We design a novel empirical framework to examine market efficiency through out-of-sample(OOS) predictability. We frame the classic empirical asset pricing problem as a machine learningclassification problem. We construct classification models to predict return states. The prediction- based...

Although the trade-boosting effect of the Internet is well-documented, two critical questions remain unsatisfactorily answered. First, does the Internet benefit the trade in services greater than the trade in goods? Second, does the Internet eliminate or at least, weaken the negative effect of...

I construct a 300-year monthly testing sample for the UK market and study the return predictability in both the UK and the US. I conduct out-of-sample tests with 312 prediction setups based on 23 popular predictors, 3 model updating windows, and 3 common forecast combinations. Over the long run,...

We analyze the relationship between insider trading density and the future stock returns in Chinese listed companies. We introduce a new aspect of the trading pattern, insider trading density, to investigate the information advantage held by insiders. Insiders who trade at a low density during...