What is the market impact of predictable order flow? Leveraged exchange-traded products are useful for answering this question because they generate daily rebalancing flows whose size, sign and timing are predictable. This paper presents new evidence from the market for leveraged volatility...

We propose option-implied measures of conditional asymmetry based upon quantiles and expectiles inferred from weekly options. All quantities are by construction forward looking and estimated non-parametrically through a novel arbitrage-free natural smoothing spline technique that produces quick...

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...

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...

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...

This paper aims at contributing to the literature in three ways: First, we re-evaluate the performance of popular Value-at-Risk (VaR) estimation methods on freight rates amid the adverse economic consequences of the recent financial and sovereign debt crisis. Secondly we provide a detailed and...

A central consideration for the use of any pricing model is the ability to calibrate that model to market or historical prices. Whether the information needed by the model can be effectively implied from the data or not is one part of the calibration problem. However, in many applications, the...

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...

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...