Recent research suggests that machine learning models dominate traditional linear models in predicting cross-sectional stock returns. We confirm this finding when predicting one-month forward-looking returns based on a set of common stock characteristics, including predictors such as short-term...

We document significant persistence in the market timing performance of active individual investors, suggesting that some investors are skilled at timing. Using data on all trades by active Finnish individual investors over almost 15 years, we also show that the net purchases of skilled versus...

We provide a historical perspective focusing on Ziemba's experiences and research on the bond-stock earnings yield differential model (BSEYD) starting from when he first used it in Japan in 1988 through to the present in 2014. The model has called many but not all crashes. Those called have high...

We suggest that the term structure of volatility futures (e.g. VIX futures) shows a clear pattern of dependence on the current level of VIX index. At the low level of VIX (below 20) the term structure is highly upward sloping; at the high VIX level (over 30) it is strongly downward sloping. We...

The efficient market hypothesis describes an efficient market as one in which investors cannot consistently predict stock returns because prices instantly reflect all the information flowing into the market. However, return predictability has been documented in many markets. This study tests the...

This study discusses the trading behavior of foreign investors with respect to economic uncertainty in the South Korean stock market from a time-varying perspective. We employ a news-based measure of economic uncertainty along with the model of time-varying parameter vector autoregression with...

We show that aggregate insider trading (AIT) in the S&P 500 is a reliable predictor of the U.S. equity premium, while AIT outside the S&P 500 seems to be uninformative. Aggregate trading of S&P 500 insiders outperforms a broad set of well-established predictors considering in- and out-of-sample...

We construct a global implied volatility surface by combining information from the index options of twenty countries and regions. The convexity of the global surface positively predicts equity premia around the world, in- and out-of-sample, at horizons from one to twelve months. Semi-annually,...

This paper uses Monte Carlo techniques to assess the loss in terms of forecast accuracy which is incurred when the true DGP exhibits parameter instability which is either overlooked or incorrectly modelled. We find that the loss is considerable when a FCM is estimated instead of the true TVCM,...

This paper examines return predictability when the investor is uncertain about the right state variables. A novel feature of the model averaging approach used in this paper is to account for finite-sample bias of the coefficients in the predictive regressions. Drawing on an extensive...