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Predictive Analytics","\u002Fen\u002Fbusiness-analytics\u002F02-predictive","en\u002Fbusiness-analytics\u002F02-predictive\u002Findex",[343,344,348,352,356,360,364],{"title":339,"path":340,"stem":341,"sidebar":12},{"title":345,"path":346,"stem":347,"sidebar":12},"Validation, Baselines and Leakage","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F09-validation-leakage","en\u002Fbusiness-analytics\u002F02-predictive\u002F09-validation-leakage",{"title":349,"path":350,"stem":351,"sidebar":12},"Regression and Forecasting","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F10-regression-forecasting","en\u002Fbusiness-analytics\u002F02-predictive\u002F10-regression-forecasting",{"title":353,"path":354,"stem":355,"sidebar":12},"Classification and Calibration","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F11-classification-calibration","en\u002Fbusiness-analytics\u002F02-predictive\u002F11-classification-calibration",{"title":357,"path":358,"stem":359,"sidebar":12},"Trees and Ensembles","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F12-trees-ensembles","en\u002Fbusiness-analytics\u002F02-predictive\u002F12-trees-ensembles",{"title":361,"path":362,"stem":363,"sidebar":12},"Decision Metrics and Thresholds","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F13-decision-metrics-thresholds","en\u002Fbusiness-analytics\u002F02-predictive\u002F13-decision-metrics-thresholds",{"title":365,"path":366,"stem":367,"sidebar":12},"Explainability, Monitoring and Drift","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F14-explainability-drift","en\u002Fbusiness-analytics\u002F02-predictive\u002F14-explainability-drift",{"title":369,"path":370,"stem":371,"children":372,"sidebar":12},"3. Prescriptive Analytics","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive","en\u002Fbusiness-analytics\u002F03-prescriptive\u002Findex",[373,374,378,382,386,390,394],{"title":369,"path":370,"stem":371,"sidebar":12},{"title":375,"path":376,"stem":377,"sidebar":12},"Decision-Making under Uncertainty","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F15-decision-uncertainty","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F15-decision-uncertainty",{"title":379,"path":380,"stem":381,"sidebar":12},"Linear Optimisation","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F16-linear-optimization","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F16-linear-optimization",{"title":383,"path":384,"stem":385,"sidebar":12},"Inventory and Allocation","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F17-inventory-allocation","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F17-inventory-allocation",{"title":387,"path":388,"stem":389,"sidebar":12},"Queueing and Simulation","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F18-queueing-simulation","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F18-queueing-simulation",{"title":391,"path":392,"stem":393,"sidebar":12},"Pricing and Revenue Management","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F19-pricing-experimentation","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F19-pricing-experimentation",{"title":395,"path":396,"stem":397,"sidebar":12},"Causal Targeting and Policy Learning","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F20-causal-targeting","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F20-causal-targeting",{"title":399,"path":400,"stem":401,"children":402,"sidebar":12},"4. Deployment and Governance","\u002Fen\u002Fbusiness-analytics\u002F04-deployment","en\u002Fbusiness-analytics\u002F04-deployment\u002Findex",[403,404,408,412],{"title":399,"path":400,"stem":401,"sidebar":12},{"title":405,"path":406,"stem":407,"sidebar":12},"Data Products and Monitoring","\u002Fen\u002Fbusiness-analytics\u002F04-deployment\u002F21-data-products-monitoring","en\u002Fbusiness-analytics\u002F04-deployment\u002F21-data-products-monitoring",{"title":409,"path":410,"stem":411,"sidebar":12},"Governance, Fairness and Privacy","\u002Fen\u002Fbusiness-analytics\u002F04-deployment\u002F22-governance-fairness-privacy","en\u002Fbusiness-analytics\u002F04-deployment\u002F22-governance-fairness-privacy",{"title":413,"path":414,"stem":415,"sidebar":12},"Adoption and Business Value","\u002Fen\u002Fbusiness-analytics\u002F04-deployment\u002F23-adoption-value","en\u002Fbusiness-analytics\u002F04-deployment\u002F23-adoption-value",{"title":417,"path":418,"stem":419,"children":420,"sidebar":12},"Appendix and Revision Tools","\u002Fen\u002Fbusiness-analytics\u002Fappendix","en\u002Fbusiness-analytics\u002Fappendix\u002Findex",[421,422,426,430],{"title":417,"path":418,"stem":419,"sidebar":12},{"title":423,"path":424,"stem":425,"sidebar":12},"Formula and Decision Map","\u002Fen\u002Fbusiness-analytics\u002Fappendix\u002F24-formula-map","en\u002Fbusiness-analytics\u002Fappendix\u002F24-formula-map",{"title":427,"path":428,"stem":429,"sidebar":12},"Worked Examples and Pitfalls","\u002Fen\u002Fbusiness-analytics\u002Fappendix\u002F25-worked-examples-pitfalls","en\u002Fbusiness-analytics\u002Fappendix\u002F25-worked-examples-pitfalls",{"title":88,"path":431,"stem":432,"sidebar":12},"\u002Fen\u002Fbusiness-analytics\u002Fappendix\u002F26-reading-map","en\u002Fbusiness-analytics\u002Fappendix\u002F26-reading-map",{"title":434,"path":435,"stem":436,"children":437,"sidebar":12},"Capstone — The Evening Delivery Promise","\u002Fen\u002Fbusiness-analytics\u002Fcapstone","en\u002Fbusiness-analytics\u002Fcapstone\u002Findex",[438],{"title":434,"path":435,"stem":436,"sidebar":12},{"title":440,"path":441,"stem":442,"children":443,"page":280},"Financial Economic Time Series","\u002Fen\u002Ffinancial-economic-time-series","en\u002Ffinancial-economic-time-series",[444,452,460,468,476,484,493,502,511,520,529],{"title":445,"path":446,"stem":447,"children":448,"sidebar":451},"Financial and Economic Time Series — Course Guide","\u002Fen\u002Ffinancial-economic-time-series\u002F00-intro","en\u002Ffinancial-economic-time-series\u002F00-intro\u002Findex",[449],{"title":445,"path":446,"stem":447,"sidebar":450},{"order":71},{"order":71},{"title":453,"path":454,"stem":455,"children":456,"sidebar":459},"Three Versions of Time Series","\u002Fen\u002Ffinancial-economic-time-series\u002F01-bridge","en\u002Ffinancial-economic-time-series\u002F01-bridge\u002Findex",[457],{"title":453,"path":454,"stem":455,"sidebar":458},{"order":204},{"order":204},{"title":461,"path":462,"stem":463,"children":464,"sidebar":467},"Data, Clocks, and Transformations","\u002Fen\u002Ffinancial-economic-time-series\u002F02-data-transformations","en\u002Ffinancial-economic-time-series\u002F02-data-transformations\u002Findex",[465],{"title":461,"path":462,"stem":463,"sidebar":466},{"order":210},{"order":210},{"title":469,"path":470,"stem":471,"children":472,"sidebar":475},"Predictive Regressions and Persistent Predictors","\u002Fen\u002Ffinancial-economic-time-series\u002F03-predictive-regressions","en\u002Ffinancial-economic-time-series\u002F03-predictive-regressions\u002Findex",[473],{"title":469,"path":470,"stem":471,"sidebar":474},{"order":216},{"order":216},{"title":477,"path":478,"stem":479,"children":480,"sidebar":483},"Volatility, Tails, and Financial Risk","\u002Fen\u002Ffinancial-economic-time-series\u002F04-volatility-risk","en\u002Ffinancial-economic-time-series\u002F04-volatility-risk\u002Findex",[481],{"title":477,"path":478,"stem":479,"sidebar":482},{"order":222},{"order":222},{"title":485,"path":486,"stem":487,"children":488,"sidebar":492},"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",[489],{"title":485,"path":486,"stem":487,"sidebar":490},{"order":491},5,{"order":491},{"title":494,"path":495,"stem":496,"children":497,"sidebar":501},"VAR, Structural Identification, and Local Projections","\u002Fen\u002Ffinancial-economic-time-series\u002F06-var-identification","en\u002Ffinancial-economic-time-series\u002F06-var-identification\u002Findex",[498],{"title":494,"path":495,"stem":496,"sidebar":499},{"order":500},6,{"order":500},{"title":503,"path":504,"stem":505,"children":506,"sidebar":510},"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",[507],{"title":503,"path":504,"stem":505,"sidebar":508},{"order":509},7,{"order":509},{"title":512,"path":513,"stem":514,"children":515,"sidebar":519},"Forecast Evaluation for Decisions","\u002Fen\u002Ffinancial-economic-time-series\u002F08-forecast-evaluation","en\u002Ffinancial-economic-time-series\u002F08-forecast-evaluation\u002Findex",[516],{"title":512,"path":513,"stem":514,"sidebar":517},{"order":518},8,{"order":518},{"title":521,"path":522,"stem":523,"children":524,"sidebar":528},"Integrated R Laboratory","\u002Fen\u002Ffinancial-economic-time-series\u002F09-r-laboratory","en\u002Ffinancial-economic-time-series\u002F09-r-laboratory\u002Findex",[525],{"title":521,"path":522,"stem":523,"sidebar":526},{"order":527},9,{"order":527},{"title":530,"path":531,"stem":532,"children":533,"sidebar":537},"Capstones, Data, and Reading Ladder","\u002Fen\u002Ffinancial-economic-time-series\u002F10-capstone-readings","en\u002Ffinancial-economic-time-series\u002F10-capstone-readings\u002Findex",[534],{"title":530,"path":531,"stem":532,"sidebar":535},{"order":536},10,{"order":536},{"title":539,"path":540,"stem":541,"children":542,"page":280},"Intro To Economics","\u002Fen\u002Fintro-to-economics","en\u002Fintro-to-economics",[543,547,551,555,559,563,567,571,575,579,583,587,591],{"title":544,"path":545,"stem":546,"sidebar":12},"Introduction to Economics — Decisions, Markets, and the Macroeconomy","\u002Fen\u002Fintro-to-economics\u002F00-intro","en\u002Fintro-to-economics\u002F00-intro",{"title":548,"path":549,"stem":550,"sidebar":12},"Chapter 1 — Choice, Opportunity Cost, and Trade","\u002Fen\u002Fintro-to-economics\u002F01-foundations","en\u002Fintro-to-economics\u002F01-foundations",{"title":552,"path":553,"stem":554,"sidebar":12},"Chapter 2 — Demand, Supply, Equilibrium, and Welfare","\u002Fen\u002Fintro-to-economics\u002F02-demand-and-supply","en\u002Fintro-to-economics\u002F02-demand-and-supply",{"title":556,"path":557,"stem":558,"sidebar":12},"Chapter 3 — Elasticity, Revenue, and Tax Incidence","\u002Fen\u002Fintro-to-economics\u002F03-elasticity","en\u002Fintro-to-economics\u002F03-elasticity",{"title":560,"path":561,"stem":562,"sidebar":12},"Chapter 4 — Firms, Market Power, and Market Failure","\u002Fen\u002Fintro-to-economics\u002F04-market-structures","en\u002Fintro-to-economics\u002F04-market-structures",{"title":564,"path":565,"stem":566,"sidebar":12},"Chapter 5 — GDP, Income, Wealth, and Welfare","\u002Fen\u002Fintro-to-economics\u002F05-gdp-and-wealth","en\u002Fintro-to-economics\u002F05-gdp-and-wealth",{"title":568,"path":569,"stem":570,"sidebar":12},"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":572,"path":573,"stem":574,"sidebar":12},"Chapter 7 — Productivity, Technology, and Economic Growth","\u002Fen\u002Fintro-to-economics\u002F07-economic-growth","en\u002Fintro-to-economics\u002F07-economic-growth",{"title":576,"path":577,"stem":578,"sidebar":12},"Chapter 8 — Money, Credit, and Banking","\u002Fen\u002Fintro-to-economics\u002F08-money-and-banking","en\u002Fintro-to-economics\u002F08-money-and-banking",{"title":580,"path":581,"stem":582,"sidebar":12},"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":584,"path":585,"stem":586,"sidebar":12},"Chapter 10 — Fiscal Policy, Distribution, and Public Debt","\u002Fen\u002Fintro-to-economics\u002F10-fiscal-policy","en\u002Fintro-to-economics\u002F10-fiscal-policy",{"title":588,"path":589,"stem":590,"sidebar":12},"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":592,"path":593,"stem":594,"sidebar":12},"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":596,"path":597,"stem":598,"children":599,"page":280},"Microeconometrics","\u002Fen\u002Fmicroeconometrics","en\u002Fmicroeconometrics",[600,618,626,644,666,692,716,740,760,780],{"title":601,"path":602,"stem":603,"children":604,"sidebar":12},"0. Causal Questions and Designs","\u002Fen\u002Fmicroeconometrics\u002F00-foundations","en\u002Fmicroeconometrics\u002F00-foundations\u002Findex",[605,606,610,614],{"title":601,"path":602,"stem":603,"sidebar":12},{"title":607,"path":608,"stem":609,"sidebar":12},"Causal Questions and Estimands","\u002Fen\u002Fmicroeconometrics\u002F00-foundations\u002F01-causal-question-estimands","en\u002Fmicroeconometrics\u002F00-foundations\u002F01-causal-question-estimands",{"title":611,"path":612,"stem":613,"sidebar":12},"Potential Outcomes and Experiments","\u002Fen\u002Fmicroeconometrics\u002F00-foundations\u002F02-potential-outcomes-experiments","en\u002Fmicroeconometrics\u002F00-foundations\u002F02-potential-outcomes-experiments",{"title":615,"path":616,"stem":617,"sidebar":12},"Causal Diagrams and Controls","\u002Fen\u002Fmicroeconometrics\u002F00-foundations\u002F03-dags-controls","en\u002Fmicroeconometrics\u002F00-foundations\u002F03-dags-controls",{"title":619,"path":620,"stem":621,"children":622,"sidebar":625},"Microeconometrics — Designing Credible Counterfactuals","\u002Fen\u002Fmicroeconometrics\u002F00-index","en\u002Fmicroeconometrics\u002F00-index",[623],{"title":619,"path":620,"stem":621,"sidebar":624},{"order":71},{"order":71},{"title":627,"path":628,"stem":629,"children":630,"sidebar":12},"1. Regression and Inference","\u002Fen\u002Fmicroeconometrics\u002F01-regression","en\u002Fmicroeconometrics\u002F01-regression\u002Findex",[631,632,636,640],{"title":627,"path":628,"stem":629,"sidebar":12},{"title":633,"path":634,"stem":635,"sidebar":12},"OLS as a Projection","\u002Fen\u002Fmicroeconometrics\u002F01-regression\u002F04-ols-projection","en\u002Fmicroeconometrics\u002F01-regression\u002F04-ols-projection",{"title":637,"path":638,"stem":639,"sidebar":12},"FWL, Selection and Controls","\u002Fen\u002Fmicroeconometrics\u002F01-regression\u002F05-fwl-selection-controls","en\u002Fmicroeconometrics\u002F01-regression\u002F05-fwl-selection-controls",{"title":641,"path":642,"stem":643,"sidebar":12},"Inference and Clustering","\u002Fen\u002Fmicroeconometrics\u002F01-regression\u002F06-inference-clustering","en\u002Fmicroeconometrics\u002F01-regression\u002F06-inference-clustering",{"title":645,"path":646,"stem":647,"children":648,"sidebar":12},"2. Instruments and Panel Data","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel","en\u002Fmicroeconometrics\u002F02-iv-panel\u002Findex",[649,650,654,658,662],{"title":645,"path":646,"stem":647,"sidebar":12},{"title":651,"path":652,"stem":653,"sidebar":12},"Instrumental Variables","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel\u002F07-iv-identification","en\u002Fmicroeconometrics\u002F02-iv-panel\u002F07-iv-identification",{"title":655,"path":656,"stem":657,"sidebar":12},"Weak Instruments and LATE","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel\u002F08-weak-iv-late","en\u002Fmicroeconometrics\u002F02-iv-panel\u002F08-weak-iv-late",{"title":659,"path":660,"stem":661,"sidebar":12},"Panel Fixed Effects","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel\u002F09-panel-fixed-effects","en\u002Fmicroeconometrics\u002F02-iv-panel\u002F09-panel-fixed-effects",{"title":663,"path":664,"stem":665,"sidebar":12},"Dynamic Panels and Limits","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel\u002F10-dynamic-panel","en\u002Fmicroeconometrics\u002F02-iv-panel\u002F10-dynamic-panel",{"title":667,"path":668,"stem":669,"children":670,"sidebar":12},"3. Policy Evaluation Designs","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs","en\u002Fmicroeconometrics\u002F03-policy-designs\u002Findex",[671,672,676,680,684,688],{"title":667,"path":668,"stem":669,"sidebar":12},{"title":673,"path":674,"stem":675,"sidebar":12},"Difference-in-Differences","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F11-did-core","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F11-did-core",{"title":677,"path":678,"stem":679,"sidebar":12},"Staggered DID and Event Studies","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F12-staggered-event-studies","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F12-staggered-event-studies",{"title":681,"path":682,"stem":683,"sidebar":12},"Regression Discontinuity","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F13-rdd","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F13-rdd",{"title":685,"path":686,"stem":687,"sidebar":12},"Matching, Weighting and Overlap","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F14-matching-weighting","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F14-matching-weighting",{"title":689,"path":690,"stem":691,"sidebar":12},"Synthetic Control","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F15-synthetic-control","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F15-synthetic-control",{"title":693,"path":694,"stem":695,"children":696,"sidebar":715},"Module 4 — Choice and Limited Outcomes","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002Findex",[697,699,703,707,711],{"title":693,"path":694,"stem":695,"sidebar":698},{"order":222},{"title":700,"path":701,"stem":702,"sidebar":12},"Binary Choice","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F16-binary-choice","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F16-binary-choice",{"title":704,"path":705,"stem":706,"sidebar":12},"Multinomial and Ordered Choice","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F17-multinomial-choice","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F17-multinomial-choice",{"title":708,"path":709,"stem":710,"sidebar":12},"Count Outcomes","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F18-count-outcomes","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F18-count-outcomes",{"title":712,"path":713,"stem":714,"sidebar":12},"Censoring, Truncation and Selection","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F19-censoring-selection","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F19-censoring-selection",{"order":222},{"title":717,"path":718,"stem":719,"children":720,"sidebar":739},"Module 5 — Modern Causal Analysis","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal","en\u002Fmicroeconometrics\u002F05-modern-causal\u002Findex",[721,723,727,731,735],{"title":717,"path":718,"stem":719,"sidebar":722},{"order":491},{"title":724,"path":725,"stem":726,"sidebar":12},"Double Machine Learning","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal\u002F20-dml","en\u002Fmicroeconometrics\u002F05-modern-causal\u002F20-dml",{"title":728,"path":729,"stem":730,"sidebar":12},"Heterogeneity and Policy Learning","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal\u002F21-heterogeneity-policy","en\u002Fmicroeconometrics\u002F05-modern-causal\u002F21-heterogeneity-policy",{"title":732,"path":733,"stem":734,"sidebar":12},"Sensitivity and Partial Identification","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal\u002F22-sensitivity-partial-id","en\u002Fmicroeconometrics\u002F05-modern-causal\u002F22-sensitivity-partial-id",{"title":736,"path":737,"stem":738,"sidebar":12},"External Validity and Transport","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal\u002F23-external-validity","en\u002Fmicroeconometrics\u002F05-modern-causal\u002F23-external-validity",{"order":491},{"title":741,"path":742,"stem":743,"children":744,"sidebar":759},"Module 6 — From Data to Auditable Evidence","\u002Fen\u002Fmicroeconometrics\u002F06-workflow","en\u002Fmicroeconometrics\u002F06-workflow\u002Findex",[745,747,751,755],{"title":741,"path":742,"stem":743,"sidebar":746},{"order":500},{"title":748,"path":749,"stem":750,"sidebar":12},"Data Provenance","\u002Fen\u002Fmicroeconometrics\u002F06-workflow\u002F24-data-provenance","en\u002Fmicroeconometrics\u002F06-workflow\u002F24-data-provenance",{"title":752,"path":753,"stem":754,"sidebar":12},"Reproducibility and Reporting","\u002Fen\u002Fmicroeconometrics\u002F06-workflow\u002F25-reproducibility-reporting","en\u002Fmicroeconometrics\u002F06-workflow\u002F25-reproducibility-reporting",{"title":756,"path":757,"stem":758,"sidebar":12},"Paper and Evidence Audit","\u002Fen\u002Fmicroeconometrics\u002F06-workflow\u002F26-paper-audit","en\u002Fmicroeconometrics\u002F06-workflow\u002F26-paper-audit",{"order":500},{"title":761,"path":762,"stem":763,"children":764,"sidebar":779},"Appendix — Revision and Evidence Map","\u002Fen\u002Fmicroeconometrics\u002Fappendix","en\u002Fmicroeconometrics\u002Fappendix\u002Findex",[765,767,771,775],{"title":761,"path":762,"stem":763,"sidebar":766},{"order":518},{"title":768,"path":769,"stem":770,"sidebar":12},"Formula and Design Map","\u002Fen\u002Fmicroeconometrics\u002Fappendix\u002F27-formula-design-map","en\u002Fmicroeconometrics\u002Fappendix\u002F27-formula-design-map",{"title":772,"path":773,"stem":774,"sidebar":12},"Ten Worked Microeconometric Pitfalls","\u002Fen\u002Fmicroeconometrics\u002Fappendix\u002F28-worked-pitfalls","en\u002Fmicroeconometrics\u002Fappendix\u002F28-worked-pitfalls",{"title":776,"path":777,"stem":778,"sidebar":12},"Reading and Software 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Duality, and Revealed Preference","\u002Fen\u002Fmicroeconomics\u002F01-fundations","en\u002Fmicroeconomics\u002F01-fundations\u002Findex",[804],{"title":800,"path":801,"stem":802,"sidebar":12},{"title":806,"path":807,"stem":808,"children":809,"sidebar":12},"Module 2 — Comparative Statics and Welfare Measurement","\u002Fen\u002Fmicroeconomics\u002F02-comparative-statics","en\u002Fmicroeconomics\u002F02-comparative-statics\u002Findex",[810],{"title":806,"path":807,"stem":808,"sidebar":12},{"title":812,"path":813,"stem":814,"children":815,"sidebar":12},"Module 3 — Choice under Risk and Insurance","\u002Fen\u002Fmicroeconomics\u002F03-uncertainty","en\u002Fmicroeconomics\u002F03-uncertainty\u002Findex",[816],{"title":812,"path":813,"stem":814,"sidebar":12},{"title":818,"path":819,"stem":820,"children":821,"sidebar":12},"Module 4 — General Equilibrium and Welfare","\u002Fen\u002Fmicroeconomics\u002F04-general-equilibrium","en\u002Fmicroeconomics\u002F04-general-equilibrium\u002Findex",[822],{"title":818,"path":819,"stem":820,"sidebar":12},{"title":824,"path":825,"stem":826,"children":827,"sidebar":12},"Module 5 — Static, Dynamic, and Repeated Games","\u002Fen\u002Fmicroeconomics\u002F05-game-theory","en\u002Fmicroeconomics\u002F05-game-theory\u002Findex",[828],{"title":824,"path":825,"stem":826,"sidebar":12},{"title":830,"path":831,"stem":832,"children":833,"sidebar":12},"Module 6 — Oligopoly, Entry, and Algorithmic Pricing","\u002Fen\u002Fmicroeconomics\u002F06-oligopoly","en\u002Fmicroeconomics\u002F06-oligopoly\u002Findex",[834],{"title":830,"path":831,"stem":832,"sidebar":12},{"title":836,"path":837,"stem":838,"children":839,"sidebar":12},"Module 7 — Information Economics and Contracts","\u002Fen\u002Fmicroeconomics\u002F07-information-economics","en\u002Fmicroeconomics\u002F07-information-economics\u002Findex",[840],{"title":836,"path":837,"stem":838,"sidebar":12},{"title":842,"path":843,"stem":844,"children":845,"sidebar":12},"Module 8 — Mechanism Design and Auctions","\u002Fen\u002Fmicroeconomics\u002F08-mechanism-design","en\u002Fmicroeconomics\u002F08-mechanism-design\u002Findex",[846],{"title":842,"path":843,"stem":844,"sidebar":12},{"title":848,"path":849,"stem":850,"children":851,"sidebar":12},"Module 9 — Behavioural and Experimental Microeconomics","\u002Fen\u002Fmicroeconomics\u002F09-behavioural-economics","en\u002Fmicroeconomics\u002F09-behavioural-economics\u002Findex",[852],{"title":848,"path":849,"stem":850,"sidebar":12},{"title":854,"path":855,"stem":856,"children":857,"sidebar":12},"Module 10 — Externalities, Public Goods, and Collective Action","\u002Fen\u002Fmicroeconomics\u002F10-externalities-public-goods","en\u002Fmicroeconomics\u002F10-externalities-public-goods\u002Findex",[858],{"title":854,"path":855,"stem":856,"sidebar":12},{"title":860,"path":861,"stem":862,"children":863,"sidebar":12},"Module 11 — Matching and Market Design","\u002Fen\u002Fmicroeconomics\u002F11-market-design","en\u002Fmicroeconomics\u002F11-market-design\u002Findex",[864],{"title":860,"path":861,"stem":862,"sidebar":12},{"title":866,"path":867,"stem":868,"children":869,"sidebar":12},"Module 12 — Integrated Microeconomic Design Studio","\u002Fen\u002Fmicroeconomics\u002F12-review","en\u002Fmicroeconomics\u002F12-review\u002Findex",[870],{"title":866,"path":867,"stem":868,"sidebar":12},{"title":872,"path":873,"stem":874,"children":875,"sidebar":12},"Playground","\u002Fen\u002Fplayground","en\u002Fplayground\u002Findex",[876,877,881,885,889,893],{"title":872,"path":873,"stem":874,"sidebar":12},{"title":878,"path":879,"stem":880,"sidebar":12},"Typst Plugin Playground","\u002Fen\u002Fplayground\u002F01-typstex","en\u002Fplayground\u002F01-typstex",{"title":882,"path":883,"stem":884,"sidebar":12},"Citation Plugin Test","\u002Fen\u002Fplayground\u002F02-citation","en\u002Fplayground\u002F02-citation",{"title":886,"path":887,"stem":888,"sidebar":12},"Pyodide Playground","\u002Fen\u002Fplayground\u002F03-pyodide","en\u002Fplayground\u002F03-pyodide",{"title":890,"path":891,"stem":892,"sidebar":12},"WebR Playground","\u002Fen\u002Fplayground\u002F04-webr","en\u002Fplayground\u002F04-webr",{"title":894,"path":895,"stem":896,"sidebar":12},"Chart.js Visualizations","\u002Fen\u002Fplayground\u002F05-chartjs","en\u002Fplayground\u002F05-chartjs",{"title":898,"path":899,"stem":900,"children":901,"page":280},"Statistics For Insurance","\u002Fen\u002Fstatistics-for-insurance","en\u002Fstatistics-for-insurance",[902,910,938,971,999,1027,1040],{"title":903,"path":904,"stem":905,"children":906,"sidebar":909},"Statistics for General Insurance","\u002Fen\u002Fstatistics-for-insurance\u002F01-intro","en\u002Fstatistics-for-insurance\u002F01-intro\u002Findex",[907],{"title":903,"path":904,"stem":905,"sidebar":908},{"order":71},{"order":71},{"title":911,"path":912,"stem":913,"children":914,"sidebar":937},"Claims Development and Reserving","\u002Fen\u002Fstatistics-for-insurance\u002F02-chain-ladder","en\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002Findex",[915,917,922,927,932],{"title":911,"path":912,"stem":913,"sidebar":916},{"order":71},{"title":918,"path":919,"stem":920,"sidebar":921},"Basic Chain Ladder","\u002Fen\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F01-basic-chain","en\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F01-basic-chain",{"order":204},{"title":923,"path":924,"stem":925,"sidebar":926},"Frequency–Severity Reserving","\u002Fen\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F02-average-per-claim","en\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F02-average-per-claim",{"order":210},{"title":928,"path":929,"stem":930,"sidebar":931},"Bornhuetter–Ferguson Method","\u002Fen\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F03-b-f-method","en\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F03-b-f-method",{"order":216},{"title":933,"path":934,"stem":935,"sidebar":936},"Uncertainty and Diagnostics","\u002Fen\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F04-uncertainty-diagnostics","en\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F04-uncertainty-diagnostics",{"order":222},{"order":71},{"title":939,"path":940,"stem":941,"children":942,"sidebar":970},"Frequency and Severity Models","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002Findex",[943,945,950,955,960,965],{"title":939,"path":940,"stem":941,"sidebar":944},{"order":71},{"title":946,"path":947,"stem":948,"sidebar":949},"Core Severity Models","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist\u002F01-loss-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002F01-loss-dist",{"order":204},{"title":951,"path":952,"stem":953,"sidebar":954},"Tail Models and Extreme Values","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist\u002F02-more-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002F02-more-dist",{"order":210},{"title":956,"path":957,"stem":958,"sidebar":959},"Claim Count Models","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist\u002F03-case-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002F03-case-dist",{"order":216},{"title":961,"path":962,"stem":963,"sidebar":964},"Fitting and Validating Loss Models","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist\u002F04-fit-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002F04-fit-dist",{"order":222},{"title":966,"path":967,"stem":968,"sidebar":969},"Mixtures and Heterogeneity","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist\u002F05-mix-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002F05-mix-dist",{"order":491},{"order":71},{"title":972,"path":973,"stem":974,"children":975,"sidebar":998},"Reinsurance as a Loss Transformation","\u002Fen\u002Fstatistics-for-insurance\u002F04-reinsurance","en\u002Fstatistics-for-insurance\u002F04-reinsurance\u002Findex",[976,978,983,988,993],{"title":972,"path":973,"stem":974,"sidebar":977},{"order":71},{"title":979,"path":980,"stem":981,"sidebar":982},"Proportional Reinsurance","\u002Fen\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F01-proportional","en\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F01-proportional",{"order":204},{"title":984,"path":985,"stem":986,"sidebar":987},"Excess-of-Loss Reinsurance","\u002Fen\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F02-excess","en\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F02-excess",{"order":210},{"title":989,"path":990,"stem":991,"sidebar":992},"Inflation and Layer Erosion","\u002Fen\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F03-inflation","en\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F03-inflation",{"order":216},{"title":994,"path":995,"stem":996,"sidebar":997},"Reinsurance Decision Lab","\u002Fen\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F04-examples","en\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F04-examples",{"order":222},{"order":71},{"title":1000,"path":1001,"stem":1002,"children":1003,"sidebar":1026},"Aggregate Risk and Capital","\u002Fen\u002Fstatistics-for-insurance\u002F05-risk-theory","en\u002Fstatistics-for-insurance\u002F05-risk-theory\u002Findex",[1004,1006,1011,1016,1021],{"title":1000,"path":1001,"stem":1002,"sidebar":1005},{"order":71},{"title":1007,"path":1008,"stem":1009,"sidebar":1010},"Collective Risk Model","\u002Fen\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F01-collective","en\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F01-collective",{"order":204},{"title":1012,"path":1013,"stem":1014,"sidebar":1015},"Individual Risk Model","\u002Fen\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F02-individual","en\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F02-individual",{"order":210},{"title":1017,"path":1018,"stem":1019,"sidebar":1020},"Aggregate Risk Computation Lab","\u002Fen\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F03-examples","en\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F03-examples",{"order":216},{"title":1022,"path":1023,"stem":1024,"sidebar":1025},"Tail Risk, Dependence, and Capital","\u002Fen\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F04-tail-capital","en\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F04-tail-capital",{"order":222},{"order":71},{"title":1028,"path":1029,"stem":1030,"children":1031,"sidebar":1039},"Surplus and Ruin Theory","\u002Fen\u002Fstatistics-for-insurance\u002F06-ruin-theory","en\u002Fstatistics-for-insurance\u002F06-ruin-theory\u002Findex",[1032,1034],{"title":1028,"path":1029,"stem":1030,"sidebar":1033},{"order":71},{"title":1035,"path":1036,"stem":1037,"sidebar":1038},"Finite-Time Ruin Simulation","\u002Fen\u002Fstatistics-for-insurance\u002F06-ruin-theory\u002F01-finite-time-simulation","en\u002Fstatistics-for-insurance\u002F06-ruin-theory\u002F01-finite-time-simulation",{"order":204},{"order":71},{"title":1041,"path":1042,"stem":1043,"children":1044,"sidebar":1047},"Portfolio Risk Capstone","\u002Fen\u002Fstatistics-for-insurance\u002F07-capstone","en\u002Fstatistics-for-insurance\u002F07-capstone\u002Findex",[1045],{"title":1041,"path":1042,"stem":1043,"sidebar":1046},{"order":71},{"order":71},{"title":1049,"path":1050,"stem":1051,"children":1052,"page":280},"Time Series","\u002Fen\u002Ftime-series","en\u002Ftime-series",[1053,1066,1074,1082,1090,1098,1106,1114,1142],{"title":1054,"path":1055,"stem":1056,"children":1057,"sidebar":1065},"Classical Time Series — Course Guide","\u002Fen\u002Ftime-series\u002F00-intro","en\u002Ftime-series\u002F00-intro\u002Findex",[1058,1060],{"title":1054,"path":1055,"stem":1056,"sidebar":1059},{"order":71},{"title":1061,"path":1062,"stem":1063,"sidebar":1064},"Preparation — Stationarity in 30 Minutes","\u002Fen\u002Ftime-series\u002F00-intro\u002F01-stationary","en\u002Ftime-series\u002F00-intro\u002F01-stationary",{"order":204},{"order":71},{"title":1067,"path":1068,"stem":1069,"children":1070,"sidebar":1073},"Module 1 — Processes, Dependence, and Stationarity","\u002Fen\u002Ftime-series\u002F01-stochastic-process","en\u002Ftime-series\u002F01-stochastic-process\u002Findex",[1071],{"title":1067,"path":1068,"stem":1069,"sidebar":1072},{"order":204},{"order":204},{"title":1075,"path":1076,"stem":1077,"children":1078,"sidebar":1081},"Module 2 — ARMA, ARIMA, and Model Identification","\u002Fen\u002Ftime-series\u002F02-arma","en\u002Ftime-series\u002F02-arma\u002Findex",[1079],{"title":1075,"path":1076,"stem":1077,"sidebar":1080},{"order":210},{"order":210},{"title":1083,"path":1084,"stem":1085,"children":1086,"sidebar":1089},"Module 3 — Linear Prediction and State-Space Recursions","\u002Fen\u002Ftime-series\u002F03-prediction","en\u002Ftime-series\u002F03-prediction\u002Findex",[1087],{"title":1083,"path":1084,"stem":1085,"sidebar":1088},{"order":216},{"order":216},{"title":1091,"path":1092,"stem":1093,"children":1094,"sidebar":1097},"Module 4 — Estimation, Likelihood, and Inference","\u002Fen\u002Ftime-series\u002F04-estimation","en\u002Ftime-series\u002F04-estimation\u002Findex",[1095],{"title":1091,"path":1092,"stem":1093,"sidebar":1096},{"order":222},{"order":222},{"title":1099,"path":1100,"stem":1101,"children":1102,"sidebar":1105},"Module 5 — Systems, Seasonality, and Cointegration","\u002Fen\u002Ftime-series\u002F05-multi-ar","en\u002Ftime-series\u002F05-multi-ar\u002Findex",[1103],{"title":1099,"path":1100,"stem":1101,"sidebar":1104},{"order":491},{"order":491},{"title":1107,"path":1108,"stem":1109,"children":1110,"sidebar":1113},"Module 6 — Spectral Analysis, Cycles, and Filters","\u002Fen\u002Ftime-series\u002F06-spectral-analysis","en\u002Ftime-series\u002F06-spectral-analysis\u002Findex",[1111],{"title":1107,"path":1108,"stem":1109,"sidebar":1112},{"order":500},{"order":500},{"title":1115,"path":1116,"stem":1117,"children":1118,"sidebar":1141},"R Matrix Laboratory","\u002Fen\u002Ftime-series\u002F07-r-implementation","en\u002Ftime-series\u002F07-r-implementation\u002Findex",[1119,1121,1126,1131,1136],{"title":1115,"path":1116,"stem":1117,"sidebar":1120},{"order":509},{"title":1122,"path":1123,"stem":1124,"sidebar":1125},"R Matrix Lab 1 — Covariance Geometry","\u002Fen\u002Ftime-series\u002F07-r-implementation\u002F01-covariance-matrices","en\u002Ftime-series\u002F07-r-implementation\u002F01-covariance-matrices",{"order":204},{"title":1127,"path":1128,"stem":1129,"sidebar":1130},"R Matrix Lab 2 — AR Recursions and Yule–Walker Equations","\u002Fen\u002Ftime-series\u002F07-r-implementation\u002F02-ar-recursions","en\u002Ftime-series\u002F07-r-implementation\u002F02-ar-recursions",{"order":210},{"title":1132,"path":1133,"stem":1134,"sidebar":1135},"R Matrix Lab 3 — Prediction and Gaussian Likelihood","\u002Fen\u002Ftime-series\u002F07-r-implementation\u002F03-prediction-likelihood","en\u002Ftime-series\u002F07-r-implementation\u002F03-prediction-likelihood",{"order":216},{"title":1137,"path":1138,"stem":1139,"sidebar":1140},"R Matrix Lab 4 — State Space and Kalman Filtering","\u002Fen\u002Ftime-series\u002F07-r-implementation\u002F04-state-space","en\u002Ftime-series\u002F07-r-implementation\u002F04-state-space",{"order":222},{"order":509},{"title":1143,"path":1144,"stem":1145,"children":1146,"sidebar":1169},"Optional Python Appendix — Empirical Forecasting","\u002Fen\u002Ftime-series\u002F08-python-implementation","en\u002Ftime-series\u002F08-python-implementation\u002Findex",[1147,1149,1154,1159,1164],{"title":1143,"path":1144,"stem":1145,"sidebar":1148},{"order":518},{"title":1150,"path":1151,"stem":1152,"sidebar":1153},"Optional Python Lab 1 — Explore Before Modeling","\u002Fen\u002Ftime-series\u002F08-python-implementation\u002F01-exploration","en\u002Ftime-series\u002F08-python-implementation\u002F01-exploration",{"order":204},{"title":1155,"path":1156,"stem":1157,"sidebar":1158},"Optional Python Lab 2 — Diagnose Stationarity","\u002Fen\u002Ftime-series\u002F08-python-implementation\u002F02-stationarity","en\u002Ftime-series\u002F08-python-implementation\u002F02-stationarity",{"order":210},{"title":1160,"path":1161,"stem":1162,"sidebar":1163},"Optional Python Lab 3 — Fit and Audit ARMA Errors","\u002Fen\u002Ftime-series\u002F08-python-implementation\u002F03-arma-fitting","en\u002Ftime-series\u002F08-python-implementation\u002F03-arma-fitting",{"order":216},{"title":1165,"path":1166,"stem":1167,"sidebar":1168},"Optional Python Lab 4 — Forecast, Backtest, and 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Statistics","\u002Fzh\u002Fprob-and-stats\u002F02-statistics","zh\u002Fprob-and-stats\u002F02-statistics",[1979,1987,1995,2003,2011,2019,2027],{"title":1980,"path":1981,"stem":1982,"children":1983,"sidebar":1986},"第六章：抽样分布","\u002Fzh\u002Fprob-and-stats\u002F02-statistics\u002F01-sampling","zh\u002Fprob-and-stats\u002F02-statistics\u002F01-sampling\u002Findex",[1984],{"title":1980,"path":1981,"stem":1982,"sidebar":1985},{"order":509},{"order":509},{"title":1988,"path":1989,"stem":1990,"children":1991,"sidebar":1994},"第七章：区间估计","\u002Fzh\u002Fprob-and-stats\u002F02-statistics\u002F02-interval-estimation","zh\u002Fprob-and-stats\u002F02-statistics\u002F02-interval-estimation\u002Findex",[1992],{"title":1988,"path":1989,"stem":1990,"sidebar":1993},{"order":518},{"order":518},{"title":1996,"path":1997,"stem":1998,"children":1999,"sidebar":2002},"第八章：点估计理论","\u002Fzh\u002Fprob-and-stats\u002F02-statistics\u002F03-point-estimation","zh\u002Fprob-and-stats\u002F02-statistics\u002F03-point-estimation\u002Findex",[2000],{"title":1996,"path":1997,"stem":1998,"sidebar":2001},{"order":527},{"order":527},{"title":2004,"path":2005,"stem":2006,"children":2007,"sidebar":2010},"第九章：点估计方法","\u002Fzh\u002Fprob-and-stats\u002F02-statistics\u002F04-pe-method","zh\u002Fprob-and-stats\u002F02-statistics\u002F04-pe-method\u002Findex",[2008],{"title":2004,"path":2005,"stem":2006,"sidebar":2009},{"order":536},{"order":536},{"title":2012,"path":2013,"stem":2014,"children":2015,"sidebar":2018},"第十章：假设检验原理","\u002Fzh\u002Fprob-and-stats\u002F02-statistics\u002F05-hypothesis","zh\u002Fprob-and-stats\u002F02-statistics\u002F05-hypothesis\u002Findex",[2016],{"title":2012,"path":2013,"stem":2014,"sidebar":2017},{"order":1307},{"order":1307},{"title":2020,"path":2021,"stem":2022,"children":2023,"sidebar":2026},"第十一章：常用检验方法与选择","\u002Fzh\u002Fprob-and-stats\u002F02-statistics\u002F06-hypothesis-method","zh\u002Fprob-and-stats\u002F02-statistics\u002F06-hypothesis-method\u002Findex",[2024],{"title":2020,"path":2021,"stem":2022,"sidebar":2025},{"order":1313},{"order":1313},{"title":2028,"path":2029,"stem":2030,"children":2031,"sidebar":2034},"第十二章：Bootstrap 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Alpha 策略全流程","\u002Fzh\u002Fquant\u002F09-case-study","zh\u002Fquant\u002F09-case-study",{"order":527},{"title":2100,"path":2101,"stem":2102,"sidebar":2103},"量化投资文献与软件图谱","\u002Fzh\u002Fquant\u002F10-reading-software-map","zh\u002Fquant\u002F10-reading-software-map",{"order":536},{"path":199},{"id":2106,"title":1368,"body":2107,"description":2447,"extension":2448,"features":12,"hero":12,"layout":12,"locale":12,"meta":2449,"navigation":12,"path":1369,"published":2450,"seo":2451,"sidebar":2452,"stem":1370,"__hash__":2453},"docs\u002Fzh\u002Faccounting\u002Ffoundation\u002Findex.md",{"type":2108,"value":2109,"toc":2439},"minimark",[2110,2113,2117,2120,2124,2176,2179,2182,2198,2219,2222,2225,2363,2366,2369,2372,2387,2390,2393,2405,2408,2411,2434],[2111,2112],"span",{"id":1368},[2114,2115,2116],"p",{},"如果你会计算百分比，但还没有学过会计，可以从这里开始。这组笔记围绕几个反复出现的问题展开：业务应在哪个期间记录，账户余额怎样变化，利润为什么不同于现金，以及面对不同决策应选用什么数字。每个问题都配有总结、例题和进一步阅读的入口。",[2114,2118,2119],{},"先读概念总结建立整体认识，再通过例题看清推导过程。计算器和纸笔，或电子表格，就足以完成计算。Python 单元用于尝试改变假设；不运行代码，也能根据正文和表格理解结论。",[2121,2122,2123],"h2",{"id":2123},"先串起几个核心概念",[2125,2126,2127,2140],"table",{},[2128,2129,2130],"thead",{},[2131,2132,2133,2137],"tr",{},[2134,2135,2136],"th",{},"核心概念",[2134,2138,2139],{},"它解释了什么",[2141,2142,2143,2152,2160,2168],"tbody",{},[2131,2144,2145,2149],{},[2146,2147,2148],"td",{},"一项业务可能影响多个账户，也可能跨越多个期间",[2146,2150,2151],{},"分录为什么平衡，以及平衡之后为什么仍可能需要调整",[2131,2153,2154,2157],{},[2146,2155,2156],{},"余额描述一个时点，流量描述一段期间的变化",[2146,2158,2159],{},"利润、资本和财务状况怎样通过同一套记录相互联系",[2131,2161,2162,2165],{},[2146,2163,2164],{},"确认与收付款可能发生在不同时间",[2146,2166,2167],{},"为什么企业有利润，却仍然可能需要融资",[2131,2169,2170,2173],{},[2146,2171,2172],{},"比较需要明确目的，并选择合适的基准",[2146,2174,2175],{},"比率、边际贡献、差异和 NPV 分别能回答什么问题",[2121,2177,2178],{"id":2178},"入门诊断",[2114,2180,2181],{},"先用自己的话解释，再展开反馈比较推理过程。",[2183,2184,2185,2189,2192,2195],"ol",{},[2186,2187,2188],"li",{},"商店收到 £900，下个月才提供对应服务。现在什么增加了？",[2186,2190,2191],{},"收回上月已完成销售的 £700 欠款，会再产生收入吗？",[2186,2193,2194],{},"用现金 £6,000 购买设备，是否全部计入本月费用？",[2186,2196,2197],{},"尚未收款的供应商和商店业主，各自会要求查看什么信息？",[2199,2200,2202,2216],"legacy-spoiler",{"title":2201},"参考反馈",[2183,2203,2204,2207,2210,2213],{},[2186,2205,2206],{},"现金和提供服务的义务同时增加，尚不能因为收款就确认已履约的收入。",[2186,2208,2209],{},"现金增加、应收账款减少，不会因此产生第二笔销售收入。",[2186,2211,2212],{},"初始时设备资产替代现金资产；折旧将应折旧金额分配到使用期间，不是再付一次设备款。",[2186,2214,2215],{},"供应商关心付款时间和偿付能力，业主还关心盈利与经营前景。仅凭银行余额无法回答这些问题。",[2114,2217,2218],{},"如果还容易混淆收款与收入、付款与费用，可以从下方的记录与调整笔记开始。如果已经理解这些区别，就通过例题寻找下一步想深入的问题。",[2121,2220,2221],{"id":2221},"按知识关系阅读",[2114,2223,2224],{},"下表按照概念之间的依赖关系组织。你可以依次阅读，也可以在后面的例题暴露出疑问时，返回相应专题查阅。",[2125,2226,2227,2240],{},[2128,2228,2229],{},[2131,2230,2231,2234,2237],{},[2134,2232,2233],{},"主题与要点",[2134,2235,2236],{},"阅读和例题",[2134,2238,2239],{},"值得继续追问的问题",[2141,2241,2242,2262,2279,2295,2313,2329,2346],{},[2131,2243,2244,2247,2259],{},[2146,2245,2246],{},"记录：先说明业务，再选择账户",[2146,2248,2249,2254,2255],{},[2250,2251,2253],"a",{"href":2252},"..\u002Ffinancial-accounting\u002F01-foundations\u002F","基础模块","、",[2250,2256,2258],{"href":2257},"..\u002Ffinancial-accounting\u002F02-recording-transactions\u002F04-double-entry-dr-cr","复式记账",[2146,2260,2261],{},"借贷相等时，业务仍可能记错吗？",[2131,2263,2264,2267,2276],{},[2146,2265,2266],{},"调整：分清已记金额与应有余额",[2146,2268,2269,2254,2272],{},[2250,2270,1270],{"href":2271},"..\u002Ffinancial-accounting\u002F02-recording-transactions\u002F05-accounting-cycle",[2250,2273,2275],{"href":2274},".\u002F01-adjustments-to-statements","完整报表例题",[2146,2277,2278],{},"为什么有些调整改变利润，却不改变现金？",[2131,2280,2281,2284,2292],{},[2146,2282,2283],{},"报表：从不同角度呈现同一套记录",[2146,2285,2286,2254,2289],{},[2250,2287,2288],{"href":2274},"利润与资本例题",[2250,2290,1329],{"href":2291},"..\u002Ffinancial-accounting\u002F04-reporting-cash\u002F06-financial-statements",[2146,2293,2294],{},"为什么利润进入权益，而业主提款不属于费用？",[2131,2296,2297,2300,2310],{},[2146,2298,2299],{},"分析：同时看指标和指标内部的构成",[2146,2301,2302,2254,2306],{},[2250,2303,2305],{"href":2304},"..\u002Ffinancial-accounting\u002F04-reporting-cash\u002F14-cash-control","现金与内部控制",[2250,2307,2309],{"href":2308},"..\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F15-ratio-analysis","比率分析",[2146,2311,2312],{},"流动比率不变，流动性是否仍可能变化？",[2131,2314,2315,2318,2326],{},[2146,2316,2317],{},"成本：贡献先弥补固定成本，再形成利润",[2146,2319,2320,2254,2323],{},[2250,2321,1405],{"href":2322},"..\u002Fmanagement-accounting\u002F01-cost-foundations\u002F16-cost-concepts",[2250,2324,1431],{"href":2325},"..\u002Fmanagement-accounting\u002F02-planning-control\u002F18-cvp-analysis",[2146,2327,2328],{},"保本计算有用的前提是什么？",[2131,2330,2331,2334,2343],{},[2146,2332,2333],{},"预算：分清时间、业务量和成本表现",[2146,2335,2336,2254,2340],{},[2250,2337,2339],{"href":2338},".\u002F02-cash-budget","现金预算例题",[2250,2341,1437],{"href":2342},"..\u002Fmanagement-accounting\u002F02-planning-control\u002F20-budgeting-variances",[2146,2344,2345],{},"成本总额上升，是因为多生产了，还是相同产量下成本发生了偏差？",[2131,2347,2348,2351,2360],{},[2146,2349,2350],{},"投资：把未来增量现金流折算到同一时点",[2146,2352,2353,2254,2356],{},[2250,2354,1463],{"href":2355},"..\u002Fmanagement-accounting\u002F03-decisions-investment\u002F23-capital-budgeting",[2250,2357,2359],{"href":2358},".\u002F03-decision-workshop","决策比较例题",[2146,2361,2362],{},"哪项预测或时间假设的变化可能使方案排名反转？",[2121,2364,2365],{"id":2365},"怎样读一个例题",[2114,2367,2368],{},"先读业务事实，再确定这项计算要解释什么。跟随底稿时，留意哪些金额是余额，哪些是期间变化，哪些来自假设。理解这些关系后，即使例题更换了数字，也能重新推导。",[2114,2370,2371],{},"复习时可以暂时遮住解答，先解释下一步为什么这样处理，再动手计算。如果结果不同，检查差异来自分类、时间还是算术。把错误原因写成一句话，比只抄下正确合计更有帮助。",[2114,2373,2374,2375,2378,2379,2382,2383,2386],{},"三个基础例题各有侧重：",[2250,2376,2377],{"href":2274},"从记录到报表","贯通一套账户，",[2250,2380,2381],{"href":2338},"现金预算","追踪收付款日期，",[2250,2384,2385],{"href":2358},"决策比较","解释为什么要根据问题选择指标。它们使用相互独立的虚构数据。",[2121,2388,2389],{"id":2389},"从总结走向延伸",[2114,2391,2392],{},"可以沿着下面三条联系，把零散的计算连起来：",[2394,2395,2396,2399,2402],"ul",{},[2186,2397,2398],{},"**权责发生制与现金：**确认赊销收入时，货款未必已经收回。把应收账款接入现金预算，再思考比率能够说明什么，以及为什么它不能直接给出回款日期。",[2186,2400,2401],{},"**业务量与经营表现：**即使单位成本不变，产量增加也可能使变动成本总额上升。弹性预算先排除比较中的业务量差异，再让我们分析剩余的成本偏差。",[2186,2403,2404],{},"**流动性与价值：**项目的 NPV 可以为正，却仍然需要先投入现金、以后才收到回款。投资评价和资金安排彼此相关，需要分别分析。",[2114,2406,2407],{},"每条联系都可以通过改变例题中的一个假设来检验：哪些结果随之变化，哪些关系仍然成立？上方专题链接提供更完整的推导和适用边界。",[2121,2409,2410],{"id":2410},"接入完整课程",[2114,2412,2413,2414,2418,2419,2423,2424,2428,2429,2433],{},"想进一步理解确认与计量，可以阅读",[2250,2415,2417],{"href":2416},"..\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F","收入、存货与长期资产","；想深入经营选择，可以进入",[2250,2420,2422],{"href":2421},"..\u002Fmanagement-accounting\u002F03-decisions-investment\u002F","短期决策与投资","。",[2250,2425,2427],{"href":2426},"..\u002F00-index","会计课程首页","列出其余专题，英文的 ",[2250,2430,2432],{"href":2431},"..\u002F..\u002F..\u002Fen\u002Faccounting\u002Fcapstone\u002F","Northstar 综合案例","可用于整合知识。Harbour 与 Northstar 的账户余额仍需分别使用。",[2114,2435,2436,2423],{},[2250,2437,2438],{"href":2274},"开始完整报表案例",{"title":10,"searchDepth":210,"depth":210,"links":2440},[2441,2442,2443,2444,2445,2446],{"id":2123,"depth":210,"text":2123},{"id":2178,"depth":210,"text":2178},{"id":2221,"depth":210,"text":2221},{"id":2365,"depth":210,"text":2365},{"id":2389,"depth":210,"text":2389},{"id":2410,"depth":210,"text":2410},"用概念总结、推导、例题与延伸串起会计基础知识","md",{},true,{"title":1368,"description":2447},{"order":204},"b4_y-rnq9rUj7Oh0ZRiE5YgoNIsuV_PG3czxZ_eXFfk",[2455,2457],{"title":1360,"path":1361,"stem":1362,"description":2456,"children":-1},"用 IFRS 18、IFRS 19、2026 年 IFRS 修订和 FASB 费用分拆要求训练准则状态判断与报表解释。",{"title":1375,"path":1376,"stem":1377,"description":2458,"children":-1},"理解期末调整的逻辑，并通过完整例题追踪利润、资本与报表的联系",1791046371304]