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.