The keys of predictability : a comprehensive study
Giovanni Barone-Adesi (Università della Svizzera italiana and Swiss Finance Institute), Antonietta Mira (Università della Svizzera italiana), Matteo Pisati (Università della Svizzera italiana)
The problem of market predictability can be decomposed into two parts: predictive models and predictors. At first, we show how the joint employment of model selection and machine learning models can dramatically increase our capability to forecast the equity premium out-of-sample. Secondly, we introduce batteries of powerful predictors which brings the monthly S&P500 R-square to a high level of 24%. Finally, we prove how predictability is a generalized characteristic of U.S. equity markets. For each of the three parts, we consider potential and challenges posed by the new approaches in the asset pricing field