We backtest 59 instruments and investigate the predictability of daily returns using Bayesian variable selection methods. Through these models we show the importance of variable selection and reduction of over tting. We also visualize how... more
We backtest 59 instruments and investigate the predictability of daily returns using Bayesian variable selection methods. Through these models we show the importance of variable selection and reduction of over tting. We also visualize how the driving factors of daily returns from di erent classes vary over time. Predicting daily returns' magnitude is again con rmed to be a hard task but we show that for some instruments it is possible to achieve above average hit-rates that could lead to pro table strategies. Simulation results show that predictability levels of daily returns also vary over time.
