The objective of this paper is to present the technical efficiency of individual companies and their respective groups of Bangladesh stock market (i.e., Dhaka Stock Exchange, DSE) by using two risk factors (co-skewness and co-kurtosis) as the additional input variables in the Stochastic Frontier Analysis (SFA). The co-skewness and co-kurtosis are derived from the Higher Moment Capital Asset Pricing Model (H-CAPM). To investigate the contribution of these two factors, two types of technical efficiency are derived: (1) technical efficiency with considering co-skewness and co-kurtosis (WSK) and (2) technical efficiency without considering co-skewness and co-kurtosis (WOSK). By comparing these two types of technical efficiency, it is noticed that the technical efficiency of WSK is higher than the technical efficiency of WOSK for the individual companies and their respective groups. As per available literature in the context Bangladesh stock market, no study has been conducted thus far to measure technical efficiency of companies and their respective groups by using the risk factors which are derived from the H-CAPM. In this research, the link between H-CAPM and SFA is established for measuring technical efficiency and it is believed that the findings of this study may be applied to other emerging stock markets. 1. Introduction In the finance literature, CAPM is one of the most important developments which predicts that the expected return on an asset is linearly related to systemic risk. But, because of the large number of empirical evidence against the CAPM, the financial researchers started to search for a substitute model to describe the risk-return relationship of risky assets. This searching had led the researchers to the extension of the CAPM. The higher moment CAPM was initially proposed by Rubinstein [1] and sequentially developed by Kraus and Litzenberger [2], Fang and Lai [3], Hwang and Satchell [4], and Harvey and Siddique [5]. Rubinstein [1] noted that when the market returns are not normal (but skewed or leptokurtic), the standard CAPM is not enough to price equity returns. So, he recommended for the addition of higher moments. Kraus and Litzenberger [2] extended the Sharpe-Lintner CAPM model by introducing the third moment “skewness” and examined the effect of skewness in return distributions. They found that the systematic skewness (co-skewness) is capable of explaining the behavior of asset returns which was not fully explained by the traditional CAPM. Fang and Lai [3] showed that in the presence of skewness and kurtosis in asset return
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