Asset allocation with dynamic conditional correlations (DCC) model: an implementation in the R program

This study demonstrates how to use the R programming language to estimate time varying volatility in returns and correlations between several asset classes by employing a model called Dynamic Conditional Correlations (DCC) and to form portfolios using those estimates. A number of user-written R commands are presented in the study, designed for practitioners, academics, and students of nance interested in active portfolio optimization. The study uses these commands to access nancial data, analyze statistical characteristics of the data, estimate dynamic correlations, and nally compute the optimal weights of several asset classes in portfolios optimized for a variety of purposes.