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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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Python 与 R 版本。代码使用相同输入和公式，适合做交叉核验。点击“运行”后，先检查基准输出，再显示代码修改参数。",[1804,1805,1806],"h2",{"id":1806},"学习成果",[1793,1808,1809],{},"完成本章后，你应能够：",[1811,1812,1813,1817,1820,1916,1919,1922,1925],"ul",{},[1814,1815,1816],"li",{},"正确计算简单收益率、对数收益率、总收益率和现值；",[1814,1818,1819],{},"用协方差矩阵构造全局最小方差与切点组合；",[1814,1821,1822,1823,1915],{},"估计 CAPM 和多因子回归，解释 alpha、beta、标准误和 ",[1824,1825,1828,1858],"span",{"className":1826},[1827],"katex",[1824,1829,1832],{"className":1830},[1831],"katex-mathml",[1833,1834,1836],"math",{"xmlns":1835},"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML",[1837,1838,1839,1853],"semantics",{},[1840,1841,1842],"mrow",{},[1843,1844,1845,1849],"msup",{},[1846,1847,1848],"mi",{},"R",[1850,1851,1852],"mn",{},"2",[1854,1855,1857],"annotation",{"encoding":1856},"application\u002Fx-tex","R^2",[1824,1859,1863],{"className":1860,"ariaHidden":1862},[1861],"katex-html","true",[1824,1864,1867,1872],{"className":1865},[1866],"base",[1824,1868],{"className":1869,"style":1871},[1870],"strut","height:0.8141em;",[1824,1873,1876,1881],{"className":1874},[1875],"mord",[1824,1877,1848],{"className":1878,"style":1880},[1875,1879],"mathnormal","margin-right:0.0077em;",[1824,1882,1885],{"className":1883},[1884],"msupsub",[1824,1886,1889],{"className":1887},[1888],"vlist-t",[1824,1890,1893],{"className":1891},[1892],"vlist-r",[1824,1894,1897],{"className":1895,"style":1871},[1896],"vlist",[1824,1898,1900,1905],{"style":1899},"top:-3.063em;margin-right:0.05em;",[1824,1901],{"className":1902,"style":1904},[1903],"pstrut","height:2.7em;",[1824,1906,1912],{"className":1907},[1908,1909,1910,1911],"sizing","reset-size6","size3","mtight",[1824,1913,1852],{"className":1914},[1875,1911],"；",[1814,1917,1918],{},"用 Euler 方程矩条件理解 SDF 参数估计；",[1814,1920,1921],{},"用风险中性二叉树计算欧式期权价格；",[1814,1923,1924],{},"计算债券价格、Macaulay 久期、修正久期和凸性；",[1814,1926,1927],{},"区分教学模拟、统计证据和真实可交易结论。",[1929,1930,1932],"tip",{"title":1931},"运行环境","Python 单元由项目已有的 Pyodide 运行时执行，R 单元由 webR 执行。首次运行需要加载浏览器运行时。示例优先使用 NumPy、SciPy、Statsmodels、Matplotlib 和 base R，避免依赖无法在 WebAssembly 中运行的本地库。",[1804,1934,1936],{"id":1935},"实验一收益率现金流与现值","实验一：收益率、现金流与现值",[1938,1939,1940],"h3",{"id":1940},"收益率定义",[1793,1942,1943,1944,2044,2045,2118,2119,2192],{},"若期初价格为 ",[1824,1945,1947,1977],{"className":1946},[1827],[1824,1948,1950],{"className":1949},[1831],[1833,1951,1952],{"xmlns":1835},[1837,1953,1954,1974],{},[1840,1955,1956],{},[1957,1958,1959,1962],"msub",{},[1846,1960,1961],{},"P",[1840,1963,1964,1967,1971],{},[1846,1965,1966],{},"t",[1968,1969,1970],"mo",{},"−",[1850,1972,1973],{},"1",[1854,1975,1976],{"encoding":1856},"P_{t-1}",[1824,1978,1980],{"className":1979,"ariaHidden":1862},[1861],[1824,1981,1983,1987],{"className":1982},[1866],[1824,1984],{"className":1985,"style":1986},[1870],"height:0.8917em;vertical-align:-0.2083em;",[1824,1988,1990,1994],{"className":1989},[1875],[1824,1991,1961],{"className":1992,"style":1993},[1875,1879],"margin-right:0.1389em;",[1824,1995,1997],{"className":1996},[1884],[1824,1998,2001,2035],{"className":1999},[1888,2000],"vlist-t2",[1824,2002,2004,2030],{"className":2003},[1892],[1824,2005,2008],{"className":2006,"style":2007},[1896],"height:0.3011em;",[1824,2009,2011,2014],{"style":2010},"top:-2.55em;margin-left:-0.1389em;margin-right:0.05em;",[1824,2012],{"className":2013,"style":1904},[1903],[1824,2015,2017],{"className":2016},[1908,1909,1910,1911],[1824,2018,2020,2023,2027],{"className":2019},[1875,1911],[1824,2021,1966],{"className":2022},[1875,1879,1911],[1824,2024,1970],{"className":2025},[2026,1911],"mbin",[1824,2028,1973],{"className":2029},[1875,1911],[1824,2031,2034],{"className":2032},[2033],"vlist-s","​",[1824,2036,2038],{"className":2037},[1892],[1824,2039,2042],{"className":2040,"style":2041},[1896],"height:0.2083em;",[1824,2043],{},"、期末价格为 ",[1824,2046,2048,2066],{"className":2047},[1827],[1824,2049,2051],{"className":2050},[1831],[1833,2052,2053],{"xmlns":1835},[1837,2054,2055,2063],{},[1840,2056,2057],{},[1957,2058,2059,2061],{},[1846,2060,1961],{},[1846,2062,1966],{},[1854,2064,2065],{"encoding":1856},"P_t",[1824,2067,2069],{"className":2068,"ariaHidden":1862},[1861],[1824,2070,2072,2076],{"className":2071},[1866],[1824,2073],{"className":2074,"style":2075},[1870],"height:0.8333em;vertical-align:-0.15em;",[1824,2077,2079,2082],{"className":2078},[1875],[1824,2080,1961],{"className":2081,"style":1993},[1875,1879],[1824,2083,2085],{"className":2084},[1884],[1824,2086,2088,2109],{"className":2087},[1888,2000],[1824,2089,2091,2106],{"className":2090},[1892],[1824,2092,2095],{"className":2093,"style":2094},[1896],"height:0.2806em;",[1824,2096,2097,2100],{"style":2010},[1824,2098],{"className":2099,"style":1904},[1903],[1824,2101,2103],{"className":2102},[1908,1909,1910,1911],[1824,2104,1966],{"className":2105},[1875,1879,1911],[1824,2107,2034],{"className":2108},[2033],[1824,2110,2112],{"className":2111},[1892],[1824,2113,2116],{"className":2114,"style":2115},[1896],"height:0.15em;",[1824,2117],{},"、期间分红为 ",[1824,2120,2122,2141],{"className":2121},[1827],[1824,2123,2125],{"className":2124},[1831],[1833,2126,2127],{"xmlns":1835},[1837,2128,2129,2138],{},[1840,2130,2131],{},[1957,2132,2133,2136],{},[1846,2134,2135],{},"D",[1846,2137,1966],{},[1854,2139,2140],{"encoding":1856},"D_t",[1824,2142,2144],{"className":2143,"ariaHidden":1862},[1861],[1824,2145,2147,2150],{"className":2146},[1866],[1824,2148],{"className":2149,"style":2075},[1870],[1824,2151,2153,2157],{"className":2152},[1875],[1824,2154,2135],{"className":2155,"style":2156},[1875,1879],"margin-right:0.0278em;",[1824,2158,2160],{"className":2159},[1884],[1824,2161,2163,2184],{"className":2162},[1888,2000],[1824,2164,2166,2181],{"className":2165},[1892],[1824,2167,2169],{"className":2168,"style":2094},[1896],[1824,2170,2172,2175],{"style":2171},"top:-2.55em;margin-left:-0.0278em;margin-right:0.05em;",[1824,2173],{"className":2174,"style":1904},[1903],[1824,2176,2178],{"className":2177},[1908,1909,1910,1911],[1824,2179,1966],{"className":2180},[1875,1879,1911],[1824,2182,2034],{"className":2183},[2033],[1824,2185,2187],{"className":2186},[1892],[1824,2188,2190],{"className":2189,"style":2115},[1896],[1824,2191],{},"，总简单收益率为：",[1824,2194,2197],{"className":2195},[2196],"katex-display",[1824,2198,2200,2272],{"className":2199},[1827],[1824,2201,2203],{"className":2202},[1831],[1833,2204,2206],{"xmlns":1835,"display":2205},"block",[1837,2207,2208,2269],{},[1840,2209,2210,2216,2219,2265],{},[1957,2211,2212,2214],{},[1846,2213,1848],{},[1846,2215,1966],{},[1968,2217,2218],{},"=",[2220,2221,2222,2253],"mfrac",{},[1840,2223,2224,2230,2233,2239,2241],{},[1957,2225,2226,2228],{},[1846,2227,1961],{},[1846,2229,1966],{},[1968,2231,2232],{},"+",[1957,2234,2235,2237],{},[1846,2236,2135],{},[1846,2238,1966],{},[1968,2240,1970],{},[1957,2242,2243,2245],{},[1846,2244,1961],{},[1840,2246,2247,2249,2251],{},[1846,2248,1966],{},[1968,2250,1970],{},[1850,2252,1973],{},[1957,2254,2255,2257],{},[1846,2256,1961],{},[1840,2258,2259,2261,2263],{},[1846,2260,1966],{},[1968,2262,1970],{},[1850,2264,1973],{},[1846,2266,2268],{"mathvariant":2267},"normal",".",[1854,2270,2271],{"encoding":1856},"R_t=\\frac{P_t+D_t-P_{t-1}}{P_{t-1}}.",[1824,2273,2275,2334],{"className":2274,"ariaHidden":1862},[1861],[1824,2276,2278,2281,2322,2327,2331],{"className":2277},[1866],[1824,2279],{"className":2280,"style":2075},[1870],[1824,2282,2284,2287],{"className":2283},[1875],[1824,2285,1848],{"className":2286,"style":1880},[1875,1879],[1824,2288,2290],{"className":2289},[1884],[1824,2291,2293,2314],{"className":2292},[1888,2000],[1824,2294,2296,2311],{"className":2295},[1892],[1824,2297,2299],{"className":2298,"style":2094},[1896],[1824,2300,2302,2305],{"style":2301},"top:-2.55em;margin-left:-0.0077em;margin-right:0.05em;",[1824,2303],{"className":2304,"style":1904},[1903],[1824,2306,2308],{"className":2307},[1908,1909,1910,1911],[1824,2309,1966],{"className":2310},[1875,1879,1911],[1824,2312,2034],{"className":2313},[2033],[1824,2315,2317],{"className":2316},[1892],[1824,2318,2320],{"className":2319,"style":2115},[1896],[1824,2321],{},[1824,2323],{"className":2324,"style":2326},[2325],"mspace","margin-right:0.2778em;",[1824,2328,2218],{"className":2329},[2330],"mrel",[1824,2332],{"className":2333,"style":2326},[2325],[1824,2335,2337,2341,2605],{"className":2336},[1866],[1824,2338],{"className":2339,"style":2340},[1870],"height:2.2547em;vertical-align:-0.8943em;",[1824,2342,2344,2349,2601],{"className":2343},[1875],[1824,2345],{"className":2346},[2347,2348],"mopen","nulldelimiter",[1824,2350,2352],{"className":2351},[2220],[1824,2353,2355,2592],{"className":2354},[1888,2000],[1824,2356,2358,2589],{"className":2357},[1892],[1824,2359,2362,2421,2432],{"className":2360,"style":2361},[1896],"height:1.3603em;",[1824,2363,2365,2369],{"style":2364},"top:-2.314em;",[1824,2366],{"className":2367,"style":2368},[1903],"height:3em;",[1824,2370,2372],{"className":2371},[1875],[1824,2373,2375,2378],{"className":2374},[1875],[1824,2376,1961],{"className":2377,"style":1993},[1875,1879],[1824,2379,2381],{"className":2380},[1884],[1824,2382,2384,2413],{"className":2383},[1888,2000],[1824,2385,2387,2410],{"className":2386},[1892],[1824,2388,2390],{"className":2389,"style":2007},[1896],[1824,2391,2392,2395],{"style":2010},[1824,2393],{"className":2394,"style":1904},[1903],[1824,2396,2398],{"className":2397},[1908,1909,1910,1911],[1824,2399,2401,2404,2407],{"className":2400},[1875,1911],[1824,2402,1966],{"className":2403},[1875,1879,1911],[1824,2405,1970],{"className":2406},[2026,1911],[1824,2408,1973],{"className":2409},[1875,1911],[1824,2411,2034],{"className":2412},[2033],[1824,2414,2416],{"className":2415},[1892],[1824,2417,2419],{"className":2418,"style":2041},[1896],[1824,2420],{},[1824,2422,2424,2427],{"style":2423},"top:-3.23em;",[1824,2425],{"className":2426,"style":2368},[1903],[1824,2428],{"className":2429,"style":2431},[2430],"frac-line","border-bottom-width:0.04em;",[1824,2433,2435,2438],{"style":2434},"top:-3.677em;",[1824,2436],{"className":2437,"style":2368},[1903],[1824,2439,2441,2481,2485,2488,2491,2531,2534,2537,2540],{"className":2440},[1875],[1824,2442,2444,2447],{"className":2443},[1875],[1824,2445,1961],{"className":2446,"style":1993},[1875,1879],[1824,2448,2450],{"className":2449},[1884],[1824,2451,2453,2473],{"className":2452},[1888,2000],[1824,2454,2456,2470],{"className":2455},[1892],[1824,2457,2459],{"className":2458,"style":2094},[1896],[1824,2460,2461,2464],{"style":2010},[1824,2462],{"className":2463,"style":1904},[1903],[1824,2465,2467],{"className":2466},[1908,1909,1910,1911],[1824,2468,1966],{"className":2469},[1875,1879,1911],[1824,2471,2034],{"className":2472},[2033],[1824,2474,2476],{"className":2475},[1892],[1824,2477,2479],{"className":2478,"style":2115},[1896],[1824,2480],{},[1824,2482],{"className":2483,"style":2484},[2325],"margin-right:0.2222em;",[1824,2486,2232],{"className":2487},[2026],[1824,2489],{"className":2490,"style":2484},[2325],[1824,2492,2494,2497],{"className":2493},[1875],[1824,2495,2135],{"className":2496,"style":2156},[1875,1879],[1824,2498,2500],{"className":2499},[1884],[1824,2501,2503,2523],{"className":2502},[1888,2000],[1824,2504,2506,2520],{"className":2505},[1892],[1824,2507,2509],{"className":2508,"style":2094},[1896],[1824,2510,2511,2514],{"style":2171},[1824,2512],{"className":2513,"style":1904},[1903],[1824,2515,2517],{"className":2516},[1908,1909,1910,1911],[1824,2518,1966],{"className":2519},[1875,1879,1911],[1824,2521,2034],{"className":2522},[2033],[1824,2524,2526],{"className":2525},[1892],[1824,2527,2529],{"className":2528,"style":2115},[1896],[1824,2530],{},[1824,2532],{"className":2533,"style":2484},[2325],[1824,2535,1970],{"className":2536},[2026],[1824,2538],{"className":2539,"style":2484},[2325],[1824,2541,2543,2546],{"className":2542},[1875],[1824,2544,1961],{"className":2545,"style":1993},[1875,1879],[1824,2547,2549],{"className":2548},[1884],[1824,2550,2552,2581],{"className":2551},[1888,2000],[1824,2553,2555,2578],{"className":2554},[1892],[1824,2556,2558],{"className":2557,"style":2007},[1896],[1824,2559,2560,2563],{"style":2010},[1824,2561],{"className":2562,"style":1904},[1903],[1824,2564,2566],{"className":2565},[1908,1909,1910,1911],[1824,2567,2569,2572,2575],{"className":2568},[1875,1911],[1824,2570,1966],{"className":2571},[1875,1879,1911],[1824,2573,1970],{"className":2574},[2026,1911],[1824,2576,1973],{"className":2577},[1875,1911],[1824,2579,2034],{"className":2580},[2033],[1824,2582,2584],{"className":2583},[1892],[1824,2585,2587],{"className":2586,"style":2041},[1896],[1824,2588],{},[1824,2590,2034],{"className":2591},[2033],[1824,2593,2595],{"className":2594},[1892],[1824,2596,2599],{"className":2597,"style":2598},[1896],"height:0.8943em;",[1824,2600],{},[1824,2602],{"className":2603},[2604,2348],"mclose",[1824,2606,2268],{"className":2607},[1875],[1793,2609,2610,2611,2704],{},"财富增长因子是 ",[1824,2612,2614,2636],{"className":2613},[1827],[1824,2615,2617],{"className":2616},[1831],[1833,2618,2619],{"xmlns":1835},[1837,2620,2621,2633],{},[1840,2622,2623,2625,2627],{},[1850,2624,1973],{},[1968,2626,2232],{},[1957,2628,2629,2631],{},[1846,2630,1848],{},[1846,2632,1966],{},[1854,2634,2635],{"encoding":1856},"1+R_t",[1824,2637,2639,2658],{"className":2638,"ariaHidden":1862},[1861],[1824,2640,2642,2646,2649,2652,2655],{"className":2641},[1866],[1824,2643],{"className":2644,"style":2645},[1870],"height:0.7278em;vertical-align:-0.0833em;",[1824,2647,1973],{"className":2648},[1875],[1824,2650],{"className":2651,"style":2484},[2325],[1824,2653,2232],{"className":2654},[2026],[1824,2656],{"className":2657,"style":2484},[2325],[1824,2659,2661,2664],{"className":2660},[1866],[1824,2662],{"className":2663,"style":2075},[1870],[1824,2665,2667,2670],{"className":2666},[1875],[1824,2668,1848],{"className":2669,"style":1880},[1875,1879],[1824,2671,2673],{"className":2672},[1884],[1824,2674,2676,2696],{"className":2675},[1888,2000],[1824,2677,2679,2693],{"className":2678},[1892],[1824,2680,2682],{"className":2681,"style":2094},[1896],[1824,2683,2684,2687],{"style":2301},[1824,2685],{"className":2686,"style":1904},[1903],[1824,2688,2690],{"className":2689},[1908,1909,1910,1911],[1824,2691,1966],{"className":2692},[1875,1879,1911],[1824,2694,2034],{"className":2695},[2033],[1824,2697,2699],{"className":2698},[1892],[1824,2700,2702],{"className":2701,"style":2115},[1896],[1824,2703],{},"，多期累计收益必须连乘：",[1824,2706,2708],{"className":2707},[2196],[1824,2709,2711,2778],{"className":2710},[1827],[1824,2712,2714],{"className":2713},[1831],[1833,2715,2716],{"xmlns":1835,"display":2205},[1837,2717,2718,2775],{},[1840,2719,2720,2722,2724,2738,2740,2756,2760,2762,2764,2770,2773],{},[1850,2721,1973],{},[1968,2723,2232],{},[1957,2725,2726,2728],{},[1846,2727,1848],{},[1840,2729,2730,2732,2735],{},[1850,2731,1973],{},[1968,2733,2734],{},":",[1846,2736,2737],{},"T",[1968,2739,2218],{},[2741,2742,2743,2746,2754],"munderover",{},[1968,2744,2745],{},"∏",[1840,2747,2748,2750,2752],{},[1846,2749,1966],{},[1968,2751,2218],{},[1850,2753,1973],{},[1846,2755,2737],{},[1968,2757,2759],{"stretchy":2758},"false","(",[1850,2761,1973],{},[1968,2763,2232],{},[1957,2765,2766,2768],{},[1846,2767,1848],{},[1846,2769,1966],{},[1968,2771,2772],{"stretchy":2758},")",[1846,2774,2268],{"mathvariant":2267},[1854,2776,2777],{"encoding":1856},"1+R_{1:T}=\\prod_{t=1}^T(1+R_t).",[1824,2779,2781,2799,2864,2960],{"className":2780,"ariaHidden":1862},[1861],[1824,2782,2784,2787,2790,2793,2796],{"className":2783},[1866],[1824,2785],{"className":2786,"style":2645},[1870],[1824,2788,1973],{"className":2789},[1875],[1824,2791],{"className":2792,"style":2484},[2325],[1824,2794,2232],{"className":2795},[2026],[1824,2797],{"className":2798,"style":2484},[2325],[1824,2800,2802,2805,2855,2858,2861],{"className":2801},[1866],[1824,2803],{"className":2804,"style":2075},[1870],[1824,2806,2808,2811],{"className":2807},[1875],[1824,2809,1848],{"className":2810,"style":1880},[1875,1879],[1824,2812,2814],{"className":2813},[1884],[1824,2815,2817,2847],{"className":2816},[1888,2000],[1824,2818,2820,2844],{"className":2819},[1892],[1824,2821,2824],{"className":2822,"style":2823},[1896],"height:0.3283em;",[1824,2825,2826,2829],{"style":2301},[1824,2827],{"className":2828,"style":1904},[1903],[1824,2830,2832],{"className":2831},[1908,1909,1910,1911],[1824,2833,2835,2838,2841],{"className":2834},[1875,1911],[1824,2836,1973],{"className":2837},[1875,1911],[1824,2839,2734],{"className":2840},[2330,1911],[1824,2842,2737],{"className":2843,"style":1993},[1875,1879,1911],[1824,2845,2034],{"className":2846},[2033],[1824,2848,2850],{"className":2849},[1892],[1824,2851,2853],{"className":2852,"style":2115},[1896],[1824,2854],{},[1824,2856],{"className":2857,"style":2326},[2325],[1824,2859,2218],{"className":2860},[2330],[1824,2862],{"className":2863,"style":2326},[2325],[1824,2865,2867,2871,2945,2948,2951,2954,2957],{"className":2866},[1866],[1824,2868],{"className":2869,"style":2870},[1870],"height:3.0954em;vertical-align:-1.2671em;",[1824,2872,2876],{"className":2873},[2874,2875],"mop","op-limits",[1824,2877,2879,2936],{"className":2878},[1888,2000],[1824,2880,2882,2933],{"className":2881},[1892],[1824,2883,2886,2908,2921],{"className":2884,"style":2885},[1896],"height:1.8283em;",[1824,2887,2889,2893],{"style":2888},"top:-1.8829em;margin-left:0em;",[1824,2890],{"className":2891,"style":2892},[1903],"height:3.05em;",[1824,2894,2896],{"className":2895},[1908,1909,1910,1911],[1824,2897,2899,2902,2905],{"className":2898},[1875,1911],[1824,2900,1966],{"className":2901},[1875,1879,1911],[1824,2903,2218],{"className":2904},[2330,1911],[1824,2906,1973],{"className":2907},[1875,1911],[1824,2909,2911,2914],{"style":2910},"top:-3.05em;",[1824,2912],{"className":2913,"style":2892},[1903],[1824,2915,2916],{},[1824,2917,2745],{"className":2918},[2874,2919,2920],"op-symbol","large-op",[1824,2922,2924,2927],{"style":2923},"top:-4.3em;margin-left:0em;",[1824,2925],{"className":2926,"style":2892},[1903],[1824,2928,2930],{"className":2929},[1908,1909,1910,1911],[1824,2931,2737],{"className":2932,"style":1993},[1875,1879,1911],[1824,2934,2034],{"className":2935},[2033],[1824,2937,2939],{"className":2938},[1892],[1824,2940,2943],{"className":2941,"style":2942},[1896],"height:1.2671em;",[1824,2944],{},[1824,2946,2759],{"className":2947},[2347],[1824,2949,1973],{"className":2950},[1875],[1824,2952],{"className":2953,"style":2484},[2325],[1824,2955,2232],{"className":2956},[2026],[1824,2958],{"className":2959,"style":2484},[2325],[1824,2961,2963,2967,3007,3010],{"className":2962},[1866],[1824,2964],{"className":2965,"style":2966},[1870],"height:1em;vertical-align:-0.25em;",[1824,2968,2970,2973],{"className":2969},[1875],[1824,2971,1848],{"className":2972,"style":1880},[1875,1879],[1824,2974,2976],{"className":2975},[1884],[1824,2977,2979,2999],{"className":2978},[1888,2000],[1824,2980,2982,2996],{"className":2981},[1892],[1824,2983,2985],{"className":2984,"style":2094},[1896],[1824,2986,2987,2990],{"style":2301},[1824,2988],{"className":2989,"style":1904},[1903],[1824,2991,2993],{"className":2992},[1908,1909,1910,1911],[1824,2994,1966],{"className":2995},[1875,1879,1911],[1824,2997,2034],{"className":2998},[2033],[1824,3000,3002],{"className":3001},[1892],[1824,3003,3005],{"className":3004,"style":2115},[1896],[1824,3006],{},[1824,3008,2772],{"className":3009},[2604],[1824,3011,2268],{"className":3012},[1875],[1793,3014,3015,3016,3197],{},"对数收益率 ",[1824,3017,3019,3060],{"className":3018},[1827],[1824,3020,3022],{"className":3021},[1831],[1833,3023,3024],{"xmlns":1835},[1837,3025,3026,3057],{},[1840,3027,3028,3035,3037,3040,3043,3045,3047,3049,3055],{},[1957,3029,3030,3033],{},[1846,3031,3032],{},"r",[1846,3034,1966],{},[1968,3036,2218],{},[1846,3038,3039],{},"log",[1968,3041,3042],{},"⁡",[1968,3044,2759],{"stretchy":2758},[1850,3046,1973],{},[1968,3048,2232],{},[1957,3050,3051,3053],{},[1846,3052,1848],{},[1846,3054,1966],{},[1968,3056,2772],{"stretchy":2758},[1854,3058,3059],{"encoding":1856},"r_t=\\log(1+R_t)",[1824,3061,3063,3119,3148],{"className":3062,"ariaHidden":1862},[1861],[1824,3064,3066,3070,3110,3113,3116],{"className":3065},[1866],[1824,3067],{"className":3068,"style":3069},[1870],"height:0.5806em;vertical-align:-0.15em;",[1824,3071,3073,3076],{"className":3072},[1875],[1824,3074,3032],{"className":3075,"style":2156},[1875,1879],[1824,3077,3079],{"className":3078},[1884],[1824,3080,3082,3102],{"className":3081},[1888,2000],[1824,3083,3085,3099],{"className":3084},[1892],[1824,3086,3088],{"className":3087,"style":2094},[1896],[1824,3089,3090,3093],{"style":2171},[1824,3091],{"className":3092,"style":1904},[1903],[1824,3094,3096],{"className":3095},[1908,1909,1910,1911],[1824,3097,1966],{"className":3098},[1875,1879,1911],[1824,3100,2034],{"className":3101},[2033],[1824,3103,3105],{"className":3104},[1892],[1824,3106,3108],{"className":3107,"style":2115},[1896],[1824,3109],{},[1824,3111],{"className":3112,"style":2326},[2325],[1824,3114,2218],{"className":3115},[2330],[1824,3117],{"className":3118,"style":2326},[2325],[1824,3120,3122,3125,3133,3136,3139,3142,3145],{"className":3121},[1866],[1824,3123],{"className":3124,"style":2966},[1870],[1824,3126,3128,3129],{"className":3127},[2874],"lo",[1824,3130,3132],{"style":3131},"margin-right:0.0139em;","g",[1824,3134,2759],{"className":3135},[2347],[1824,3137,1973],{"className":3138},[1875],[1824,3140],{"className":3141,"style":2484},[2325],[1824,3143,2232],{"className":3144},[2026],[1824,3146],{"className":3147,"style":2484},[2325],[1824,3149,3151,3154,3194],{"className":3150},[1866],[1824,3152],{"className":3153,"style":2966},[1870],[1824,3155,3157,3160],{"className":3156},[1875],[1824,3158,1848],{"className":3159,"style":1880},[1875,1879],[1824,3161,3163],{"className":3162},[1884],[1824,3164,3166,3186],{"className":3165},[1888,2000],[1824,3167,3169,3183],{"className":3168},[1892],[1824,3170,3172],{"className":3171,"style":2094},[1896],[1824,3173,3174,3177],{"style":2301},[1824,3175],{"className":3176,"style":1904},[1903],[1824,3178,3180],{"className":3179},[1908,1909,1910,1911],[1824,3181,1966],{"className":3182},[1875,1879,1911],[1824,3184,2034],{"className":3185},[2033],[1824,3187,3189],{"className":3188},[1892],[1824,3190,3192],{"className":3191,"style":2115},[1896],[1824,3193],{},[1824,3195,2772],{"className":3196},[2604]," 可以跨期相加，但横截面组合仍应使用简单收益率。",[1938,3199,3200],{"id":3200},"现值",[1793,3202,3203,3204,3282,3283,3312],{},"确定现金流 ",[1824,3205,3207,3229],{"className":3206},[1827],[1824,3208,3210],{"className":3209},[1831],[1833,3211,3212],{"xmlns":1835},[1837,3213,3214,3226],{},[1840,3215,3216,3219],{},[1846,3217,3218],{},"C",[1957,3220,3221,3224],{},[1846,3222,3223],{},"F",[1846,3225,1966],{},[1854,3227,3228],{"encoding":1856},"CF_t",[1824,3230,3232],{"className":3231,"ariaHidden":1862},[1861],[1824,3233,3235,3238,3242],{"className":3234},[1866],[1824,3236],{"className":3237,"style":2075},[1870],[1824,3239,3218],{"className":3240,"style":3241},[1875,1879],"margin-right:0.0715em;",[1824,3243,3245,3248],{"className":3244},[1875],[1824,3246,3223],{"className":3247,"style":1993},[1875,1879],[1824,3249,3251],{"className":3250},[1884],[1824,3252,3254,3274],{"className":3253},[1888,2000],[1824,3255,3257,3271],{"className":3256},[1892],[1824,3258,3260],{"className":3259,"style":2094},[1896],[1824,3261,3262,3265],{"style":2010},[1824,3263],{"className":3264,"style":1904},[1903],[1824,3266,3268],{"className":3267},[1908,1909,1910,1911],[1824,3269,1966],{"className":3270},[1875,1879,1911],[1824,3272,2034],{"className":3273},[2033],[1824,3275,3277],{"className":3276},[1892],[1824,3278,3280],{"className":3279,"style":2115},[1896],[1824,3281],{}," 在固定贴现率 ",[1824,3284,3286,3299],{"className":3285},[1827],[1824,3287,3289],{"className":3288},[1831],[1833,3290,3291],{"xmlns":1835},[1837,3292,3293,3297],{},[1840,3294,3295],{},[1846,3296,3032],{},[1854,3298,3032],{"encoding":1856},[1824,3300,3302],{"className":3301,"ariaHidden":1862},[1861],[1824,3303,3305,3309],{"className":3304},[1866],[1824,3306],{"className":3307,"style":3308},[1870],"height:0.4306em;",[1824,3310,3032],{"className":3311,"style":2156},[1875,1879]," 下的价格为：",[1824,3314,3316],{"className":3315},[2196],[1824,3317,3319,3385],{"className":3318},[1827],[1824,3320,3322],{"className":3321},[1831],[1833,3323,3324],{"xmlns":1835,"display":2205},[1837,3325,3326,3382],{},[1840,3327,3328,3335,3337,3352,3380],{},[1957,3329,3330,3332],{},[1846,3331,1961],{},[1850,3333,3334],{},"0",[1968,3336,2218],{},[2741,3338,3339,3342,3350],{},[1968,3340,3341],{},"∑",[1840,3343,3344,3346,3348],{},[1846,3345,1966],{},[1968,3347,2218],{},[1850,3349,1973],{},[1846,3351,2737],{},[2220,3353,3354,3364],{},[1840,3355,3356,3358],{},[1846,3357,3218],{},[1957,3359,3360,3362],{},[1846,3361,3223],{},[1846,3363,1966],{},[1840,3365,3366,3368,3370,3372,3374],{},[1968,3367,2759],{"stretchy":2758},[1850,3369,1973],{},[1968,3371,2232],{},[1846,3373,3032],{},[1843,3375,3376,3378],{},[1968,3377,2772],{"stretchy":2758},[1846,3379,1966],{},[1846,3381,2268],{"mathvariant":2267},[1854,3383,3384],{"encoding":1856},"P_0=\\sum_{t=1}^T\\frac{CF_t}{(1+r)^t}.",[1824,3386,3388,3443],{"className":3387,"ariaHidden":1862},[1861],[1824,3389,3391,3394,3434,3437,3440],{"className":3390},[1866],[1824,3392],{"className":3393,"style":2075},[1870],[1824,3395,3397,3400],{"className":3396},[1875],[1824,3398,1961],{"className":3399,"style":1993},[1875,1879],[1824,3401,3403],{"className":3402},[1884],[1824,3404,3406,3426],{"className":3405},[1888,2000],[1824,3407,3409,3423],{"className":3408},[1892],[1824,3410,3412],{"className":3411,"style":2007},[1896],[1824,3413,3414,3417],{"style":2010},[1824,3415],{"className":3416,"style":1904},[1903],[1824,3418,3420],{"className":3419},[1908,1909,1910,1911],[1824,3421,3334],{"className":3422},[1875,1911],[1824,3424,2034],{"className":3425},[2033],[1824,3427,3429],{"className":3428},[1892],[1824,3430,3432],{"className":3431,"style":2115},[1896],[1824,3433],{},[1824,3435],{"className":3436,"style":2326},[2325],[1824,3438,2218],{"className":3439},[2330],[1824,3441],{"className":3442,"style":2326},[2325],[1824,3444,3446,3449,3513,3517,3666],{"className":3445},[1866],[1824,3447],{"className":3448,"style":2870},[1870],[1824,3450,3452],{"className":3451},[2874,2875],[1824,3453,3455,3505],{"className":3454},[1888,2000],[1824,3456,3458,3502],{"className":3457},[1892],[1824,3459,3461,3481,3491],{"className":3460,"style":2885},[1896],[1824,3462,3463,3466],{"style":2888},[1824,3464],{"className":3465,"style":2892},[1903],[1824,3467,3469],{"className":3468},[1908,1909,1910,1911],[1824,3470,3472,3475,3478],{"className":3471},[1875,1911],[1824,3473,1966],{"className":3474},[1875,1879,1911],[1824,3476,2218],{"className":3477},[2330,1911],[1824,3479,1973],{"className":3480},[1875,1911],[1824,3482,3483,3486],{"style":2910},[1824,3484],{"className":3485,"style":2892},[1903],[1824,3487,3488],{},[1824,3489,3341],{"className":3490},[2874,2919,2920],[1824,3492,3493,3496],{"style":2923},[1824,3494],{"className":3495,"style":2892},[1903],[1824,3497,3499],{"className":3498},[1908,1909,1910,1911],[1824,3500,2737],{"className":3501,"style":1993},[1875,1879,1911],[1824,3503,2034],{"className":3504},[2033],[1824,3506,3508],{"className":3507},[1892],[1824,3509,3511],{"className":3510,"style":2942},[1896],[1824,3512],{},[1824,3514],{"className":3515,"style":3516},[2325],"margin-right:0.1667em;",[1824,3518,3520,3523,3663],{"className":3519},[1875],[1824,3521],{"className":3522},[2347,2348],[1824,3524,3526],{"className":3525},[2220],[1824,3527,3529,3654],{"className":3528},[1888,2000],[1824,3530,3532,3651],{"className":3531},[1892],[1824,3533,3535,3592,3600],{"className":3534,"style":2361},[1896],[1824,3536,3537,3540],{"style":2364},[1824,3538],{"className":3539,"style":2368},[1903],[1824,3541,3543,3546,3549,3552,3555,3558,3561],{"className":3542},[1875],[1824,3544,2759],{"className":3545},[2347],[1824,3547,1973],{"className":3548},[1875],[1824,3550],{"className":3551,"style":2484},[2325],[1824,3553,2232],{"className":3554},[2026],[1824,3556],{"className":3557,"style":2484},[2325],[1824,3559,3032],{"className":3560,"style":2156},[1875,1879],[1824,3562,3564,3567],{"className":3563},[2604],[1824,3565,2772],{"className":3566},[2604],[1824,3568,3570],{"className":3569},[1884],[1824,3571,3573],{"className":3572},[1888],[1824,3574,3576],{"className":3575},[1892],[1824,3577,3580],{"className":3578,"style":3579},[1896],"height:0.7196em;",[1824,3581,3583,3586],{"style":3582},"top:-2.989em;margin-right:0.05em;",[1824,3584],{"className":3585,"style":1904},[1903],[1824,3587,3589],{"className":3588},[1908,1909,1910,1911],[1824,3590,1966],{"className":3591},[1875,1879,1911],[1824,3593,3594,3597],{"style":2423},[1824,3595],{"className":3596,"style":2368},[1903],[1824,3598],{"className":3599,"style":2431},[2430],[1824,3601,3602,3605],{"style":2434},[1824,3603],{"className":3604,"style":2368},[1903],[1824,3606,3608,3611],{"className":3607},[1875],[1824,3609,3218],{"className":3610,"style":3241},[1875,1879],[1824,3612,3614,3617],{"className":3613},[1875],[1824,3615,3223],{"className":3616,"style":1993},[1875,1879],[1824,3618,3620],{"className":3619},[1884],[1824,3621,3623,3643],{"className":3622},[1888,2000],[1824,3624,3626,3640],{"className":3625},[1892],[1824,3627,3629],{"className":3628,"style":2094},[1896],[1824,3630,3631,3634],{"style":2010},[1824,3632],{"className":3633,"style":1904},[1903],[1824,3635,3637],{"className":3636},[1908,1909,1910,1911],[1824,3638,1966],{"className":3639},[1875,1879,1911],[1824,3641,2034],{"className":3642},[2033],[1824,3644,3646],{"className":3645},[1892],[1824,3647,3649],{"className":3648,"style":2115},[1896],[1824,3650],{},[1824,3652,2034],{"className":3653},[2033],[1824,3655,3657],{"className":3656},[1892],[1824,3658,3661],{"className":3659,"style":3660},[1896],"height:0.936em;",[1824,3662],{},[1824,3664],{"className":3665},[2604,2348],[1824,3667,2268],{"className":3668},[1875],[3670,3671],"pyodide",{"code64":3672,"layout":3673,"locale":7,"packages":3674,"title":3675},"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","vertical","numpy","Python：总收益率与贴现现金流",[3677,3678],"web-r",{"code64":3679,"layout":3673,"locale":7,"title":3680},"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","R：总收益率与贴现现金流",[1938,3682,3683],{"id":3683},"审计任务",[1811,3685,3686,3689,3692],{},[1814,3687,3688],{},"把贴现率从 8% 改为 10%，解释价格为何下降。",[1814,3690,3691],{},"删除分红后重新计算累计收益，量化价格收益与总收益的差异。",[1814,3693,3694],{},"检查简单收益率平均值与对数收益率平均值为何不完全相同。",[1804,3696,3698],{"id":3697},"实验二均值方差组合","实验二：均值—方差组合",[1938,3700,3701],{"id":3701},"全局最小方差组合",[1793,3703,3704,3705,3736],{},"给定协方差矩阵 ",[1824,3706,3708,3723],{"className":3707},[1827],[1824,3709,3711],{"className":3710},[1831],[1833,3712,3713],{"xmlns":1835},[1837,3714,3715,3720],{},[1840,3716,3717],{},[1846,3718,3719],{"mathvariant":2267},"Σ",[1854,3721,3722],{"encoding":1856},"\\Sigma",[1824,3724,3726],{"className":3725,"ariaHidden":1862},[1861],[1824,3727,3729,3733],{"className":3728},[1866],[1824,3730],{"className":3731,"style":3732},[1870],"height:0.6833em;",[1824,3734,3719],{"className":3735},[1875],"，权重和为 1 的全局最小方差组合为：",[1824,3738,3740],{"className":3739},[2196],[1824,3741,3743,3814],{"className":3742},[1827],[1824,3744,3746],{"className":3745},[1831],[1833,3747,3748],{"xmlns":1835,"display":2205},[1837,3749,3750,3811],{},[1840,3751,3752,3768,3770,3809],{},[1957,3753,3754,3757],{},[1846,3755,3756],{},"w",[1840,3758,3759,3762,3765],{},[1846,3760,3761],{},"G",[1846,3763,3764],{},"M",[1846,3766,3767],{},"V",[1968,3769,2218],{},[2220,3771,3772,3787],{},[1840,3773,3774,3784],{},[1843,3775,3776,3778],{},[1846,3777,3719],{"mathvariant":2267},[1840,3779,3780,3782],{},[1968,3781,1970],{},[1850,3783,1973],{},[1850,3785,1973],{"mathvariant":3786},"bold",[1840,3788,3789,3797,3807],{},[1843,3790,3791,3793],{},[1850,3792,1973],{"mathvariant":3786},[1968,3794,3796],{"mathvariant":2267,"lspace":3795,"rspace":3795},"0em","′",[1843,3798,3799,3801],{},[1846,3800,3719],{"mathvariant":2267},[1840,3802,3803,3805],{},[1968,3804,1970],{},[1850,3806,1973],{},[1850,3808,1973],{"mathvariant":3786},[1846,3810,2268],{"mathvariant":2267},[1854,3812,3813],{"encoding":1856},"w_{GMV}\n=\\frac{\\Sigma^{-1}\\mathbf 1}\n{\\mathbf 1'\\Sigma^{-1}\\mathbf 1}.",[1824,3815,3817,3882],{"className":3816,"ariaHidden":1862},[1861],[1824,3818,3820,3823,3873,3876,3879],{"className":3819},[1866],[1824,3821],{"className":3822,"style":3069},[1870],[1824,3824,3826,3830],{"className":3825},[1875],[1824,3827,3756],{"className":3828,"style":3829},[1875,1879],"margin-right:0.0269em;",[1824,3831,3833],{"className":3832},[1884],[1824,3834,3836,3865],{"className":3835},[1888,2000],[1824,3837,3839,3862],{"className":3838},[1892],[1824,3840,3842],{"className":3841,"style":2823},[1896],[1824,3843,3845,3848],{"style":3844},"top:-2.55em;margin-left:-0.0269em;margin-right:0.05em;",[1824,3846],{"className":3847,"style":1904},[1903],[1824,3849,3851],{"className":3850},[1908,1909,1910,1911],[1824,3852,3854,3859],{"className":3853},[1875,1911],[1824,3855,3858],{"className":3856,"style":3857},[1875,1879,1911],"margin-right:0.109em;","GM",[1824,3860,3767],{"className":3861,"style":2484},[1875,1879,1911],[1824,3863,2034],{"className":3864},[2033],[1824,3866,3868],{"className":3867},[1892],[1824,3869,3871],{"className":3870,"style":2115},[1896],[1824,3872],{},[1824,3874],{"className":3875,"style":2326},[2325],[1824,3877,2218],{"className":3878},[2330],[1824,3880],{"className":3881,"style":2326},[2325],[1824,3883,3885,3889,4058],{"className":3884},[1866],[1824,3886],{"className":3887,"style":3888},[1870],"height:2.1771em;vertical-align:-0.686em;",[1824,3890,3892,3895,4055],{"className":3891},[1875],[1824,3893],{"className":3894},[2347,2348],[1824,3896,3898],{"className":3897},[2220],[1824,3899,3901,4046],{"className":3900},[1888,2000],[1824,3902,3904,4043],{"className":3903},[1892],[1824,3905,3908,3989,3997],{"className":3906,"style":3907},[1896],"height:1.4911em;",[1824,3909,3910,3913],{"style":2364},[1824,3911],{"className":3912,"style":2368},[1903],[1824,3914,3916,3950,3986],{"className":3915},[1875],[1824,3917,3919,3923],{"className":3918},[1875],[1824,3920,1973],{"className":3921},[1875,3922],"mathbf",[1824,3924,3926],{"className":3925},[1884],[1824,3927,3929],{"className":3928},[1888],[1824,3930,3932],{"className":3931},[1892],[1824,3933,3936],{"className":3934,"style":3935},[1896],"height:0.6779em;",[1824,3937,3938,3941],{"style":3582},[1824,3939],{"className":3940,"style":1904},[1903],[1824,3942,3944],{"className":3943},[1908,1909,1910,1911],[1824,3945,3947],{"className":3946},[1875,1911],[1824,3948,3796],{"className":3949},[1875,1911],[1824,3951,3953,3956],{"className":3952},[1875],[1824,3954,3719],{"className":3955},[1875],[1824,3957,3959],{"className":3958},[1884],[1824,3960,3962],{"className":3961},[1888],[1824,3963,3965],{"className":3964},[1892],[1824,3966,3969],{"className":3967,"style":3968},[1896],"height:0.7401em;",[1824,3970,3971,3974],{"style":3582},[1824,3972],{"className":3973,"style":1904},[1903],[1824,3975,3977],{"className":3976},[1908,1909,1910,1911],[1824,3978,3980,3983],{"className":3979},[1875,1911],[1824,3981,1970],{"className":3982},[1875,1911],[1824,3984,1973],{"className":3985},[1875,1911],[1824,3987,1973],{"className":3988},[1875,3922],[1824,3990,3991,3994],{"style":2423},[1824,3992],{"className":3993,"style":2368},[1903],[1824,3995],{"className":3996,"style":2431},[2430],[1824,3998,3999,4002],{"style":2434},[1824,4000],{"className":4001,"style":2368},[1903],[1824,4003,4005,4040],{"className":4004},[1875],[1824,4006,4008,4011],{"className":4007},[1875],[1824,4009,3719],{"className":4010},[1875],[1824,4012,4014],{"className":4013},[1884],[1824,4015,4017],{"className":4016},[1888],[1824,4018,4020],{"className":4019},[1892],[1824,4021,4023],{"className":4022,"style":1871},[1896],[1824,4024,4025,4028],{"style":1899},[1824,4026],{"className":4027,"style":1904},[1903],[1824,4029,4031],{"className":4030},[1908,1909,1910,1911],[1824,4032,4034,4037],{"className":4033},[1875,1911],[1824,4035,1970],{"className":4036},[1875,1911],[1824,4038,1973],{"className":4039},[1875,1911],[1824,4041,1973],{"className":4042},[1875,3922],[1824,4044,2034],{"className":4045},[2033],[1824,4047,4049],{"className":4048},[1892],[1824,4050,4053],{"className":4051,"style":4052},[1896],"height:0.686em;",[1824,4054],{},[1824,4056],{"className":4057},[2604,2348],[1824,4059,2268],{"className":4060},[1875],[1793,4062,4063],{},"若允许卖空，切点组合满足：",[1824,4065,4067],{"className":4066},[2196],[1824,4068,4070,4158],{"className":4069},[1827],[1824,4071,4073],{"className":4072},[1831],[1833,4074,4075],{"xmlns":1835,"display":2205},[1837,4076,4077,4155],{},[1840,4078,4079,4085,4087,4153],{},[1957,4080,4081,4083],{},[1846,4082,3756],{},[1846,4084,2737],{},[1968,4086,2218],{},[2220,4088,4089,4119],{},[1840,4090,4091,4101,4103,4106,4108,4115,4117],{},[1843,4092,4093,4095],{},[1846,4094,3719],{"mathvariant":2267},[1840,4096,4097,4099],{},[1968,4098,1970],{},[1850,4100,1973],{},[1968,4102,2759],{"stretchy":2758},[1846,4104,4105],{},"μ",[1968,4107,1970],{},[1957,4109,4110,4112],{},[1846,4111,3032],{},[1846,4113,4114],{},"f",[1850,4116,1973],{"mathvariant":3786},[1968,4118,2772],{"stretchy":2758},[1840,4120,4121,4127,4137,4139,4141,4143,4149,4151],{},[1843,4122,4123,4125],{},[1850,4124,1973],{"mathvariant":3786},[1968,4126,3796],{"mathvariant":2267,"lspace":3795,"rspace":3795},[1843,4128,4129,4131],{},[1846,4130,3719],{"mathvariant":2267},[1840,4132,4133,4135],{},[1968,4134,1970],{},[1850,4136,1973],{},[1968,4138,2759],{"stretchy":2758},[1846,4140,4105],{},[1968,4142,1970],{},[1957,4144,4145,4147],{},[1846,4146,3032],{},[1846,4148,4114],{},[1850,4150,1973],{"mathvariant":3786},[1968,4152,2772],{"stretchy":2758},[1846,4154,2268],{"mathvariant":2267},[1854,4156,4157],{"encoding":1856},"w_T\n=\\frac{\\Sigma^{-1}(\\mu-r_f\\mathbf 1)}\n{\\mathbf 1'\\Sigma^{-1}(\\mu-r_f\\mathbf 1)}.",[1824,4159,4161,4216],{"className":4160,"ariaHidden":1862},[1861],[1824,4162,4164,4167,4207,4210,4213],{"className":4163},[1866],[1824,4165],{"className":4166,"style":3069},[1870],[1824,4168,4170,4173],{"className":4169},[1875],[1824,4171,3756],{"className":4172,"style":3829},[1875,1879],[1824,4174,4176],{"className":4175},[1884],[1824,4177,4179,4199],{"className":4178},[1888,2000],[1824,4180,4182,4196],{"className":4181},[1892],[1824,4183,4185],{"className":4184,"style":2823},[1896],[1824,4186,4187,4190],{"style":3844},[1824,4188],{"className":4189,"style":1904},[1903],[1824,4191,4193],{"className":4192},[1908,1909,1910,1911],[1824,4194,2737],{"className":4195,"style":1993},[1875,1879,1911],[1824,4197,2034],{"className":4198},[2033],[1824,4200,4202],{"className":4201},[1892],[1824,4203,4205],{"className":4204,"style":2115},[1896],[1824,4206],{},[1824,4208],{"className":4209,"style":2326},[2325],[1824,4211,2218],{"className":4212},[2330],[1824,4214],{"className":4215,"style":2326},[2325],[1824,4217,4219,4223,4507],{"className":4218},[1866],[1824,4220],{"className":4221,"style":4222},[1870],"height:2.4632em;vertical-align:-0.9721em;",[1824,4224,4226,4229,4504],{"className":4225},[1875],[1824,4227],{"className":4228},[2347,2348],[1824,4230,4232],{"className":4231},[2220],[1824,4233,4235,4495],{"className":4234},[1888,2000],[1824,4236,4238,4492],{"className":4237},[1892],[1824,4239,4241,4380,4388],{"className":4240,"style":3907},[1896],[1824,4242,4243,4246],{"style":2364},[1824,4244],{"className":4245,"style":2368},[1903],[1824,4247,4249,4281,4316,4319,4322,4325,4328,4331,4374,4377],{"className":4248},[1875],[1824,4250,4252,4255],{"className":4251},[1875],[1824,4253,1973],{"className":4254},[1875,3922],[1824,4256,4258],{"className":4257},[1884],[1824,4259,4261],{"className":4260},[1888],[1824,4262,4264],{"className":4263},[1892],[1824,4265,4267],{"className":4266,"style":3935},[1896],[1824,4268,4269,4272],{"style":3582},[1824,4270],{"className":4271,"style":1904},[1903],[1824,4273,4275],{"className":4274},[1908,1909,1910,1911],[1824,4276,4278],{"className":4277},[1875,1911],[1824,4279,3796],{"className":4280},[1875,1911],[1824,4282,4284,4287],{"className":4283},[1875],[1824,4285,3719],{"className":4286},[1875],[1824,4288,4290],{"className":4289},[1884],[1824,4291,4293],{"className":4292},[1888],[1824,4294,4296],{"className":4295},[1892],[1824,4297,4299],{"className":4298,"style":3968},[1896],[1824,4300,4301,4304],{"style":3582},[1824,4302],{"className":4303,"style":1904},[1903],[1824,4305,4307],{"className":4306},[1908,1909,1910,1911],[1824,4308,4310,4313],{"className":4309},[1875,1911],[1824,4311,1970],{"className":4312},[1875,1911],[1824,4314,1973],{"className":4315},[1875,1911],[1824,4317,2759],{"className":4318},[2347],[1824,4320,4105],{"className":4321},[1875,1879],[1824,4323],{"className":4324,"style":2484},[2325],[1824,4326,1970],{"className":4327},[2026],[1824,4329],{"className":4330,"style":2484},[2325],[1824,4332,4334,4337],{"className":4333},[1875],[1824,4335,3032],{"className":4336,"style":2156},[1875,1879],[1824,4338,4340],{"className":4339},[1884],[1824,4341,4343,4365],{"className":4342},[1888,2000],[1824,4344,4346,4362],{"className":4345},[1892],[1824,4347,4350],{"className":4348,"style":4349},[1896],"height:0.3361em;",[1824,4351,4352,4355],{"style":2171},[1824,4353],{"className":4354,"style":1904},[1903],[1824,4356,4358],{"className":4357},[1908,1909,1910,1911],[1824,4359,4114],{"className":4360,"style":4361},[1875,1879,1911],"margin-right:0.1076em;",[1824,4363,2034],{"className":4364},[2033],[1824,4366,4368],{"className":4367},[1892],[1824,4369,4372],{"className":4370,"style":4371},[1896],"height:0.2861em;",[1824,4373],{},[1824,4375,1973],{"className":4376},[1875,3922],[1824,4378,2772],{"className":4379},[2604],[1824,4381,4382,4385],{"style":2423},[1824,4383],{"className":4384,"style":2368},[1903],[1824,4386],{"className":4387,"style":2431},[2430],[1824,4389,4390,4393],{"style":2434},[1824,4391],{"className":4392,"style":2368},[1903],[1824,4394,4396,4431,4434,4437,4440,4443,4446,4486,4489],{"className":4395},[1875],[1824,4397,4399,4402],{"className":4398},[1875],[1824,4400,3719],{"className":4401},[1875],[1824,4403,4405],{"className":4404},[1884],[1824,4406,4408],{"className":4407},[1888],[1824,4409,4411],{"className":4410},[1892],[1824,4412,4414],{"className":4413,"style":1871},[1896],[1824,4415,4416,4419],{"style":1899},[1824,4417],{"className":4418,"style":1904},[1903],[1824,4420,4422],{"className":4421},[1908,1909,1910,1911],[1824,4423,4425,4428],{"className":4424},[1875,1911],[1824,4426,1970],{"className":4427},[1875,1911],[1824,4429,1973],{"className":4430},[1875,1911],[1824,4432,2759],{"className":4433},[2347],[1824,4435,4105],{"className":4436},[1875,1879],[1824,4438],{"className":4439,"style":2484},[2325],[1824,4441,1970],{"className":4442},[2026],[1824,4444],{"className":4445,"style":2484},[2325],[1824,4447,4449,4452],{"className":4448},[1875],[1824,4450,3032],{"className":4451,"style":2156},[1875,1879],[1824,4453,4455],{"className":4454},[1884],[1824,4456,4458,4478],{"className":4457},[1888,2000],[1824,4459,4461,4475],{"className":4460},[1892],[1824,4462,4464],{"className":4463,"style":4349},[1896],[1824,4465,4466,4469],{"style":2171},[1824,4467],{"className":4468,"style":1904},[1903],[1824,4470,4472],{"className":4471},[1908,1909,1910,1911],[1824,4473,4114],{"className":4474,"style":4361},[1875,1879,1911],[1824,4476,2034],{"className":4477},[2033],[1824,4479,4481],{"className":4480},[1892],[1824,4482,4484],{"className":4483,"style":4371},[1896],[1824,4485],{},[1824,4487,1973],{"className":4488},[1875,3922],[1824,4490,2772],{"className":4491},[2604],[1824,4493,2034],{"className":4494},[2033],[1824,4496,4498],{"className":4497},[1892],[1824,4499,4502],{"className":4500,"style":4501},[1896],"height:0.9721em;",[1824,4503],{},[1824,4505],{"className":4506},[2604,2348],[1824,4508,2268],{"className":4509},[1875],[1793,4511,4512],{},"这些闭式解依赖期望收益和协方差已知。现实中它们是估计量，输入误差尤其会放大切点权重。",[3670,4514],{"code64":4515,"layout":3673,"locale":7,"packages":4516,"title":4517},"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","numpy, matplotlib","Python：最小方差与切点组合",[3677,4519],{"code64":4520,"layout":3673,"locale":7,"title":4521},"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","R：最小方差与切点组合",[1938,4523,4524],{"id":4524},"修改任务",[1811,4526,4527,4530,4533],{},[1814,4528,4529],{},"把第一与第三个资产的相关系数从 0.15 改为 0.80，观察分散化收益。",[1814,4531,4532],{},"将预期收益都增加 2 个百分点，解释 GMV 权重为何不变而切点权重可能改变。",[1814,4534,4535],{},"现实组合加入“不允许卖空”和单资产权重上限后，闭式解不再直接适用，需要约束优化。",[1804,4537,4539],{"id":4538},"实验三capm-时间序列回归","实验三：CAPM 时间序列回归",[1793,4541,4542],{},"CAPM 常用时间序列回归检验：",[1824,4544,4546],{"className":4545},[2196],[1824,4547,4549,4628],{"className":4548},[1827],[1824,4550,4552],{"className":4551},[1831],[1833,4553,4554],{"xmlns":1835,"display":2205},[1837,4555,4556,4625],{},[1840,4557,4558,4576,4578,4585,4587,4594,4608,4610,4623],{},[4559,4560,4561,4563,4573],"msubsup",{},[1846,4562,1848],{},[1840,4564,4565,4568,4571],{},[1846,4566,4567],{},"i",[1968,4569,4570],{"separator":1862},",",[1846,4572,1966],{},[1846,4574,4575],{},"e",[1968,4577,2218],{},[1957,4579,4580,4583],{},[1846,4581,4582],{},"α",[1846,4584,4567],{},[1968,4586,2232],{},[1957,4588,4589,4592],{},[1846,4590,4591],{},"β",[1846,4593,4567],{},[4559,4595,4596,4598,4606],{},[1846,4597,1848],{},[1840,4599,4600,4602,4604],{},[1846,4601,3764],{},[1968,4603,4570],{"separator":1862},[1846,4605,1966],{},[1846,4607,4575],{},[1968,4609,2232],{},[1957,4611,4612,4615],{},[1846,4613,4614],{},"ε",[1840,4616,4617,4619,4621],{},[1846,4618,4567],{},[1968,4620,4570],{"separator":1862},[1846,4622,1966],{},[1846,4624,2268],{"mathvariant":2267},[1854,4626,4627],{"encoding":1856},"R_{i,t}^e\n=\\alpha_i+\\beta_i R_{M,t}^e+\\varepsilon_{i,t}.",[1824,4629,4631,4712,4771,4888],{"className":4630,"ariaHidden":1862},[1861],[1824,4632,4634,4638,4703,4706,4709],{"className":4633},[1866],[1824,4635],{"className":4636,"style":4637},[1870],"height:1.0975em;vertical-align:-0.3831em;",[1824,4639,4641,4644],{"className":4640},[1875],[1824,4642,1848],{"className":4643,"style":1880},[1875,1879],[1824,4645,4647],{"className":4646},[1884],[1824,4648,4650,4694],{"className":4649},[1888,2000],[1824,4651,4653,4691],{"className":4652},[1892],[1824,4654,4657,4679],{"className":4655,"style":4656},[1896],"height:0.7144em;",[1824,4658,4660,4663],{"style":4659},"top:-2.453em;margin-left:-0.0077em;margin-right:0.05em;",[1824,4661],{"className":4662,"style":1904},[1903],[1824,4664,4666],{"className":4665},[1908,1909,1910,1911],[1824,4667,4669,4672,4676],{"className":4668},[1875,1911],[1824,4670,4567],{"className":4671},[1875,1879,1911],[1824,4673,4570],{"className":4674},[4675,1911],"mpunct",[1824,4677,1966],{"className":4678},[1875,1879,1911],[1824,4680,4682,4685],{"style":4681},"top:-3.113em;margin-right:0.05em;",[1824,4683],{"className":4684,"style":1904},[1903],[1824,4686,4688],{"className":4687},[1908,1909,1910,1911],[1824,4689,4575],{"className":4690},[1875,1879,1911],[1824,4692,2034],{"className":4693},[2033],[1824,4695,4697],{"className":4696},[1892],[1824,4698,4701],{"className":4699,"style":4700},[1896],"height:0.3831em;",[1824,4702],{},[1824,4704],{"className":4705,"style":2326},[2325],[1824,4707,2218],{"className":4708},[2330],[1824,4710],{"className":4711,"style":2326},[2325],[1824,4713,4715,4719,4762,4765,4768],{"className":4714},[1866],[1824,4716],{"className":4717,"style":4718},[1870],"height:0.7333em;vertical-align:-0.15em;",[1824,4720,4722,4726],{"className":4721},[1875],[1824,4723,4582],{"className":4724,"style":4725},[1875,1879],"margin-right:0.0037em;",[1824,4727,4729],{"className":4728},[1884],[1824,4730,4732,4754],{"className":4731},[1888,2000],[1824,4733,4735,4751],{"className":4734},[1892],[1824,4736,4739],{"className":4737,"style":4738},[1896],"height:0.3117em;",[1824,4740,4742,4745],{"style":4741},"top:-2.55em;margin-left:-0.0037em;margin-right:0.05em;",[1824,4743],{"className":4744,"style":1904},[1903],[1824,4746,4748],{"className":4747},[1908,1909,1910,1911],[1824,4749,4567],{"className":4750},[1875,1879,1911],[1824,4752,2034],{"className":4753},[2033],[1824,4755,4757],{"className":4756},[1892],[1824,4758,4760],{"className":4759,"style":2115},[1896],[1824,4761],{},[1824,4763],{"className":4764,"style":2484},[2325],[1824,4766,2232],{"className":4767},[2026],[1824,4769],{"className":4770,"style":2484},[2325],[1824,4772,4774,4777,4819,4879,4882,4885],{"className":4773},[1866],[1824,4775],{"className":4776,"style":4637},[1870],[1824,4778,4780,4784],{"className":4779},[1875],[1824,4781,4591],{"className":4782,"style":4783},[1875,1879],"margin-right:0.0528em;",[1824,4785,4787],{"className":4786},[1884],[1824,4788,4790,4811],{"className":4789},[1888,2000],[1824,4791,4793,4808],{"className":4792},[1892],[1824,4794,4796],{"className":4795,"style":4738},[1896],[1824,4797,4799,4802],{"style":4798},"top:-2.55em;margin-left:-0.0528em;margin-right:0.05em;",[1824,4800],{"className":4801,"style":1904},[1903],[1824,4803,4805],{"className":4804},[1908,1909,1910,1911],[1824,4806,4567],{"className":4807},[1875,1879,1911],[1824,4809,2034],{"className":4810},[2033],[1824,4812,4814],{"className":4813},[1892],[1824,4815,4817],{"className":4816,"style":2115},[1896],[1824,4818],{},[1824,4820,4822,4825],{"className":4821},[1875],[1824,4823,1848],{"className":4824,"style":1880},[1875,1879],[1824,4826,4828],{"className":4827},[1884],[1824,4829,4831,4871],{"className":4830},[1888,2000],[1824,4832,4834,4868],{"className":4833},[1892],[1824,4835,4837,4857],{"className":4836,"style":4656},[1896],[1824,4838,4839,4842],{"style":4659},[1824,4840],{"className":4841,"style":1904},[1903],[1824,4843,4845],{"className":4844},[1908,1909,1910,1911],[1824,4846,4848,4851,4854],{"className":4847},[1875,1911],[1824,4849,3764],{"className":4850,"style":3857},[1875,1879,1911],[1824,4852,4570],{"className":4853},[4675,1911],[1824,4855,1966],{"className":4856},[1875,1879,1911],[1824,4858,4859,4862],{"style":4681},[1824,4860],{"className":4861,"style":1904},[1903],[1824,4863,4865],{"className":4864},[1908,1909,1910,1911],[1824,4866,4575],{"className":4867},[1875,1879,1911],[1824,4869,2034],{"className":4870},[2033],[1824,4872,4874],{"className":4873},[1892],[1824,4875,4877],{"className":4876,"style":4700},[1896],[1824,4878],{},[1824,4880],{"className":4881,"style":2484},[2325],[1824,4883,2232],{"className":4884},[2026],[1824,4886],{"className":4887,"style":2484},[2325],[1824,4889,4891,4895,4945],{"className":4890},[1866],[1824,4892],{"className":4893,"style":4894},[1870],"height:0.7167em;vertical-align:-0.2861em;",[1824,4896,4898,4901],{"className":4897},[1875],[1824,4899,4614],{"className":4900},[1875,1879],[1824,4902,4904],{"className":4903},[1884],[1824,4905,4907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衡量资产对市场超额收益的暴露；",[1824,5023,5025,5043],{"className":5024},[1827],[1824,5026,5028],{"className":5027},[1831],[1833,5029,5030],{"xmlns":1835},[1837,5031,5032,5040],{},[1840,5033,5034],{},[1957,5035,5036,5038],{},[1846,5037,4582],{},[1846,5039,4567],{},[1854,5041,5042],{"encoding":1856},"\\alpha_i",[1824,5044,5046],{"className":5045,"ariaHidden":1862},[1861],[1824,5047,5049,5052],{"className":5048},[1866],[1824,5050],{"className":5051,"style":3069},[1870],[1824,5053,5055,5058],{"className":5054},[1875],[1824,5056,4582],{"className":5057,"style":4725},[1875,1879],[1824,5059,5061],{"className":5060},[1884],[1824,5062,5064,5084],{"className":5063},[1888,2000],[1824,5065,5067,5081],{"className":5066},[1892],[1824,5068,5070],{"className":5069,"style":4738},[1896],[1824,5071,5072,5075],{"style":4741},[1824,5073],{"className":5074,"style":1904},[1903],[1824,5076,5078],{"className":5077},[1908,1909,1910,1911],[1824,5079,4567],{"className":5080},[1875,1879,1911],[1824,5082,2034],{"className":5083},[2033],[1824,5085,5087],{"className":5086},[1892],[1824,5088,5090],{"className":5089,"style":2115},[1896],[1824,5091],{}," 是相对于该模型的平均定价误差。显著 alpha 可能来自错误定价，也可能来自遗漏风险、样本选择或标准误不当。",[3670,5094],{"code64":5095,"layout":3673,"locale":7,"packages":5096,"title":5097},"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","numpy, statsmodels, matplotlib","Python：CAPM 回归",[3677,5099],{"code64":5100,"layout":3673,"locale":7,"title":5101},"c2V0LnNlZWQoMTEwMykKbW9udGhzIDwtIDI0MAp0cnVlX2FscGhhIDwtIDAuMDAxCnRydWVfYmV0YSA8LSAxLjI1CgptYXJrZXRfZXhjZXNzIDwtIHJub3JtKG1vbnRocywgbWVhbiA9IDAuMDA1LCBzZCA9IDAuMDQ1KQppZGlvc3luY3JhdGljIDwtIHJub3JtKG1vbnRocywgc2QgPSAwLjAzNSkKYXNzZXRfZXhjZXNzIDwtIHRydWVfYWxwaGEgKyB0cnVlX2JldGEgKiBtYXJrZXRfZXhjZXNzICsgaWRpb3N5bmNyYXRpYwoKbW9kZWwgPC0gbG0oYXNzZXRfZXhjZXNzIH4gbWFya2V0X2V4Y2VzcykKY29lZmZpY2llbnRfdGFibGUgPC0gc3VtbWFyeShtb2RlbCkkY29lZmZpY2llbnRzCgpwcmludChjKAogIHRydWVfbW9udGhseV9hbHBoYSA9IHRydWVfYWxwaGEsCiAgZXN0aW1hdGVkX2FscGhhID0gY29lZihtb2RlbClbIihJbnRlcmNlcHQpIl0sCiAgb3JkaW5hcnlfYWxwaGFfc2UgPSBjb2VmZmljaWVudF90YWJsZVsiKEludGVyY2VwdCkiLCAiU3RkLiBFcnJvciJdLAogIHRydWVfYmV0YSA9IHRydWVfYmV0YSwKICBlc3RpbWF0ZWRfYmV0YSA9IGNvZWYobW9kZWwpWyJtYXJrZXRfZXhjZXNzIl0sCiAgb3JkaW5hcnlfYmV0YV9zZSA9IGNvZWZmaWNpZW50X3RhYmxlWyJtYXJrZXRfZXhjZXNzIiwgIlN0ZC4gRXJyb3IiXSwKICBSX3NxdWFyZWQgPSBzdW1tYXJ5KG1vZGVsKSRyLnNxdWFyZWQsCiAgYW5udWFsaXplZF9hbHBoYV9hcHByb3hpbWF0aW9uID0gMTIgKiBjb2VmKG1vZGVsKVsiKEludGVyY2VwdCkiXQopKQoKcGxvdCgKICBtYXJrZXRfZXhjZXNzLAogIGFzc2V0X2V4Y2VzcywKICBwY2ggPSAxNiwKICBjb2wgPSByZ2IoMCwgMCwgMCwgMC4zNSksCiAgeGxhYiA9ICJNYXJrZXQgZXhjZXNzIHJldHVybiIsCiAgeWxhYiA9ICJBc3NldCBleGNlc3MgcmV0dXJuIiwKICBtYWluID0gIkNBUE0gdGltZS1zZXJpZXMgcmVncmVzc2lvbiIKKQphYmxpbmUobW9kZWwsIGNvbCA9ICJyZWQiLCBsd2QgPSAyKQ==","R：CAPM 回归",[1793,5103,5104],{},"Python 示例报告 HAC 标准误，R 示例报告普通标准误，以提醒读者：系数相同不代表推断相同。真实月度收益可能有自相关和条件异方差，应根据数据结构选择 HAC、Bootstrap 或其他推断。",[1804,5106,5108],{"id":5107},"实验四多因子回归与遗漏风险","实验四：多因子回归与遗漏风险",[1793,5110,5111],{},"设测试资产由市场、规模、价值与动量因子驱动：",[1824,5113,5115],{"className":5114},[2196],[1824,5116,5118,5231],{"className":5117},[1827],[1824,5119,5121],{"className":5120},[1831],[1833,5122,5123],{"xmlns":1835,"display":2205},[1837,5124,5125,5228],{},[1840,5126,5127,5135,5137,5139,5141,5147,5149,5152,5158,5160,5167,5169,5171,5178,5180,5187,5189,5191,5198,5200,5207,5209,5212,5218,5220,5226],{},[4559,5128,5129,5131,5133],{},[1846,5130,1848],{},[1846,5132,1966],{},[1846,5134,4575],{},[1968,5136,2218],{},[1846,5138,4582],{},[1968,5140,2232],{},[1957,5142,5143,5145],{},[1846,5144,4591],{},[1846,5146,3764],{},[1846,5148,3764],{},[1846,5150,5151],{},"K",[1957,5153,5154,5156],{},[1846,5155,2737],{},[1846,5157,1966],{},[1968,5159,2232],{},[1957,5161,5162,5164],{},[1846,5163,4591],{},[1846,5165,5166],{},"S",[1846,5168,5166],{},[1846,5170,3764],{},[1957,5172,5173,5176],{},[1846,5174,5175],{},"B",[1846,5177,1966],{},[1968,5179,2232],{},[1957,5181,5182,5184],{},[1846,5183,4591],{},[1846,5185,5186],{},"H",[1846,5188,5186],{},[1846,5190,3764],{},[1957,5192,5193,5196],{},[1846,5194,5195],{},"L",[1846,5197,1966],{},[1968,5199,2232],{},[1957,5201,5202,5204],{},[1846,5203,4591],{},[1846,5205,5206],{},"U",[1846,5208,3764],{},[1846,5210,5211],{},"O",[1957,5213,5214,5216],{},[1846,5215,3764],{},[1846,5217,1966],{},[1968,5219,2232],{},[1957,5221,5222,5224],{},[1846,5223,4614],{},[1846,5225,1966],{},[1846,5227,2268],{"mathvariant":2267},[1854,5229,5230],{"encoding":1856},"R_t^e\n=\\alpha+\\beta_M MKT_t+\\beta_S SMB_t\n+\\beta_H HML_t+\\beta_U MOM_t+\\varepsilon_t.",[1824,5232,5234,5302,5321,5422,5526,5628,5730],{"className":5233,"ariaHidden":1862},[1861],[1824,5235,5237,5241,5293,5296,5299],{"className":5236},[1866],[1824,5238],{"className":5239,"style":5240},[1870],"height:0.9614em;vertical-align:-0.247em;",[1824,5242,5244,5247],{"className":5243},[1875],[1824,5245,1848],{"className":5246,"style":1880},[1875,1879],[1824,5248,5250],{"className":5249},[1884],[1824,5251,5253,5284],{"className":5252},[1888,2000],[1824,5254,5256,5281],{"className":5255},[1892],[1824,5257,5259,5270],{"className":5258,"style":4656},[1896],[1824,5260,5261,5264],{"style":4659},[1824,5262],{"className":5263,"style":1904},[1903],[1824,5265,5267],{"className":5266},[1908,1909,1910,1911],[1824,5268,1966],{"className":5269},[1875,1879,1911],[1824,5271,5272,5275],{"style":4681},[1824,5273],{"className":5274,"style":1904},[1903],[1824,5276,5278],{"className":5277},[1908,1909,1910,1911],[1824,5279,4575],{"className":5280},[1875,1879,1911],[1824,5282,2034],{"className":5283},[2033],[1824,5285,5287],{"className":5286},[1892],[1824,5288,5291],{"className":5289,"style":5290},[1896],"height:0.247em;",[1824,5292],{},[1824,5294],{"className":5295,"style":2326},[2325],[1824,5297,2218],{"className":5298},[2330],[1824,5300],{"className":5301,"style":2326},[2325],[1824,5303,5305,5309,5312,5315,5318],{"className":5304},[1866],[1824,5306],{"className":5307,"style":5308},[1870],"height:0.6667em;vertical-align:-0.0833em;",[1824,5310,4582],{"className":5311,"style":4725},[1875,1879],[1824,5313],{"className":5314,"style":2484},[2325],[1824,5316,2232],{"className":5317},[2026],[1824,5319],{"className":5320,"style":2484},[2325],[1824,5322,5324,5327,5367,5370,5373,5413,5416,5419],{"className":5323},[1866],[1824,5325],{"className":5326,"style":4980},[1870],[1824,5328,5330,5333],{"className":5329},[1875],[1824,5331,4591],{"className":5332,"style":4783},[1875,1879],[1824,5334,5336],{"className":5335},[1884],[1824,5337,5339,5359],{"className":5338},[1888,2000],[1824,5340,5342,5356],{"className":5341},[1892],[1824,5343,5345],{"className":5344,"style":2823},[1896],[1824,5346,5347,5350],{"style":4798},[1824,5348],{"className":5349,"style":1904},[1903],[1824,5351,5353],{"className":5352},[1908,1909,1910,1911],[1824,5354,3764],{"className":5355,"style":3857},[1875,1879,1911],[1824,5357,2034],{"className":5358},[2033],[1824,5360,5362],{"className":5361},[1892],[1824,5363,5365],{"className":5364,"style":2115},[1896],[1824,5366],{},[1824,5368,3764],{"className":5369,"style":3857},[1875,1879],[1824,5371,5151],{"className":5372,"style":3241},[1875,1879],[1824,5374,5376,5379],{"className":5375},[1875],[1824,5377,2737],{"className":5378,"style":1993},[1875,1879],[1824,5380,5382],{"className":5381},[1884],[1824,5383,5385,5405],{"className":5384},[1888,2000],[1824,5386,5388,5402],{"className":5387},[1892],[1824,5389,5391],{"className":5390,"style":2094},[1896],[1824,5392,5393,5396],{"style":2010},[1824,5394],{"className":5395,"style":1904},[1903],[1824,5397,5399],{"className":5398},[1908,1909,1910,1911],[1824,5400,1966],{"className":5401},[1875,1879,1911],[1824,5403,2034],{"className":5404},[2033],[1824,5406,5408],{"className":5407},[1892],[1824,5409,5411],{"className":5410,"style":2115},[1896],[1824,5412],{},[1824,5414],{"className":5415,"style":2484},[2325],[1824,5417,2232],{"className":5418},[2026],[1824,5420],{"className":5421,"style":2484},[2325],[1824,5423,5425,5428,5469,5472,5475,5517,5520,5523],{"className":5424},[1866],[1824,5426],{"className":5427,"style":4980},[1870],[1824,5429,5431,5434],{"className":5430},[1875],[1824,5432,4591],{"className":5433,"style":4783},[1875,1879],[1824,5435,5437],{"className":5436},[1884],[1824,5438,5440,5461],{"className":5439},[1888,2000],[1824,5441,5443,5458],{"className":5442},[1892],[1824,5444,5446],{"className":5445,"style":2823},[1896],[1824,5447,5448,5451],{"style":4798},[1824,5449],{"className":5450,"style":1904},[1903],[1824,5452,5454],{"className":5453},[1908,1909,1910,1911],[1824,5455,5166],{"className":5456,"style":5457},[1875,1879,1911],"margin-right:0.0576em;",[1824,5459,2034],{"className":5460},[2033],[1824,5462,5464],{"className":5463},[1892],[1824,5465,5467],{"className":5466,"style":2115},[1896],[1824,5468],{},[1824,5470,5166],{"className":5471,"style":5457},[1875,1879],[1824,5473,3764],{"className":5474,"style":3857},[1875,1879],[1824,5476,5478,5482],{"className":5477},[1875],[1824,5479,5175],{"className":5480,"style":5481},[1875,1879],"margin-right:0.0502em;",[1824,5483,5485],{"className":5484},[1884],[1824,5486,5488,5509],{"className":5487},[1888,2000],[1824,5489,5491,5506],{"className":5490},[1892],[1824,5492,5494],{"className":5493,"style":2094},[1896],[1824,5495,5497,5500],{"style":5496},"top:-2.55em;margin-left:-0.0502em;margin-right:0.05em;",[1824,5498],{"className":5499,"style":1904},[1903],[1824,5501,5503],{"className":5502},[1908,1909,1910,1911],[1824,5504,1966],{"className":5505},[1875,1879,1911],[1824,5507,2034],{"className":5508},[2033],[1824,5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CAPM，遗漏且与市场相关的因子可能进入 alpha 或市场 beta。",[3670,5783],{"code64":5784,"layout":3673,"locale":7,"packages":5785,"title":5786},"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","numpy, statsmodels","Python：CAPM 与四因子模型比较",[3677,5788],{"code64":5789,"layout":3673,"locale":7,"title":5790},"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","R：CAPM 与四因子模型比较",[1938,5792,5793],{"id":5793},"模型比较边界",[1793,5795,5796,5797,5855],{},"增加因子几乎总能提高样本内 ",[1824,5798,5800,5817],{"className":5799},[1827],[1824,5801,5803],{"className":5802},[1831],[1833,5804,5805],{"xmlns":1835},[1837,5806,5807,5815],{},[1840,5808,5809],{},[1843,5810,5811,5813],{},[1846,5812,1848],{},[1850,5814,1852],{},[1854,5816,1857],{"encoding":1856},[1824,5818,5820],{"className":5819,"ariaHidden":1862},[1861],[1824,5821,5823,5826],{"className":5822},[1866],[1824,5824],{"className":5825,"style":1871},[1870],[1824,5827,5829,5832],{"className":5828},[1875],[1824,5830,1848],{"className":5831,"style":1880},[1875,1879],[1824,5833,5835],{"className":5834},[1884],[1824,5836,5838],{"className":5837},[1888],[1824,5839,5841],{"className":5840},[1892],[1824,5842,5844],{"className":5843,"style":1871},[1896],[1824,5845,5846,5849],{"style":1899},[1824,5847],{"className":5848,"style":1904},[1903],[1824,5850,5852],{"className":5851},[1908,1909,1910,1911],[1824,5853,1852],{"className":5854},[1875,1911],"。更好的模型还应有经济机制、样本外表现、稳定风险价格和较小定价误差，并控制多重检验。因子数量多于可靠独立信息时，回归会过拟合。",[1804,5857,5859],{"id":5858},"实验五随机贴现因子与-euler-方程","实验五：随机贴现因子与 Euler 方程",[1793,5861,5862],{},"资产定价的统一条件是：",[1824,5864,5866],{"className":5865},[2196],[1824,5867,5869,5920],{"className":5868},[1827],[1824,5870,5872],{"className":5871},[1831],[1833,5873,5874],{"xmlns":1835,"display":2205},[1837,5875,5876,5917],{},[1840,5877,5878,5881,5884,5897,5909,5912,5914],{},[1846,5879,5880],{},"E",[1968,5882,5883],{"stretchy":2758},"[",[1957,5885,5886,5889],{},[1846,5887,5888],{},"m",[1840,5890,5891,5893,5895],{},[1846,5892,1966],{},[1968,5894,2232],{},[1850,5896,1973],{},[1957,5898,5899,5901],{},[1846,5900,1848],{},[1840,5902,5903,5905,5907],{},[1846,5904,1966],{},[1968,5906,2232],{},[1850,5908,1973],{},[1968,5910,5911],{"stretchy":2758},"]",[1968,5913,2218],{},[1850,5915,5916],{},"1.",[1854,5918,5919],{"encoding":1856},"E[m_{t+1}R_{t+1}]=1.",[1824,5921,5923,6045],{"className":5922,"ariaHidden":1862},[1861],[1824,5924,5926,5929,5932,5935,5984,6033,6036,6039,6042],{"className":5925},[1866],[1824,5927],{"className":5928,"style":2966},[1870],[1824,5930,5880],{"className":5931,"style":5457},[1875,1879],[1824,5933,5883],{"className":5934},[2347],[1824,5936,5938,5941],{"className":5937},[1875],[1824,5939,5888],{"className":5940},[1875,1879],[1824,5942,5944],{"className":5943},[1884],[1824,5945,5947,5976],{"className":5946},[1888,2000],[1824,5948,5950,5973],{"className":5949},[1892],[1824,5951,5953],{"className":5952,"style":2007},[1896],[1824,5954,5955,5958],{"style":4915},[1824,5956],{"className":5957,"style":1904},[1903],[1824,5959,5961],{"className":5960},[1908,1909,1910,1911],[1824,5962,5964,5967,5970],{"className":5963},[1875,1911],[1824,5965,1966],{"className":5966},[1875,1879,1911],[1824,5968,2232],{"className":5969},[2026,1911],[1824,5971,1973],{"className":5972},[1875,1911],[1824,5974,2034],{"className":5975},[2033],[1824,5977,5979],{"className":5978},[1892],[1824,5980,5982],{"className":5981,"style":2041},[1896],[1824,5983],{},[1824,5985,5987,5990],{"className":5986},[1875],[1824,5988,1848],{"className":5989,"style":1880},[1875,1879],[1824,5991,5993],{"className":5992},[1884],[1824,5994,5996,6025],{"className":5995},[1888,2000],[1824,5997,5999,6022],{"className":5998},[1892],[1824,6000,6002],{"className":6001,"style":2007},[1896],[1824,6003,6004,6007],{"style":2301},[1824,6005],{"className":6006,"style":1904},[1903],[1824,6008,6010],{"className":6009},[1908,1909,1910,1911],[1824,6011,6013,6016,6019],{"className":6012},[1875,1911],[1824,6014,1966],{"className":6015},[1875,1879,1911],[1824,6017,2232],{"className":6018},[2026,1911],[1824,6020,1973],{"className":6021},[1875,1911],[1824,6023,2034],{"className":6024},[2033],[1824,6026,6028],{"className":6027},[1892],[1824,6029,6031],{"className":6030,"style":2041},[1896],[1824,6032],{},[1824,6034,5911],{"className":6035},[2604],[1824,6037],{"className":6038,"style":2326},[2325],[1824,6040,2218],{"className":6041},[2330],[1824,6043],{"className":6044,"style":2326},[2325],[1824,6046,6048,6052],{"className":6047},[1866],[1824,6049],{"className":6050,"style":6051},[1870],"height:0.6444em;",[1824,6053,5916],{"className":6054},[1875],[1793,6056,6057],{},"CRRA 消费模型常设：",[1824,6059,6061],{"className":6060},[2196],[1824,6062,6064,6129],{"className":6063},[1827],[1824,6065,6067],{"className":6066},[1831],[1833,6068,6069],{"xmlns":1835,"display":2205},[1837,6070,6071,6126],{},[1840,6072,6073,6085,6087,6089,6124],{},[1957,6074,6075,6077],{},[1846,6076,5888],{},[1840,6078,6079,6081,6083],{},[1846,6080,1966],{},[1968,6082,2232],{},[1850,6084,1973],{},[1968,6086,2218],{},[1846,6088,4591],{},[1843,6090,6091,6117],{},[1840,6092,6093,6095,6115],{},[1968,6094,2759],{"fence":1862},[2220,6096,6097,6109],{},[1957,6098,6099,6101],{},[1846,6100,3218],{},[1840,6102,6103,6105,6107],{},[1846,6104,1966],{},[1968,6106,2232],{},[1850,6108,1973],{},[1957,6110,6111,6113],{},[1846,6112,3218],{},[1846,6114,1966],{},[1968,6116,2772],{"fence":1862},[1840,6118,6119,6121],{},[1968,6120,1970],{},[1846,6122,6123],{},"γ",[1968,6125,4570],{"separator":1862},[1854,6127,6128],{"encoding":1856},"m_{t+1}=\\beta\n\\left(\\frac{C_{t+1}}{C_t}\\right)^{-\\gamma},",[1824,6130,6132,6197],{"className":6131,"ariaHidden":1862},[1861],[1824,6133,6135,6139,6188,6191,6194],{"className":6134},[1866],[1824,6136],{"className":6137,"style":6138},[1870],"height:0.6389em;vertical-align:-0.2083em;",[1824,6140,6142,6145],{"className":6141},[1875],[1824,6143,5888],{"className":6144},[1875,1879],[1824,6146,6148],{"className":6147},[1884],[1824,6149,6151,6180],{"className":6150},[1888,2000],[1824,6152,6154,6177],{"className":6153},[1892],[1824,6155,6157],{"className":6156,"style":2007},[1896],[1824,6158,6159,6162],{"style":4915},[1824,6160],{"className":6161,"style":1904},[1903],[1824,6163,6165],{"className":6164},[1908,1909,1910,1911],[1824,6166,6168,6171,6174],{"className":6167},[1875,1911],[1824,6169,1966],{"className":6170},[1875,1879,1911],[1824,6172,2232],{"className":6173},[2026,1911],[1824,6175,1973],{"className":6176},[1875,1911],[1824,6178,2034],{"className":6179},[2033],[1824,6181,6183],{"className":6182},[1892],[1824,6184,6186],{"className":6185,"style":2041},[1896],[1824,6187],{},[1824,6189],{"className":6190,"style":2326},[2325],[1824,6192,2218],{"className":6193},[2330],[1824,6195],{"className":6196,"style":2326},[2325],[1824,6198,6200,6204,6207,6210,6411,6414],{"className":6199},[1866],[1824,6201],{"className":6202,"style":6203},[1870],"height:2.5613em;vertical-align:-0.95em;",[1824,6205,4591],{"className":6206,"style":4783},[1875,1879],[1824,6208],{"className":6209,"style":3516},[2325],[1824,6211,6214,6379],{"className":6212},[6213],"minner",[1824,6215,6217,6226,6373],{"className":6216},[6213],[1824,6218,6222],{"className":6219,"style":6221},[2347,6220],"delimcenter","top:0em;",[1824,6223,2759],{"className":6224},[6225,1910],"delimsizing",[1824,6227,6229,6232,6370],{"className":6228},[1875],[1824,6230],{"className":6231},[2347,2348],[1824,6233,6235],{"className":6234},[2220],[1824,6236,6238,6361],{"className":6237},[1888,2000],[1824,6239,6241,6358],{"className":6240},[1892],[1824,6242,6244,6293,6301],{"className":6243,"style":2361},[1896],[1824,6245,6246,6249],{"style":2364},[1824,6247],{"className":6248,"style":2368},[1903],[1824,6250,6252],{"className":6251},[1875],[1824,6253,6255,6258],{"className":6254},[1875],[1824,6256,3218],{"className":6257,"style":3241},[1875,1879],[1824,6259,6261],{"className":6260},[1884],[1824,6262,6264,6285],{"className":6263},[1888,2000],[1824,6265,6267,6282],{"className":6266},[1892],[1824,6268,6270],{"className":6269,"style":2094},[1896],[1824,6271,6273,6276],{"style":6272},"top:-2.55em;margin-left:-0.0715em;margin-right:0.05em;",[1824,6274],{"className":6275,"style":1904},[1903],[1824,6277,6279],{"className":6278},[1908,1909,1910,1911],[1824,6280,1966],{"className":6281},[1875,1879,1911],[1824,6283,2034],{"className":6284},[2033],[1824,6286,6288],{"className":6287},[1892],[1824,6289,6291],{"className":6290,"style":2115},[1896],[1824,6292],{},[1824,6294,6295,6298],{"style":2423},[1824,6296],{"className":6297,"style":2368},[1903],[1824,6299],{"className":6300,"style":2431},[2430],[1824,6302,6303,6306],{"style":2434},[1824,6304],{"className":6305,"style":2368},[1903],[1824,6307,6309],{"className":6308},[1875],[1824,6310,6312,6315],{"className":6311},[1875],[1824,6313,3218],{"className":6314,"style":3241},[1875,1879],[1824,6316,6318],{"className":6317},[1884],[1824,6319,6321,6350],{"className":6320},[1888,2000],[1824,6322,6324,6347],{"className":6323},[1892],[1824,6325,6327],{"className":6326,"style":2007},[1896],[1824,6328,6329,6332],{"style":6272},[1824,6330],{"className":6331,"style":1904},[1903],[1824,6333,6335],{"className":6334},[1908,1909,1910,1911],[1824,6336,6338,6341,6344],{"className":6337},[1875,1911],[1824,6339,1966],{"className":6340},[1875,1879,1911],[1824,6342,2232],{"className":6343},[2026,1911],[1824,6345,1973],{"className":6346},[1875,1911],[1824,6348,2034],{"className":6349},[2033],[1824,6351,6353],{"className":6352},[1892],[1824,6354,6356],{"className":6355,"style":2041},[1896],[1824,6357],{},[1824,6359,2034],{"className":6360},[2033],[1824,6362,6364],{"className":6363},[1892],[1824,6365,6368],{"className":6366,"style":6367},[1896],"height:0.836em;",[1824,6369],{},[1824,6371],{"className":6372},[2604,2348],[1824,6374,6376],{"className":6375,"style":6221},[2604,6220],[1824,6377,2772],{"className":6378},[6225,1910],[1824,6380,6382],{"className":6381},[1884],[1824,6383,6385],{"className":6384},[1888],[1824,6386,6388],{"className":6387},[1892],[1824,6389,6392],{"className":6390,"style":6391},[1896],"height:1.6112em;",[1824,6393,6395,6398],{"style":6394},"top:-3.9029em;margin-right:0.05em;",[1824,6396],{"className":6397,"style":1904},[1903],[1824,6399,6401],{"className":6400},[1908,1909,1910,1911],[1824,6402,6404,6407],{"className":6403},[1875,1911],[1824,6405,1970],{"className":6406},[1875,1911],[1824,6408,6123],{"className":6409,"style":6410},[1875,1879,1911],"margin-right:0.0556em;",[1824,6412],{"className":6413,"style":3516},[2325],[1824,6415,4570],{"className":6416},[4675],[1793,6418,6419,6420,6450,6451,6479],{},"其中 ",[1824,6421,6423,6437],{"className":6422},[1827],[1824,6424,6426],{"className":6425},[1831],[1833,6427,6428],{"xmlns":1835},[1837,6429,6430,6434],{},[1840,6431,6432],{},[1846,6433,6123],{},[1854,6435,6436],{"encoding":1856},"\\gamma",[1824,6438,6440],{"className":6439,"ariaHidden":1862},[1861],[1824,6441,6443,6447],{"className":6442},[1866],[1824,6444],{"className":6445,"style":6446},[1870],"height:0.625em;vertical-align:-0.1944em;",[1824,6448,6123],{"className":6449,"style":6410},[1875,1879]," 是相对风险厌恶系数。下面用网格搜索寻找使样本 Euler 误差最接近 0 的 ",[1824,6452,6454,6467],{"className":6453},[1827],[1824,6455,6457],{"className":6456},[1831],[1833,6458,6459],{"xmlns":1835},[1837,6460,6461,6465],{},[1840,6462,6463],{},[1846,6464,6123],{},[1854,6466,6436],{"encoding":1856},[1824,6468,6470],{"className":6469,"ariaHidden":1862},[1861],[1824,6471,6473,6476],{"className":6472},[1866],[1824,6474],{"className":6475,"style":6446},[1870],[1824,6477,6123],{"className":6478,"style":6410},[1875,1879],"。",[3670,6481],{"code64":6482,"layout":3673,"locale":7,"packages":4516,"title":6483},"aW1wb3J0IG51bXB5IGFzIG5wCmltcG9ydCBtYXRwbG90bGliLnB5cGxvdCBhcyBwbHQKCnJuZyA9IG5wLnJhbmRvbS5kZWZhdWx0X3JuZygxMTA1KQpzYW1wbGVfc2l6ZSA9IDIwMDAKYmV0YSA9IDAuOTkKdHJ1ZV9nYW1tYSA9IDQuMAoKY29uc3VtcHRpb25fZ3Jvd3RoID0gbnAuZXhwKAogICAgcm5nLm5vcm1hbChsb2M9MC4wMDIsIHNjYWxlPTAuMDI1LCBzaXplPXNhbXBsZV9zaXplKQopCnRydWVfc2RmID0gYmV0YSAqIGNvbnN1bXB0aW9uX2dyb3d0aCAqKiAoLXRydWVfZ2FtbWEpCnByaWNpbmdfbm9pc2UgPSBybmcubm9ybWFsKGxvYz0wLjAsIHNjYWxlPTAuMDMsIHNpemU9c2FtcGxlX3NpemUpCmdyb3NzX3JldHVybiA9ICgxIC8gdHJ1ZV9zZGYpICogKDEgKyBwcmljaW5nX25vaXNlKQoKZ2FtbWFfZ3JpZCA9IG5wLmxpbnNwYWNlKDAuMCwgOC4wLCAxNjEpCmV1bGVyX2Vycm9ycyA9IG5wLmFycmF5KFsKICAgIG5wLm1lYW4oYmV0YSAqIGNvbnN1bXB0aW9uX2dyb3d0aCAqKiAoLWdhbW1hKSAqIGdyb3NzX3JldHVybikgLSAxCiAgICBmb3IgZ2FtbWEgaW4gZ2FtbWFfZ3JpZApdKQplc3RpbWF0ZWRfZ2FtbWEgPSBnYW1tYV9ncmlkW25wLmFyZ21pbihldWxlcl9lcnJvcnMgKiogMildCgpwcmludChmIlRydWUgZ2FtbWE6IHt0cnVlX2dhbW1hOi4yZn0iKQpwcmludChmIkdyaWQtc2VhcmNoIGdhbW1hOiB7ZXN0aW1hdGVkX2dhbW1hOi4yZn0iKQpwcmludChmIkV1bGVyIGVycm9yIGF0IGVzdGltYXRlOiB7ZXVsZXJfZXJyb3JzW25wLmFyZ21pbihldWxlcl9lcnJvcnMgKiogMildOi42Zn0iKQoKcGx0LnBsb3QoZ2FtbWFfZ3JpZCwgZXVsZXJfZXJyb3JzKQpwbHQuYXhobGluZSgwLCBjb2xvcj0iYmxhY2siLCBsaW5ld2lkdGg9MSkKcGx0LmF4dmxpbmUodHJ1ZV9nYW1tYSwgY29sb3I9InJlZCIsIGxpbmVzdHlsZT0iLS0iLCBsYWJlbD0iVHJ1ZSBnYW1tYSIpCnBsdC54bGFiZWwoIlJpc2stYXZlcnNpb24gcGFyYW1ldGVyIGdhbW1hIikKcGx0LnlsYWJlbCgiU2FtcGxlIEV1bGVyIGVycm9yIikKcGx0LmxlZ2VuZCgpCnBsdC5ncmlkKGFscGhhPTAuMykKcGx0LnNob3coKQ==","Python：SDF 矩条件网格搜索",[3677,6485],{"code64":6486,"layout":3673,"locale":7,"title":6487},"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","R：SDF 矩条件网格搜索",[1938,6489,6490],{"id":6490},"研究生审计",[1793,6492,6493,6494,6522],{},"这个模拟让收益按真 SDF 构造，因此模型设定正确。真实消费数据有测量误差、时间聚合和有限波动，单一矩条件也可能弱识别 ",[1824,6495,6497,6510],{"className":6496},[1827],[1824,6498,6500],{"className":6499},[1831],[1833,6501,6502],{"xmlns":1835},[1837,6503,6504,6508],{},[1840,6505,6506],{},[1846,6507,6123],{},[1854,6509,6436],{"encoding":1856},[1824,6511,6513],{"className":6512,"ariaHidden":1862},[1861],[1824,6514,6516,6519],{"className":6515},[1866],[1824,6517],{"className":6518,"style":6446},[1870],[1824,6520,6123],{"className":6521,"style":6410},[1875,1879],"。正式 GMM 还要选择测试资产、工具变量和权重矩阵，并估计参数不确定性与过度识别检验。",[1804,6524,6526],{"id":6525},"实验六风险中性二叉树期权定价","实验六：风险中性二叉树期权定价",[1793,6528,6529],{},"在 Cox–Ross–Rubinstein 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",[1824,6984,6986,7021],{"className":6985},[1827],[1824,6987,6989],{"className":6988},[1831],[1833,6990,6991],{"xmlns":1835},[1837,6992,6993,7018],{},[1840,6994,6995,6998,7000,7002,7008,7010,7012,7014,7016],{},[1846,6996,6997],{},"max",[1968,6999,3042],{},[1968,7001,2759],{"stretchy":2758},[1957,7003,7004,7006],{},[1846,7005,5166],{},[1846,7007,2737],{},[1968,7009,1970],{},[1846,7011,5151],{},[1968,7013,4570],{"separator":1862},[1850,7015,3334],{},[1968,7017,2772],{"stretchy":2758},[1854,7019,7020],{"encoding":1856},"\\max(S_T-K,0)",[1824,7022,7024,7086],{"className":7023,"ariaHidden":1862},[1861],[1824,7025,7027,7030,7033,7036,7077,7080,7083],{"className":7026},[1866],[1824,7028],{"className":7029,"style":2966},[1870],[1824,7031,6997],{"className":7032},[2874],[1824,7034,2759],{"className":7035},[2347],[1824,7037,7039,7042],{"className":7038},[1875],[1824,7040,5166],{"className":7041,"style":5457},[1875,1879],[1824,7043,7045],{"className":7044},[1884],[1824,7046,7048,7069],{"className":7047},[1888,2000],[1824,7049,7051,7066],{"className":7050},[1892],[1824,7052,7054],{"className":7053,"style":2823},[1896],[1824,7055,7057,7060],{"style":7056},"top:-2.55em;margin-left:-0.0576em;margin-right:0.05em;",[1824,7058],{"className":7059,"style":1904},[1903],[1824,7061,7063],{"className":7062},[1908,1909,1910,1911],[1824,7064,2737],{"className":7065,"style":1993},[1875,1879,1911],[1824,7067,2034],{"className":7068},[2033],[1824,7070,7072],{"className":7071},[1892],[1824,7073,7075],{"className":7074,"style":2115},[1896],[1824,7076],{},[1824,7078],{"className":7079,"style":2484},[2325],[1824,7081,1970],{"className":7082},[2026],[1824,7084],{"className":7085,"style":2484},[2325],[1824,7087,7089,7092,7095,7098,7101,7104],{"className":7088},[1866],[1824,7090],{"className":7091,"style":2966},[1870],[1824,7093,5151],{"className":7094,"style":3241},[1875,1879],[1824,7096,4570],{"className":7097},[4675],[1824,7099],{"className":7100,"style":3516},[2325],[1824,7102,3334],{"className":7103},[1875],[1824,7105,2772],{"className":7106},[2604],"，然后按风险中性概率逐层贴现。",[3670,7109],{"code64":7110,"layout":3673,"locale":7,"packages":7111,"title":7112},"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","numpy, scipy","Python：二叉树与 Black–Scholes 对照",[3677,7114],{"code64":7115,"layout":3673,"locale":7,"title":7116},"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","R：二叉树与 Black–Scholes 对照",[1938,7118,4524],{"id":7119},"修改任务-1",[1811,7121,7122,7125,7128,7208],{},[1814,7123,7124],{},"把波动率从 20% 提高到 40%，解释看涨期权价值为何上升。",[1814,7126,7127],{},"修改执行价，比较实值、平值和虚值期权。",[1814,7129,7130,7131,7207],{},"检查 ",[1824,7132,7134,7157],{"className":7133},[1827],[1824,7135,7137],{"className":7136},[1831],[1833,7138,7139],{"xmlns":1835},[1837,7140,7141,7154],{},[1840,7142,7143,7145,7148,7150,7152],{},[1850,7144,3334],{},[1968,7146,7147],{},"\u003C",[1846,7149,6595],{},[1968,7151,7147],{},[1850,7153,1973],{},[1854,7155,7156],{"encoding":1856},"0\u003Cq\u003C1",[1824,7158,7160,7179,7198],{"className":7159,"ariaHidden":1862},[1861],[1824,7161,7163,7167,7170,7173,7176],{"className":7162},[1866],[1824,7164],{"className":7165,"style":7166},[1870],"height:0.6835em;vertical-align:-0.0391em;",[1824,7168,3334],{"className":7169},[1875],[1824,7171],{"className":7172,"style":2326},[2325],[1824,7174,7147],{"className":7175},[2330],[1824,7177],{"className":7178,"style":2326},[2325],[1824,7180,7182,7186,7189,7192,7195],{"className":7181},[1866],[1824,7183],{"className":7184,"style":7185},[1870],"height:0.7335em;vertical-align:-0.1944em;",[1824,7187,6595],{"className":7188,"style":6692},[1875,1879],[1824,7190],{"className":7191,"style":2326},[2325],[1824,7193,7147],{"className":7194},[2330],[1824,7196],{"className":7197,"style":2326},[2325],[1824,7199,7201,7204],{"className":7200},[1866],[1824,7202],{"className":7203,"style":6051},[1870],[1824,7205,1973],{"className":7206},[1875],"；若不满足，树参数与无套利条件不兼容。",[1814,7209,7210],{},"欧式二叉树随步数增加趋近 Black–Scholes，并不表示市场真实满足连续对冲和常波动率假设。",[1804,7212,7214],{"id":7213},"实验七债券久期与凸性","实验七：债券久期与凸性",[1793,7216,7217],{},"固定票息债券价格为：",[1824,7219,7221],{"className":7220},[2196],[1824,7222,7224,7291],{"className":7223},[1827],[1824,7225,7227],{"className":7226},[1831],[1833,7228,7229],{"xmlns":1835,"display":2205},[1837,7230,7231,7288],{},[1840,7232,7233,7235,7237,7240,7242,7244,7258,7286],{},[1846,7234,1961],{},[1968,7236,2759],{"stretchy":2758},[1846,7238,7239],{},"y",[1968,7241,2772],{"stretchy":2758},[1968,7243,2218],{},[2741,7245,7246,7248,7256],{},[1968,7247,3341],{},[1840,7249,7250,7252,7254],{},[1846,7251,1966],{},[1968,7253,2218],{},[1850,7255,1973],{},[1846,7257,2737],{},[2220,7259,7260,7270],{},[1840,7261,7262,7264],{},[1846,7263,3218],{},[1957,7265,7266,7268],{},[1846,7267,3223],{},[1846,7269,1966],{},[1840,7271,7272,7274,7276,7278,7280],{},[1968,7273,2759],{"stretchy":2758},[1850,7275,1973],{},[1968,7277,2232],{},[1846,7279,7239],{},[1843,7281,7282,7284],{},[1968,7283,2772],{"stretchy":2758},[1846,7285,1966],{},[1846,7287,2268],{"mathvariant":2267},[1854,7289,7290],{"encoding":1856},"P(y)=\\sum_{t=1}^T\\frac{CF_t}{(1+y)^t}.",[1824,7292,7294,7321],{"className":7293,"ariaHidden":1862},[1861],[1824,7295,7297,7300,7303,7306,7309,7312,7315,7318],{"className":7296},[1866],[1824,7298],{"className":7299,"style":2966},[1870],[1824,7301,1961],{"className":7302,"style":1993},[1875,1879],[1824,7304,2759],{"className":7305},[2347],[1824,7307,7239],{"className":7308,"style":6692},[1875,1879],[1824,7310,2772],{"className":7311},[2604],[1824,7313],{"className":7314,"style":2326},[2325],[1824,7316,2218],{"className":7317},[2330],[1824,7319],{"className":7320,"style":2326},[2325],[1824,7322,7324,7327,7391,7394,7540],{"className":7323},[1866],[1824,7325],{"className":7326,"style":2870},[1870],[1824,7328,7330],{"className":7329},[2874,2875],[1824,7331,7333,7383],{"className":7332},[1888,2000],[1824,7334,7336,7380],{"className":7335},[1892],[1824,7337,7339,7359,7369],{"className":7338,"style":2885},[1896],[1824,7340,7341,7344],{"style":2888},[1824,7342],{"className":7343,"style":2892},[1903],[1824,7345,7347],{"className":7346},[1908,1909,1910,1911],[1824,7348,7350,7353,7356],{"className":7349},[1875,1911],[1824,7351,1966],{"className":7352},[1875,1879,1911],[1824,7354,2218],{"className":7355},[2330,1911],[1824,7357,1973],{"className":7358},[1875,1911],[1824,7360,7361,7364],{"style":2910},[1824,7362],{"className":7363,"style":2892},[1903],[1824,7365,7366],{},[1824,7367,3341],{"className":7368},[2874,2919,2920],[1824,7370,7371,7374],{"style":2923},[1824,7372],{"className":7373,"style":2892},[1903],[1824,7375,7377],{"className":7376},[1908,1909,1910,1911],[1824,7378,2737],{"className":7379,"style":1993},[1875,1879,1911],[1824,7381,2034],{"className":7382},[2033],[1824,7384,7386],{"className":7385},[1892],[1824,7387,7389],{"className":7388,"style":2942},[1896],[1824,7390],{},[1824,7392],{"className":7393,"style":3516},[2325],[1824,7395,7397,7400,7537],{"className":7396},[1875],[1824,7398],{"className":7399},[2347,2348],[1824,7401,7403],{"className":7402},[2220],[1824,7404,7406,7529],{"className":7405},[1888,2000],[1824,7407,7409,7526],{"className":7408},[1892],[1824,7410,7412,7467,7475],{"className":7411,"style":2361},[1896],[1824,7413,7414,7417],{"style":2364},[1824,7415],{"className":7416,"style":2368},[1903],[1824,7418,7420,7423,7426,7429,7432,7435,7438],{"className":7419},[1875],[1824,7421,2759],{"className":7422},[2347],[1824,7424,1973],{"className":7425},[1875],[1824,7427],{"className":7428,"style":2484},[2325],[1824,7430,2232],{"className":7431},[2026],[1824,7433],{"className":7434,"style":2484},[2325],[1824,7436,7239],{"className":7437,"style":6692},[1875,1879],[1824,7439,7441,7444],{"className":7440},[2604],[1824,7442,2772],{"className":7443},[2604],[1824,7445,7447],{"className":7446},[1884],[1824,7448,7450],{"className":7449},[1888],[1824,7451,7453],{"className":7452},[1892],[1824,7454,7456],{"className":7455,"style":3579},[1896],[1824,7457,7458,7461],{"style":3582},[1824,7459],{"className":7460,"style":1904},[1903],[1824,7462,7464],{"className":7463},[1908,1909,1910,1911],[1824,7465,1966],{"className":7466},[1875,1879,1911],[1824,7468,7469,7472],{"style":2423},[1824,7470],{"className":7471,"style":2368},[1903],[1824,7473],{"className":7474,"style":2431},[2430],[1824,7476,7477,7480],{"style":2434},[1824,7478],{"className":7479,"style":2368},[1903],[1824,7481,7483,7486],{"className":7482},[1875],[1824,7484,3218],{"className":7485,"style":3241},[1875,1879],[1824,7487,7489,7492],{"className":7488},[1875],[1824,7490,3223],{"className":7491,"style":1993},[1875,1879],[1824,7493,7495],{"className":7494},[1884],[1824,7496,7498,7518],{"className":7497},[1888,2000],[1824,7499,7501,7515],{"className":7500},[1892],[1824,7502,7504],{"className":7503,"style":2094},[1896],[1824,7505,7506,7509],{"style":2010},[1824,7507],{"className":7508,"style":1904},[1903],[1824,7510,7512],{"className":7511},[1908,1909,1910,1911],[1824,7513,1966],{"className":7514},[1875,1879,1911],[1824,7516,2034],{"className":7517},[2033],[1824,7519,7521],{"className":7520},[1892],[1824,7522,7524],{"className":7523,"style":2115},[1896],[1824,7525],{},[1824,7527,2034],{"className":7528},[2033],[1824,7530,7532],{"className":7531},[1892],[1824,7533,7535],{"className":7534,"style":3660},[1896],[1824,7536],{},[1824,7538],{"className":7539},[2604,2348],[1824,7541,2268],{"className":7542},[1875],[1793,7544,7545],{},"Macaulay 久期是现金流时间的现值加权平均：",[1824,7547,7549],{"className":7548},[2196],[1824,7550,7552,7609],{"className":7551},[1827],[1824,7553,7555],{"className":7554},[1831],[1833,7556,7557],{"xmlns":1835,"display":2205},[1837,7558,7559,7606],{},[1840,7560,7561,7567,7569,7604],{},[1957,7562,7563,7565],{},[1846,7564,2135],{},[1846,7566,3764],{},[1968,7568,2218],{},[2220,7570,7571,7602],{},[1840,7572,7573,7580,7582,7586,7588,7590,7592,7594,7600],{},[7574,7575,7576,7578],"munder",{},[1968,7577,3341],{},[1846,7579,1966],{},[1846,7581,1966],{},[7583,7584,7585],"mtext",{}," ",[1846,7587,1961],{},[1846,7589,3767],{},[1968,7591,2759],{"stretchy":2758},[1846,7593,3218],{},[1957,7595,7596,7598],{},[1846,7597,3223],{},[1846,7599,1966],{},[1968,7601,2772],{"stretchy":2758},[1846,7603,1961],{},[1846,7605,2268],{"mathvariant":2267},[1854,7607,7608],{"encoding":1856},"D_M=\\frac{\\sum_t 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给出一阶价格敏感性，凸性提供二阶修正：",[1824,8044,8046],{"className":8045},[2196],[1824,8047,8049,8135],{"className":8048},[1827],[1824,8050,8052],{"className":8051},[1831],[1833,8053,8054],{"xmlns":1835,"display":2205},[1837,8055,8056,8132],{},[1840,8057,8058,8068,8071,8073,8085,8087,8089,8091,8097,8099,8101,8104,8107,8109,8112,8114,8116,8118,8120,8122,8124,8130],{},[2220,8059,8060,8066],{},[1840,8061,8062,8064],{},[1846,8063,6566],{"mathvariant":2267},[1846,8065,1961],{},[1846,8067,1961],{},[1968,8069,8070],{},"≈",[1968,8072,1970],{},[1957,8074,8075,8077],{},[1846,8076,2135],{},[1840,8078,8079,8081,8083],{},[1846,8080,5888],{},[1846,8082,7872],{},[1846,8084,6576],{},[1846,8086,6566],{"mathvariant":2267},[1846,8088,7239],{},[1968,8090,2232],{},[2220,8092,8093,8095],{},[1850,8094,1973],{},[1850,8096,1852],{},[1846,8098,3218],{},[1846,8100,7872],{},[1846,8102,8103],{},"n",[1846,8105,8106],{},"v",[1846,8108,4575],{},[1846,8110,8111],{},"x",[1846,8113,4567],{},[1846,8115,1966],{},[1846,8117,7239],{},[1968,8119,2759],{"stretchy":2758},[1846,8121,6566],{"mathvariant":2267},[1846,8123,7239],{},[1843,8125,8126,8128],{},[1968,8127,2772],{"stretchy":2758},[1850,8129,1852],{},[1846,8131,2268],{"mathvariant":2267},[1854,8133,8134],{"encoding":1856},"\\frac{\\Delta P}{P}\n\\approx -D_{mod}\\Delta y\n+\\frac12 Convexity(\\Delta 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Derivatives",[1814,8528,8529,8530,1915],{},"Campbell, ",[8504,8531,8532],{},"Financial Decisions and Markets",[1814,8534,8535],{},"Gibbons, Ross and Shanken (1989)：多资产 alpha 的联合检验；",[1814,8537,8538],{},"Harvey, Liu and Zhu (2016)：因子发现与多重检验。",[1793,8540,8541,8546,8547],{},[8542,8543,8545],"a",{"href":8544},"..\u002F","返回资产定价首页"," · ",[8542,8548,8550],{"href":8549},"..\u002F10-empirical\u002F","进入实证与数值方法",{"title":10,"searchDepth":8552,"depth":8552,"links":8553},2,[8554,8555,8561,8565,8566,8569,8572,8575,8578,8582],{"id":1806,"depth":8552,"text":1806},{"id":1935,"depth":8552,"text":1936,"children":8556},[8557,8559,8560],{"id":1940,"depth":8558,"text":1940},3,{"id":3200,"depth":8558,"text":3200},{"id":3683,"depth":8558,"text":3683},{"id":3697,"depth":8552,"text":3698,"children":8562},[8563,8564],{"id":3701,"depth":8558,"text":3701},{"id":4524,"depth":8558,"text":4524},{"id":4538,"depth":8552,"text":4539},{"id":5107,"depth":8552,"text":5108,"children":8567},[8568],{"id":5793,"depth":8558,"text":5793},{"id":5858,"depth":8552,"text":5859,"children":8570},[8571],{"id":6490,"depth":8558,"text":6490},{"id":6525,"depth":8552,"text":6526,"children":8573},[8574],{"id":7119,"depth":8558,"text":4524},{"id":7213,"depth":8552,"text":7214,"children":8576},[8577],{"id":8441,"depth":8558,"text":8441},{"id":8447,"depth":8552,"text":8447,"children":8579},[8580,8581],{"id":8453,"depth":8558,"text":8453},{"id":8474,"depth":8558,"text":8474},{"id":8497,"depth":8552,"text":8497},"使用可点击运行的 Python 与 R 单元完成收益率、组合优化、CAPM、多因子、SDF、期权和债券定价实验。","md",{"sidebar":8586},{"order":8587},11,true,{"title":1314,"description":8583},"ZXeBf8v-tP0XPXOnheo6-3ogHhFKcB8-Z60HFBwEb3U",[8592,8594],{"title":1308,"path":1309,"stem":1310,"description":8593,"children":-1},"蒙特卡洛模拟、优化方法与模型检验",{"title":1320,"path":1321,"stem":1322,"description":8595,"children":-1},"通过深度资产定价、因子复现与公司气候暴露研究连接无套利、模型选择、文本度量和样本外检验。",1785754746923]