Deep Structural Estimation: With an Application to Option Pricing

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See all articles by Hui Chen

Hui Chen

Massachusetts Institute of Technology; National Bureau of Economic Research (NBER)

Antoine Didisheim

Swiss Finance Institute, UNIL

Simon Scheidegger

University of Lausanne - School of Economics and Business Administration (HEC-Lausanne)

Date Written: February 9, 2021

Abstract

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 one's ability to conduct analyses that require frequent parameter re-estimation. As an empirical application, we compare two popular option pricing models (the Heston and the Bates model with double-exponential jumps) against a non-parametric random forest model. We document that: a) the Bates model produces better out-of-sample pricing on average, but both structural models fail to outperform random forest for large areas of the volatility surface; b) random forest is more competitive at short horizons (e.g., 1-day), for short-dated options (with less than 7 days to maturity), and on days with poor liquidity; c) both structural models outperform random forest in out-of-sample delta hedging; d) the Heston model's relative performance has deteriorated significantly after the 2008 financial crisis.

Keywords: Deep Learning, Structural Estimation, Option Pricing, Parameter Stability

JEL Classification: C45, C52, C58, C61, G17

Suggested Citation

Chen, Hui and Didisheim, Antoine and Scheidegger, Simon, Deep Structural Estimation: With an Application to Option Pricing (February 9, 2021). Available at SSRN: https://ssrn.com/abstract=

Hui Chen

Massachusetts Institute of Technology ( email )

50 Memorial Drive
Cambridge, MA 02142
United States
617-324-3896 (Phone)

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Antoine Didisheim

Swiss Finance Institute, UNIL ( email )

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland
0797605012 (Phone)

Simon Scheidegger (Contact Author)

University of Lausanne - School of Economics and Business Administration (HEC-Lausanne) ( email )

Unil Dorigny, Batiment Internef
Lausanne, 1015
Switzerland

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