This paper provides an empirical study on the predictability of implied volatility using dataset collected from the London over-the-counter currency option market. The present work is motivated by the lack of empirical studies that address implied volatility characteristics across various...

A growing body of literature confirms the significance of the commodity futures basis factor: It has a significantly positive premium and it explains the cross-section of commodity-futures excess returns. We extend the literature by documenting predictive relation between this factor and the...

Divergence in investor beliefs is an important driver of the negative relation between option trading volume and future stock returns. We find a strong negative relation between disagreement-based option trades and future stock returns, and this relation is markedly amplified when the underlying...

Drawing upon more than 12 million observations over the period from 1996 to 2020, we find that allowing for nonlinearities significantly increases the out-of-sample performance of option and stock characteristics in predicting future option returns. Besides statistical significance, the...

We investigate the cross-sectional return predictability of delta-hedged equity options using machine learning and big data. Drawing upon more than 12 million observations over the period from 1996 to 2020, we find that allowing for nonlinearities significantly increases the out-of-sample...

In an empirical study of Standard & Poor's 500 index options, this paper analyses the predictability of future market excess returns by means of decomposed higher-moment risk premiums. The study proposes a new measure of kurtosis risk premium and suggests a decomposition of higher-moment risk...

Which market has leading informational advantage: stocks or options? Using large set of stock and option characteristics, and machine learning, we provide a comprehensive analysis of which characteristics are the first order importance predictors of options and stock returns. First, we find that...

We document that a theoretically founded, real-time, and easy-to-implement option-based measure, termed synthetic-stock difference (SSD), accurately estimates the part of stock's expected return arising from stock's transaction costs. We calculate SSD for U.S. optionable stocks. SSD can be more...

We investigate whether there are predictable patterns in the dynamics of higher order risk-neutral moments extracted from the market prices of S&P 500 index options. To this end, we conduct a horse race among alternative forecasting models within an out-of-sample context over various forecasting...

We forecast monthly Value at Risk (VaR) and Conditional Value at Risk (CVaR) using option market data and four different econometric techniques. Independently from the econometric approach used, all models produce quick to estimate forward-looking risk measures that do not depend from the amount...