Asset Price Dynamics, Volatility, and Prediction资产价格动力学、易变性与预测 pdf kindle caj 下载 azw3 umd 电子版 夸克云

This book shows how current and recent market prices convey information about the probability distributi*** that govern future prices. Moving beyond purely theoretical models, Stephen Taylor applies methods ***ed by empirical research of equity and foreign exchange markets to show how daily and more frequent asset prices, and the prices of option contracts, can be used to c***truct and assess predicti*** about future prices, their volatility, and their probability distributi***.

Stephen Taylor provides a comprehensive introduction to the dynamic behavior of asset prices, relying on finance theory and statistical evidence. He uses stochastic processes to define mathematical models for price dynamics, but with less mathematics than in alternative texts. The key topics covered include random walk tests, trading rules, ARCH models, stochastic volatility models, high-frequency datasets, and the information that option prices imply about volatility and distributi***.

Asset Price Dynamics, Volatility, and Prediction is ideal for students of economics, finance, and mathematics who are studying financial econometrics, and will enable researchers to identify and apply appropriate models and methods. It will likewise be a valuable resource for quantitative ***ysts, fund managers, risk managers, and investors who seek realistic expectati*** about future asset prices and the risks to which they are exposed.

Preface

1. Introduction

　1.1 Asset Price Dynamics

　1.2 Volatility

　1.3 Prediction

　1.4 Information

　1.5 Contents

　1.6 Software

　1.7 Web Resources

PART I: Foundati***

　2. Prices and Returns

　　2.1 Introduction

　　2.2 Two Examples of Price Series

　　2.3 Data-Collection Issues

　　2.4 Two Returns Series

　　2.5 Definiti*** of Returns

　　2.6 Further Examples of Time Series of Returns

　3. Stochastic Processes: Definiti*** and Examples

　　3.1 Introduction

　　3.2 Random Variables

　　3.3 Stationary Stochastic Processes

　　3.4 Uncorrelated Processes

　　3.5 ARMA Processes

　　3.6 Examples of ARMA 1 1 Specificati***

　　3.7 ARIMA Processes

　　3.8 ARFIMA Processes

　　3.9 Linear Stochastic Processes

　　3.10 Continuous-Time Stochastic Processes

　　3.11 Notation for Random Variables and Observati***

　4. Stylized Facts for Financial Returns

　　4.1 Introduction

　　4.2 Summary Statistics

　　4.3 Average Returns and Risk Premia

　　4.4 Standard Deviati***

　　4.5 Calendar Effects

　　4.6 Skewness and Kurtosis

　　4.7 The Shape of the Returns Distribution

　　4.8 Probability Distributi*** for Returns

　　4.9 Autocorrelati*** of Returns

　　4.10 Autocorrelati*** of Transformed Returns

　　4.11 Nonlinearity of the Returns Process

　　4.12 Concluding Remarks

　　4.13 Appendix: Autocorrelation Caused by Day-of-the-Week Effects

　　4.14 Appendix: Autocorrelati*** of a Squared Linear Process

PART II: Conditional Expected Returns

　5. The Variance-Ratio Test of the Random Walk Hypothesis

　　5.1 Introduction

　　5.2 The Random Walk Hypothesis

　　5.3 Variance-Ratio Tests

　　5.4 An Example of Variance-Ratio Calculati***

　　5.5 Selected Test Results

　　5.6 Sample Autocorrelation Theory

　　5.7 Random Walk Tests Using Rescaled Returns

　　5.8 Summary

　6. Further Tests of the Random Walk Hypothesis

　　6.1 Introduction

　　6.2 Test Methodology

　　6.3 Further Autocorrelation Tests

　　*** Spectral Tests

　　6.5 The Runs Test

　　6.6 Rescaled Range Tests

　　6.7 The BDS Test

　　6.8 Test Results for the Random Walk Hypothesis

　　6.9 The Size and Power of Random Walk Tests

　　6.10 Sources of Minor Dependence in Returns

　　6.11 Concluding Remarks

　　6.12 Appendix: the Correlation between Test Values for Two Correlated Series

　　6.13 Appendix: Autocorrelation Induced by Rescaling Returns

　7. Trading Rules and Market Efficiency

　　7.1 Introduction

　　7.2 Four Trading Rules

　　7.3 Measures of Return Predictability

　　7.4 Evidence about Equity Return Predictability

　　7.5 Evidence about the Predictability of Currency and Other Returns

　　7.6 An Example of Calculati*** for the Moving-Average Rule

　　7.7 Efficient Markets: Methodological Issues

　　7.8 Breakeven Costs for Trading Rules Applied to Equities

　　7.9 Trading Rule Performance for Futures Contracts

　　7.10 The Efficiency of Currency Markets

　　7.11 Theoretical Trading Profits for Autocorrelated Return Processes

　　7.12 Concluding Remarks

PART III: Volatility Processes

　8. An Introduction to Volatility

　9. ARCH Models: Definiti*** and Examples

　10. ARCH Models: Selection and Likelihood Methods

　11. Stochastic Volatility Models

PART IV: High-Frequency Methods

　12. High-Frequency Data and Models

PART V: Inferences from Option Prices

　13. Continuous-Time Stochastic Processes

　14. Option Pricing Formulae

　15. Forecasting Volatility

　16. Density Prediction for Asset Prices

Symbols

References

Author Index

Subject Index

Stephen J. Taylor is Professor of Finance at Lancaster University, England. He is the author of "Modelling Financial Time Series" and many influential articles about applicati*** of financial econometrics.

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