Incluye referencias bibliográficas (páginas 473-501) e índice.

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 -- I. Foundations: 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 Definitions of returns ; 2.6 Further examples of time series of returns -- 3. Stochastic processes: definitions 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 specifications ; 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 observations -- 4. Stylized facts for financial returns: 4.1 Introduction ; 4.2 Summary statistics ; 4.3 Average returns and risk premia ; 4.4 Standard deviations ; 4.5 Calendar effects ; 4.6 Skewness and kurtosis ; 4.7 The Shape of the returns distribution ; 4.8 Probability distributions for returns ; 4.9 Autocorrelations of returns ; 4.10 Autocorrelations 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: autocorrelations of a squared linear process -- 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 calculations ; 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 ; 6.4 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 1; 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 calculations 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 -- III. Volatility processes: 8. An introduction to volatility: 8.1 Definitions of volatility ; 8.2 Explanations of changes in volatility ; 8.3 Volatility and information arrivals ; 8.4 Volatility and the stylized facts for returns ; 8.5 Concluding remarks -- 9. ARCH models: definitions and examples: 9.1 Introduction ; 9.2 ARCH(1) ; 9.3 GARCH ; 9.4 An Exchange rate example of the GARCH 1 1 model ; 9.5 A General ARCH framework ; 9.6 Nonnormal conditional distributions ; 9.7 Asymmetric volatility models ; 9.8 Equity examples of asymmetric volatility models ; 9.9 Summary -- 10. ARCH Models: selection and likelihood methods: 10.1 Introduction ; 10.2 Asymmetric volatility: further specifications and evidence ; 10.3 Long memory ARCH models ; 10.4 Likelihood methods ; 10.5 Results from hypothesis tests ; 10.6 Model building ; 10.7 Further volatility specifications ; 10.8 Concluding remarks ; 10.9 Appendix: formulae for the score vector -- 11. Stochastic volatility models: 11.1 Introduction ; 11.2 Motivation and definitions ; 11.3 Moments of independent sv processes ; 11.4 Markov chain models for volatility ; 11.5 The standard stochastic volatility model ; 11.6 Parameter estimation for the standard sv model ; 11.7 An example of SV model estimation for exchange rates ; 11.8 Independent SV models with heavy tails ; 11.9 Asymmetric stochastic volatility models ; 11.10 Long memory SV models ; 11.11 Multivariate stochastic volatility models ; 11.12 ARCH versus SV ; 11.13 Concluding remarks ; 11.14 Appendix: filtering equations -- IV. High-frequency methods: 12. High-frequency data and models: 12.1 Introduction ; 12.2 High-frequency prices ; 12.3 One day of high-frequency price data ; 12.4 Stylized facts for intraday returns ; 12.5 Intraday volatility patterns ; 12.6 Discrete-time intraday volatility models ; 12.7 Trading rules and intraday prices ; 12.8 Realized volatility: theoretical results ; 12.9 Realized volatility: empirical results ; 12.10 Price discovery ; 12.11 Durations ; 12.12 Extreme price changes ; 12.13 Daily high and low prices ; 12.14 Concluding remarks ; 12.15 Appendix: formulae for the variance of the realized volatility estimator -- V. Inferences from option prices: 13. Continuous-time stochastic processes: 13.1 Introduction ; 13.2 The wiener process ; 13.3 Diffusion processes ; 13.4 Bivariate diffusion processes ; 13.5 Jump processes ; 13.6 Jump-diffusion processes ; 13.7 Appendix: a construction of the wiener process ; 14. Option pricing formulae ; 14.1 Introduction ; 14.2 Definitions, notation, and assumptions ; 14.3 Black-Scholes and related formulae ; 14.4 Implied volatility ; 14.5 Option prices when volatility is stochastic ; 14.6 Closed-form stochastic volatility option prices ; 14.7 Option prices for arch processes ; 14.8 Summary ; 14.9 Appendix: Heston's option pricing formula -- 15. Forecasting volatility: 15.1 Introduction ; 15.2 Forecasting methodology ; 15.3 Two measures of forecast accuracy ; 15.4 Historical volatility forecasts ; 15.5 Forecasts from implied volatilities ; 15.6 ARCH forecasts that incorporate implied volatilities ; 15.7 High-frequency forecasting results ; 15.8 Concluding remarks -- 16. Density prediction for asset prices: 16.1 Introduction ; 16.2 Simulated real-world densities ; 16.3 Risk-neutral density concepts and definitions ; 16.4 Estimation of implied risk-neutral densities ; 16.5 Parametric risk-neutral densities ; 16.6 Risk-neutral densities from implied volatility functions ; 16.7 Nonparametric RND methods ; 16.8 Towards recommendations ; 16.9 From risk-neutral to real-world densities ; 16.10 An excel spreadsheet for density estimation ; 16.11 Risk aversion and rational RNDs ; 16.12 Tail density estimates ; 16.13 Concluding remarks.