Stochastic dominance applications on lognormally distributed stock return data

Abstract

In investing, investors consider the movement of return to find the right investment decision. Stochastic Dominance (SD) rule shows the dominant stock among stock returns where a particular distribution can be added to give more relevant results. The lognormal distribution represents the value of return on the capital market because it is positively skewed. The aim of this research is to apply stochastic dominance method on stock return with the assumption that data comes from a lognormally distributed population. The daily closing stock price data from stock indexes listed on the Indonesia Stock Exchange (IDX) were used in this research. SD method with log normal distribution were applied on the data after testing whether stock returns follow the lognormal distribution. Based on the analysis, the method used in this research can be applied to JKII, LQ45, SRI KEHATI, JKII 70, ISSI, JKAGRI, JKBIND, JKCONS, JKMING, and KOMPAS 100 indexes. It can be concluded that additional distribution information on stock returns data increase the decision rule of SD.