We apply machine learning techniques and use stock characteristics to predict the cross-section of stock returns in 33 international markets. We conduct a stringent out-of-sample test to examine concerns about overfitting: the models are trained with past U.S. data and used to predict...

The spillover effects of interconnectedness between financial assets are decomposed into both sources of shocks and whether they amplify or dampen volatility conditions in the target market. We use historical decompositions to rearrange information from a VAR which includes sources, direction...

We investigate the impact of order flow imbalance (OFI) on price movements in equity markets in a multi-asset setting. First, we show that taking into account multiple levels of the order book when defining order book imbalance leads to higher explanatory power for the contemporaneous price...

As defined contribution (DC) plans have grown and have increasingly become the primary retirement savings vehicle, asset allocators are increasingly interested in incorporating illiquid private assets in these retirement funds to offer participants access to investment portfolios and...

We examine return predictability with machine learning in 46 international stock markets. We calculate 148 stock characteristics and use them to feed a repertoire of different models. The algorithms extract predictability mainly from simple, yet popular, factor types—such as momentum,...

We study the performance of many traditional and novel, text-based variables for in-sample and out-of-sample forecasting of oil spot, futures, and energy company stock returns, and changes in oil volatility, production, and inventories. After controlling for small-sample biases, we find evidence...

For nearly every major stock market there exist equity and implied volatility indices. These play important roles within finance: be it as a benchmark, a measure of general uncertainty or a way of investing or hedging. It is well known in the academic literature that correlations and higher...

This paper proposes a simple chartist-fundamentalist model in which we allow for nonlinear time variation in chartists' extrapolation rate. Estimation of the model using monthly data for the major currencies vis-a-vis the US dollar shows that the model is significant in-sample and that it has...

The purpose of this paper is to estimate the money demand function of Cagan (1956) using a panel data set covering 27 countries with different economic levels over the period 1988-98. The static fixed effects and the dynamic fixed effects reveal that a money demand equation exists. However, in...