Improvements the Performances of the Fama-French Model with New Factors: Evidence from US Technology Industry

Fama-French 3-factor (FF3F) and 5-factor (FF5F) model is one of the most used asset pricing models after CAPM. However, there are still scopes to improve the efficiency of this model by adding further factors. This research aims to conduct research on such asset pricing models and identify whether the accuracy of the FF model increases with the inclusion of new factors or not. Therefore, this study chooses technical indicators including MACD and CCI to add to the Fama French multifactor model (FFNF) to show whether this factor can improve the performance and robustness of the model. It will also compare the result with other popular asset pricing models like CAPM, FF3F and FF5F models to get a comprehensive result. This report will use weekly trading data of 10 US technology firms and will conduct regression analysis to evaluate the models. From the regression result it can be seen that the multifactor model with technical indicators shows much more precision in predicting asset price changes. All the parameters like R square value, Standard error value, and P-value proved that the multifactor is more efficient compared to the other three models.