How does the market makers' aversion to unhedgeable risks influence option prices? We answer this question by introducing a new structural approach: deep replication. With this method, we extract the risk aversion of S&P500 options per contract and per day. Cross-sectionally, we show the...

We introduce a novel numerical framework for pricing American options in high dimensions. Our scheme manages to alleviate the problem of dimension scaling through the use of adaptive sparse grids. We approximate the value function with a low number of points and recursively apply fast...

We propose a novel structural estimation framework in which we train a surrogate of an economic model with deep neural networks. Our methodology alleviates the curse of dimensionality and speeds up the evaluation and parameter estimation by orders of magnitudes, which significantly enhances...