What drives volatility on financial markets? This paper takes a comprehensive look at the predictability of financial market volatility by macroeconomic and financial variables. We go beyond forecasting stock market volatility (by large the focus in previous studies) and additionally investigate...

Models for the conditional joint distribution of the U.S. Dollar/Japanese Yen and Euro/Japanese Yen exchange rates, from November 2001 until June 2007, are evaluated and compared. The conditional dependency is allowed to vary across time, as a function of either historical returns or a...

Out-of-sample tests of forecast performance depend on how a given data set is split into estimation and evaluation periods, yet no guidance exists on how to choose the split point. Empirical forecast evaluation results can therefore be difficult to interpret, particularly when several values of...

We establish the equivalence between a commonly used out-of-sample test of equal predictive accuracy and the difference between two Wald statistics. This equivalence greatly simpli?es the computational burden of calculating recursive out-of-sample tests and evaluating their critical values. Our...

In this paper we are interested in the term structure of futures contracts on oil. The objective is to specify a relatively parsimonious model which explains data well and performs well in a real time out of sample forecasting. The dynamic Nelson-Siegel model is normally used to analyze and...

This chapter surveys the methods available for extracting forward-looking information from option prices. We consider volatility, skewness, kurtosis, and density forecasting. More generally, we discuss how any forecasting object which is a twice differentiable function of the future realization...

We construct daily house price indices for ten major U.S. metropolitan areas. Our calculations are based on a comprehensive database of several million residential property transactions and a standard repeat-sales method that closely mimics the methodology of the popular monthly Case-Shiller...

Stock return predictability is subject to great uncertainty. In this paper we use the model confidence set approach to quantify uncertainty about expected utility from investment, accounting for potential return predictability. For monthly US data and six representative return prediction models,...

The VPIN, or Volume-synchronized Probability of INformed trading, metric is introduced by Easley, Lopez de Prado and O'Hara (ELO) as a real-time indicator of order flow toxicity. They find the measure useful in predicting return volatility and conclude it may help signal impending market...

Easley, Lopez de Prado and O'Hara introduce VPIN as a real-time indicator of order flow toxicity. They find it useful for monitoring order fl ow imbalances and signaling impending market turmoil, exemplified by the ash crash. They also deem VPIN a good forecaster of short-term volatility. In...