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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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Alpha 策略全流程","\u002Fzh\u002Fquant\u002F09-case-study","zh\u002Fquant\u002F09-case-study",{"title":1779,"path":1780,"stem":1781},"量化投资文献与软件图谱","\u002Fzh\u002Fquant\u002F10-reading-software-map","zh\u002Fquant\u002F10-reading-software-map",null,{"id":1784,"title":1272,"body":1785,"description":4552,"extension":4553,"features":1782,"hero":1782,"layout":1782,"locale":1782,"meta":4554,"navigation":1782,"path":1273,"published":4557,"seo":4558,"stem":1274,"__hash__":4559},"docs\u002Fzh\u002Fasset-pricing\u002F04-capm\u002Findex.md",{"type":1786,"value":1787,"toc":4531},"minimark",[1788,1792,1796,1799,1803,1871,1874,1877,1896,1899,1917,1920,1923,1969,1972,1975,2390,2393,2753,2912,2916,2919,2923,2926,2929,2932,2935,3208,3211,3214,3217,3220,3223,3226,3631,3634,3638,3641,3851,3854,3963,3966,3970,3973,3980,3983,3986,4069,4072,4105,4108,4122,4125,4525,4528],[1789,1790,1272],"h1",{"id":1791},"第四章资本资产定价模型capm",[1793,1794,1795],"p",{},"第三章讨论了单个投资者如何在均值和方差之间选择。本章进一步问：如果市场上所有投资者都这样选择，资产的预期收益应该如何由风险决定？CAPM 的答案非常简洁：只有不能被分散掉的系统性风险才应该获得风险补偿，而这种风险用 beta 衡量。",[1793,1797,1798],{},"CAPM 在现实中并不完美，但它是资产定价的核心基准。你会在公司金融中用它估计权益资本成本，在投资管理中用它分解主动收益，在实证研究中用它作为检验其他模型的起点。",[1800,1801,1802],"h2",{"id":1802},"本章路线",[1804,1805,1806,1819],"table",{},[1807,1808,1809],"thead",{},[1810,1811,1812,1816],"tr",{},[1813,1814,1815],"th",{},"课次",[1813,1817,1818],{},"核心问题",[1820,1821,1822,1831,1839,1847,1855,1863],"tbody",{},[1810,1823,1824,1828],{},[1825,1826,1827],"td",{},"4.1 推导",[1825,1829,1830],{},"哪些均衡假设使所有人持有同一风险组合？",[1810,1832,1833,1836],{},[1825,1834,1835],{},"4.2 beta",[1825,1837,1838],{},"资产对市场共同波动的暴露如何度量？",[1810,1840,1841,1844],{},[1825,1842,1843],{},"4.3 应用",[1825,1845,1846],{},"必要收益率、资本成本与业绩评价怎样连接？",[1810,1848,1849,1852],{},[1825,1850,1851],{},"4.4 实证检验",[1825,1853,1854],{},"alpha 不为零究竟反驳模型还是基准组合？",[1810,1856,1857,1860],{},[1825,1858,1859],{},"4.5 扩展",[1825,1861,1862],{},"税、借贷限制和动态机会集会改变什么？",[1810,1864,1865,1868],{},[1825,1866,1867],{},"4.6 替代模型",[1825,1869,1870],{},"多因子与 SDF 如何保留 CAPM 的基准作用？",[1800,1872,1873],{"id":1873},"学习成果",[1793,1875,1876],{},"通过本章学习，你将掌握：",[1878,1879,1880,1884,1887,1890,1893],"ol",{},[1881,1882,1883],"li",{},"CAPM模型的理论推导",[1881,1885,1886],{},"贝塔系数的计算和解释",[1881,1888,1889],{},"证券市场线的应用",[1881,1891,1892],{},"CAPM在资本预算和业绩评估中的使用",[1881,1894,1895],{},"CAPM的实证表现和理论局限",[1793,1897,1898],{},"读完本章后，你应能完成以下任务：",[1900,1901,1902,1905,1908,1911,1914],"ul",{},[1881,1903,1904],{},"从均值-方差选择和市场出清解释市场组合为什么进入定价公式。",[1881,1906,1907],{},"计算并解释资产 beta，说明 beta 与相关系数、波动率的关系。",[1881,1909,1910],{},"用证券市场线判断资产预期收益是否偏离 CAPM 基准。",[1881,1912,1913],{},"区分总风险、系统性风险和特质风险。",[1881,1915,1916],{},"说明 CAPM 的实证失败为什么推动多因子模型发展。",[1800,1918,1919],{"id":1919},"金融与经济动机",[1793,1921,1922],{},"投资者不会因为承担任何风险都得到补偿。持有一只个股的特质风险可以通过买更多股票分散掉，因此市场没有理由为这种风险支付稳定溢价。真正需要补偿的是无法通过分散化消除、会随着整体市场一起恶化的风险。",[1804,1924,1925,1935],{},[1807,1926,1927],{},[1810,1928,1929,1932],{},[1813,1930,1931],{},"问题",[1813,1933,1934],{},"CAPM 的回答",[1820,1936,1937,1945,1953,1961],{},[1810,1938,1939,1942],{},[1825,1940,1941],{},"哪类风险有价格",[1825,1943,1944],{},"与市场组合共同波动的系统性风险",[1810,1946,1947,1950],{},[1825,1948,1949],{},"如何衡量系统性风险",[1825,1951,1952],{},"beta，即资产收益对市场收益的敏感度",[1810,1954,1955,1958],{},[1825,1956,1957],{},"风险补偿多大",[1825,1959,1960],{},"beta 乘以市场风险溢价",[1810,1962,1963,1966],{},[1825,1964,1965],{},"CAPM 的用途",[1825,1967,1968],{},"资本成本、业绩评价、异常收益基准",[1800,1970,1971],{"id":1971},"模型设置与直觉",[1793,1973,1974],{},"CAPM 的核心公式是：",[1976,1977,1980],"span",{"className":1978},[1979],"katex-display",[1976,1981,1984,2072],{"className":1982},[1983],"katex",[1976,1985,1988],{"className":1986},[1987],"katex-mathml",[1989,1990,1993],"math",{"xmlns":1991,"display":1992},"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML","block",[1994,1995,1996,2067],"semantics",{},[1997,1998,1999,2003,2008,2017,2020,2023,2030,2033,2040,2043,2045,2047,2054,2056,2058,2064],"mrow",{},[2000,2001,2002],"mi",{},"E",[2004,2005,2007],"mo",{"stretchy":2006},"false","[",[2009,2010,2011,2014],"msub",{},[2000,2012,2013],{},"R",[2000,2015,2016],{},"i",[2004,2018,2019],{"stretchy":2006},"]",[2004,2021,2022],{},"−",[2009,2024,2025,2027],{},[2000,2026,2013],{},[2000,2028,2029],{},"f",[2004,2031,2032],{},"=",[2009,2034,2035,2038],{},[2000,2036,2037],{},"β",[2000,2039,2016],{},[2004,2041,2042],{"stretchy":2006},"(",[2000,2044,2002],{},[2004,2046,2007],{"stretchy":2006},[2009,2048,2049,2051],{},[2000,2050,2013],{},[2000,2052,2053],{},"m",[2004,2055,2019],{"stretchy":2006},[2004,2057,2022],{},[2009,2059,2060,2062],{},[2000,2061,2013],{},[2000,2063,2029],{},[2004,2065,2066],{"stretchy":2006},")",[2068,2069,2071],"annotation",{"encoding":2070},"application\u002Fx-tex","E[R_i]-R_f=\\beta_i(E[R_m]-R_f)",[1976,2073,2077,2169,2230,2340],{"className":2074,"ariaHidden":2076},[2075],"katex-html","true",[1976,2078,2081,2086,2092,2096,2153,2157,2162,2166],{"className":2079},[2080],"base",[1976,2082],{"className":2083,"style":2085},[2084],"strut","height:1em;vertical-align:-0.25em;",[1976,2087,2002],{"className":2088,"style":2091},[2089,2090],"mord","mathnormal","margin-right:0.0576em;",[1976,2093,2007],{"className":2094},[2095],"mopen",[1976,2097,2099,2103],{"className":2098},[2089],[1976,2100,2013],{"className":2101,"style":2102},[2089,2090],"margin-right:0.0077em;",[1976,2104,2107],{"className":2105},[2106],"msupsub",[1976,2108,2112,2144],{"className":2109},[2110,2111],"vlist-t","vlist-t2",[1976,2113,2116,2139],{"className":2114},[2115],"vlist-r",[1976,2117,2121],{"className":2118,"style":2120},[2119],"vlist","height:0.3117em;",[1976,2122,2124,2129],{"style":2123},"top:-2.55em;margin-left:-0.0077em;margin-right:0.05em;",[1976,2125],{"className":2126,"style":2128},[2127],"pstrut","height:2.7em;",[1976,2130,2136],{"className":2131},[2132,2133,2134,2135],"sizing","reset-size6","size3","mtight",[1976,2137,2016],{"className":2138},[2089,2090,2135],[1976,2140,2143],{"className":2141},[2142],"vlist-s","​",[1976,2145,2147],{"className":2146},[2115],[1976,2148,2151],{"className":2149,"style":2150},[2119],"height:0.15em;",[1976,2152],{},[1976,2154,2019],{"className":2155},[2156],"mclose",[1976,2158],{"className":2159,"style":2161},[2160],"mspace","margin-right:0.2222em;",[1976,2163,2022],{"className":2164},[2165],"mbin",[1976,2167],{"className":2168,"style":2161},[2160],[1976,2170,2172,2176,2219,2223,2227],{"className":2171},[2080],[1976,2173],{"className":2174,"style":2175},[2084],"height:0.9694em;vertical-align:-0.2861em;",[1976,2177,2179,2182],{"className":2178},[2089],[1976,2180,2013],{"className":2181,"style":2102},[2089,2090],[1976,2183,2185],{"className":2184},[2106],[1976,2186,2188,2210],{"className":2187},[2110,2111],[1976,2189,2191,2207],{"className":2190},[2115],[1976,2192,2195],{"className":2193,"style":2194},[2119],"height:0.3361em;",[1976,2196,2197,2200],{"style":2123},[1976,2198],{"className":2199,"style":2128},[2127],[1976,2201,2203],{"className":2202},[2132,2133,2134,2135],[1976,2204,2029],{"className":2205,"style":2206},[2089,2090,2135],"margin-right:0.1076em;",[1976,2208,2143],{"className":2209},[2142],[1976,2211,2213],{"className":2212},[2115],[1976,2214,2217],{"className":2215,"style":2216},[2119],"height:0.2861em;",[1976,2218],{},[1976,2220],{"className":2221,"style":2222},[2160],"margin-right:0.2778em;",[1976,2224,2032],{"className":2225},[2226],"mrel",[1976,2228],{"className":2229,"style":2222},[2160],[1976,2231,2233,2236,2278,2281,2284,2287,2328,2331,2334,2337],{"className":2232},[2080],[1976,2234],{"className":2235,"style":2085},[2084],[1976,2237,2239,2243],{"className":2238},[2089],[1976,2240,2037],{"className":2241,"style":2242},[2089,2090],"margin-right:0.0528em;",[1976,2244,2246],{"className":2245},[2106],[1976,2247,2249,2270],{"className":2248},[2110,2111],[1976,2250,2252,2267],{"className":2251},[2115],[1976,2253,2255],{"className":2254,"style":2120},[2119],[1976,2256,2258,2261],{"style":2257},"top:-2.55em;margin-left:-0.0528em;margin-right:0.05em;",[1976,2259],{"className":2260,"style":2128},[2127],[1976,2262,2264],{"className":2263},[2132,2133,2134,2135],[1976,2265,2016],{"className":2266},[2089,2090,2135],[1976,2268,2143],{"className":2269},[2142],[1976,2271,2273],{"className":2272},[2115],[1976,2274,2276],{"className":2275,"style":2150},[2119],[1976,2277],{},[1976,2279,2042],{"className":2280},[2095],[1976,2282,2002],{"className":2283,"style":2091},[2089,2090],[1976,2285,2007],{"className":2286},[2095],[1976,2288,2290,2293],{"className":2289},[2089],[1976,2291,2013],{"className":2292,"style":2102},[2089,2090],[1976,2294,2296],{"className":2295},[2106],[1976,2297,2299,2320],{"className":2298},[2110,2111],[1976,2300,2302,2317],{"className":2301},[2115],[1976,2303,2306],{"className":2304,"style":2305},[2119],"height:0.1514em;",[1976,2307,2308,2311],{"style":2123},[1976,2309],{"className":2310,"style":2128},[2127],[1976,2312,2314],{"className":2313},[2132,2133,2134,2135],[1976,2315,2053],{"className":2316},[2089,2090,2135],[1976,2318,2143],{"className":2319},[2142],[1976,2321,2323],{"className":2322},[2115],[1976,2324,2326],{"className":2325,"style":2150},[2119],[1976,2327],{},[1976,2329,2019],{"className":2330},[2156],[1976,2332],{"className":2333,"style":2161},[2160],[1976,2335,2022],{"className":2336},[2165],[1976,2338],{"className":2339,"style":2161},[2160],[1976,2341,2343,2347,2387],{"className":2342},[2080],[1976,2344],{"className":2345,"style":2346},[2084],"height:1.0361em;vertical-align:-0.2861em;",[1976,2348,2350,2353],{"className":2349},[2089],[1976,2351,2013],{"className":2352,"style":2102},[2089,2090],[1976,2354,2356],{"className":2355},[2106],[1976,2357,2359,2379],{"className":2358},[2110,2111],[1976,2360,2362,2376],{"className":2361},[2115],[1976,2363,2365],{"className":2364,"style":2194},[2119],[1976,2366,2367,2370],{"style":2123},[1976,2368],{"className":2369,"style":2128},[2127],[1976,2371,2373],{"className":2372},[2132,2133,2134,2135],[1976,2374,2029],{"className":2375,"style":2206},[2089,2090,2135],[1976,2377,2143],{"className":2378},[2142],[1976,2380,2382],{"className":2381},[2115],[1976,2383,2385],{"className":2384,"style":2216},[2119],[1976,2386],{},[1976,2388,2066],{"className":2389},[2156],[1793,2391,2392],{},"其中：",[1976,2394,2396],{"className":2395},[1979],[1976,2397,2399,2467],{"className":2398},[1983],[1976,2400,2402],{"className":2401},[1987],[1989,2403,2404],{"xmlns":1991,"display":1992},[1994,2405,2406,2464],{},[1997,2407,2408,2414,2416],{},[2009,2409,2410,2412],{},[2000,2411,2037],{},[2000,2413,2016],{},[2004,2415,2032],{},[2417,2418,2419,2447],"mfrac",{},[1997,2420,2421,2425,2428,2430,2436,2439,2445],{},[2000,2422,2424],{"mathvariant":2423},"normal","Cov",[2004,2426,2427],{},"⁡",[2004,2429,2042],{"stretchy":2006},[2009,2431,2432,2434],{},[2000,2433,2013],{},[2000,2435,2016],{},[2004,2437,2438],{"separator":2076},",",[2009,2440,2441,2443],{},[2000,2442,2013],{},[2000,2444,2053],{},[2004,2446,2066],{"stretchy":2006},[1997,2448,2449,2452,2454,2456,2462],{},[2000,2450,2451],{"mathvariant":2423},"Var",[2004,2453,2427],{},[2004,2455,2042],{"stretchy":2006},[2009,2457,2458,2460],{},[2000,2459,2013],{},[2000,2461,2053],{},[2004,2463,2066],{"stretchy":2006},[2068,2465,2466],{"encoding":2070},"\\beta_i=\\frac{\\operatorname{Cov}(R_i,R_m)}{\\operatorname{Var}(R_m)}",[1976,2468,2470,2526],{"className":2469,"ariaHidden":2076},[2075],[1976,2471,2473,2477,2517,2520,2523],{"className":2472},[2080],[1976,2474],{"className":2475,"style":2476},[2084],"height:0.8889em;vertical-align:-0.1944em;",[1976,2478,2480,2483],{"className":2479},[2089],[1976,2481,2037],{"className":2482,"style":2242},[2089,2090],[1976,2484,2486],{"className":2485},[2106],[1976,2487,2489,2509],{"className":2488},[2110,2111],[1976,2490,2492,2506],{"className":2491},[2115],[1976,2493,2495],{"className":2494,"style":2120},[2119],[1976,2496,2497,2500],{"style":2257},[1976,2498],{"className":2499,"style":2128},[2127],[1976,2501,2503],{"className":2502},[2132,2133,2134,2135],[1976,2504,2016],{"className":2505},[2089,2090,2135],[1976,2507,2143],{"className":2508},[2142],[1976,2510,2512],{"className":2511},[2115],[1976,2513,2515],{"className":2514,"style":2150},[2119],[1976,2516],{},[1976,2518],{"className":2519,"style":2222},[2160],[1976,2521,2032],{"className":2522},[2226],[1976,2524],{"className":2525,"style":2222},[2160],[1976,2527,2529,2533],{"className":2528},[2080],[1976,2530],{"className":2531,"style":2532},[2084],"height:2.363em;vertical-align:-0.936em;",[1976,2534,2536,2540,2750],{"className":2535},[2089],[1976,2537],{"className":2538},[2095,2539],"nulldelimiter",[1976,2541,2543],{"className":2542},[2417],[1976,2544,2546,2741],{"className":2545},[2110,2111],[1976,2547,2549,2738],{"className":2548},[2115],[1976,2550,2553,2617,2628],{"className":2551,"style":2552},[2119],"height:1.427em;",[1976,2554,2556,2560],{"style":2555},"top:-2.314em;",[1976,2557],{"className":2558,"style":2559},[2127],"height:3em;",[1976,2561,2563,2571,2574,2614],{"className":2562},[2089],[1976,2564,2567],{"className":2565},[2566],"mop",[1976,2568,2451],{"className":2569},[2089,2570],"mathrm",[1976,2572,2042],{"className":2573},[2095],[1976,2575,2577,2580],{"className":2576},[2089],[1976,2578,2013],{"className":2579,"style":2102},[2089,2090],[1976,2581,2583],{"className":2582},[2106],[1976,2584,2586,2606],{"className":2585},[2110,2111],[1976,2587,2589,2603],{"className":2588},[2115],[1976,2590,2592],{"className":2591,"style":2305},[2119],[1976,2593,2594,2597],{"style":2123},[1976,2595],{"className":2596,"style":2128},[2127],[1976,2598,2600],{"className":2599},[2132,2133,2134,2135],[1976,2601,2053],{"className":2602},[2089,2090,2135],[1976,2604,2143],{"className":2605},[2142],[1976,2607,2609],{"className":2608},[2115],[1976,2610,2612],{"className":2611,"style":2150},[2119],[1976,2613],{},[1976,2615,2066],{"className":2616},[2156],[1976,2618,2620,2623],{"style":2619},"top:-3.23em;",[1976,2621],{"className":2622,"style":2559},[2127],[1976,2624],{"className":2625,"style":2627},[2626],"frac-line","border-bottom-width:0.04em;",[1976,2629,2631,2634],{"style":2630},"top:-3.677em;",[1976,2632],{"className":2633,"style":2559},[2127],[1976,2635,2637,2644,2647,2687,2691,2695,2735],{"className":2636},[2089],[1976,2638,2640],{"className":2639},[2566],[1976,2641,2424],{"className":2642,"style":2643},[2089,2570],"margin-right:0.0139em;",[1976,2645,2042],{"className":2646},[2095],[1976,2648,2650,2653],{"className":2649},[2089],[1976,2651,2013],{"className":2652,"style":2102},[2089,2090],[1976,2654,2656],{"className":2655},[2106],[1976,2657,2659,2679],{"className":2658},[2110,2111],[1976,2660,2662,2676],{"className":2661},[2115],[1976,2663,2665],{"className":2664,"style":2120},[2119],[1976,2666,2667,2670],{"style":2123},[1976,2668],{"className":2669,"style":2128},[2127],[1976,2671,2673],{"className":2672},[2132,2133,2134,2135],[1976,2674,2016],{"className":2675},[2089,2090,2135],[1976,2677,2143],{"className":2678},[2142],[1976,2680,2682],{"className":2681},[2115],[1976,2683,2685],{"className":2684,"style":2150},[2119],[1976,2686],{},[1976,2688,2438],{"className":2689},[2690],"mpunct",[1976,2692],{"className":2693,"style":2694},[2160],"margin-right:0.1667em;",[1976,2696,2698,2701],{"className":2697},[2089],[1976,2699,2013],{"className":2700,"style":2102},[2089,2090],[1976,2702,2704],{"className":2703},[2106],[1976,2705,2707,2727],{"className":2706},[2110,2111],[1976,2708,2710,2724],{"className":2709},[2115],[1976,2711,2713],{"className":2712,"style":2305},[2119],[1976,2714,2715,2718],{"style":2123},[1976,2716],{"className":2717,"style":2128},[2127],[1976,2719,2721],{"className":2720},[2132,2133,2134,2135],[1976,2722,2053],{"className":2723},[2089,2090,2135],[1976,2725,2143],{"className":2726},[2142],[1976,2728,2730],{"className":2729},[2115],[1976,2731,2733],{"className":2732,"style":2150},[2119],[1976,2734],{},[1976,2736,2066],{"className":2737},[2156],[1976,2739,2143],{"className":2740},[2142],[1976,2742,2744],{"className":2743},[2115],[1976,2745,2748],{"className":2746,"style":2747},[2119],"height:0.936em;",[1976,2749],{},[1976,2751],{"className":2752},[2156,2539],[1793,2754,2755,2756,2826,2827,2856,2857,2911],{},"直觉上，",[1976,2757,2759,2777],{"className":2758},[1983],[1976,2760,2762],{"className":2761},[1987],[1989,2763,2764],{"xmlns":1991},[1994,2765,2766,2774],{},[1997,2767,2768],{},[2009,2769,2770,2772],{},[2000,2771,2037],{},[2000,2773,2016],{},[2068,2775,2776],{"encoding":2070},"\\beta_i",[1976,2778,2780],{"className":2779,"ariaHidden":2076},[2075],[1976,2781,2783,2786],{"className":2782},[2080],[1976,2784],{"className":2785,"style":2476},[2084],[1976,2787,2789,2792],{"className":2788},[2089],[1976,2790,2037],{"className":2791,"style":2242},[2089,2090],[1976,2793,2795],{"className":2794},[2106],[1976,2796,2798,2818],{"className":2797},[2110,2111],[1976,2799,2801,2815],{"className":2800},[2115],[1976,2802,2804],{"className":2803,"style":2120},[2119],[1976,2805,2806,2809],{"style":2257},[1976,2807],{"className":2808,"style":2128},[2127],[1976,2810,2812],{"className":2811},[2132,2133,2134,2135],[1976,2813,2016],{"className":2814},[2089,2090,2135],[1976,2816,2143],{"className":2817},[2142],[1976,2819,2821],{"className":2820},[2115],[1976,2822,2824],{"className":2823,"style":2150},[2119],[1976,2825],{}," 衡量资产 ",[1976,2828,2830,2843],{"className":2829},[1983],[1976,2831,2833],{"className":2832},[1987],[1989,2834,2835],{"xmlns":1991},[1994,2836,2837,2841],{},[1997,2838,2839],{},[2000,2840,2016],{},[2068,2842,2016],{"encoding":2070},[1976,2844,2846],{"className":2845,"ariaHidden":2076},[2075],[1976,2847,2849,2853],{"className":2848},[2080],[1976,2850],{"className":2851,"style":2852},[2084],"height:0.6595em;",[1976,2854,2016],{"className":2855},[2089,2090]," 对市场组合的“放大倍数”。若 ",[1976,2858,2860,2880],{"className":2859},[1983],[1976,2861,2863],{"className":2862},[1987],[1989,2864,2865],{"xmlns":1991},[1994,2866,2867,2877],{},[1997,2868,2869,2871,2873],{},[2000,2870,2037],{},[2004,2872,2032],{},[2874,2875,2876],"mn",{},"1.5",[2068,2878,2879],{"encoding":2070},"\\beta=1.5",[1976,2881,2883,2901],{"className":2882,"ariaHidden":2076},[2075],[1976,2884,2886,2889,2892,2895,2898],{"className":2885},[2080],[1976,2887],{"className":2888,"style":2476},[2084],[1976,2890,2037],{"className":2891,"style":2242},[2089,2090],[1976,2893],{"className":2894,"style":2222},[2160],[1976,2896,2032],{"className":2897},[2226],[1976,2899],{"className":2900,"style":2222},[2160],[1976,2902,2904,2908],{"className":2903},[2080],[1976,2905],{"className":2906,"style":2907},[2084],"height:0.6444em;",[1976,2909,2876],{"className":2910},[2089],"，市场超额收益上升 1 个百分点时，该资产平均上升 1.5 个百分点；市场下跌时也更容易放大损失。投资者要求更高预期收益，是因为这种资产在全市场不好时也容易表现不好。",[2913,2914],"mermaid-diagram",{"code64":2915,"locale":7},"Zmxvd2NoYXJ0IExSCiAgQVsi5Z2H5YC8LeaWueW3ruaKlei1hOiAhSJdIC0tPiBCWyLmjIHmnInliIfngrnnu4TlkIgiXQogIEIgLS0+IENbIuW4guWcuuWHuua4hSJdCiAgQyAtLT4gRFsi5YiH54K557uE5ZCIPeW4guWcuue7hOWQiCJdCiAgRCAtLT4gRVsi57O757uf5oCn6aOO6Zmp55SxIGJldGEg5a6a5Lu3Il0=",[1800,2917,2918],{"id":2918},"关键定义与定理",[2920,2921,2922],"h3",{"id":2922},"市场组合",[1793,2924,2925],{},"市场中所有风险资产按市值权重组成的组合。",[1793,2927,2928],{},"中文解释：如果每个投资者都持有某个最优风险组合，且所有资产都必须被持有，那么这个组合在总量上就是市场组合。",[2920,2930,2931],{"id":2931},"beta",[1793,2933,2934],{},"资产收益对市场收益的协方差除以市场方差：",[1976,2936,2938],{"className":2937},[1979],[1976,2939,2941,2984],{"className":2940},[1983],[1976,2942,2944],{"className":2943},[1987],[1989,2945,2946],{"xmlns":1991,"display":1992},[1994,2947,2948,2981],{},[1997,2949,2950,2956,2958],{},[2009,2951,2952,2954],{},[2000,2953,2037],{},[2000,2955,2016],{},[2004,2957,2032],{},[2417,2959,2960,2971],{},[2009,2961,2962,2965],{},[2000,2963,2964],{},"σ",[1997,2966,2967,2969],{},[2000,2968,2016],{},[2000,2970,2053],{},[2972,2973,2974,2976,2978],"msubsup",{},[2000,2975,2964],{},[2000,2977,2053],{},[2874,2979,2980],{},"2",[2068,2982,2983],{"encoding":2070},"\\beta_i=\\frac{\\sigma_{im}}{\\sigma_m^2}",[1976,2985,2987,3042],{"className":2986,"ariaHidden":2076},[2075],[1976,2988,2990,2993,3033,3036,3039],{"className":2989},[2080],[1976,2991],{"className":2992,"style":2476},[2084],[1976,2994,2996,2999],{"className":2995},[2089],[1976,2997,2037],{"className":2998,"style":2242},[2089,2090],[1976,3000,3002],{"className":3001},[2106],[1976,3003,3005,3025],{"className":3004},[2110,2111],[1976,3006,3008,3022],{"className":3007},[2115],[1976,3009,3011],{"className":3010,"style":2120},[2119],[1976,3012,3013,3016],{"style":2257},[1976,3014],{"className":3015,"style":2128},[2127],[1976,3017,3019],{"className":3018},[2132,2133,2134,2135],[1976,3020,2016],{"className":3021},[2089,2090,2135],[1976,3023,2143],{"className":3024},[2142],[1976,3026,3028],{"className":3027},[2115],[1976,3029,3031],{"className":3030,"style":2150},[2119],[1976,3032],{},[1976,3034],{"className":3035,"style":2222},[2160],[1976,3037,2032],{"className":3038},[2226],[1976,3040],{"className":3041,"style":2222},[2160],[1976,3043,3045,3049],{"className":3044},[2080],[1976,3046],{"className":3047,"style":3048},[2084],"height:2.0406em;vertical-align:-0.933em;",[1976,3050,3052,3055,3205],{"className":3051},[2089],[1976,3053],{"className":3054},[2095,2539],[1976,3056,3058],{"className":3057},[2417],[1976,3059,3061,3196],{"className":3060},[2110,2111],[1976,3062,3064,3193],{"className":3063},[2115],[1976,3065,3068,3132,3140],{"className":3066,"style":3067},[2119],"height:1.1076em;",[1976,3069,3070,3073],{"style":2555},[1976,3071],{"className":3072,"style":2559},[2127],[1976,3074,3076],{"className":3075},[2089],[1976,3077,3079,3083],{"className":3078},[2089],[1976,3080,2964],{"className":3081,"style":3082},[2089,2090],"margin-right:0.0359em;",[1976,3084,3086],{"className":3085},[2106],[1976,3087,3089,3123],{"className":3088},[2110,2111],[1976,3090,3092,3120],{"className":3091},[2115],[1976,3093,3096,3108],{"className":3094,"style":3095},[2119],"height:0.7401em;",[1976,3097,3099,3102],{"style":3098},"top:-2.453em;margin-left:-0.0359em;margin-right:0.05em;",[1976,3100],{"className":3101,"style":2128},[2127],[1976,3103,3105],{"className":3104},[2132,2133,2134,2135],[1976,3106,2053],{"className":3107},[2089,2090,2135],[1976,3109,3111,3114],{"style":3110},"top:-2.989em;margin-right:0.05em;",[1976,3112],{"className":3113,"style":2128},[2127],[1976,3115,3117],{"className":3116},[2132,2133,2134,2135],[1976,3118,2980],{"className":3119},[2089,2135],[1976,3121,2143],{"className":3122},[2142],[1976,3124,3126],{"className":3125},[2115],[1976,3127,3130],{"className":3128,"style":3129},[2119],"height:0.247em;",[1976,3131],{},[1976,3133,3134,3137],{"style":2619},[1976,3135],{"className":3136,"style":2559},[2127],[1976,3138],{"className":3139,"style":2627},[2626],[1976,3141,3142,3145],{"style":2630},[1976,3143],{"className":3144,"style":2559},[2127],[1976,3146,3148],{"className":3147},[2089],[1976,3149,3151,3154],{"className":3150},[2089],[1976,3152,2964],{"className":3153,"style":3082},[2089,2090],[1976,3155,3157],{"className":3156},[2106],[1976,3158,3160,3185],{"className":3159},[2110,2111],[1976,3161,3163,3182],{"className":3162},[2115],[1976,3164,3166],{"className":3165,"style":2120},[2119],[1976,3167,3169,3172],{"style":3168},"top:-2.55em;margin-left:-0.0359em;margin-right:0.05em;",[1976,3170],{"className":3171,"style":2128},[2127],[1976,3173,3175],{"className":3174},[2132,2133,2134,2135],[1976,3176,3178],{"className":3177},[2089,2135],[1976,3179,3181],{"className":3180},[2089,2090,2135],"im",[1976,3183,2143],{"className":3184},[2142],[1976,3186,3188],{"className":3187},[2115],[1976,3189,3191],{"className":3190,"style":2150},[2119],[1976,3192],{},[1976,3194,2143],{"className":3195},[2142],[1976,3197,3199],{"className":3198},[2115],[1976,3200,3203],{"className":3201,"style":3202},[2119],"height:0.933em;",[1976,3204],{},[1976,3206],{"className":3207},[2156,2539],[1793,3209,3210],{},"中文解释：beta 不是“这个资产有多波动”，而是“它有多跟市场一起波动”。",[2920,3212,3213],{"id":3213},"证券市场线",[1793,3215,3216],{},"CAPM 公式在预期收益-beta 平面上的直线。",[1793,3218,3219],{},"中文解释：在 CAPM 成立时，所有资产和组合都应落在这条线上；偏离直线的部分称为 alpha。",[2920,3221,3222],{"id":3222},"alpha",[1793,3224,3225],{},"回归或模型中无法由 beta 风险解释的平均超额收益：",[1976,3227,3229],{"className":3228},[1979],[1976,3230,3232,3301],{"className":3231},[1983],[1976,3233,3235],{"className":3234},[1987],[1989,3236,3237],{"xmlns":1991,"display":1992},[1994,3238,3239,3298],{},[1997,3240,3241,3248,3250,3252,3254,3260,3262,3268,3270,3272,3278,3280,3282,3288,3290,3296],{},[2009,3242,3243,3246],{},[2000,3244,3245],{},"α",[2000,3247,2016],{},[2004,3249,2032],{},[2000,3251,2002],{},[2004,3253,2007],{"stretchy":2006},[2009,3255,3256,3258],{},[2000,3257,2013],{},[2000,3259,2016],{},[2004,3261,2022],{},[2009,3263,3264,3266],{},[2000,3265,2013],{},[2000,3267,2029],{},[2004,3269,2019],{"stretchy":2006},[2004,3271,2022],{},[2009,3273,3274,3276],{},[2000,3275,2037],{},[2000,3277,2016],{},[2000,3279,2002],{},[2004,3281,2007],{"stretchy":2006},[2009,3283,3284,3286],{},[2000,3285,2013],{},[2000,3287,2053],{},[2004,3289,2022],{},[2009,3291,3292,3294],{},[2000,3293,2013],{},[2000,3295,2029],{},[2004,3297,2019],{"stretchy":2006},[2068,3299,3300],{"encoding":2070},"\\alpha_i=E[R_i-R_f]-\\beta_iE[R_m-R_f]",[1976,3302,3304,3362,3423,3481,3582],{"className":3303,"ariaHidden":2076},[2075],[1976,3305,3307,3311,3353,3356,3359],{"className":3306},[2080],[1976,3308],{"className":3309,"style":3310},[2084],"height:0.5806em;vertical-align:-0.15em;",[1976,3312,3314,3318],{"className":3313},[2089],[1976,3315,3245],{"className":3316,"style":3317},[2089,2090],"margin-right:0.0037em;",[1976,3319,3321],{"className":3320},[2106],[1976,3322,3324,3345],{"className":3323},[2110,2111],[1976,3325,3327,3342],{"className":3326},[2115],[1976,3328,3330],{"className":3329,"style":2120},[2119],[1976,3331,3333,3336],{"style":3332},"top:-2.55em;margin-left:-0.0037em;margin-right:0.05em;",[1976,3334],{"className":3335,"style":2128},[2127],[1976,3337,3339],{"className":3338},[2132,2133,2134,2135],[1976,3340,2016],{"className":3341},[2089,2090,2135],[1976,3343,2143],{"className":3344},[2142],[1976,3346,3348],{"className":3347},[2115],[1976,3349,3351],{"className":3350,"style":2150},[2119],[1976,3352],{},[1976,3354],{"className":3355,"style":2222},[2160],[1976,3357,2032],{"className":3358},[2226],[1976,3360],{"className":3361,"style":2222},[2160],[1976,3363,3365,3368,3371,3374,3414,3417,3420],{"className":3364},[2080],[1976,3366],{"className":3367,"style":2085},[2084],[1976,3369,2002],{"className":3370,"style":2091},[2089,2090],[1976,3372,2007],{"className":3373},[2095],[1976,3375,3377,3380],{"className":3376},[2089],[1976,3378,2013],{"className":3379,"style":2102},[2089,2090],[1976,3381,3383],{"className":3382},[2106],[1976,3384,3386,3406],{"className":3385},[2110,2111],[1976,3387,3389,3403],{"className":3388},[2115],[1976,3390,3392],{"className":3391,"style":2120},[2119],[1976,3393,3394,3397],{"style":2123},[1976,3395],{"className":3396,"style":2128},[2127],[1976,3398,3400],{"className":3399},[2132,2133,2134,2135],[1976,3401,2016],{"className":3402},[2089,2090,2135],[1976,3404,2143],{"className":3405},[2142],[1976,3407,3409],{"className":3408},[2115],[1976,3410,3412],{"className":3411,"style":2150},[2119],[1976,3413],{},[1976,3415],{"className":3416,"style":2161},[2160],[1976,3418,2022],{"className":3419},[2165],[1976,3421],{"className":3422,"style":2161},[2160],[1976,3424,3426,3429,3469,3472,3475,3478],{"className":3425},[2080],[1976,3427],{"className":3428,"style":2346},[2084],[1976,3430,3432,3435],{"className":3431},[2089],[1976,3433,2013],{"className":3434,"style":2102},[2089,2090],[1976,3436,3438],{"className":3437},[2106],[1976,3439,3441,3461],{"className":3440},[2110,2111],[1976,3442,3444,3458],{"className":3443},[2115],[1976,3445,3447],{"className":3446,"style":2194},[2119],[1976,3448,3449,3452],{"style":2123},[1976,3450],{"className":3451,"style":2128},[2127],[1976,3453,3455],{"className":3454},[2132,2133,2134,2135],[1976,3456,2029],{"className":3457,"style":2206},[2089,2090,2135],[1976,3459,2143],{"className":3460},[2142],[1976,3462,3464],{"className":3463},[2115],[1976,3465,3467],{"className":3466,"style":2216},[2119],[1976,3468],{},[1976,3470,2019],{"className":3471},[2156],[1976,3473],{"className":3474,"style":2161},[2160],[1976,3476,2022],{"className":3477},[2165],[1976,3479],{"className":3480,"style":2161},[2160],[1976,3482,3484,3487,3527,3530,3533,3573,3576,3579],{"className":3483},[2080],[1976,3485],{"className":3486,"style":2085},[2084],[1976,3488,3490,3493],{"className":3489},[2089],[1976,3491,2037],{"className":3492,"style":2242},[2089,2090],[1976,3494,3496],{"className":3495},[2106],[1976,3497,3499,3519],{"className":3498},[2110,2111],[1976,3500,3502,3516],{"className":3501},[2115],[1976,3503,3505],{"className":3504,"style":2120},[2119],[1976,3506,3507,3510],{"style":2257},[1976,3508],{"className":3509,"style":2128},[2127],[1976,3511,3513],{"className":3512},[2132,2133,2134,2135],[1976,3514,2016],{"className":3515},[2089,2090,2135],[1976,3517,2143],{"className":3518},[2142],[1976,3520,3522],{"className":3521},[2115],[1976,3523,3525],{"className":3524,"style":2150},[2119],[1976,3526],{},[1976,3528,2002],{"className":3529,"style":2091},[2089,2090],[1976,3531,2007],{"className":3532},[2095],[1976,3534,3536,3539],{"className":3535},[2089],[1976,3537,2013],{"className":3538,"style":2102},[2089,2090],[1976,3540,3542],{"className":3541},[2106],[1976,3543,3545,3565],{"className":3544},[2110,2111],[1976,3546,3548,3562],{"className":3547},[2115],[1976,3549,3551],{"className":3550,"style":2305},[2119],[1976,3552,3553,3556],{"style":2123},[1976,3554],{"className":3555,"style":2128},[2127],[1976,3557,3559],{"className":3558},[2132,2133,2134,2135],[1976,3560,2053],{"className":3561},[2089,2090,2135],[1976,3563,2143],{"className":3564},[2142],[1976,3566,3568],{"className":3567},[2115],[1976,3569,3571],{"className":3570,"style":2150},[2119],[1976,3572],{},[1976,3574],{"className":3575,"style":2161},[2160],[1976,3577,2022],{"className":3578},[2165],[1976,3580],{"className":3581,"style":2161},[2160],[1976,3583,3585,3588,3628],{"className":3584},[2080],[1976,3586],{"className":3587,"style":2346},[2084],[1976,3589,3591,3594],{"className":3590},[2089],[1976,3592,2013],{"className":3593,"style":2102},[2089,2090],[1976,3595,3597],{"className":3596},[2106],[1976,3598,3600,3620],{"className":3599},[2110,2111],[1976,3601,3603,3617],{"className":3602},[2115],[1976,3604,3606],{"className":3605,"style":2194},[2119],[1976,3607,3608,3611],{"style":2123},[1976,3609],{"className":3610,"style":2128},[2127],[1976,3612,3614],{"className":3613},[2132,2133,2134,2135],[1976,3615,2029],{"className":3616,"style":2206},[2089,2090,2135],[1976,3618,2143],{"className":3619},[2142],[1976,3621,3623],{"className":3622},[2115],[1976,3624,3626],{"className":3625,"style":2216},[2119],[1976,3627],{},[1976,3629,2019],{"className":3630},[2156],[1793,3632,3633],{},"中文解释：正 alpha 常被解释为异常收益，但也可能来自模型遗漏、数据挖掘或风险度量错误。",[1800,3635,3637],{"id":3636},"例子用-beta-估计必要收益率","例子：用 beta 估计必要收益率",[1793,3639,3640],{},"假设无风险利率为 3%，市场预期收益为 9%，某股票 beta 为 1.2。CAPM 给出的必要收益率是：",[1976,3642,3644],{"className":3643},[1979],[1976,3645,3647,3707],{"className":3646},[1983],[1976,3648,3650],{"className":3649},[1987],[1989,3651,3652],{"xmlns":1991,"display":1992},[1994,3653,3654,3704],{},[1997,3655,3656,3658,3660,3666,3668,3670,3673,3676,3679,3682,3684,3687,3689,3691,3693,3695,3697,3699,3702],{},[2000,3657,2002],{},[2004,3659,2007],{"stretchy":2006},[2009,3661,3662,3664],{},[2000,3663,2013],{},[2000,3665,2016],{},[2004,3667,2019],{"stretchy":2006},[2004,3669,2032],{},[2874,3671,3672],{},"3",[2000,3674,3675],{"mathvariant":2423},"%",[2004,3677,3678],{},"+",[2874,3680,3681],{},"1.2",[2004,3683,2042],{"stretchy":2006},[2874,3685,3686],{},"9",[2000,3688,3675],{"mathvariant":2423},[2004,3690,2022],{},[2874,3692,3672],{},[2000,3694,3675],{"mathvariant":2423},[2004,3696,2066],{"stretchy":2006},[2004,3698,2032],{},[2874,3700,3701],{},"10.2",[2000,3703,3675],{"mathvariant":2423},[2068,3705,3706],{"encoding":2070},"E[R_i]=3\\%+1.2(9\\%-3\\%)=10.2\\%",[1976,3708,3710,3774,3794,3819,3840],{"className":3709,"ariaHidden":2076},[2075],[1976,3711,3713,3716,3719,3722,3762,3765,3768,3771],{"className":3712},[2080],[1976,3714],{"className":3715,"style":2085},[2084],[1976,3717,2002],{"className":3718,"style":2091},[2089,2090],[1976,3720,2007],{"className":3721},[2095],[1976,3723,3725,3728],{"className":3724},[2089],[1976,3726,2013],{"className":3727,"style":2102},[2089,2090],[1976,3729,3731],{"className":3730},[2106],[1976,3732,3734,3754],{"className":3733},[2110,2111],[1976,3735,3737,3751],{"className":3736},[2115],[1976,3738,3740],{"className":3739,"style":2120},[2119],[1976,3741,3742,3745],{"style":2123},[1976,3743],{"className":3744,"style":2128},[2127],[1976,3746,3748],{"className":3747},[2132,2133,2134,2135],[1976,3749,2016],{"className":3750},[2089,2090,2135],[1976,3752,2143],{"className":3753},[2142],[1976,3755,3757],{"className":3756},[2115],[1976,3758,3760],{"className":3759,"style":2150},[2119],[1976,3761],{},[1976,3763,2019],{"className":3764},[2156],[1976,3766],{"className":3767,"style":2222},[2160],[1976,3769,2032],{"className":3770},[2226],[1976,3772],{"className":3773,"style":2222},[2160],[1976,3775,3777,3781,3785,3788,3791],{"className":3776},[2080],[1976,3778],{"className":3779,"style":3780},[2084],"height:0.8333em;vertical-align:-0.0833em;",[1976,3782,3784],{"className":3783},[2089],"3%",[1976,3786],{"className":3787,"style":2161},[2160],[1976,3789,3678],{"className":3790},[2165],[1976,3792],{"className":3793,"style":2161},[2160],[1976,3795,3797,3800,3803,3806,3810,3813,3816],{"className":3796},[2080],[1976,3798],{"className":3799,"style":2085},[2084],[1976,3801,3681],{"className":3802},[2089],[1976,3804,2042],{"className":3805},[2095],[1976,3807,3809],{"className":3808},[2089],"9%",[1976,3811],{"className":3812,"style":2161},[2160],[1976,3814,2022],{"className":3815},[2165],[1976,3817],{"className":3818,"style":2161},[2160],[1976,3820,3822,3825,3828,3831,3834,3837],{"className":3821},[2080],[1976,3823],{"className":3824,"style":2085},[2084],[1976,3826,3784],{"className":3827},[2089],[1976,3829,2066],{"className":3830},[2156],[1976,3832],{"className":3833,"style":2222},[2160],[1976,3835,2032],{"className":3836},[2226],[1976,3838],{"className":3839,"style":2222},[2160],[1976,3841,3843,3847],{"className":3842},[2080],[1976,3844],{"className":3845,"style":3846},[2084],"height:0.8056em;vertical-align:-0.0556em;",[1976,3848,3850],{"className":3849},[2089],"10.2%",[1793,3852,3853],{},"若分析师预测该股票预期收益为 12%，则 CAPM alpha 为：",[1976,3855,3857],{"className":3856},[1979],[1976,3858,3860,3894],{"className":3859},[1983],[1976,3861,3863],{"className":3862},[1987],[1989,3864,3865],{"xmlns":1991,"display":1992},[1994,3866,3867,3891],{},[1997,3868,3869,3871,3873,3876,3878,3880,3882,3884,3886,3889],{},[2000,3870,3245],{},[2004,3872,2032],{},[2874,3874,3875],{},"12",[2000,3877,3675],{"mathvariant":2423},[2004,3879,2022],{},[2874,3881,3701],{},[2000,3883,3675],{"mathvariant":2423},[2004,3885,2032],{},[2874,3887,3888],{},"1.8",[2000,3890,3675],{"mathvariant":2423},[2068,3892,3893],{"encoding":2070},"\\alpha=12\\%-10.2\\%=1.8\\%",[1976,3895,3897,3916,3935,3953],{"className":3896,"ariaHidden":2076},[2075],[1976,3898,3900,3904,3907,3910,3913],{"className":3899},[2080],[1976,3901],{"className":3902,"style":3903},[2084],"height:0.4306em;",[1976,3905,3245],{"className":3906,"style":3317},[2089,2090],[1976,3908],{"className":3909,"style":2222},[2160],[1976,3911,2032],{"className":3912},[2226],[1976,3914],{"className":3915,"style":2222},[2160],[1976,3917,3919,3922,3926,3929,3932],{"className":3918},[2080],[1976,3920],{"className":3921,"style":3780},[2084],[1976,3923,3925],{"className":3924},[2089],"12%",[1976,3927],{"className":3928,"style":2161},[2160],[1976,3930,2022],{"className":3931},[2165],[1976,3933],{"className":3934,"style":2161},[2160],[1976,3936,3938,3941,3944,3947,3950],{"className":3937},[2080],[1976,3939],{"className":3940,"style":3846},[2084],[1976,3942,3850],{"className":3943},[2089],[1976,3945],{"className":3946,"style":2222},[2160],[1976,3948,2032],{"className":3949},[2226],[1976,3951],{"className":3952,"style":2222},[2160],[1976,3954,3956,3959],{"className":3955},[2080],[1976,3957],{"className":3958,"style":3846},[2084],[1976,3960,3962],{"className":3961},[2089],"1.8%",[1793,3964,3965],{},"这并不自动说明股票“被低估”。你还要检查 beta 估计是否稳定、市场组合代理是否合适、预测收益是否可实现，以及是否遗漏规模、价值、盈利能力等其他风险因子。",[1800,3967,3969],{"id":3968},"可运行例题alpha-对-beta-误差有多敏感","可运行例题：alpha 对 beta 误差有多敏感",[1793,3971,3972],{},"分析师预测收益仍为 12%，但 beta 的合理估计区间是 0.9—1.5。比较区间两端。",[3974,3975],"pyodide",{"code64":3976,"layout":3977,"locale":7,"packages":3978,"title":3979},"aW1wb3J0IG51bXB5IGFzIG5wCgpyaXNrX2ZyZWUgPSAwLjAzCm1hcmtldF9yZXR1cm4gPSAwLjA5CmZvcmVjYXN0X3JldHVybiA9IDAuMTIKCmZvciBiZXRhIGluIG5wLmFycmF5KFswLjksIDEuMiwgMS41XSk6CiAgICByZXF1aXJlZCA9IHJpc2tfZnJlZSArIGJldGEgKiAobWFya2V0X3JldHVybiAtIHJpc2tfZnJlZSkKICAgIGFscGhhID0gZm9yZWNhc3RfcmV0dXJuIC0gcmVxdWlyZWQKICAgIHByaW50KGYiYmV0YT17YmV0YTouMWZ9OiDlv4XopoHmlLbnm4o9e3JlcXVpcmVkOi4yJX0sIOmihOa1i+WHj+W\u002FheimgeaUtuebij17YWxwaGE6LjIlfSIp","vertical","numpy","Python：CAPM 必要收益与 beta 敏感性",[1793,3981,3982],{},"同一份 12% 预测，在 beta=0.9 时看似有 3.6% 超额，在 beta=1.5 时恰好没有。报告 alpha 时至少应同时报告 beta 的估计方法、标准误、窗口与市场代理。",[1800,3984,3985],{"id":3985},"学习顺序建议",[1804,3987,3988,4001],{},[1807,3989,3990],{},[1810,3991,3992,3995,3998],{},[1813,3993,3994],{},"小节",[1813,3996,3997],{},"先抓住的问题",[1813,3999,4000],{},"需要特别留意",[1820,4002,4003,4014,4025,4036,4047,4058],{},[1810,4004,4005,4008,4011],{},[1825,4006,4007],{},"4.1 CAPM的假设与推导",[1825,4009,4010],{},"CAPM 从哪些假设推出",[1825,4012,4013],{},"市场组合、切点组合、市场出清",[1810,4015,4016,4019,4022],{},[1825,4017,4018],{},"4.2 市场组合与贝塔",[1825,4020,4021],{},"beta 衡量什么风险",[1825,4023,4024],{},"beta 与相关系数、波动率的区别",[1810,4026,4027,4030,4033],{},[1825,4028,4029],{},"4.3 CAPM的应用",[1825,4031,4032],{},"如何用证券市场线做估值和评价",[1825,4034,4035],{},"资本成本、alpha、业绩归因",[1810,4037,4038,4041,4044],{},[1825,4039,4040],{},"4.4 CAPM的实证检验",[1825,4042,4043],{},"CAPM 在数据中表现如何",[1825,4045,4046],{},"时间序列回归、横截面检验",[1810,4048,4049,4052,4055],{},[1825,4050,4051],{},"4.5 CAPM的扩展与批评",[1825,4053,4054],{},"哪些假设过强",[1825,4056,4057],{},"借贷限制、异质预期、非正态收益",[1810,4059,4060,4063,4066],{},[1825,4061,4062],{},"4.6 替代模型总结",[1825,4064,4065],{},"为什么需要多因子模型",[1825,4067,4068],{},"APT、ICAPM、行为解释",[1800,4070,4071],{"id":4071},"常见错误与考试陷阱",[1878,4073,4074,4081,4087,4093,4099],{},[1881,4075,4076,4080],{},[4077,4078,4079],"strong",{},"把 beta 当成波动率","：高波动但与市场低相关的资产，beta 可能不高。",[1881,4082,4083,4086],{},[4077,4084,4085],{},"认为特质风险也应被补偿","：在充分分散组合中，特质风险可被消除，CAPM 不给它定价。",[1881,4088,4089,4092],{},[4077,4090,4091],{},"混淆资本市场线和证券市场线","：资本市场线用总波动率描述有效组合；证券市场线用 beta 描述任意资产。",[1881,4094,4095,4098],{},[4077,4096,4097],{},"把 alpha 当成必然套利机会","：alpha 估计可能受模型错误、样本选择和交易成本影响。",[1881,4100,4101,4104],{},[4077,4102,4103],{},"忽略市场组合不可观测","：实证中常用股票指数代理市场组合，这会带来 Roll 批评。",[1800,4106,4107],{"id":4107},"自测题",[1878,4109,4110,4113,4116,4119],{},[1881,4111,4112],{},"为什么 CAPM 认为只有系统性风险获得补偿？",[1881,4114,4115],{},"某资产与市场相关系数为 0.6，资产波动率 30%，市场波动率 15%。它的 beta 是多少？",[1881,4117,4118],{},"无风险利率 2%，市场风险溢价 6%，资产 beta 为 0.8。CAPM 必要收益率是多少？",[1881,4120,4121],{},"若一个低 beta 股票长期平均收益高于 CAPM 预测，你会提出哪些可能解释？",[1800,4123,4124],{"id":4124},"答案指引",[1878,4126,4127,4130,4412,4522],{},[1881,4128,4129],{},"特质风险可以通过分散化消除；系统性风险与整体市场一起波动，无法由持有更多资产完全消除。",[1881,4131,4132,4411],{},[1976,4133,4135,4201],{"className":4134},[1983],[1976,4136,4138],{"className":4137},[1987],[1989,4139,4140],{"xmlns":1991},[1994,4141,4142,4198],{},[1997,4143,4144,4146,4148,4159,4165,4168,4174,4176,4179,4182,4185,4187,4189,4192,4194,4196],{},[2000,4145,2037],{},[2004,4147,2032],{},[2009,4149,4150,4153],{},[2000,4151,4152],{},"ρ",[1997,4154,4155,4157],{},[2000,4156,2016],{},[2000,4158,2053],{},[2009,4160,4161,4163],{},[2000,4162,2964],{},[2000,4164,2016],{},[2000,4166,4167],{"mathvariant":2423},"\u002F",[2009,4169,4170,4172],{},[2000,4171,2964],{},[2000,4173,2053],{},[2004,4175,2032],{},[2874,4177,4178],{},"0.6",[2004,4180,4181],{},"×",[2874,4183,4184],{},"30",[2000,4186,3675],{"mathvariant":2423},[2000,4188,4167],{"mathvariant":2423},[2874,4190,4191],{},"15",[2000,4193,3675],{"mathvariant":2423},[2004,4195,2032],{},[2874,4197,3681],{},[2068,4199,4200],{"encoding":2070},"\\beta=\\rho_{im}\\sigma_i\u002F\\sigma_m=0.6\\times30\\%\u002F15\\%=1.2",[1976,4202,4204,4222,4364,4383,4402],{"className":4203,"ariaHidden":2076},[2075],[1976,4205,4207,4210,4213,4216,4219],{"className":4206},[2080],[1976,4208],{"className":4209,"style":2476},[2084],[1976,4211,2037],{"className":4212,"style":2242},[2089,2090],[1976,4214],{"className":4215,"style":2222},[2160],[1976,4217,2032],{"className":4218},[2226],[1976,4220],{"className":4221,"style":2222},[2160],[1976,4223,4225,4228,4272,4312,4315,4355,4358,4361],{"className":4224},[2080],[1976,4226],{"className":4227,"style":2085},[2084],[1976,4229,4231,4234],{"className":4230},[2089],[1976,4232,4152],{"className":4233},[2089,2090],[1976,4235,4237],{"className":4236},[2106],[1976,4238,4240,4264],{"className":4239},[2110,2111],[1976,4241,4243,4261],{"className":4242},[2115],[1976,4244,4246],{"className":4245,"style":2120},[2119],[1976,4247,4249,4252],{"style":4248},"top:-2.55em;margin-left:0em;margin-right:0.05em;",[1976,4250],{"className":4251,"style":2128},[2127],[1976,4253,4255],{"className":4254},[2132,2133,2134,2135],[1976,4256,4258],{"className":4257},[2089,2135],[1976,4259,3181],{"className":4260},[2089,2090,2135],[1976,4262,2143],{"className":4263},[2142],[1976,4265,4267],{"className":4266},[2115],[1976,4268,4270],{"className":4269,"style":2150},[2119],[1976,4271],{},[1976,4273,4275,4278],{"className":4274},[2089],[1976,4276,2964],{"className":4277,"style":3082},[2089,2090],[1976,4279,4281],{"className":4280},[2106],[1976,4282,4284,4304],{"className":4283},[2110,2111],[1976,4285,4287,4301],{"className":4286},[2115],[1976,4288,4290],{"className":4289,"style":2120},[2119],[1976,4291,4292,4295],{"style":3168},[1976,4293],{"className":4294,"style":2128},[2127],[1976,4296,4298],{"className":4297},[2132,2133,2134,2135],[1976,4299,2016],{"className":4300},[2089,2090,2135],[1976,4302,2143],{"className":4303},[2142],[1976,4305,4307],{"className":4306},[2115],[1976,4308,4310],{"className":4309,"style":2150},[2119],[1976,4311],{},[1976,4313,4167],{"className":4314},[2089],[1976,4316,4318,4321],{"className":4317},[2089],[1976,4319,2964],{"className":4320,"style":3082},[2089,2090],[1976,4322,4324],{"className":4323},[2106],[1976,4325,4327,4347],{"className":4326},[2110,2111],[1976,4328,4330,4344],{"className":4329},[2115],[1976,4331,4333],{"className":4332,"style":2305},[2119],[1976,4334,4335,4338],{"style":3168},[1976,4336],{"className":4337,"style":2128},[2127],[1976,4339,4341],{"className":4340},[2132,2133,2134,2135],[1976,4342,2053],{"className":4343},[2089,2090,2135],[1976,4345,2143],{"className":4346},[2142],[1976,4348,4350],{"className":4349},[2115],[1976,4351,4353],{"className":4352,"style":2150},[2119],[1976,4354],{},[1976,4356],{"className":4357,"style":2222},[2160],[1976,4359,2032],{"className":4360},[2226],[1976,4362],{"className":4363,"style":2222},[2160],[1976,4365,4367,4371,4374,4377,4380],{"className":4366},[2080],[1976,4368],{"className":4369,"style":4370},[2084],"height:0.7278em;vertical-align:-0.0833em;",[1976,4372,4178],{"className":4373},[2089],[1976,4375],{"className":4376,"style":2161},[2160],[1976,4378,4181],{"className":4379},[2165],[1976,4381],{"className":4382,"style":2161},[2160],[1976,4384,4386,4389,4393,4396,4399],{"className":4385},[2080],[1976,4387],{"className":4388,"style":2085},[2084],[1976,4390,4392],{"className":4391},[2089],"30%\u002F15%",[1976,4394],{"className":4395,"style":2222},[2160],[1976,4397,2032],{"className":4398},[2226],[1976,4400],{"className":4401,"style":2222},[2160],[1976,4403,4405,4408],{"className":4404},[2080],[1976,4406],{"className":4407,"style":2907},[2084],[1976,4409,3681],{"className":4410},[2089],"。",[1881,4413,4414,4415,4411],{},"必要收益率为 ",[1976,4416,4418,4453],{"className":4417},[1983],[1976,4419,4421],{"className":4420},[1987],[1989,4422,4423],{"xmlns":1991},[1994,4424,4425,4450],{},[1997,4426,4427,4429,4431,4433,4436,4438,4441,4443,4445,4448],{},[2874,4428,2980],{},[2000,4430,3675],{"mathvariant":2423},[2004,4432,3678],{},[2874,4434,4435],{},"0.8",[2004,4437,4181],{},[2874,4439,4440],{},"6",[2000,4442,3675],{"mathvariant":2423},[2004,4444,2032],{},[2874,4446,4447],{},"6.8",[2000,4449,3675],{"mathvariant":2423},[2068,4451,4452],{"encoding":2070},"2\\%+0.8\\times6\\%=6.8\\%",[1976,4454,4456,4475,4493,4512],{"className":4455,"ariaHidden":2076},[2075],[1976,4457,4459,4462,4466,4469,4472],{"className":4458},[2080],[1976,4460],{"className":4461,"style":3780},[2084],[1976,4463,4465],{"className":4464},[2089],"2%",[1976,4467],{"className":4468,"style":2161},[2160],[1976,4470,3678],{"className":4471},[2165],[1976,4473],{"className":4474,"style":2161},[2160],[1976,4476,4478,4481,4484,4487,4490],{"className":4477},[2080],[1976,4479],{"className":4480,"style":4370},[2084],[1976,4482,4435],{"className":4483},[2089],[1976,4485],{"className":4486,"style":2161},[2160],[1976,4488,4181],{"className":4489},[2165],[1976,4491],{"className":4492,"style":2161},[2160],[1976,4494,4496,4499,4503,4506,4509],{"className":4495},[2080],[1976,4497],{"className":4498,"style":3846},[2084],[1976,4500,4502],{"className":4501},[2089],"6%",[1976,4504],{"className":4505,"style":2222},[2160],[1976,4507,2032],{"className":4508},[2226],[1976,4510],{"className":4511,"style":2222},[2160],[1976,4513,4515,4518],{"className":4514},[2080],[1976,4516],{"className":4517,"style":3846},[2084],[1976,4519,4521],{"className":4520},[2089],"6.8%",[1881,4523,4524],{},"可能是 CAPM 遗漏风险因子、beta 估计误差、样本期特殊、交易成本或限制套利，也可能是行为偏差造成的误定价。",[1800,4526,4527],{"id":4527},"小结与过渡",[1793,4529,4530],{},"CAPM 把均值-方差选择推进到市场均衡，并给出“beta 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