|| The objective of this study is to discover the sources of securities return in forecasting stock return from different sides of potential factors including fundamental and market information. We test currency sensitivity, earnings variability, earnings yield, growth, leverage, trading activity, momentum, size, value, volatility, capital spending discipline, free cash flow, efficiency, solvency, earnings quality, corporate finance policy and technical 17 factors basing on different factor dimensions in this study. We construct a Taiwan multi-factor model by using the most significant factors for universal stocks according to 0HMSCI Barra’s Multiple-Factor Modeling process, and then apply market neutral investment to build portfolios for performance back-testing.|
As a result, the most significant top five factors in forecasting are respectively “Volatility2,” “Earnings Quality1,” “Trading1,” “Volatility1” and “Growth1” factors. In addition, we find the most useless bottom four factors in forecasting are respectively “Size1,” “Earning Yield1,” “Value1,” and “Capital Spending1.” No matter which strategies we adopt to build the portfolio, the Sharpe ratios of back-testing performance are all higher than the Benchmark, and all bring stable and consistent performance. It actually proves that this model is robust.