Portfolio Optimization Using Value-at-Risk: Assessment Using Historical Simulation Method for Energy Stocks

Debasis PATNAIK, Utkarsh TIWARI

Abstract


Value at Risk is an important measure of market risk. It gives the maximum amount of loss in a portfolio of assets. Conditional Value-at-Risk covers the amount of losses exceeding Value-at-Risk and does not suffer from the functional problems (Non-Convexity and non-additivity. See Rockafellar and Uryasev (2000)) of VaR. Here VaR is calculated using Historical Simulation and portfolio optimization is done with the help of Genetic Algorithm. This methodology is applied to energy stocks of different countries. Optimization is done to maximize returns and minimize risk separately as well as for combined multi-objective optimization

Keywords


Value-at-Risk, Historical simulation, Genetic Algorithm, Portfolio optimization.


DOI
10.12783/dtcse/mcsse2016/10953

Refbacks

  • There are currently no refbacks.