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Quantitative Financial Economics: Stocks, Bonds and Foreign Exchange, 2nd Edition

Quantitative Financial Economics: Stocks, Bonds and Foreign Exchange, 2nd Edition

Keith Cuthbertson, Dirk Nitzsche

ISBN: 978-0-470-09171-5

Dec 2004

736 pages

Out of stock

$85.00

Description

This new edition of the hugely successful Quantitative Financial Economics has been revised and updated to reflect the most recent theoretical and econometric/empirical advances in the financial markets.   It provides an introduction to models of economic behaviour in financial markets, focusing on discrete time series analysis.   Emphasis is placed on theory, testing and explaining ‘real-world’ issues.

The new edition will include:

  • Updated charts and cases studies.
  • New companion website allowing students to put theory into practice and to test their knowledge through questions and answers.
  • Chapters on Monte Carlo simulation, bootstrapping and market microstructure.

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Preface.

Acknowledgements.

1 Basic Concepts in Finance.

Aims.

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.

1.7 Summary.

Appendix: Mean-Variance Model and Utility Functions.

2 Basic Statistics in Finance.

Aims.

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.

2.5 Summary.

3 Efficient Markets Hypothesis.

Aims.

3.1 Overview.

3.2 Implications of the EMH.

3.3 Expectations, Martingales and Fair Game.

3.4 Testing the EMH.

3.5 Using Survey Data.

3.6 Summary.

Appendix: Cross-Equation Restrictions.

4 Are Stock Returns Predictable?

Aims.

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?

4.9 Summary.

5 Mean-Variance Portfolio Theory and the CAPM.

Aims.

5.1 An Overview.

5.2 Mean-Variance Model.

5.3 Capital Asset Pricing Model.

5.4 Beta and Systematic Risk.

5.5 Summary.

6 International Portfolio Diversification.

Aims.

6.1 Mathematics of the Mean-Variance Model.

6.2 International Diversification.

6.3 Mean-Variance Optimisation in Practice.

6.4 Summary.

Appendix I: Efficient Frontier and the CML.

Appendix II: Market Portfolio.

7 Performance Measures, CAPM and APT.

Aims.

7.1 Performance Measures.

7.2 Extensions of the CAPM.

7.3 Single Index Model.

7.4 Arbitrage Pricing Theory.

7.5 Summary.

8 Empirical Evidence: CAPM and APT.

Aims.

8.1 CAPM: Time-Series Tests.

8.2 CAPM: Cross-Section Tests.

8.3 CAPM, Multifactor Models and APT.

8.4 Summary.

Appendix: Fama–MacBeth Two-Step Procedure.

9 Applications of Linear Factor Models.

Aims.

9.1 Event Studies.

9.2 Mutual Fund Performance.

9.3 Mutual Fund ‘Stars’?

9.4 Summary.

10 Valuation Models and Asset Returns.

Aims.

10.1 The Rational Valuation Formula (RVF).

10.2 Special Cases of the RVF.

10.3 Time-Varying Expected Returns.

10.4 Summary.

11 Stock Price Volatility.

Aims.

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.

11.5 Summary.

Appendix: LeRoy–Porter and West Tests.

12 Stock Prices: The VAR Approach.

Aims.

12.1 Linearisation of Returns and the RVF.

12.2 Empirical Results.

12.3 Persistence and Volatility.

12.4 Summary.

Appendix: Returns, Variance Decomposition and Persistence.

13 SDF Model and the C-CAPM.

Aims.

13.1 Consumption-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.

13.6 Summary.

Appendix: Joint Lognormality and Power Utility.

14 C-CAPM: Evidence and Extensions.

Aims.

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.

14.7 Summary.

Appendix: Hansen–Jagannathan Bound.

15 Intertemporal Asset Allocation: Theory.

Aims.

15.1 Two-Period Model.

15.2 Multi-Period Model.

15.3 SDF Model of Expected Returns.

15.4 Summary.

Appendix I: Envelope Condition for Consumption-Portfolio Problem.

Appendix II: Solution for Log Utility.

16 Intertemporal Asset Allocation: Empirics.

Aims.

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.

16.7 Robustness.

16.8 Summary.

Appendix: Parameter Uncertainty and Bayes Theorem.

17 Rational Bubbles and Learning.

Aims.

17.1 Rational Bubbles.

17.2 Tests of Rational Bubbles.

17.3 Intrinsic Bubbles.

17.4 Learning.

17.5 Summary.

18 Behavioural Finance and Anomalies.

Aims.

18.1 Key Ideas.

18.2 Beliefs and Preferences.

18.3 Survival of Noise Traders.

18.4 Anomalies.

18.5 Corporate Finance.

18.6 Summary.

19 Behavioural Models.

Aims.

19.1 Simple Model.

19.2 Optimising Model of Noise Trader Behaviour.

19.3 Shleifer–Vishny Model: Short-Termism.

19.4 Contagion.

19.5 Beliefs and Expectations.

19.6 Momentum and Newswatchers.

19.7 Style Investing.

19.8 Prospect Theory.

19.9 Summary.

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.

Aims.

20.1 Prices, Yields and the RVF.

20.2 Theories of the Term Structure.

20.3 Expectations Hypothesis.

20.4 Summary.

21 The EH–From Theory to Testing.

Aims.

21.1 Alternative Representations of the EH.

21.2 VAR Approach.

21.3 Time-Varying Term Premium–VAR Methodology.

21.4 Summary.

22 Empirical Evidence on the Term Structure.

Aims.

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.

22.6 Summary.

23 SDF and Affine Term Structure Models.

Aims.

23.1 SDF Model.

23.2 Single-Factor Affine Models.

23.3 Multi-Factor Affine Models.

23.4 Summary.

Appendix I: Math of SDF Model of Term Structure.

Appendix II: Single-Factor Affine Models.

24 The Foreign Exchange Market.

Aims.

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.

24.7 Summary.

Appendix: PPP and the Wage–Price Spiral.

25 Testing CIP, UIP and FRU.

Aims.

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.

25.6 Summary.

26 Modelling the FX Risk Premium.

Aims.

26.1 Implications of β < 1 in FRU Regressions.

26.2 Consumption-CAPM.

26.3 Affine Models of FX Returns.

26.4 FRU and Cash-in-Advance Models.

26.5 Summary.

27 Exchange Rate and Fundamentals.

Aims.

27.1 Monetary Models.

27.2 Testing the Models.

27.3 New Open-Economy Macroeconomics.

27.4 Summary.

28 Market Risk.

Aims.

28.1 Measuring VaR.

28.2 Mapping Assets: Simplifications.

28.3 Non-Parametric Measures.

28.4 Monte Carlo Simulation.

28.5 Alternative Methods.

28.6 Summary.

Appendix I: Monte Carlo Analysis and VaR.

Appendix II: Single Index Model (SIM).

29 Volatility and Market Microstructure.

Aims.

29.1 Volatility.

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.

29.7 Summary.

References.

Recommended Reading.

Index.

  • Updated charts and cases studies.
  • New companion website allowing students to put theory into practice and to test their knowledge through questions and answers.
  • Chapters on Monte Carlo simulation, bootstrapping and market microstructure.
  • Covers the most recent theoretical and econometric/empirical advances in the financial markets field.
  • Empirical results illustrate technical theories.
  • Lucid and accessible - the reader progresses from simple to more complex models.
  • Skillfully blends theory and practice.