Financial Valuation and Econometrics.pdf
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In this 3 edition, some expositions are updated, including expansions on the maximum likelihood method and the generalized method of moments. Several worked examples with new data are added such as geopolitical event study, hedging, and exchange rate dynamics. In the worked examples, Python programming is introduced and modules such as statsmodel are used. An appendix illustrating the road map is also added. Some of the problem sets at the end of chapters are also expanded.

1. Probability Distribution and Statistics 1
2. Statistical Laws and Central Limit Theorem
Application: Stock Return Distributions 29
3. Two-Variable Linear Regression Application:
Financial Hedging 47
4. Model Estimation Application: Capital Asset
Pricing Model 77
5. Constrained Regression Application: Cost of Capital 95
6. Time Series Analysis Application: Inflation Forecasting 115
7. Random Walk Application: Market Efficiency 143
8. Autoregression and Persistence Application:
Predictability 167
Estimation Errors and T-Tests Application:
Event Studies 181
10. Multiple Linear Regression and Stochastic Regressors 207
11. Dummy Variables and Anova Application: Time
Effect Anomalies 231
12. Specification Errors 247
13. Cross-Sectional Regression Application: Testing CAPM 283
14. More Multiple Linear Regression Applications:
Multi-Factor Asset Pricing 305
15. Errors-in-Variable Application: Exchange Rates
and Risk Premium 329
16. Unit Root Processes Application: Purchasing
Power Parity 347
17. Conditional Heteroskedasticity and Maximum
Likelihood Application: Risk Estimation 373
18. Maximum Likelihood and Goodness-of-Fit
Application: Choice of Copulas 405
19. Mean Reverting Continuous Time Process
Application: Bonds and Term Structures 423
20. Implied Parameters Application: Option Pricing 449
21. Generalised Method of Moments Application:
Consumption-Based Asset Pricing 465
22. Multiple Time Series Regression Application:
Term Structure of Volatilities 483
23. Fixed and Random Effects Models Application:
Synchronicity of Stock Returns 509
24. LOGIT and PROBIT Regressions Application:
Categorisation and Prediction 531
A. Matrix Algebra 555
B. EVIEWS Guide 577
C. Linear Regression in Excel 591
D. Multiple Choice Question Tests 597
E. Solutions to Problem Sets 621
F. Programming in Python 663
Index 667