1

1-23

23

 

John Wiley & Sons, Inc. (Visit publisher website)

2005

English

 

 

 

Intermediate

 

 

Quantitative analysis, financial time series, asset returns, one-period simple return, multiperiod simple return, continuous compounding, portfolio return, dividend payment, excess return, return distribution properties, joint distribution, marginal distribution, conditional distribution, random variable moments, mean, variance, skewness, kurtosis, normal distribution, lognormal distribution, stable distribution, mixture of normal distributions, multivariate returns, likelihood function of returns, empirical properties of asset returns

 

This chapter provides an overview of the statistical modelling of financial asset returns, beginning with return definitions and ending with the statstical properties exhibited by equity returns, interest rates and exchange rates. The strengths and weakness of competing return definitions and distribtuional assumptions are clearly illustrated. Chapter ending review questions provide general data handling exercises.

 

1.1 Asset Returns
1.2 Distributional Properties of Returns
1.2.1 Review of Statistical Distributions and Their Moments
1.2.2 Distributions of Returns
1.2.3 Multivariate Returns
1.2.4 Likelihood Function of Returns
1.2.5 Empirical Properties of Returns
1.3 Processes Considered
Exercises
References

 

If you are interested in purchasing the book, please click here.

 

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 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 author begins with the basic characteristics of financial time series data, setting the foundation for the three main topics:

* Analysis and application of univariate financial time series
* Return series of multiple assets
* Bayesian inference in finance methods

This new edition is a thoroughly revised and updated text, including the addition of S-Plus® commands and illustrations. Among the new material, readers will find:

* Consistent covariance estimation under heteroscedasticity and serial correlation
* Alternative approaches to volatility modeling
* Financial factor models
* State-space models
* Kalman filtering
* Estimation of stochastic diffusion models

This is an ideal textbook for MBA students as well as a reference for researchers and professionals in business and finance.