A New Wavelet Regression Based Approach That Calculates Portfolio Risk

Abstract

For investors, one of the primary methods to reduce their risks is to create a portfolio by diversifying their investments. In studies conducted on portfolio management, a relation between the highest income and the lowest risk is aimed at. This is because investors tend to avoid risk and chose minimum level of risk at a given level of income, while choosing the highest level of income at a given risk level. In this case, accurate calculation of portfolio risk is crucial in terms of not misleading investors.

In recent years, the statistically based Value at Risk (VaR) method has started to be widely used in determining market risk. VaR summarizes the maximum (worst) loss, at aimed time and at a given level of confidence. In the present study a new VaR calculation approach was proposed by using Wavelet regression. Effectiveness of this new method was tried to be demonstrated with an exemplary case.