Mean-standard deviation-conditional value-at-risk portfolio optimization

The use of variance as a risk measure is limited by its non-coherent nature. On the other hand, standard deviation has been demonstrated as a coherent and effective measure of market volatility. This paper suggests the use of standard deviation in portfolio optimization problems with cardinality constraints and short selling, specifically in the mean-conditional value at risk framework. It is shown that, subject to certain conditions, this approach leads to lower standard deviation. Empirical results obtained from experiments on the S P index data set from 2016-2021 using various numbers of stocks and confidence levels indicate that the proposed model outperforms existing models in terms of Sharpe ratios.