Enhanced prediction for stock performance of manufacturing companies - Ho Chi Minh city stock exchange
Abstract
Prediction for performance of stocks is undoubtedly vital concerns for every participants of
the market. Many approaches and methods have been conducted with the hope of sorting out
potential targets in the vast number of listed companies in various industries. This research
focuses on five major groups of independent variables: company financial ratio, market
ratios, company size, leverage level of the company, and daily average trading value in the
time frame from 2010 to 2014. By applying logistic regression model with the collected
underlined sample, four variables have been selected for the equation, namely as Cash
earnings per share, Earning before Interest and Tax over Sales, Sales over Total Assets, and
Price to Book Value, applied for Vietnam equity trading market, especially the manufacturing
industry in HOSE. The obtained result shows that it has a statistically and theoretically
correct predicting percentage of 64.2%, which was introduced by SPSS®, while adapting the
practical handout sample, a general accuracy level of 58.33% has been tested.