"An introduction to the theory and practice of financial simulation and optimization In recent years, there has been a notable increase in the use of simulation and optimization methods in the financial industry. Applications include portfolio allocation, risk management, pricing, and capital...

Engaging and accessible, this book and its companion Web site provide an introduction to the simulation and optimization techniques most widely used in finance, while, at the same time, offering essential information on the financial concepts surrounding these applications. This practical guide...

Bayesian Methods in Finance provides a detailed overview of the theory of Bayesian methods and explains their real-world applications to financial modeling. While the principles and concepts explained throughout the book can be used in financial modeling and decision making in general, the...

While existing asset pricing studies focus on macroeconomic variables to predict stock market risk premium, we find that an aggregate index of corporate activities has substantially greater predictive power both in- and out-of sample, and yields much greater economic gain for a mean-variance...

We analyze the joint out-of-sample predictive ability of a comprehensive set of 299 firm characteristics for cross-sectional stock returns. We develop a cross-sectional out-of-sample R2 statistic that provides an informative measure of the accuracy of cross-sectional return forecasts in terms of...

We find a pricing error profitability pattern for well-known asset pricing models: the CAPM, Fama-French, Hou-Xue-Zhang, Stambaugh-Yuan, and Daniel-Hirshleifer-Sun. A trading strategy that buys low pricing error stocks and sells high pricing error ones earns significant average and risk-adjusted...