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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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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":213},{"id":2106,"title":1380,"body":2107,"description":3579,"extension":3580,"features":12,"hero":12,"layout":12,"locale":12,"meta":3581,"navigation":12,"path":1381,"published":3582,"seo":3583,"sidebar":3584,"stem":1382,"__hash__":3585},"docs\u002Fzh\u002Faccounting\u002Ffoundation\u002F02-cash-budget.md",{"type":2108,"value":2109,"toc":3568},"minimark",[2110,2113,2117,2131,2135,2138,2141,2145,2148,2243,2250,2260,2264,2643,2954,3115,3119,3274,3348,3352,3359,3477,3481,3484,3490,3493,3497,3503,3520,3524,3535,3538,3542,3545,3557],[2111,2112],"span",{"id":1380},[2114,2115,2116],"p",{},"现金预算预测未来何时收款和付款，历史现金流量表说明已经发生的现金变动，利润表则反映确认的收入和费用。阅读时，既要分清它们针对哪个期间，也要分清所列金额是现金收付还是收入费用。",[2114,2118,2119,2120,2124,2125,2130],{},"下面通过例题，把收付款时间表、逐月现金余额和融资需求连起来。这一原创 ",[2121,2122,2123],"strong",{},"Harbour 预算情景","与",[2126,2127,2129],"a",{"href":2128},".\u002F01-adjustments-to-statements","报表案例","相互独立，请只使用本页提供的期初余额。",[2132,2133,2134],"h2",{"id":2134},"先理解时间表的作用",[2114,2136,2137],{},"销售预测说明销售在哪个月发生，收款计划则把这些销售额放到实际预计收款的月份。信用期使两个时间点分开，购货与供应商付款也有同样的关系。这里还要区分购货额与销售成本：付款条款针对购入的货物，销售成本反映的则是已经出售的存货。",[2114,2139,2140],{},"把收付款放入恰当的月份后，再将剩余现金结转到下个月。因此，某个月净流入为正，也可能还不够弥补以前的短缺。融资安排是在此基础上的下一步：它改变现金和借款，同时保留原有收付款计划，便于看清缺口来自哪里。",[2132,2142,2144],{"id":2143},"_1-预测与假设","1. 预测与假设",[2114,2146,2147],{},"金额均为英镑。每月销售额的 40% 当月收现，60% 在下月收取；每月购货的 50% 当月支付，另 50% 下月支付。假设没有更早的应收应付、坏账、退货或其他收付款。",[2149,2150,2151,2174],"table",{},[2152,2153,2154],"thead",{},[2155,2156,2157,2161,2165,2168,2171],"tr",{},[2158,2159,2160],"th",{},"预测项目",[2158,2162,2164],{"align":2163},"right","12 月",[2158,2166,2167],{"align":2163},"1 月",[2158,2169,2170],{"align":2163},"2 月",[2158,2172,2173],{"align":2163},"3 月",[2175,2176,2177,2195,2212,2229],"tbody",{},[2155,2178,2179,2183,2186,2189,2192],{},[2180,2181,2182],"td",{},"销售额",[2180,2184,2185],{"align":2163},"20,000",[2180,2187,2188],{"align":2163},"30,000",[2180,2190,2191],{"align":2163},"36,000",[2180,2193,2194],{"align":2163},"40,000",[2155,2196,2197,2200,2203,2206,2209],{},[2180,2198,2199],{},"购货额",[2180,2201,2202],{"align":2163},"12,000",[2180,2204,2205],{"align":2163},"18,000",[2180,2207,2208],{"align":2163},"22,000",[2180,2210,2211],{"align":2163},"24,000",[2155,2213,2214,2217,2220,2223,2226],{},[2180,2215,2216],{},"其他经营现金付款",[2180,2218,2219],{"align":2163},"—",[2180,2221,2222],{"align":2163},"8,000",[2180,2224,2225],{"align":2163},"9,000",[2180,2227,2228],{"align":2163},"10,000",[2155,2230,2231,2234,2236,2239,2241],{},[2180,2232,2233],{},"支付设备款",[2180,2235,2219],{"align":2163},[2180,2237,2238],{"align":2163},"0",[2180,2240,2205],{"align":2163},[2180,2242,2238],{"align":2163},[2114,2244,2245,2246,2249],{},"1 月初现金为 ",[2121,2247,2248],{},"£5,000","。其他经营付款包括工资、租金等经营现金支出，不包括另行计算的供应商付款和设备款，也不包含非现金的折旧。忽略税款、利息和融资费用；这是练习假设，不代表真实借款没有这些成本。",[2114,2251,2252,2253,2259],{},"阅读每张表时，把现金收付追溯到产生它的销售或购货月份。",[2126,2254,2258],{"href":2255,"rel":2256},"https:\u002F\u002Fopenstax.org\u002Fbooks\u002Fprinciples-managerial-accounting\u002Fpages\u002F7-3-prepare-financial-budgets",[2257],"nofollow","OpenStax 的财务预算章节","进一步解释收款、付款与融资计划之间的联系。",[2132,2261,2263],{"id":2262},"_2-收款和付款","2. 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£",[2175,2977,2978,2991,3003,3024,3036,3048,3069,3080,3091],{},[2155,2979,2980,2983,2985,2988],{},[2180,2981,2982],{},"本月销售当月收现",[2180,2984,2202],{"align":2163},[2180,2986,2987],{"align":2163},"14,400",[2180,2989,2990],{"align":2163},"16,000",[2155,2992,2993,2996,2998,3000],{},[2180,2994,2995],{},"收回上月赊销款",[2180,2997,2202],{"align":2163},[2180,2999,2205],{"align":2163},[2180,3001,3002],{"align":2163},"21,600",[2155,3004,3005,3010,3014,3019],{},[2180,3006,3007],{},[2121,3008,3009],{},"收款合计",[2180,3011,3012],{"align":2163},[2121,3013,2211],{},[2180,3015,3016],{"align":2163},[2121,3017,3018],{},"32,400",[2180,3020,3021],{"align":2163},[2121,3022,3023],{},"37,600",[2155,3025,3026,3029,3031,3034],{},[2180,3027,3028],{},"支付本月购货款",[2180,3030,2225],{"align":2163},[2180,3032,3033],{"align":2163},"11,000",[2180,3035,2202],{"align":2163},[2155,3037,3038,3041,3044,3046],{},[2180,3039,3040],{},"支付上月购货款",[2180,3042,3043],{"align":2163},"6,000",[2180,3045,2225],{"align":2163},[2180,3047,3033],{"align":2163},[2155,3049,3050,3055,3060,3064],{},[2180,3051,3052],{},[2121,3053,3054],{},"供应商付款合计",[2180,3056,3057],{"align":2163},[2121,3058,3059],{},"15,000",[2180,3061,3062],{"align":2163},[2121,3063,2185],{},[2180,3065,3066],{"align":2163},[2121,3067,3068],{},"23,000",[2155,3070,3071,3074,3076,3078],{},[2180,3072,3073],{},"其他经营付款",[2180,3075,2222],{"align":2163},[2180,3077,2225],{"align":2163},[2180,3079,2228],{"align":2163},[2155,3081,3082,3085,3087,3089],{},[2180,3083,3084],{},"设备款",[2180,3086,2238],{"align":2163},[2180,3088,2205],{"align":2163},[2180,3090,2238],{"align":2163},[2155,3092,3093,3098,3102,3107],{},[2180,3094,3095],{},[2121,3096,3097],{},"付款合计",[2180,3099,3100],{"align":2163},[2121,3101,3068],{},[2180,3103,3104],{"align":2163},[2121,3105,3106],{},"47,000",[2180,3108,3109],{"align":2163},[2121,3110,3111],{},"33,000",[2114,3113,3114],{},"1 月的收付款表包括 12 月形成的 £12,000 应收账款和 £6,000 应付账款。3 月末仍有 £24,000 的 3 月销售款未收，£12,000 的 3 月购货款未付。虽然销售或采购发生在 3 月，这些尚未收付的款项并不属于 3 月的现金流量。",[2132,3116,3118],{"id":3117},"_3-未融资情况下的现金状况","3. 未融资情况下的现金状况",[2111,3120,3122],{"className":3121},[2267],[2111,3123,3125,3170],{"className":3124},[2271],[2111,3126,3128],{"className":3127},[2275],[2277,3129,3130],{"xmlns":2279,"display":2280},[2282,3131,3132,3167],{},[2285,3133,3134,3150],{"rowspacing":2287,"columnalign":2288,"columnspacing":2289},[2291,3135,3136],{},[2294,3137,3138],{},[2297,3139,3140],{"scriptlevel":2238,"displaystyle":2299},[2318,3141,3142,3145,3147],{},[2304,3143,3144],{},"期末现金",[2321,3146,2323],{},[2304,3148,3149],{},"期初现金",[2291,3151,3152],{},[2294,3153,3154],{},[2297,3155,3156],{"scriptlevel":2238,"displaystyle":2299},[2318,3157,3158,3160,3162,3164],{},[2321,3159,2347],{},[2304,3161,2306],{},[2321,3163,2363],{},[2304,3165,3166],{},"付款",[2368,3168,3169],{"encoding":2370},"\\begin{gathered}\n\\text{期末现金}=\\text{期初现金}\\\\\n+\\text{收款}-\\text{付款}\n\\end{gathered}",[2111,3171,3173],{"className":3172,"ariaHidden":2299},[2375],[2111,3174,3176,3180],{"className":3175},[2379],[2111,3177],{"className":3178,"style":3179},[2383],"height:2.7em;vertical-align:-1.1em;",[2111,3181,3183],{"className":3182},[2388],[2111,3184,3186],{"className":3185},[2285],[2111,3187,3189],{"className":3188},[2395],[2111,3190,3192,3265],{"className":3191},[2399,2400],[2111,3193,3195,3262],{"className":3194},[2404],[2111,3196,3199,3229],{"className":3197,"style":3198},[2408],"height:1.6em;",[2111,3200,3202,3205],{"style":3201},"top:-3.76em;",[2111,3203],{"className":3204,"style":2417},[2416],[2111,3206,3208,3214,3217,3220,3223],{"className":3207},[2388],[2111,3209,3211],{"className":3210},[2388,2427],[2111,3212,3144],{"className":3213},[2388,2431],[2111,3215],{"className":3216,"style":2495},[2494],[2111,3218,2323],{"className":3219},[2490],[2111,3221],{"className":3222,"style":2495},[2494],[2111,3224,3226],{"className":3225},[2388,2427],[2111,3227,3149],{"className":3228},[2388,2431],[2111,3230,3232,3235],{"style":3231},"top:-2.26em;",[2111,3233],{"className":3234,"style":2417},[2416],[2111,3236,3238,3241,3247,3250,3253,3256],{"className":3237},[2388],[2111,3239,2347],{"className":3240},[2388],[2111,3242,3244],{"className":3243},[2388,2427],[2111,3245,2306],{"className":3246},[2388,2431],[2111,3248],{"className":3249,"style":2502},[2494],[2111,3251,2363],{"className":3252},[2506],[2111,3254],{"className":3255,"style":2502},[2494],[2111,3257,3259],{"className":3258},[2388,2427],[2111,3260,3166],{"className":3261},[2388,2431],[2111,3263,2468],{"className":3264},[2467],[2111,3266,3268],{"className":3267},[2404],[2111,3269,3272],{"className":3270,"style":3271},[2408],"height:1.1em;",[2111,3273],{},[2955,3275,3277,3341],{"title":3276},"新增融资前的现金预算",[2149,3278,3279,3292],{},[2152,3280,3281],{},[2155,3282,3283,3286,3288,3290],{},[2158,3284,3285],{},"项目",[2158,3287,2969],{"align":2163},[2158,3289,2972],{"align":2163},[2158,3291,2975],{"align":2163},[2175,3293,3294,3307,3321],{},[2155,3295,3296,3299,3302,3304],{},[2180,3297,3298],{},"期初现金／未融资头寸",[2180,3300,3301],{"align":2163},"5,000",[2180,3303,3043],{"align":2163},[2180,3305,3306],{"align":2163},"(8,600)",[2155,3308,3309,3312,3315,3318],{},[2180,3310,3311],{},"收款减付款",[2180,3313,3314],{"align":2163},"1,000",[2180,3316,3317],{"align":2163},"(14,600)",[2180,3319,3320],{"align":2163},"4,600",[2155,3322,3323,3328,3332,3336],{},[2180,3324,3325],{},[2121,3326,3327],{},"期末现金／未融资头寸",[2180,3329,3330],{"align":2163},[2121,3331,3043],{},[2180,3333,3334],{"align":2163},[2121,3335,3306],{},[2180,3337,3338],{"align":2163},[2121,3339,3340],{},"(4,000)",[2114,3342,3343,3344,3347],{},"负数表示",[2121,3345,3346],{},"尚待解决的资金缺口","，并不意味着银行已经批准透支。3 月净现金流为正，虽然缩小了缺口，却还不足以补足此前累计的短缺。",[2132,3349,3351],{"id":3350},"_4-单独编制融资安排","4. 单独编制融资安排",[2114,3353,3354,3355,3358],{},"本例假设企业可以按需借款，期初借款为零，管理层要求",[2121,3356,3357],{},"每月末至少保留 £3,000 现金","。现金不足时，借款补足至该下限；超过下限的部分用于还款，还款额不超过尚欠本金。仍按前述假设忽略利息和费用。实际安排融资时，还要核实可用额度、契约条件和月内付款日期。",[2955,3360,3362,3474],{"title":3361},"融资计划",[2149,3363,3364,3376],{},[2152,3365,3366],{},[2155,3367,3368,3370,3372,3374],{},[2158,3369,3285],{},[2158,3371,2969],{"align":2163},[2158,3373,2972],{"align":2163},[2158,3375,2975],{"align":2163},[2175,3377,3378,3390,3400,3412,3424,3436,3454],{},[2155,3379,3380,3383,3385,3387],{},[2180,3381,3382],{},"已考虑前月融资的期初现金",[2180,3384,3301],{"align":2163},[2180,3386,3043],{"align":2163},[2180,3388,3389],{"align":2163},"3,000",[2155,3391,3392,3394,3396,3398],{},[2180,3393,3311],{},[2180,3395,3314],{"align":2163},[2180,3397,3317],{"align":2163},[2180,3399,3320],{"align":2163},[2155,3401,3402,3405,3407,3409],{},[2180,3403,3404],{},"本月融资前现金",[2180,3406,3043],{"align":2163},[2180,3408,3306],{"align":2163},[2180,3410,3411],{"align":2163},"7,600",[2155,3413,3414,3417,3419,3422],{},[2180,3415,3416],{},"新增借款",[2180,3418,2238],{"align":2163},[2180,3420,3421],{"align":2163},"11,600",[2180,3423,2238],{"align":2163},[2155,3425,3426,3429,3431,3433],{},[2180,3427,3428],{},"偿还本金",[2180,3430,2238],{"align":2163},[2180,3432,2238],{"align":2163},[2180,3434,3435],{"align":2163},"(4,600)",[2155,3437,3438,3442,3446,3450],{},[2180,3439,3440],{},[2121,3441,3144],{},[2180,3443,3444],{"align":2163},[2121,3445,3043],{},[2180,3447,3448],{"align":2163},[2121,3449,3389],{},[2180,3451,3452],{"align":2163},[2121,3453,3389],{},[2155,3455,3456,3461,3465,3469],{},[2180,3457,3458],{},[2121,3459,3460],{},"期末借款",[2180,3462,3463],{"align":2163},[2121,3464,2238],{},[2180,3466,3467],{"align":2163},[2121,3468,3421],{},[2180,3470,3471],{"align":2163},[2121,3472,3473],{},"7,000",[2114,3475,3476],{},"为维持最低现金余额，2 月需要借入 £11,600，仅借 £8,600 还不够。3 月应以融资后的 £3,000 作为期初现金，不能再沿用未融资表中的 −£8,600。",[2132,3478,3480],{"id":3479},"_5-自行重算未融资预算","5. 自行重算未融资预算",[2114,3482,3483],{},"下面的可选代码复算第 3 节。修改现金销售比例或设备付款，先解释收付款时间的变化，再重新安排融资。这是仅覆盖三个月、赊销赊购均延后一个月的教学模型。",[3485,3486],"pyodide",{"code64":3487,"layout":3488,"locale":1173,"title":3489},"c2FsZXMgPSBbMjBfMDAwLCAzMF8wMDAsIDM2XzAwMCwgNDBfMDAwXSAgIyBEZWNlbWJlciB0byBNYXJjaApwdXJjaGFzZXMgPSBbMTJfMDAwLCAxOF8wMDAsIDIyXzAwMCwgMjRfMDAwXQpvcGVyYXRpbmcgPSBbOF8wMDAsIDlfMDAwLCAxMF8wMDBdCmVxdWlwbWVudCA9IFswLCAxOF8wMDAsIDBdCmNhc2hfc2hhcmUgPSAwLjQwCmNhc2ggPSA1XzAwMAphc3NlcnQgMCA8PSBjYXNoX3NoYXJlIDw9IDEsICJDYXNoLXNhbGVzIHNoYXJlIG11c3QgYmUgYmV0d2VlbiAwIGFuZCAxIgoKcm93cyA9IFtdCmZvciBpLCBtb250aCBpbiBlbnVtZXJhdGUoWyJKYW4iLCAiRmViIiwgIk1hciJdLCBzdGFydD0xKToKICAgIHJlY2VpcHRzID0gY2FzaF9zaGFyZSAqIHNhbGVzW2ldICsgKDEgLSBjYXNoX3NoYXJlKSAqIHNhbGVzW2kgLSAxXQogICAgc3VwcGxpZXJzID0gMC41MCAqIHB1cmNoYXNlc1tpXSArIDAuNTAgKiBwdXJjaGFzZXNbaSAtIDFdCiAgICBwYXltZW50cyA9IHN1cHBsaWVycyArIG9wZXJhdGluZ1tpIC0gMV0gKyBlcXVpcG1lbnRbaSAtIDFdCiAgICBuZXQgPSByZWNlaXB0cyAtIHBheW1lbnRzCiAgICBjYXNoICs9IG5ldAogICAgcm93cy5hcHBlbmQoKHJlY2VpcHRzLCBwYXltZW50cywgbmV0LCBjYXNoKSkKICAgIHByaW50KGYie21vbnRofTogcmVjZWlwdHMgwqN7cmVjZWlwdHM6LC4wZn07IHBheW1lbnRzIMKje3BheW1lbnRzOiwuMGZ9OyAiCiAgICAgICAgICBmIm5ldCDCo3tuZXQ6LC4wZn07IHVuZnVuZGVkIGNsb3NpbmcgwqN7Y2FzaDosLjBmfSIp","vertical","逐月现金收款与付款",[2114,3491,3492],{},"输出中 receipts 是收款，payments 是付款，net 是当月净流量，unfunded closing 是未融资的期末头寸。先预测结果，再运行核对。",[2132,3494,3496],{"id":3495},"_6-延迟回款练习","6. 延迟回款练习",[2114,3498,3499,3502],{},[2121,3500,3501],{},"2 月原应收回的 £18,000 赊销款","中，有 20% 延至 3 月到账。其他收款、付款和融资假设不变。重算收款、2 月借款和 3 月还款。延迟是否改变 1–3 月收款总额？",[2955,3504,3506,3517],{"title":3505},"参考反馈",[2114,3507,3508,3509,3512,3513,3516],{},"£3,600 从 2 月移到 3 月，两月收款分别变为 £28,800 和 £41,200。2 月净现金流为 −£18,200，融资前现金 −£12,200，要达到 £3,000 下限需借 ",[2121,3510,3511],{},"£15,200","。3 月净现金流为 £8,200，可还款 ",[2121,3514,3515],{},"£8,200","，期末现金仍为 £3,000，借款仍为 £7,000。",[2114,3518,3519],{},"季度收款总额仍是 £94,000，但借款峰值增加了 £3,600。实际借款若涉及利息或费用，即使收款总额不变，总成本也可能变化。因此，只看季度合计会漏掉 2 月的融资需求。",[2132,3521,3523],{"id":3522},"_7-从例题中归纳什么","7. 从例题中归纳什么",[2114,3525,3526,3527,3530,3531,3534],{},"企业期初有 £10,000，当期净流出 £3,000，期末仍有 £7,000：正的",[2121,3528,3529],{},"余额","可以与负的",[2121,3532,3533],{},"流量","同时存在。反过来，第 3 节的 3 月是正流量和负的未融资头寸。两者都不能直接说明利润。",[2114,3536,3537],{},"延迟回款的变式单独展示了时间的影响：收款总额相同，部分现金晚到账，仍会提高借款峰值。总结现金预算时，应说明缺口何时出现、金额多大，以及由什么假设推动。如果建议推迟向供应商付款，应先考虑约定的付款条款；即使预计月末有现金结余，也仍需检查月内是否可能短缺。",[2132,3539,3541],{"id":3540},"延伸增长为什么可能占用现金","延伸：增长为什么可能占用现金",[2114,3543,3544],{},"如果企业需要先支付购货款和工资，之后才能收回客户欠款，扩大销售就可能增加经营循环中占用的现金。销售额增长本身不足以证明企业有能力为增长提供资金，具体影响还取决于利润率、存货、付款条款和扩张时间。",[2114,3546,3547,3548,3552,3553,3556],{},"可以用",[2126,3549,3551],{"href":3550},"..\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F15-ratio-analysis","营运资本比率","检查收付款假设，再把这些假设放回月度计划。比率概括周转情况，时间表指出缺口位置。对于长期项目，",[2126,3554,1463],{"href":3555},"..\u002Fmanagement-accounting\u002F03-decisions-investment\u002F23-capital-budgeting","还会进一步追问：按选定折现率计算，未来增量现金流在当前值多少？",[2114,3558,3559,3563,3564],{},[2126,3560,3562],{"href":3561},".\u002F03-decision-workshop","下一页：会计决策练习"," · ",[2126,3565,3567],{"href":3566},".\u002F","返回基础路径",{"title":10,"searchDepth":210,"depth":210,"links":3569},[3570,3571,3572,3573,3574,3575,3576,3577,3578],{"id":2134,"depth":210,"text":2134},{"id":2143,"depth":210,"text":2144},{"id":2262,"depth":210,"text":2263},{"id":3117,"depth":210,"text":3118},{"id":3350,"depth":210,"text":3351},{"id":3479,"depth":210,"text":3480},{"id":3495,"depth":210,"text":3496},{"id":3522,"depth":210,"text":3523},{"id":3540,"depth":210,"text":3541},"从跨月收付款计划推导现金余额、融资需求和延迟回款影响","md",{},true,{"title":1380,"description":3579},{"order":216},"C5Fhdcy0iaXTUzujhHEx-90VjDgWlmxTtEjhVPUJh6s",[3587,3589],{"title":1375,"path":1376,"stem":1377,"description":3588,"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",{"title":1385,"path":1386,"stem":1387,"description":3590,"children":-1},"总结不同会计指标的用途，并通过例题理解比较、判断与结论的边界",1791046371070]