Reduction of Liquidity Proxies by Using Principal Component Analysis in Tehran Capital Markets

The purpose of this study was to investigate the possibility of using principal component analysis method as a tool for data reduction of the proxies of stock liquidity in Tehran Stock Exchange (TSE). First, the initial set of proxies of stock liquidity (8 variables) was identified and after the initial validation tests, the method was implemented at 2 levels: 1) all companies and 2) companies with much data. According to the obtained results, applicability of using this method to reduce the initial set of variables was concluded. The results showed that in both levels of analysis, the method could be used successfully for data reduction of liquidity proxies. Depending on the purpose of different researches, the initial set of liquidity proxies could be appropriately reduced by extracting 2 or 3 main components, while explaining the acceptable part of the total data variance.