FINAN VALUA & ECONOME (3RD ED)

This book provides a comprehensive introduction to financial valuation and financial data analysis using econometric methods. It is intended for advanced finance undergraduates and graduate students, offering detailed guidance on applying econometric techniques to real-world financial problems. Most chapters in the book would contain one or more finance application examples where finance concepts and theory are taught. This book weaves together the three important domains of financial valuation theory, econometrics modelling, and the empirical analyses of financial data using common programming languages and statistical software. The pedagogical approach in this book employs various suitable econometric methods such as multiple linear and panel regressions, time series analyses, cointegration, maximum likelihood, the generalized method of moments to perform estimation and testing of popular financial models using appropriate financial data. It provides for very effective learning by a finance professional or student who wants to be well equipped in both theory and the ability to investigate the models using appropriate econometrics and statistical techniques. Learning these econometric methods is also important in complementing prediction and classification techniques in AI and machine learning.

Contents:

• Preface to the Third Edition
• Preface to the Second Edition
• Preface to the First Edition
• About the Author
• Probability Distribution and Statistics
• Statistical Laws and Central Limit Theorem Application: Stock Return Distributions
• Two-Variable Linear Regression Application: Financial Hedging
• Model Estimation Application: Capital Asset Pricing Model
• Constrained Regression Application: Cost of Capital
• Time Series Analysis Application: Inflation Forecasting
• Random Walk Application: Market Efficiency
• Autoregression and Persistence Application: Predictability
• Estimation Errors and T-Tests Application: Event Studies
• Multiple Linear Regression and Stochastic Regressors
• Dummy Variables and Anova Application: Time Effect Anomalies
• Specification Errors
• Cross-Sectional Regression Application: Testing CAPM
• More Multiple Linear Regression Applications: Multi-Factor Asset Pricing
• Errors-in-Variable Application: Exchange Rates and Risk Premium
• Unit Root Processes Application: Purchasing Power Parity
• Conditional Heteroskedasticity and Maximum Likelihood Application: Risk Estimation
• Maximum Likelihood and Goodness-of-Fit Application: Choice of Copulas
• Mean Reverting Continuous Time Process Application: Bonds and Term Structures
• Implied Parameters Application: Option Pricing
• Generalised Method of Moments Application: Consumption-Based Asset Pricing
• Multiple Time Series Regression Application: Term Structure of Volatilities
• Fixed and Random Effects Models Application: Synchronicity of Stock Returns
• LOGIT and PROBIT Regressions Application: Categorisation and Prediction
• Appendices:
  • Matrix Algebra
  • EVIEWS Guide
  • Linear Regression in Excel
  • Multiple Choice Question Tests
  • Solutions to Problem Sets
  • Programming in Python
• Index

Readership: Undergraduates, Post graduates and researchers in Finance, Applied Finance, Empirical Finance, Statistical Finance, Quantitative Finance, Applied Econometrics, Econometrics courses, as well as professionals in Finance areas like banks, risk, trading and research desks.