1. Financial time series and their characteristics --
2. Linear time series analysis and its applications --
3. Conditional heteroscedastic models --
4. Nonlinear models and their applications --
5. High-frequency data analysis and market microstructure --
6. Continuous-time models and their applications --
7. Extreme values, quantile estimation, and value at risk --
8. Multivariate time series analysis and its applications --
9. Principal component analysis and factor models --
10. Multivariate volatility models and their applications --
11. State-space models and Kalman filter --
12. Markov chain Monte Carlo methods with applications.

The Second Edition of this critically acclaimed text provides a comprehensive and systematic introduction to financial econometric models and their applications in modeling and predicting financial time series data. This latest edition continues to emphasize empirical financial data and focuses on real-world examples. Following this approach, readers will master key aspects of financial time series, including volatility modeling, neural network applications, market microstructure and high-frequency financial data, continuous-time models and Ito's Lemma, Value at Risk, multiple returns analysis, financial factor models, and econometric modeling via computation-intensive methods." "The tools provided in this text aid readers in developing a deeper understanding of financial markets through firsthand experience in working with financial data. This is an ideal textbook for MBA students as well as a reference for researchers and professionals in business and finance."--Jacket.

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