Financial Valuation and Econometrics (ePub)

This book is an introduction to financial valuation and financial data analyses using econometric methods. It is intended for advanced finance undergraduates and graduates. Most chapters in the book would contain one or more finance application examples where finance concepts, and sometimes theory, are taught.This book is a modest attempt to bring together several important domains in financial valuation theory, in econometrics modelling, and in the empirical analyses of financial data. These domains are highly intertwined and should be properly understood in order to correctly and effectively harness the power of data and statistical or econometrics methods for investment and financial decision-making.The contribution in this book, and at the same time, its novelty, is in employing materials in basic econometrics, particularly linear regression analyses, and weaving into it threads of foundational finance theory, concepts, ideas, and models. It provides a clear pedagogical approach to allow very effective learning by a finance student who wants to be well equipped in both theory and ability to research the data.This is a handy book for finance professionals doing research to easily access the key techniques in data analyses using regression methods. Students learn all 3 skills at once — finance, econometrics, and data analyses. It provides for very solid and useful learning for advanced undergraduate and graduate students who wish to work in financial analyses, risk analyses, and financial research areas. Request Inspection Copy Contents:Probability Distribution and StatisticsStatistical Laws and Central Limit Theorem / Application: Stock Return DistributionsTwo-Variable Linear Regression/Application: Financial HedgingModel Estimation / Application: Capital Asset Pricing ModelConstrained Regression / Application: Cost of CapitalTime Series Analysis / Application: Inflation ForecastingRandom Walk / Application: Market EfficiencyAutoregression and Persistence / Application: PredictabilityEstimation Errors and T-Tests / Application: Event StudiesMultiple Linear Regression and Stochastic RegressorsDummy Variables and ANOVA / Application: Time Effect AnomaliesSpecification ErrorsCross-Sectional Regression / Application: Testing CAPMMore Multiple Linear Regressions / Application: Multi-Factor Asset PricingErrors-in-Variable / Application: Exchange Rates and Risk PremiumUnit Root Processes / Application: Purchasing Power ParityConditional Heteroskedasticity / Application: Risk EstimationMaximum Likelihood and Goodness of Fit / Application: Choice of CopulasMean Reverting Continuous Time Process / Application: Bonds and Term StructuresImplied Parameters / Application: Option PricingGeneralised Method of Moments / Application: Consumption-Based Asset PricingMultiple Time Series Regression / Application: Term Structure of VolatilitiesFixed and Random Effects Model / Application: Synchronicity of Stock ReturnsLOGIT and PROBIT Regressions / Application: Categorization and PredictionReadership: Advanced undergraduates and 1st year post-graduate students in finance and econometrics.Key Features:The book is a handy one for finance professionals doing research to easily access the key techniques in data analyses using regression methodsStudents learn all 3 skills at once — finance, econometrics, and data analysesIt provides for very solid and useful learning for advanced undergraduate and graduate students who wish to work in financial analyses, risk analyses, and financial research areas