959,3199],{"encoding":1830},[1805,4961,4963],{"className":4962,"ariaHidden":1835},[1834],[1805,4964,4966,4969],{"className":4965},[1839],[1805,4967],{"className":4968,"style":2892},[1843],[1805,4970,3071],{"className":4971,"style":2318},[1848,2514],"：由数据平台提供的数据集合（含数据版本信息与可用日期）；",[2992,4974,4975,5005,5006,5168,5169,5324],{},[1805,4976,4978,4992],{"className":4977},[1808],[1805,4979,4981],{"className":4980},[1812],[1814,4982,4983],{"xmlns":1816},[1818,4984,4985,4989],{},[1821,4986,4987],{},[1824,4988,2141],{},[1828,4990,4991],{"encoding":1830},"\\pi",[1805,4993,4995],{"className":4994,"ariaHidden":1835},[1834],[1805,4996,4998,5002],{"className":4997},[1839],[1805,4999],{"className":5000,"style":5001},[1843],"height:0.4306em;",[1805,5003,2141],{"className":5004,"style":2292},[1848,1849],"：策略映射 ",[1805,5007,5009,5042],{"className":5008},[1808],[1805,5010,5012],{"className":5011},[1812],[1814,5013,5014],{"xmlns":1816},[1818,5015,5016,5039],{},[1821,5017,5018,5020,5022,5029,5032],{},[1824,5019,2141],{},[1876,5021,1878],{},[1864,5023,5024,5027],{},[1824,5025,5026],{"mathvariant":2196},"F",[1824,5028,1826],{},[1876,5030,5031],{},"→",[1864,5033,5034,5037],{},[1824,5035,5036],{},"w",[1824,5038,1826],{},[1828,5040,5041],{"encoding":1830},"\\pi: \\mathcal{F}_t \\to w_t",[1805,5043,5045,5063,5120],{"className":5044,"ariaHidden":1835},[1834],[1805,5046,5048,5051,5054,5057,5060],{"className":5047},[1839],[1805,5049],{"className":5050,"style":5001},[1843],[1805,5052,2141],{"className":5053,"style":2292},[1848,1849],[1805,5055],{"className":5056,"style":2272},[2183],[1805,5058,1878],{"className":5059},[1943],[1805,5061],{"className":5062,"style":2272},[2183],[1805,5064,5066,5069,5111,5114,5117],{"className":5065},[1839],[1805,5067],{"className":5068,"style":1893},[1843],[1805,5070,5072,5076],{"className":5071},[1848],[1805,5073,5026],{"className":5074,"style":5075},[1848,2514],"margin-right:0.0993em;",[1805,5077,5079],{"className":5078},[1904],[1805,5080,5082,5103],{"className":5081},[1908,1909],[1805,5083,5085,5100],{"className":5084},[1913],[1805,5086,5088],{"className":5087,"style":2012},[1917],[1805,5089,5091,5094],{"style":5090},"top:-2.55em;margin-left:-0.0993em;margin-right:0.05em;",[1805,5092],{"className":5093,"style":1926},[1925],[1805,5095,5097],{"className":5096},[1930,1931,1932,1933],[1805,5098,1826],{"className":5099},[1848,1849,1933],[1805,5101,1951],{"className":5102},[1950],[1805,5104,5106],{"className":5105},[1913],[1805,5107,5109],{"className":5108,"style":1958},[1917],[1805,5110],{},[1805,5112],{"className":5113,"style":2272},[2183],[1805,5115,5031],{"className":5116},[1943],[1805,5118],{"className":5119,"style":2272},[2183],[1805,5121,5123,5126],{"className":5122},[1839],[1805,5124],{"className":5125,"style":1993},[1843],[1805,5127,5129,5133],{"className":5128},[1848],[1805,5130,5036],{"className":5131,"style":5132},[1848,1849],"margin-right:0.0269em;",[1805,5134,5136],{"className":5135},[1904],[1805,5137,5139,5160],{"className":5138},[1908,1909],[1805,5140,5142,5157],{"className":5141},[1913],[1805,5143,5145],{"className":5144,"style":2012},[1917],[1805,5146,5148,5151],{"style":5147},"top:-2.55em;margin-left:-0.0269em;margin-right:0.05em;",[1805,5149],{"className":5150,"style":1926},[1925],[1805,5152,5154],{"className":5153},[1930,1931,1932,1933],[1805,5155,1826],{"className":5156},[1848,1849,1933],[1805,5158,1951],{"className":5159},[1950],[1805,5161,5163],{"className":5162},[1913],[1805,5164,5166],{"className":5165,"style":1958},[1917],[1805,5167],{}," 或 ",[1805,5170,5172,5202],{"className":5171},[1808],[1805,5173,5175],{"className":5174},[1812],[1814,5176,5177],{"xmlns":1816},[1818,5178,5179,5199],{},[1821,5180,5181,5183,5185,5191,5193],{},[1824,5182,2141],{},[1876,5184,1878],{},[1864,5186,5187,5189],{},[1824,5188,5026],{"mathvariant":2196},[1824,5190,1826],{},[1876,5192,5031],{},[1864,5194,5195,5197],{},[1824,5196,1978],{},[1824,5198,1826],{},[1828,5200,5201],{"encoding":1830},"\\pi: \\mathcal{F}_t \\to u_t",[1805,5203,5205,5223,5278],{"className":5204,"ariaHidden":1835},[1834],[1805,5206,5208,5211,5214,5217,5220],{"className":5207},[1839],[1805,5209],{"className":5210,"style":5001},[1843],[1805,5212,2141],{"className":5213,"style":2292},[1848,1849],[1805,5215],{"className":5216,"style":2272},[2183],[1805,5218,1878],{"className":5219},[1943],[1805,5221],{"className":5222,"style":2272},[2183],[1805,5224,5226,5229,5269,5272,5275],{"className":5225},[1839],[1805,5227],{"className":5228,"style":1893},[1843],[1805,5230,5232,5235],{"className":5231},[1848],[1805,5233,5026],{"className":5234,"style":5075},[1848,2514],[1805,5236,5238],{"className":5237},[1904],[1805,5239,5241,5261],{"className":5240},[1908,1909],[1805,5242,5244,5258],{"className":5243},[1913],[1805,5245,5247],{"className":5246,"style":2012},[1917],[1805,5248,5249,5252],{"style":5090},[1805,5250],{"className":5251,"style":1926},[1925],[1805,5253,5255],{"className":5254},[1930,1931,1932,1933],[1805,5256,1826],{"className":5257},[1848,1849,1933],[1805,5259,1951],{"className":5260},[1950],[1805,5262,5264],{"className":5263},[1913],[1805,5265,5267],{"className":5266,"style":1958},[1917],[1805,5268],{},[1805,5270],{"className":5271,"style":2272},[2183],[1805,5273,5031],{"className":5274},[1943],[1805,5276],{"className":5277,"style":2272},[2183],[1805,5279,5281,5284],{"className":5280},[1839],[1805,5282],{"className":5283,"style":1993},[1843],[1805,5285,5287,5290],{"className":5286},[1848],[1805,5288,1978],{"className":5289},[1848,1849],[1805,5291,5293],{"className":5292},[1904],[1805,5294,5296,5316],{"className":5295},[1908,1909],[1805,5297,5299,5313],{"className":5298},[1913],[1805,5300,5302],{"className":5301,"style":2012},[1917],[1805,5303,5304,5307],{"style":2015},[1805,5305],{"className":5306,"style":1926},[1925],[1805,5308,5310],{"className":5309},[1930,1931,1932,1933],[1805,5311,1826],{"className":5312},[1848,1849,1933],[1805,5314,1951],{"className":5315},[1950],[1805,5317,5319],{"className":5318},[1913],[1805,5320,5322],{"className":5321,"style":1958},[1917],[1805,5323],{},"（从信息集到权重\u002F订单，参见第 03 章）；",[2992,5326,5327,5356],{},[1805,5328,5330,5344],{"className":5329},[1808],[1805,5331,5333],{"className":5332},[1812],[1814,5334,5335],{"xmlns":1816},[1818,5336,5337,5341],{},[1821,5338,5339],{},[1824,5340,4691],{"mathvariant":2196},[1828,5342,5343],{"encoding":1830},"\\mathcal{C}",[1805,5345,5347],{"className":5346,"ariaHidden":1835},[1834],[1805,5348,5350,5353],{"className":5349},[1839],[1805,5351],{"className":5352,"style":2892},[1843],[1805,5354,4691],{"className":5355,"style":4788},[1848,2514],"：成本与执行模型（参见第 05 章）；",[2992,5358,5359,5387],{},[1805,5360,5362,5375],{"className":5361},[1808],[1805,5363,5365],{"className":5364},[1812],[1814,5366,5367],{"xmlns":1816},[1818,5368,5369,5373],{},[1821,5370,5371],{},[1824,5372,3076],{"mathvariant":2196},[1828,5374,3229],{"encoding":1830},[1805,5376,5378],{"className":5377,"ariaHidden":1835},[1834],[1805,5379,5381,5384],{"className":5380},[1839],[1805,5382],{"className":5383,"style":2892},[1843],[1805,5385,3076],{"className":5386},[1848,2514],"：风险约束和风控规则（参见第 04、06 章）。",[1793,5389,5390,5391,5419,5420,5490],{},"“理想”的含义是：在任意时点 ",[1805,5392,5394,5407],{"className":5393},[1808],[1805,5395,5397],{"className":5396},[1812],[1814,5398,5399],{"xmlns":1816},[1818,5400,5401,5405],{},[1821,5402,5403],{},[1824,5404,1826],{},[1828,5406,1826],{"encoding":1830},[1805,5408,5410],{"className":5409,"ariaHidden":1835},[1834],[1805,5411,5413,5416],{"className":5412},[1839],[1805,5414],{"className":5415,"style":1844},[1843],[1805,5417,1826],{"className":5418},[1848,1849],"，回测中的信息集 ",[1805,5421,5423,5441],{"className":5422},[1808],[1805,5424,5426],{"className":5425},[1812],[1814,5427,5428],{"xmlns":1816},[1818,5429,5430,5438],{},[1821,5431,5432],{},[1864,5433,5434,5436],{},[1824,5435,5026],{"mathvariant":2196},[1824,5437,1826],{},[1828,5439,5440],{"encoding":1830},"\\mathcal{F}_t",[1805,5442,5444],{"className":5443,"ariaHidden":1835},[1834],[1805,5445,5447,5450],{"className":5446},[1839],[1805,5448],{"className":5449,"style":1893},[1843],[1805,5451,5453,5456],{"className":5452},[1848],[1805,5454,5026],{"className":5455,"style":5075},[1848,2514],[1805,5457,5459],{"className":5458},[1904],[1805,5460,5462,5482],{"className":5461},[1908,1909],[1805,5463,5465,5479],{"className":5464},[1913],[1805,5466,5468],{"className":5467,"style":2012},[1917],[1805,5469,5470,5473],{"style":5090},[1805,5471],{"className":5472,"style":1926},[1925],[1805,5474,5476],{"className":5475},[1930,1931,1932,1933],[1805,5477,1826],{"className":5478},[1848,1849,1933],[1805,5480,1951],{"className":5481},[1950],[1805,5483,5485],{"className":5484},[1913],[1805,5486,5488],{"className":5487,"style":1958},[1917],[1805,5489],{}," 与实盘中可用的信息集一致，不允许访问未来数据。",[1793,5492,5493,5494,4655,5496,5498],{},"在这个抽象下，一个回测框架需要在",[1800,5495,4654],{},[1800,5497,4658],{},"之间平衡：",[2999,5500,5501,5512],{},[2992,5502,5503,5504],{},"灵活性：\n",[2999,5505,5506,5509],{},[2992,5507,5508],{},"支持多种频率（日度、分钟级、事件驱动）；",[2992,5510,5511],{},"易于接入新的因子和策略逻辑；",[2992,5513,5514,5515],{},"严格性：\n",[2999,5516,5517,5520,5523],{},[2992,5518,5519],{},"强制执行“不可看未来”的信息集约束；",[2992,5521,5522],{},"对交易成本、滑点、约束等提供统一的建模接口；",[2992,5524,5525],{},"保证回测结果在给定数据版本和参数下可重复。",[1793,5527,5528],{},"从工程角度，常见做法包括：",[2999,5530,5531,5542,5557],{},[2992,5532,5533,5534,5537,5538,5541],{},"将",[1800,5535,5536],{},"数据访问层","与",[1800,5539,5540],{},"策略逻辑","解耦；",[2992,5543,5544,5545,5549,5550,5549,5553,5556],{},"提供统一的接口（如 ",[5546,5547,5548],"code",{},"on_bar",", ",[5546,5551,5552],{},"on_tick",[5546,5554,5555],{},"on_order_book","）供策略实现；",[2992,5558,5559,5560,5588,5589,5658],{},"对时间轴进行严格控制，确保策略只能使用 ",[1805,5561,5563,5576],{"className":5562},[1808],[1805,5564,5566],{"className":5565},[1812],[1814,5567,5568],{"xmlns":1816},[1818,5569,5570,5574],{},[1821,5571,5572],{},[1824,5573,1826],{},[1828,5575,1826],{"encoding":1830},[1805,5577,5579],{"className":5578,"ariaHidden":1835},[1834],[1805,5580,5582,5585],{"className":5581},[1839],[1805,5583],{"className":5584,"style":1844},[1843],[1805,5586,1826],{"className":5587},[1848,1849]," 时刻之前已经属于 ",[1805,5590,5592,5609],{"className":5591},[1808],[1805,5593,5595],{"className":5594},[1812],[1814,5596,5597],{"xmlns":1816},[1818,5598,5599,5607],{},[1821,5600,5601],{},[1864,5602,5603,5605],{},[1824,5604,5026],{"mathvariant":2196},[1824,5606,1826],{},[1828,5608,5440],{"encoding":1830},[1805,5610,5612],{"className":5611,"ariaHidden":1835},[1834],[1805,5613,5615,5618],{"className":5614},[1839],[1805,5616],{"className":5617,"style":1893},[1843],[1805,5619,5621,5624],{"className":5620},[1848],[1805,5622,5026],{"className":5623,"style":5075},[1848,2514],[1805,5625,5627],{"className":5626},[1904],[1805,5628,5630,5650],{"className":5629},[1908,1909],[1805,5631,5633,5647],{"className":5632},[1913],[1805,5634,5636],{"className":5635,"style":2012},[1917],[1805,5637,5638,5641],{"style":5090},[1805,5639],{"className":5640,"style":1926},[1925],[1805,5642,5644],{"className":5643},[1930,1931,1932,1933],[1805,5645,1826],{"className":5646},[1848,1849,1933],[1805,5648,1951],{"className":5649},[1950],[1805,5651,5653],{"className":5652},[1913],[1805,5654,5656],{"className":5655,"style":1958},[1917],[1805,5657],{}," 的数据，避免策略“回头看”。",[3338,5660,5662],{"id":5661},"_32-计算环境本地-vs-集群","3.2 计算环境：本地 vs 集群",[1793,5664,5665],{},"随着数据量（特别是高频 tick\u002FLOB 数据）和策略数量增加，单机计算往往难以满足需求：",[2999,5667,5668,5671,5674],{},[2992,5669,5670],{},"可以使用多进程\u002F多线程加速单机回测；",[2992,5672,5673],{},"对大量参数组合或蒙特卡洛模拟，可以使用分布式任务队列（如 Celery、Ray 等概念）；",[2992,5675,5676],{},"对非常大规模的数据分析，可考虑大数据框架（Spark\u002FFlink 等）。",[1793,5678,5679],{},"与纯工程项目不同，量化研究的计算通常更偏向“中等规模高密度数值计算”，需要在 I\u002FO、内存和 CPU 利用率之间综合权衡。",[2981,5681,5683],{"id":5682},"_4-交易与执行系统","4. 交易与执行系统",[3338,5685,5687],{"id":5686},"_41-系统边界与接口","4.1 系统边界与接口",[1793,5689,5690,5691,5771],{},"在许多机构中，策略逻辑与交易系统之间通过清晰的接口进行解耦。抽象来看，策略层输出的是“期望持仓路径”或“订单流” ",[1805,5692,5694,5716],{"className":5693},[1808],[1805,5695,5697],{"className":5696},[1812],[1814,5698,5699],{"xmlns":1816},[1818,5700,5701,5713],{},[1821,5702,5703,5705,5711],{},[1876,5704,2911],{"stretchy":2147},[1864,5706,5707,5709],{},[1824,5708,1978],{},[1824,5710,1826],{},[1876,5712,2920],{"stretchy":2147},[1828,5714,5715],{"encoding":1830},"\\{u_t\\}",[1805,5717,5719],{"className":5718,"ariaHidden":1835},[1834],[1805,5720,5722,5725,5728,5768],{"className":5721},[1839],[1805,5723],{"className":5724,"style":2285},[1843],[1805,5726,2911],{"className":5727},[2333],[1805,5729,5731,5734],{"className":5730},[1848],[1805,5732,1978],{"className":5733},[1848,1849],[1805,5735,5737],{"className":5736},[1904],[1805,5738,5740,5760],{"className":5739},[1908,1909],[1805,5741,5743,5757],{"className":5742},[1913],[1805,5744,5746],{"className":5745,"style":2012},[1917],[1805,5747,5748,5751],{"style":2015},[1805,5749],{"className":5750,"style":1926},[1925],[1805,5752,5754],{"className":5753},[1930,1931,1932,1933],[1805,5755,1826],{"className":5756},[1848,1849,1933],[1805,5758,1951],{"className":5759},[1950],[1805,5761,5763],{"className":5762},[1913],[1805,5764,5766],{"className":5765,"style":1958},[1917],[1805,5767],{},[1805,5769,2920],{"className":5770},[2445],"，交易系统则要把这些目标翻译成实际可执行的订单并发送到市场：",[2999,5773,5774,5777],{},[2992,5775,5776],{},"策略系统输出：目标持仓或订单建议；",[2992,5778,5779,5780],{},"交易系统负责：\n",[2999,5781,5782,5785,5788,5791],{},[2992,5783,5784],{},"将目标持仓转换为具体订单（价格、数量、类型）；",[2992,5786,5787],{},"与券商或交易所网关进行通信；",[2992,5789,5790],{},"处理订单回报和成交结果；",[2992,5792,5793],{},"实施部分风控（如价格保护、速率限制）。",[1793,5795,5796],{},"如此一来，策略开发者可以聚焦于信号与组合构建，而不需要过度关心底层协议和网络细节。",[3338,5798,5800],{"id":5799},"_42-延迟吞吐与容错","4.2 延迟、吞吐与容错",[1793,5802,5803],{},"对高频或敏感策略，交易系统需要满足：",[2999,5805,5806,5809,5812],{},[2992,5807,5808],{},"低延迟：从行情到订单的延迟尽量小；",[2992,5810,5811],{},"高吞吐：能处理高频率的行情更新和订单流；",[2992,5813,5814],{},"高可用：系统故障时能快速切换到备用节点或策略降级模式。",[1793,5816,5817],{},"可以用几个简单的定量指标来刻画：",[2999,5819,5820,6215,6429],{},[2992,5821,5822,5825,5826,5904,5905,5982,5983,6161,6164,6165,6214],{},[1800,5823,5824],{},"端到端延迟","：定义从关键行情事件时间戳 ",[1805,5827,5829,5848],{"className":5828},[1808],[1805,5830,5832],{"className":5831},[1812],[1814,5833,5834],{"xmlns":1816},[1818,5835,5836,5845],{},[1821,5837,5838],{},[1864,5839,5840,5842],{},[1824,5841,3081],{},[2210,5843,5844],{},"quote",[1828,5846,5847],{"encoding":1830},"T_{\\text{quote}}",[1805,5849,5851],{"className":5850,"ariaHidden":1835},[1834],[1805,5852,5854,5858],{"className":5853},[1839],[1805,5855],{"className":5856,"style":5857},[1843],"height:0.9694em;vertical-align:-0.2861em;",[1805,5859,5861,5864],{"className":5860},[1848],[1805,5862,3081],{"className":5863,"style":3735},[1848,1849],[1805,5865,5867],{"className":5866},[1904],[1805,5868,5870,5896],{"className":5869},[1908,1909],[1805,5871,5873,5893],{"className":5872},[1913],[1805,5874,5876],{"className":5875,"style":2012},[1917],[1805,5877,5878,5881],{"style":3750},[1805,5879],{"className":5880,"style":1926},[1925],[1805,5882,5884],{"className":5883},[1930,1931,1932,1933],[1805,5885,5887],{"className":5886},[1848,1933],[1805,5888,5890],{"className":5889},[1848,2567,1933],[1805,5891,5844],{"className":5892},[1848,1933],[1805,5894,1951],{"className":5895},[1950],[1805,5897,5899],{"className":5898},[1913],[1805,5900,5902],{"className":5901,"style":4868},[1917],[1805,5903],{}," 到订单进入市场时间戳 ",[1805,5906,5908,5927],{"className":5907},[1808],[1805,5909,5911],{"className":5910},[1812],[1814,5912,5913],{"xmlns":1816},[1818,5914,5915,5924],{},[1821,5916,5917],{},[1864,5918,5919,5921],{},[1824,5920,3081],{},[2210,5922,5923],{},"order",[1828,5925,5926],{"encoding":1830},"T_{\\text{order}}",[1805,5928,5930],{"className":5929,"ariaHidden":1835},[1834],[1805,5931,5933,5936],{"className":5932},[1839],[1805,5934],{"className":5935,"style":1893},[1843],[1805,5937,5939,5942],{"className":5938},[1848],[1805,5940,3081],{"className":5941,"style":3735},[1848,1849],[1805,5943,5945],{"className":5944},[1904],[1805,5946,5948,5974],{"className":5947},[1908,1909],[1805,5949,5951,5971],{"className":5950},[1913],[1805,5952,5954],{"className":5953,"style":2305},[1917],[1805,5955,5956,5959],{"style":3750},[1805,5957],{"className":5958,"style":1926},[1925],[1805,5960,5962],{"className":5961},[1930,1931,1932,1933],[1805,5963,5965],{"className":5964},[1848,1933],[1805,5966,5968],{"className":5967},[1848,2567,1933],[1805,5969,5923],{"className":5970},[1848,1933],[1805,5972,1951],{"className":5973},[1950],[1805,5975,5977],{"className":5976},[1913],[1805,5978,5980],{"className":5979,"style":1958},[1917],[1805,5981],{}," 的延迟",[1805,5984,5986],{"className":5985},[2114],[1805,5987,5989,6023],{"className":5988},[1808],[1805,5990,5992],{"className":5991},[1812],[1814,5993,5994],{"xmlns":1816,"display":2123},[1818,5995,5996,6020],{},[1821,5997,5998,6001,6003,6009,6012,6018],{},[1824,5999,6000],{},"L",[1876,6002,2136],{},[1864,6004,6005,6007],{},[1824,6006,3081],{},[2210,6008,5923],{},[1876,6010,6011],{},"−",[1864,6013,6014,6016],{},[1824,6015,3081],{},[2210,6017,5844],{},[1824,6019,3663],{"mathvariant":3662},[1828,6021,6022],{"encoding":1830},"L = T_{\\text{order}} - T_{\\text{quote}}.",[1805,6024,6026,6044,6106],{"className":6025,"ariaHidden":1835},[1834],[1805,6027,6029,6032,6035,6038,6041],{"className":6028},[1839],[1805,6030],{"className":6031,"style":2892},[1843],[1805,6033,6000],{"className":6034},[1848,1849],[1805,6036],{"className":6037,"style":2272},[2183],[1805,6039,2136],{"className":6040},[1943],[1805,6042],{"className":6043,"style":2272},[2183],[1805,6045,6047,6050,6096,6099,6103],{"className":6046},[1839],[1805,6048],{"className":6049,"style":1893},[1843],[1805,6051,6053,6056],{"className":6052},[1848],[1805,6054,3081],{"className":6055,"style":3735},[1848,1849],[1805,6057,6059],{"className":6058},[1904],[1805,6060,6062,6088],{"className":6061},[1908,1909],[1805,6063,6065,6085],{"className":6064},[1913],[1805,6066,6068],{"className":6067,"style":2305},[1917],[1805,6069,6070,6073],{"style":3750},[1805,6071],{"className":6072,"style":1926},[1925],[1805,6074,6076],{"className":6075},[1930,1931,1932,1933],[1805,6077,6079],{"className":6078},[1848,1933],[1805,6080,6082],{"className":6081},[1848,2567,1933],[1805,6083,5923],{"className":6084},[1848,1933],[1805,6086,1951],{"className":6087},[1950],[1805,6089,6091],{"className":6090},[1913],[1805,6092,6094],{"className":6093,"style":1958},[1917],[1805,6095],{},[1805,6097],{"className":6098,"style":2074},[2183],[1805,6100,6011],{"className":6101},[6102],"mbin",[1805,6104],{"className":6105,"style":2074},[2183],[1805,6107,6109,6112,6158],{"className":6108},[1839],[1805,6110],{"className":6111,"style":5857},[1843],[1805,6113,6115,6118],{"className":6114},[1848],[1805,6116,3081],{"className":6117,"style":3735},[1848,1849],[1805,6119,6121],{"className":6120},[1904],[1805,6122,6124,6150],{"className":6123},[1908,1909],[1805,6125,6127,6147],{"className":6126},[1913],[1805,6128,6130],{"className":6129,"style":2012},[1917],[1805,6131,6132,6135],{"style":3750},[1805,6133],{"className":6134,"style":1926},[1925],[1805,6136,6138],{"className":6137},[1930,1931,1932,1933],[1805,6139,6141],{"className":6140},[1848,1933],[1805,6142,6144],{"className":6143},[1848,2567,1933],[1805,6145,5844],{"className":6146},[1848,1933],[1805,6148,1951],{"className":6149},[1950],[1805,6151,6153],{"className":6152},[1913],[1805,6154,6156],{"className":6155,"style":4868},[1917],[1805,6157],{},[1805,6159,3663],{"className":6160},[1848],[6162,6163],"br",{},"对高频策略，不仅 ",[1805,6166,6168,6192],{"className":6167},[1808],[1805,6169,6171],{"className":6170},[1812],[1814,6172,6173],{"xmlns":1816},[1818,6174,6175,6189],{},[1821,6176,6177,6181,6184,6186],{},[1824,6178,6180],{"mathvariant":6179},"double-struck","E",[1876,6182,6183],{"stretchy":2147},"[",[1824,6185,6000],{},[1876,6187,6188],{"stretchy":2147},"]",[1828,6190,6191],{"encoding":1830},"\\mathbb{E}[L]",[1805,6193,6195],{"className":6194,"ariaHidden":1835},[1834],[1805,6196,6198,6201,6205,6208,6211],{"className":6197},[1839],[1805,6199],{"className":6200,"style":2285},[1843],[1805,6202,6180],{"className":6203},[1848,6204],"mathbb",[1805,6206,6183],{"className":6207},[2333],[1805,6209,6000],{"className":6210},[1848,1849],[1805,6212,6188],{"className":6213},[2445]," 要小，尾部分布（如 95%、99% 分位）也同样关键。",[2992,6216,6217,6220,6221,6313,6314,6344,6345,6428],{},[1800,6218,6219],{},"吞吐能力","：在给定硬件和架构下，系统在单位时间内可稳定处理的订单或行情事件数，可以记为 ",[1805,6222,6224,6247],{"className":6223},[1808],[1805,6225,6227],{"className":6226},[1812],[1814,6228,6229],{"xmlns":1816},[1818,6230,6231,6244],{},[1821,6232,6233],{},[1864,6234,6235,6238,6241],{},[1824,6236,6237],{},"Q",[1824,6239,6240],{},"max",[1876,6242,6243],{},"⁡",[1828,6245,6246],{"encoding":1830},"Q_{\\max}",[1805,6248,6250],{"className":6249,"ariaHidden":1835},[1834],[1805,6251,6253,6257],{"className":6252},[1839],[1805,6254],{"className":6255,"style":6256},[1843],"height:0.8778em;vertical-align:-0.1944em;",[1805,6258,6260,6263],{"className":6259},[1848],[1805,6261,6237],{"className":6262},[1848,1849],[1805,6264,6266],{"className":6265},[1904],[1805,6267,6269,6305],{"className":6268},[1908,1909],[1805,6270,6272,6302],{"className":6271},[1913],[1805,6273,6275],{"className":6274,"style":4049},[1917],[1805,6276,6277,6280],{"style":2015},[1805,6278],{"className":6279,"style":1926},[1925],[1805,6281,6283],{"className":6282},[1930,1931,1932,1933],[1805,6284,6286],{"className":6285},[1848,1933],[1805,6287,6290,6294,6298],{"className":6288},[6289,1933],"mop",[1805,6291,6293],{"className":6292},[1933],"m",[1805,6295,6297],{"className":6296},[1933],"a",[1805,6299,6301],{"className":6300},[1933],"x",[1805,6303,1951],{"className":6304},[1950],[1805,6306,6308],{"className":6307},[1913],[1805,6309,6311],{"className":6310,"style":1958},[1917],[1805,6312],{},"。当实际到达率 ",[1805,6315,6317,6332],{"className":6316},[1808],[1805,6318,6320],{"className":6319},[1812],[1814,6321,6322],{"xmlns":1816},[1818,6323,6324,6329],{},[1821,6325,6326],{},[1824,6327,6328],{},"λ",[1828,6330,6331],{"encoding":1830},"\\lambda",[1805,6333,6335],{"className":6334,"ariaHidden":1835},[1834],[1805,6336,6338,6341],{"className":6337},[1839],[1805,6339],{"className":6340,"style":3108},[1843],[1805,6342,6328],{"className":6343},[1848,1849]," 接近或超过 ",[1805,6346,6348,6367],{"className":6347},[1808],[1805,6349,6351],{"className":6350},[1812],[1814,6352,6353],{"xmlns":1816},[1818,6354,6355,6365],{},[1821,6356,6357],{},[1864,6358,6359,6361,6363],{},[1824,6360,6237],{},[1824,6362,6240],{},[1876,6364,6243],{},[1828,6366,6246],{"encoding":1830},[1805,6368,6370],{"className":6369,"ariaHidden":1835},[1834],[1805,6371,6373,6376],{"className":6372},[1839],[1805,6374],{"className":6375,"style":6256},[1843],[1805,6377,6379,6382],{"className":6378},[1848],[1805,6380,6237],{"className":6381},[1848,1849],[1805,6383,6385],{"className":6384},[1904],[1805,6386,6388,6420],{"className":6387},[1908,1909],[1805,6389,6391,6417],{"className":6390},[1913],[1805,6392,6394],{"className":6393,"style":4049},[1917],[1805,6395,6396,6399],{"style":2015},[1805,6397],{"className":6398,"style":1926},[1925],[1805,6400,6402],{"className":6401},[1930,1931,1932,1933],[1805,6403,6405],{"className":6404},[1848,1933],[1805,6406,6408,6411,6414],{"className":6407},[6289,1933],[1805,6409,6293],{"className":6410},[1933],[1805,6412,6297],{"className":6413},[1933],[1805,6415,6301],{"className":6416},[1933],[1805,6418,1951],{"className":6419},[1950],[1805,6421,6423],{"className":6422},[1913],[1805,6424,6426],{"className":6425,"style":1958},[1917],[1805,6427],{}," 时，系统进入“排队”状态，延迟会迅速放大（与简单排队论中的 M\u002FM\u002F1 直觉类似）。",[2992,6430,6431,6434,6435,6443,6445],{},[1800,6432,6433],{},"可用性（Availability）","：",[6436,6437,6441],"pre",{"className":6438,"code":6440,"language":2567},[6439],"language-text","   $$\n   \\text{Availability} = \\frac{\\text{正常服务时间}}{\\text{总时间}} = \\frac{\\text{MTBF}}{\\text{MTBF} + \\text{MTTR}},\n   $$\n",[5546,6442,6440],{"__ignoreMap":10},[6162,6444],{},"其中 MTBF（mean time between failures）是平均故障间隔时间，MTTR（mean time to repair）是平均修复时间。对量化平台来说，降低 MTTR（快速恢复和自动切换）往往比完全消灭故障更加现实。",[1793,6447,6448],{},"这些内容依赖于具体技术栈和架构设计（如异步 I\u002FO、消息队列、内存数据库等），本章只做概念性说明。",[2981,6450,6452],{"id":6451},"_5-风险与监控系统","5. 风险与监控系统",[3338,6454,6456],{"id":6455},"_51-实时监控","5.1 实时监控",[1793,6458,6459],{},"从抽象角度看，一个监控系统就是把“原始的系统状态和交易记录”映射成一组时间演化的指标向量：",[1805,6461,6463],{"className":6462},[2114],[1805,6464,6466,6516],{"className":6465},[1808],[1805,6467,6469],{"className":6468},[1812],[1814,6470,6471],{"xmlns":1816,"display":2123},[1818,6472,6473,6513],{},[1821,6474,6475,6477,6479,6481,6484,6486,6489,6491,6494,6496,6499,6501,6504,6511],{},[1824,6476,2197],{},[1876,6478,1878],{},[1876,6480,2911],{"stretchy":2147},[2210,6482,6483],{},"交易日志",[1876,6485,2163],{"separator":1835},[2210,6487,6488],{},"持仓",[1876,6490,2163],{"separator":1835},[2210,6492,6493],{},"市场数据",[1876,6495,2163],{"separator":1835},[2210,6497,6498],{},"系统日志",[1876,6500,2920],{"stretchy":2147},[1876,6502,6503],{},"⟶",[3366,6505,6506,6508],{},[1824,6507,3076],{"mathvariant":6179},[1824,6509,6510],{},"d",[1876,6512,2163],{"separator":1835},[1828,6514,6515],{"encoding":1830},"M: \\{\\text{交易日志}, \\text{持仓}, \\text{市场数据}, \\text{系统日志}\\} \\longrightarrow \\mathbb{R}^d,",[1805,6517,6519,6538,6602],{"className":6518,"ariaHidden":1835},[1834],[1805,6520,6522,6525,6529,6532,6535],{"className":6521},[1839],[1805,6523],{"className":6524,"style":2892},[1843],[1805,6526,2197],{"className":6527,"style":6528},[1848,1849],"margin-right:0.109em;",[1805,6530],{"className":6531,"style":2272},[2183],[1805,6533,1878],{"className":6534},[1943],[1805,6536],{"className":6537,"style":2272},[2183],[1805,6539,6541,6544,6547,6554,6557,6560,6566,6569,6572,6578,6581,6584,6590,6593,6596,6599],{"className":6540},[1839],[1805,6542],{"className":6543,"style":2285},[1843],[1805,6545,2911],{"className":6546},[2333],[1805,6548,6550],{"className":6549},[1848,2567],[1805,6551,6483],{"className":6552},[1848,6553],"cjk_fallback",[1805,6555,2163],{"className":6556},[2386],[1805,6558],{"className":6559,"style":2390},[2183],[1805,6561,6563],{"className":6562},[1848,2567],[1805,6564,6488],{"className":6565},[1848,6553],[1805,6567,2163],{"className":6568},[2386],[1805,6570],{"className":6571,"style":2390},[2183],[1805,6573,6575],{"className":6574},[1848,2567],[1805,6576,6493],{"className":6577},[1848,6553],[1805,6579,2163],{"className":6580},[2386],[1805,6582],{"className":6583,"style":2390},[2183],[1805,6585,6587],{"className":6586},[1848,2567],[1805,6588,6498],{"className":6589},[1848,6553],[1805,6591,2920],{"className":6592},[2445],[1805,6594],{"className":6595,"style":2272},[2183],[1805,6597,6503],{"className":6598},[1943],[1805,6600],{"className":6601,"style":2272},[2183],[1805,6603,6605,6609,6638],{"className":6604},[1839],[1805,6606],{"className":6607,"style":6608},[1843],"height:1.0935em;vertical-align:-0.1944em;",[1805,6610,6612,6615],{"className":6611},[1848],[1805,6613,3076],{"className":6614},[1848,6204],[1805,6616,6618],{"className":6617},[1904],[1805,6619,6621],{"className":6620},[1908],[1805,6622,6624],{"className":6623},[1913],[1805,6625,6627],{"className":6626,"style":3676},[1917],[1805,6628,6629,6632],{"style":3697},[1805,6630],{"className":6631,"style":1926},[1925],[1805,6633,6635],{"className":6634},[1930,1931,1932,1933],[1805,6636,6510],{"className":6637},[1848,1849,1933],[1805,6639,2163],{"className":6640},[2386],[1793,6642,6643,6644,6725],{},"在时间维度上得到指标时间序列 ",[1805,6645,6647,6669],{"className":6646},[1808],[1805,6648,6650],{"className":6649},[1812],[1814,6651,6652],{"xmlns":1816},[1818,6653,6654,6666],{},[1821,6655,6656,6658,6664],{},[1876,6657,2911],{"stretchy":2147},[1864,6659,6660,6662],{},[1824,6661,2197],{},[1824,6663,1826],{},[1876,6665,2920],{"stretchy":2147},[1828,6667,6668],{"encoding":1830},"\\{M_t\\}",[1805,6670,6672],{"className":6671,"ariaHidden":1835},[1834],[1805,6673,6675,6678,6681,6722],{"className":6674},[1839],[1805,6676],{"className":6677,"style":2285},[1843],[1805,6679,2911],{"className":6680},[2333],[1805,6682,6684,6687],{"className":6683},[1848],[1805,6685,2197],{"className":6686,"style":6528},[1848,1849],[1805,6688,6690],{"className":6689},[1904],[1805,6691,6693,6714],{"className":6692},[1908,1909],[1805,6694,6696,6711],{"className":6695},[1913],[1805,6697,6699],{"className":6698,"style":2012},[1917],[1805,6700,6702,6705],{"style":6701},"top:-2.55em;margin-left:-0.109em;margin-right:0.05em;",[1805,6703],{"className":6704,"style":1926},[1925],[1805,6706,6708],{"className":6707},[1930,1931,1932,1933],[1805,6709,1826],{"className":6710},[1848,1849,1933],[1805,6712,1951],{"className":6713},[1950],[1805,6715,6717],{"className":6716},[1913],[1805,6718,6720],{"className":6719,"style":1958},[1917],[1805,6721],{},[1805,6723,2920],{"className":6724},[2445],"。典型监控指标包括：",[2999,6727,6728,6731,6734],{},[2992,6729,6730],{},"策略层：净值曲线、收益率、风险指标、仓位、资金使用率；",[2992,6732,6733],{},"系统层：服务可用性、延迟、错误率、CPU\u002F内存使用；",[2992,6735,6736],{},"市场层：波动率水平、成交量、价差变化等。",[1793,6738,6739],{},"技术实现上，可以使用：",[2999,6741,6742,6745,6748],{},[2992,6743,6744],{},"指标采集（metrics）系统；",[2992,6746,6747],{},"日志集中化系统；",[2992,6749,6750],{},"告警系统（邮件、短信、IM 等）。",[1793,6752,6753],{},"在第 06 章中，我们已经将部分监控指标视为时间序列，进行滚动 t 检验和结构变点检验。从工程角度，风险与监控系统需要：",[2999,6755,6756,6759,6842],{},[2992,6757,6758],{},"支持指标的实时计算和存储；",[2992,6760,6761,6762,6841],{},"支持对 ",[1805,6763,6765,6786],{"className":6764},[1808],[1805,6766,6768],{"className":6767},[1812],[1814,6769,6770],{"xmlns":1816},[1818,6771,6772,6784],{},[1821,6773,6774,6776,6782],{},[1876,6775,2911],{"stretchy":2147},[1864,6777,6778,6780],{},[1824,6779,2197],{},[1824,6781,1826],{},[1876,6783,2920],{"stretchy":2147},[1828,6785,6668],{"encoding":1830},[1805,6787,6789],{"className":6788,"ariaHidden":1835},[1834],[1805,6790,6792,6795,6798,6838],{"className":6791},[1839],[1805,6793],{"className":6794,"style":2285},[1843],[1805,6796,2911],{"className":6797},[2333],[1805,6799,6801,6804],{"className":6800},[1848],[1805,6802,2197],{"className":6803,"style":6528},[1848,1849],[1805,6805,6807],{"className":6806},[1904],[1805,6808,6810,6830],{"className":6809},[1908,1909],[1805,6811,6813,6827],{"className":6812},[1913],[1805,6814,6816],{"className":6815,"style":2012},[1917],[1805,6817,6818,6821],{"style":6701},[1805,6819],{"className":6820,"style":1926},[1925],[1805,6822,6824],{"className":6823},[1930,1931,1932,1933],[1805,6825,1826],{"className":6826},[1848,1849,1933],[1805,6828,1951],{"className":6829},[1950],[1805,6831,6833],{"className":6832},[1913],[1805,6834,6836],{"className":6835,"style":1958},[1917],[1805,6837],{},[1805,6839,2920],{"className":6840},[2445]," 做窗口聚合、分解和告警；",[2992,6843,6844],{},"保证监控链路本身的可靠性（避免“监控挂了但策略还在跑”）。",[3338,6846,6848],{"id":6847},"_52-事后分析与报表","5.2 事后分析与报表",[2999,6850,6851,6854,6857],{},[2992,6852,6853],{},"每日\u002F每周\u002F每月自动生成策略表现和风险报表；",[2992,6855,6856],{},"支持对历史交易进行回顾和归因分析；",[2992,6858,6859],{},"为策略迭代和资金配置决策提供量化依据。",[2981,6861,6863],{"id":6862},"_6-调度与任务编排","6. 调度与任务编排",[1793,6865,6866],{},"量化系统中存在多种类型的任务，这些任务天然构成一个有向无环图（DAG）：节点是任务，边是前后依赖关系。",[2999,6868,6869,6872,6875],{},[2992,6870,6871],{},"批处理：夜间因子更新、历史回测、报表生成；",[2992,6873,6874],{},"定时任务：每日开盘前策略预计算、收盘后数据对账；",[2992,6876,6877],{},"实时任务：行情订阅、策略计算、下单执行。",[1793,6879,6880,6881,6956],{},"我们可以为每个任务 ",[1805,6882,6884,6904],{"className":6883},[1808],[1805,6885,6887],{"className":6886},[1812],[1814,6888,6889],{"xmlns":1816},[1818,6890,6891,6901],{},[1821,6892,6893],{},[1864,6894,6895,6898],{},[1824,6896,6897],{},"τ",[1824,6899,6900],{},"i",[1828,6902,6903],{"encoding":1830},"\\tau_i",[1805,6905,6907],{"className":6906,"ariaHidden":1835},[1834],[1805,6908,6910,6913],{"className":6909},[1839],[1805,6911],{"className":6912,"style":1993},[1843],[1805,6914,6916,6920],{"className":6915},[1848],[1805,6917,6897],{"className":6918,"style":6919},[1848,1849],"margin-right:0.1132em;",[1805,6921,6923],{"className":6922},[1904],[1805,6924,6926,6948],{"className":6925},[1908,1909],[1805,6927,6929,6945],{"className":6928},[1913],[1805,6930,6933],{"className":6931,"style":6932},[1917],"height:0.3117em;",[1805,6934,6936,6939],{"style":6935},"top:-2.55em;margin-left:-0.1132em;margin-right:0.05em;",[1805,6937],{"className":6938,"style":1926},[1925],[1805,6940,6942],{"className":6941},[1930,1931,1932,1933],[1805,6943,6900],{"className":6944},[1848,1849,1933],[1805,6946,1951],{"className":6947},[1950],[1805,6949,6951],{"className":6950},[1913],[1805,6952,6954],{"className":6953,"style":1958},[1917],[1805,6955],{}," 赋予：",[2999,6958,6959,6962,6965],{},[2992,6960,6961],{},"资源需求（CPU、内存、I\u002FO）；",[2992,6963,6964],{},"优先级（实盘路径 > 夜间回测 > 报表）；",[2992,6966,6967],{},"调度约束（例如“必须在开盘前完成”、“依赖某个上游任务成功”）。",[1793,6969,6970],{},"从形式化角度看，一个调度系统就是在资源约束和时序约束下，为这一组任务找到一个可行且“足够优”的执行计划。这和经典的任务调度\u002F作业车间问题（job-shop scheduling）有内在联系，工业界常借助已有的调度框架（如 Airflow 等）来实现 DAG 执行。",[1793,6972,6973],{},"典型做法是使用：",[2999,6975,6976,6979,6982],{},[2992,6977,6978],{},"Cron\u002F调度系统管理批处理；",[2992,6980,6981],{},"专门的流式计算引擎管理实时任务；",[2992,6983,6984],{},"对关键路径设置优先级和资源隔离，避免互相影响。",[2981,6986,6988],{"id":6987},"_7-工程实践建议","7. 工程实践建议",[1793,6990,6991],{},"从量化研究者与工程师协作的角度，以下实践往往能显著提高整体效率：",[2989,6993,6994,7007,7020,7033],{},[2992,6995,6996,6434,6999],{},[1800,6997,6998],{},"统一的代码规范与文档",[2999,7000,7001,7004],{},[2992,7002,7003],{},"对常用的数据结构、接口、命名方式达成共识；",[2992,7005,7006],{},"尽量避免同一概念在不同模块被命名成不同的词。",[2992,7008,7009,6434,7012],{},[1800,7010,7011],{},"模块化与可测试性",[2999,7013,7014,7017],{},[2992,7015,7016],{},"将策略逻辑、数据访问、执行逻辑拆分成相对独立的模块；",[2992,7018,7019],{},"为关键模块编写单元测试和集成测试。",[2992,7021,7022,6434,7025],{},[1800,7023,7024],{},"环境与依赖管理",[2999,7026,7027,7030],{},[2992,7028,7029],{},"使用虚拟环境或容器（如 Docker）管理依赖；",[2992,7031,7032],{},"在本地、测试和生产环境中保持尽可能一致的软件栈。",[2992,7034,7035,6434,7038],{},[1800,7036,7037],{},"研发流程与发布管理",[2999,7039,7040,7043],{},[2992,7041,7042],{},"为策略和系统的更新建立代码审查与发布流程；",[2992,7044,7045],{},"对线上版本进行灰度发布或分阶段放量，降低风险。",[2981,7047,7049],{"id":7048},"_8-小结","8. 小结",[1793,7051,7052],{},"本章从系统工程的视角勾勒了一个量化平台的主要组成部分：数据、研究、交易、风险与监控、调度。它为前几章的理论和策略提供了落地运行的“载体”。",[1793,7054,7055],{},"在实际工作中，资产定价、统计计量和工程技术是三个互相关联的维度：",[2999,7057,7058,7061,7064],{},[2992,7059,7060],{},"资产定价提供“策略应当具备什么样的风险–收益特征”的理论基准；",[2992,7062,7063],{},"计量方法提供“如何从数据中估计和检验这些特征”的工具；",[2992,7065,7066],{},"工程与工具链则保证“这些理论和策略可以在真实市场中以可控方式长期运行”。",[1793,7068,7069],{},"后续若需要，可以针对本章中的某个子系统（如数据平台或回测框架）单独扩展更技术细节的开发笔记。",[7071,7072],"hr",{},[2981,7074,7076],{"id":7075},"_9-自学手册设计一个可复现的量化研究流水线","9. 自学手册：设计一个可复现的量化研究流水线",[3338,7078,7080],{"id":7079},"_91-学习目标","9.1 学习目标",[1793,7082,7083],{},"学完本章后，你应当能够：",[2989,7085,7086,7089,7092,7095,7098],{},[2992,7087,7088],{},"画出数据平台、研究平台、交易系统、监控系统和调度系统之间的依赖关系；",[2992,7090,7091],{},"说明数据版本、代码版本、参数版本和环境版本如何共同决定一次回测结果；",[2992,7093,7094],{},"为因子更新、回测、报表和上线任务设计 DAG；",[2992,7096,7097],{},"判断一个研究项目是否具备可复现、可测试和可部署条件；",[2992,7099,7100],{},"识别量化工程中常见的耦合、隐式状态和运维风险。",[3338,7102,7104],{"id":7103},"_92-工程场景","9.2 工程场景",[1793,7106,7107],{},"团队里有三位研究员都在使用同一批数据构建因子。A 的回测结果很好，B 复现不了，C 上线后发现生产因子与研究因子不同。问题通常不在某一行模型代码，而在工程链路：",[2999,7109,7110,7113,7116,7119,7122],{},[2992,7111,7112],{},"数据是否来自同一版本？",[2992,7114,7115],{},"因子计算是否有固定依赖顺序？",[2992,7117,7118],{},"回测是否记录了参数和环境？",[2992,7120,7121],{},"研究函数是否能在生产批处理里无人工干预运行？",[2992,7123,7124],{},"失败任务是否会阻断下游报表和下单？",[1793,7126,7127],{},"本章的目标，是让你从“能跑一次”提升到“别人、明天、生产环境也能跑”。",[3338,7129,7131],{"id":7130},"_93-定义与工作流逻辑","9.3 定义与工作流逻辑",[7133,7134,7135,7151],"table",{},[7136,7137,7138],"thead",{},[7139,7140,7141,7145,7148],"tr",{},[7142,7143,7144],"th",{},"层级",[7142,7146,7147],{},"关注点",[7142,7149,7150],{},"典型失败模式",[7152,7153,7154,7166,7177,7188,7199],"tbody",{},[7139,7155,7156,7160,7163],{},[7157,7158,7159],"td",{},"数据层",[7157,7161,7162],{},"原始数据、清洗数据、因子数据的版本和血缘",[7157,7164,7165],{},"字段口径变了但回测未记录",[7139,7167,7168,7171,7174],{},[7157,7169,7170],{},"研究层",[7157,7172,7173],{},"因子、模型、回测和报告",[7157,7175,7176],{},"Notebook 隐式状态导致不可复现",[7139,7178,7179,7182,7185],{},[7157,7180,7181],{},"执行层",[7157,7183,7184],{},"目标权重到订单和成交回报",[7157,7186,7187],{},"接口变更或限额拒单未处理",[7139,7189,7190,7193,7196],{},[7157,7191,7192],{},"监控层",[7157,7194,7195],{},"指标、日志、告警和报表",[7157,7197,7198],{},"策略异常但监控链路失效",[7139,7200,7201,7204,7207],{},[7157,7202,7203],{},"调度层",[7157,7205,7206],{},"DAG、依赖、重试和资源隔离",[7157,7208,7209],{},"上游失败后下游使用旧数据",[1793,7211,7212],{},"一个最小可复现研究流水线应包含：",[2989,7214,7215,7221,7224,7227,7230],{},[2992,7216,7217,7220],{},[5546,7218,7219],{},"raw -> clean -> factor"," 的显式数据转换；",[2992,7222,7223],{},"每个转换任务记录输入版本、输出版本和运行时间；",[2992,7225,7226],{},"回测任务记录策略代码版本、参数、成本模型和数据版本；",[2992,7228,7229],{},"报表任务从回测产物生成，不重新隐式计算核心结果；",[2992,7231,7232],{},"失败任务停止依赖它的下游任务，并向负责人告警。",[3338,7234,7236],{"id":7235},"_94-迷你案例夜间因子更新-dag","9.4 迷你案例：夜间因子更新 DAG",[1793,7238,7239],{},"可以把日频因子更新设计成如下 DAG：",[7241,7242],"mermaid-diagram",{"code64":7243,"locale":7},"Zmxvd2NoYXJ0IExSCiAgQVsi5LiL6L296KGM5oOF5LiO6LSi5Yqh5aKe6YePIl0gLS0+IEJbIuWOn+Wni+aVsOaNruagoemqjCJdCiAgQiAtLT4gQ1si5riF5rSX5LiO5aSN5p2DIl0KICBDIC0tPiBEWyLmnoTlu7rlm6DlrZAiXQogIEQgLS0+IEVbIuWboOWtkOi0qOmHj+ajgOafpSJdCiAgRSAtLT4gRlsi55Sf5oiQ56CU56m25pWw5o2u5b+r54WnIl0KICBGIC0tPiBHWyLlm57mtYsv5qih5ouf55uY5L+h5Y+3Il0KICBHIC0tPiBIWyLml6XmiqXkuI7lkYroraYiXQ==",[1793,7245,7246],{},"每个节点都应有明确的成功条件。例如“因子质量检查”不只是任务退出码为 0，还包括：有效股票数量不低于阈值、缺失率不异常、与昨日因子相关性在合理范围内、极端值比例没有突然升高。",[3338,7248,7250],{"id":7249},"_95-常见错误与研究陷阱","9.5 常见错误与研究陷阱",[2999,7252,7253,7259,7265,7271,7277],{},[2992,7254,7255,7258],{},[1800,7256,7257],{},"Notebook 即平台","：交互式分析适合探索，但不适合作为唯一生产流水线。",[2992,7260,7261,7264],{},[1800,7262,7263],{},"版本只记录代码","：数据、参数、环境和外部模型不锁定，回测仍然不可复现。",[2992,7266,7267,7270],{},[1800,7268,7269],{},"任务失败后默默使用旧数据","：短期看似稳定，长期会让信号时点和数据口径混乱。",[2992,7272,7273,7276],{},[1800,7274,7275],{},"研究与生产两套实现长期分叉","：同一因子在两个系统中公式略有差异，实盘偏离难以定位。",[2992,7278,7279,7282],{},[1800,7280,7281],{},"监控系统没有被监控","：指标链路断了，策略仍继续运行，团队误以为一切正常。",[3338,7284,7286],{"id":7285},"_96-自测题与答案提示","9.6 自测题与答案提示",[2989,7288,7289,7292,7295,7298],{},[2992,7290,7291],{},"为什么回测结果应记录数据版本和参数版本？\n答案提示：收益由数据、代码、参数和成本模型共同决定；只记录代码无法复现结果。",[2992,7293,7294],{},"DAG 中为什么要显式停止依赖失败节点的下游任务？\n答案提示：防止下游使用旧数据或半成品数据，造成信号与监控失真。",[2992,7296,7297],{},"什么样的策略逻辑适合从研究迁移到生产？\n答案提示：输入输出清晰、无隐式状态、可测试、参数外置、运行时间可控。",[2992,7299,7300],{},"工程指标和投资指标为什么都重要？\n答案提示：投资指标衡量策略是否赚钱，工程指标衡量系统是否能稳定地产生这些投资结果。",[3338,7302,7304],{"id":7303},"_97-小结与过渡","9.7 小结与过渡",[1793,7306,7307],{},"工程章节回答的是“怎样让研究结果长期、稳定、可复现地运行”。没有可靠平台，数据清洗、因子检验、回测和上线监控都会变成一次性手工操作。下一章回到统计与计量方法，讨论如何用更严格的检验判断策略结果是否真实可靠，而不是偶然样本表现。",[7071,7309],{},[1793,7311,7312,6434],{},[1800,7313,7314],{},"参考资料（示意性）",[2999,7316,7317,7325,7332,7339],{},[2992,7318,7319,7320,7324],{},"Cochrane, J. H. (2005). ",[7321,7322,7323],"em",{},"Asset Pricing",". （理论背景）",[2992,7326,7327,7328,7331],{},"Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (1997). ",[7321,7329,7330],{},"The Econometrics of Financial Markets",". （实证与计量方法）",[2992,7333,7334,7335,7338],{},"Cartea, Á., Jaimungal, S., & Penalva, J. (2015). ",[7321,7336,7337],{},"Algorithmic and High-Frequency Trading."," （关于交易系统与执行）",[2992,7340,7341,7342,7345],{},"Kleppmann, M. (2017). ",[7321,7343,7344],{},"Designing Data-Intensive Applications."," （数据平台与系统设计的一般性参考）",{"title":10,"searchDepth":7347,"depth":7347,"links":7348},2,[7349,7350,7355,7359,7363,7367,7368,7369,7370],{"id":2983,"depth":7347,"text":2984},{"id":3335,"depth":7347,"text":3336,"children":7351},[7352,7354],{"id":3340,"depth":7353,"text":3341},3,{"id":3973,"depth":7353,"text":3974},{"id":4643,"depth":7347,"text":4644,"children":7356},[7357,7358],{"id":4647,"depth":7353,"text":4648},{"id":5661,"depth":7353,"text":5662},{"id":5682,"depth":7347,"text":5683,"children":7360},[7361,7362],{"id":5686,"depth":7353,"text":5687},{"id":5799,"depth":7353,"text":5800},{"id":6451,"depth":7347,"text":6452,"children":7364},[7365,7366],{"id":6455,"depth":7353,"text":6456},{"id":6847,"depth":7353,"text":6848},{"id":6862,"depth":7347,"text":6863},{"id":6987,"depth":7347,"text":6988},{"id":7048,"depth":7347,"text":7049},{"id":7075,"depth":7347,"text":7076,"children":7371},[7372,7373,7374,7375,7376,7377,7378],{"id":7079,"depth":7353,"text":7080},{"id":7103,"depth":7353,"text":7104},{"id":7130,"depth":7353,"text":7131},{"id":7235,"depth":7353,"text":7236},{"id":7249,"depth":7353,"text":7250},{"id":7285,"depth":7353,"text":7286},{"id":7303,"depth":7353,"text":7304},"设计从版本化数据、研究任务和模型制品到订单、监控和复现的工程依赖链。","md",{"sidebar":7382},{"order":7383},7,true,{"title":1767,"description":7379},"RRZSf79vuUnB0kcnUDBj8maQ_O0AjAi4X2C6PIlYDJ8",[7388,7390],{"title":1763,"path":1764,"stem":1765,"description":7389,"children":-1},"把研究原型转化为可监控、可回滚的生产系统，并识别绩效、风险和数据漂移。",{"title":1771,"path":1772,"stem":1773,"description":7391,"children":-1},"为收益、因子和策略绩效选择与时间和横截面依赖、多重检验相匹配的推断方法。",1785754759581]