RT Journal Article
SR Electronic
T1 Universal Arbitrage-Free Estimation of State Price Density
JF The Journal of Derivatives
FD Institutional Investor Journals
SP jod.2020.1.123
DO 10.3905/jod.2020.1.123
A1 Qi Hu
A1 David Newton
YR 2020
UL https://pm-research.com/content/early/2020/11/21/jod.2020.1.123.abstract
AB Given the valuable information content of Arrow-Debreu prices, the recovery of a well-behaved state price density is of considerable importance. However, this is a nontrivial task because of data limitation and the complex arbitrage-free constraints. In this article, we develop a more effective linear programming support vector machine estimator for state price density, which incorporates no-arbitrage restrictions and bid-ask spread. This method does not depend on a particular approximation function and framework and is, therefore, universally applicable. In a parallel empirical study, we apply the method to options on the S&P 500, showing it to be accurate and smooth.TOPICS: Derivatives, optionsKey Findings▪ Recovery of a well-behaved state price density is an important but nontrivial because of data limitation and the complex arbitrage-free constraints.▪ We develop a universally applicable linear programming support vector machine estimator for state price density that incorporates no-arbitrage restrictions and bid-ask spread.▪ We apply the method empirically to options on the S&P 500, showing it to be accurate and smooth.