Use Advanced Staistical and Optimization Techniques for Stock Portfolio Optimization
A R-implementation of portfolio optimization code applied on six stocks over a period of five years.The code uses ARIMA and GARCH to filter the volaltity from the time series. The dependency structure between various stocks are modelled using a vine copula structure. Finally CVaR (Conditional Value at Risk) is applied for two scenarios (Long Term and Short Term) to get optimized portfolio weights