"Apart from making complex material intelligible, the authors provide a number of insights that just make things click. I have used the first edition of this text on several Masters courses and the students loved it--so did I. The second edition is even better. Quite simply it is a book every quant financial economist will use regularly and need to have close at hand."
--Mark Salmon, Professor of Finance, Warwick Business School, University of Warwick
"Empirical finance has become a key subject in most graduate courses thanks in large part to the dramatic and important strides the subject has taken in recent years. The new edition of this popular and highly readable book has been thoroughly revised and will become essential reading for these courses. I like especially its modern treatment and comprehensive coverage of the subject, and its accessibility for students."
--Mike Wickens, Professor of Economics, University of York
"QFE provides an excellent overview of received and more recent thinking on financial markets at a level suitable for graduate students and researchers. The treatment is well balanced between theory and empirical work, the coverage is wide and up-to-date and the exposition is clear, fluent and accessible. Every researcher and student of financial markets will want to have a copy of this book – not on their shelf but open on their desk."
--Mark Taylor, Professor of Economics, University of Warwick Research Fellow, Centre for Economic Policy Research
"One of the key challenges for economists and strategists working in the fund management industry is to develop and implement an investment process which is practical, firmly rooted in finance theory and statistically sound. This book brings together all the topics necessary to meet this challenge, and in a style that will make it very popular with finance practitioners."
--Andrew Clare, Financial Economist, Legal & General Investment Management, London
"This book is an essential cornerstone for every economist who wants to learn as well as understand the ever-expanding field of quantitative financial economics. Every researcher, practitioner and graduate student will benefit from the book's skillful presentation, insight and clarity of a wide range of important topics. A wonderful text and a definite ‘must have’ and ‘must read’."
--Gregory D. Hess, Russell S. Bock Professor of Economics, Claremont McKenna College, California.
Dirk Nitzsche is an Associate Professor in Finance at CASS Business School and previously was at the Tanaka Business School, Imperial College.
1 Basic Concepts in Finance.
1.1 Returns on Stocks, Bonds and Real Assets.
1.2 Discounted Present Value, DPV.
1.3 Utility and Indifference Curves.
1.4 Asset Demands.
1.5 Indifference Curves and Intertemporal Utility.
1.6 Investment Decisions and Optimal Consumption.
Appendix: Mean-Variance Model and Utility Functions.
2 Basic Statistics in Finance.
2.1 Lognormality and Jensen’s Inequality.
2.2 Unit Roots, Random Walk and Cointegration.
2.3 Monte Carlo Simulation (MCS) and Bootstrapping.
2.4 Bayesian Learning.
3 Efficient Markets Hypothesis.
3.2 Implications of the EMH.
3.3 Expectations, Martingales and Fair Game.
3.4 Testing the EMH.
3.5 Using Survey Data.
Appendix: Cross-Equation Restrictions.
4 Are Stock Returns Predictable?
4.1 A Century of Returns.
4.2 Simple Models.
4.3 Univariate Tests.
4.4 Multivariate Tests.
4.5 Cointegration and Error Correction Models (ECM).
4.6 Non-Linear Models.
4.7 Markov Switching Models.
4.8 Profitable Trading Strategies?
5 Mean-Variance Portfolio Theory and the CAPM.
5.1 An Overview.
5.2 Mean-Variance Model.
5.3 Capital Asset Pricing Model.
5.4 Beta and Systematic Risk.
6 International Portfolio Diversification.
6.1 Mathematics of the Mean-Variance Model.
6.2 International Diversification.
6.3 Mean-Variance Optimisation in Practice.
Appendix I: Efficient Frontier and the CML.
Appendix II: Market Portfolio.
7 Performance Measures, CAPM and APT.
7.1 Performance Measures.
7.2 Extensions of the CAPM.
7.3 Single Index Model.
7.4 Arbitrage Pricing Theory.
8 Empirical Evidence: CAPM and APT.
8.1 CAPM: Time-Series Tests.
8.2 CAPM: Cross-Section Tests.
8.3 CAPM, Multifactor Models and APT.
Appendix: Fama–MacBeth Two-Step Procedure.
9 Applications of Linear Factor Models.
9.1 Event Studies.
9.2 Mutual Fund Performance.
9.3 Mutual Fund ‘Stars’?
10 Valuation Models and Asset Returns.
10.1 The Rational Valuation Formula (RVF).
10.2 Special Cases of the RVF.
10.3 Time-Varying Expected Returns.
11 Stock Price Volatility.
11.1 Shiller Volatility Tests.
11.2 Volatility Tests and Stationarity.
11.3 Peso Problems and Variance Bounds Tests.
11.4 Volatility and Regression Tests.
Appendix: LeRoy–Porter and West Tests.
12 Stock Prices: The VAR Approach.
12.1 Linearisation of Returns and the RVF.
12.2 Empirical Results.
12.3 Persistence and Volatility.
Appendix: Returns, Variance Decomposition and Persistence.
13 SDF Model and the C-CAPM.
13.2 C-CAPM and the ‘Standard’ CAPM.
13.3 Prices and Covariance.
13.4 Rational Valuation Formula and SDF.
13.5 Factor Models.
Appendix: Joint Lognormality and Power Utility.
14 C-CAPM: Evidence and Extensions.
14.1 Should Returns be Predictable in the C-CAPM?
14.2 Equity Premium Puzzle.
14.3 Testing the Euler Equations of the C-CAPM.
14.4 Extensions of the SDF Model.
14.5 Habit Formation.
14.6 Equity Premium: Further Explanations.
Appendix: Hansen–Jagannathan Bound.
15 Intertemporal Asset Allocation: Theory.
15.1 Two-Period Model.
15.2 Multi-Period Model.
15.3 SDF Model of Expected Returns.
Appendix I: Envelope Condition for Consumption-Portfolio Problem.
Appendix II: Solution for Log Utility.
16 Intertemporal Asset Allocation: Empirics.
16.1 Retirement and Stochastic Income.
16.2 Many Risky Assets.
16.3 Different Preferences.
16.4 Horizon Effects and Uncertainty.
16.5 Market Timing and Uncertainty.
16.6 Stochastic Parameters.
Appendix: Parameter Uncertainty and Bayes Theorem.
17 Rational Bubbles and Learning.
17.1 Rational Bubbles.
17.2 Tests of Rational Bubbles.
17.3 Intrinsic Bubbles.
18 Behavioural Finance and Anomalies.
18.1 Key Ideas.
18.2 Beliefs and Preferences.
18.3 Survival of Noise Traders.
18.5 Corporate Finance.
19 Behavioural Models.
19.1 Simple Model.
19.2 Optimising Model of Noise Trader Behaviour.
19.3 Shleifer–Vishny Model: Short-Termism.
19.5 Beliefs and Expectations.
19.6 Momentum and Newswatchers.
19.7 Style Investing.
19.8 Prospect Theory.
Appendix I: The DeLong et al Model of Noise Traders.
Appendix II: The Shleifer–Vishny Model of Short-Termism.
20 Theories of the Term Structure.
20.1 Prices, Yields and the RVF.
20.2 Theories of the Term Structure.
20.3 Expectations Hypothesis.
21 The EH–From Theory to Testing.
21.1 Alternative Representations of the EH.
21.2 VAR Approach.
21.3 Time-Varying Term Premium–VAR Methodology.
22 Empirical Evidence on the Term Structure.
22.1 Data and Cointegration.
22.2 Variance Bounds Tests.
22.3 Single-Equation Tests.
22.4 Expectations Hypothesis: Case Study.
22.5 Previous Studies.
23 SDF and Affine Term Structure Models.
23.1 SDF Model.
23.2 Single-Factor Affine Models.
23.3 Multi-Factor Affine Models.
Appendix I: Math of SDF Model of Term Structure.
Appendix II: Single-Factor Affine Models.
24 The Foreign Exchange Market.
24.1 Exchange Rate Regimes.
24.2 PPP and LOOP.
24.3 Covered-Interest Parity, CIP.
24.4 Uncovered Interest Parity, UIP.
24.5 Forward Rate Unbiasedness, FRU.
24.6 Real Interest Rate Parity.
Appendix: PPP and the Wage–Price Spiral.
25 Testing CIP, UIP and FRU.
25.1 Covered Interest Arbitrage.
25.2 Uncovered Interest Parity.
25.3 Forward Rate Unbiasedness, FRU.
25.4 Testing FRU: VAR Methodology.
25.5 Peso Problems and Learning.
26 Modelling the FX Risk Premium.
26.1 Implications of ² < 1 in FRU Regressions.
26.3 Affine Models of FX Returns.
26.4 FRU and Cash-in-Advance Models.
27 Exchange Rate and Fundamentals.
27.1 Monetary Models.
27.2 Testing the Models.
27.3 New Open-Economy Macroeconomics.
28 Market Risk.
28.1 Measuring VaR.
28.2 Mapping Assets: Simplifications.
28.3 Non-Parametric Measures.
28.4 Monte Carlo Simulation.
28.5 Alternative Methods.
Appendix I: Monte Carlo Analysis and VaR.
Appendix II: Single Index Model (SIM).
29 Volatility and Market Microstructure.
29.2 What Influences Volatility?
29.3 Multivariate GARCH.
29.4 Market Microstructure–FX Trading.
29.5 Survey Data and Expectations.
29.6 Technical Trading Rules.