{"product_id":"financial-econometrics-9780471784500","title":"Financial Econometrics","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eA comprehensive guide to financial econometrics  \u003cp\u003eFinancial econometrics is a quest for models that describe financial time series such as prices, returns, interest rates, and exchange rates. In Financial Econometrics, readers will be introduced to this growing discipline and the concepts and theories associated with it, including background material on probability theory and statistics. The experienced author team uses real-world data where possible and brings in the results of published research provided by investment banking firms and journals. Financial Econometrics clearly explains the techniques presented and provides illustrative examples for the topics discussed.\u003c\/p\u003e \u003cp\u003eSvetlozar T. Rachev, PhD (Karlsruhe, Germany) is currently Chair-Professor at the University of Karlsruhe. Stefan Mittnik, PhD (Munich, Germany) is Professor of Financial Econometrics at the University of Munich. Frank J. Fabozzi, PhD, CFA, CFP (New Hope, PA) is an adjunct professor of Finance at Yale Universi\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cb\u003ePreface.\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e\u003cb\u003eAbbreviations and Acronyms.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAbout the Authors.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 1: Financial Econometrics: Scope and Methods.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Data Generating Process.\u003c\/p\u003e \u003cp\u003eFinancial Econometrics at Work.\u003c\/p\u003e \u003cp\u003eTime Horizon of Models.\u003c\/p\u003e \u003cp\u003eApplications.\u003c\/p\u003e \u003cp\u003eAppendix: Investment Management Process.\u003c\/p\u003e \u003cp\u003eConcepts Explained in this Chapter (in order of presentation).\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 2: Review of Probability and Statistics.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eConcepts of Probability.\u003c\/p\u003e \u003cp\u003ePrinciples of Estimation.\u003c\/p\u003e \u003cp\u003eBayesian Modeling.\u003c\/p\u003e \u003cp\u003eAppendix A: Information Structures.\u003c\/p\u003e \u003cp\u003eAppendix B: Filtration.\u003c\/p\u003e \u003cp\u003eConcepts Explained in this Chapter (in order of presentation).\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 3: Regression Analysis: Theory and Estimation.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Concept of Dependence.\u003c\/p\u003e \u003cp\u003eRegressions and Linear Models.\u003c\/p\u003e \u003cp\u003eEstimation of Linear Regressions.\u003c\/p\u003e \u003cp\u003eSampling Distributions of Regressions.\u003c\/p\u003e \u003cp\u003eDetermining the Explanatory Power of a Regression.\u003c\/p\u003e \u003cp\u003eUsing Regression Analysis in Finance.\u003c\/p\u003e \u003cp\u003eStepwise Regression.\u003c\/p\u003e \u003cp\u003eNonnormality and Autocorrelation of the Residuals.\u003c\/p\u003e \u003cp\u003ePitfalls of Regressions.\u003c\/p\u003e \u003cp\u003eConcepts Explained in this Chapter (in order of presentation) .\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 4: Selected Topics in Regression Analysis.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCategorical and Dummy Variables in Regression Models.\u003c\/p\u003e \u003cp\u003eConstrained Least Squares.\u003c\/p\u003e \u003cp\u003eThe Method of Moments and its Generalizations.\u003c\/p\u003e \u003cp\u003eConcepts Explained in this Chapter (in order of presentation).\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 5: Regression Applications in Finance.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eApplications to the Investment Management Process.\u003c\/p\u003e \u003cp\u003eA Test of Strong-Form Pricing Efficiency.\u003c\/p\u003e \u003cp\u003eTests of the CAPM.\u003c\/p\u003e \u003cp\u003eUsing the CAPM to Evaluate Manager Performance: The Jensen Measure.\u003c\/p\u003e \u003cp\u003eEvidence for Multifactor Models.\u003c\/p\u003e \u003cp\u003eBenchmark Selection: Sharpe Benchmarks.\u003c\/p\u003e \u003cp\u003eReturn-Based Style Analysis for Hedge Funds.\u003c\/p\u003e \u003cp\u003eHedge Fund Survival.\u003c\/p\u003e \u003cp\u003eBond Portfolio Applications.\u003c\/p\u003e \u003cp\u003eConcepts Explained in this Chapter (in order of presentation).\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 6: Modeling Univariate Time Series.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDifference Equations.\u003c\/p\u003e \u003cp\u003eTerminology and Definitions.\u003c\/p\u003e \u003cp\u003eStationarity and Invertibility of ARMA Processes.\u003c\/p\u003e \u003cp\u003eLinear Processes.\u003c\/p\u003e \u003cp\u003eIdentification Tools.\u003c\/p\u003e \u003cp\u003eConcepts Explained in this Chapter (in order of presentation).\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 7: Approaches to ARIMA Modeling and Forecasting.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eOverview of Box-Jenkins Procedure.\u003c\/p\u003e \u003cp\u003eIdentification of Degree of Differencing.\u003c\/p\u003e \u003cp\u003eIdentification of Lag Orders.\u003c\/p\u003e \u003cp\u003eModel Estimation.\u003c\/p\u003e \u003cp\u003eDiagnostic Checking.\u003c\/p\u003e \u003cp\u003eForecasting.\u003c\/p\u003e \u003cp\u003eConcepts Explained in this Chapter (in order of presentation).\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 8: Autoregressive Conditional Heteroskedastic Models.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eARCH Process.\u003c\/p\u003e \u003cp\u003eGARCH Process.\u003c\/p\u003e \u003cp\u003eEstimation of the GARCH Models.\u003c\/p\u003e \u003cp\u003eStationary ARMA-GARCH Models.\u003c\/p\u003e \u003cp\u003eLagrange Multiplier Test.\u003c\/p\u003e \u003cp\u003eVariants of the GARCH Model.\u003c\/p\u003e \u003cp\u003eGARCH Model with Student’s \u003ci\u003et\u003c\/i\u003e-Distributed Innovations.\u003c\/p\u003e \u003cp\u003eMultivariate GARCH Formulations.\u003c\/p\u003e \u003cp\u003eAppendix: Analysis of the Properties of the GARCH(1,1) Model.\u003c\/p\u003e \u003cp\u003eConcepts Explained in this Chapter (in order of presentation).\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 9: Vector Autoregressive Models I.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eVAR Models Defined.\u003c\/p\u003e \u003cp\u003eStationary Autoregressive Distributed Lag Models.\u003c\/p\u003e \u003cp\u003eVector Autoregressive Moving Average Models.\u003c\/p\u003e \u003cp\u003eForecasting with VAR Models.\u003c\/p\u003e \u003cp\u003eAppendix: Eigenvectors and Eigenvalues.\u003c\/p\u003e \u003cp\u003eConcepts Explained in this Chapter (in order of presentation).\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 10: Vector Autoregressive Models II.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eEstimation of Stable VAR Models.\u003c\/p\u003e \u003cp\u003eEstimating the Number of Lags.\u003c\/p\u003e \u003cp\u003eAutocorrelation and Distributional Properties of Residuals.\u003c\/p\u003e \u003cp\u003eVAR Illustration.\u003c\/p\u003e \u003cp\u003eConcepts Explained in this Chapter (in order of presentation).\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 11: Cointegration and State Space Models.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCointegration.\u003c\/p\u003e \u003cp\u003eError Correction Models.\u003c\/p\u003e \u003cp\u003eTheory and Methods of Estimation of Nonstationary VAR Models.\u003c\/p\u003e \u003cp\u003eState-Space Models.\u003c\/p\u003e \u003cp\u003eConcepts Explained in this Chapter (in order of presentation).\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 12: Robust Estimation.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eRobust Statistics.\u003c\/p\u003e \u003cp\u003eRobust Estimators of Regressions.\u003c\/p\u003e \u003cp\u003eIllustration: Robustness of the Corporate Bond Yield Spread Model.\u003c\/p\u003e \u003cp\u003eConcepts Explained in this Chapter (in order of presentation).\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 13: Principal Components Analysis and Factor Analysis.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eFactor Models.\u003c\/p\u003e \u003cp\u003ePrincipal Components Analysis.\u003c\/p\u003e \u003cp\u003eFactor Analysis.\u003c\/p\u003e \u003cp\u003ePCA and Factor Analysis Compared.\u003c\/p\u003e \u003cp\u003eConcepts Explained in this Chapter (in order of presentation).\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 14: Heavy-Tailed and Stable Distributions in Financial Econometrics.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBasic Facts and Definitions of Stable Distributions.\u003c\/p\u003e \u003cp\u003eProperties of Stable Distributions.\u003c\/p\u003e \u003cp\u003eEstimation of the Parameters of the Stable Distribution.\u003c\/p\u003e \u003cp\u003eApplications to German Stock Data.\u003c\/p\u003e \u003cp\u003eAppendix: Comparing Probability Distributions.\u003c\/p\u003e \u003cp\u003eConcepts Explained in this Chapter (in order of presentation).\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 15: ARMA and ARCH Models with Infinite-Variance Innovations.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eInfinite Variance Autoregressive Processes.\u003c\/p\u003e \u003cp\u003eStable GARCH Models.\u003c\/p\u003e \u003cp\u003eEstimation for the Stable GARCH Model.\u003c\/p\u003e \u003cp\u003ePrediction of Conditional Densities.\u003c\/p\u003e \u003cp\u003eConcepts Explained in this Chapter (in order of presentation).\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAPPENDIX:\u003c\/b\u003e Monthly Returns for 20 Stocks: December 2000–November 2005.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eINDEX.\u003c\/b\u003e\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49402673168727,"sku":"9780471784500","price":71.25,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780471784500.jpg?v=1730481188","url":"https:\/\/bookcurl.com\/products\/financial-econometrics-9780471784500","provider":"Book 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