The entropy valuation of option (Stutzer, 1996) provides a risk-neutral probability distribution (RND, an equivalent martingale measure) as the pricing measure by minimizing the Kullback–Leibler (KL) divergence between the empirical probability distribution and its risk-neutral counterpart....

Recently the entropy-based valuation of European options (Stutzer, 1996) has been extended to American option pricing. In this paper, we improve the pricing accuracy by incorporating informative risk-neutral moments (RNMs), which are recovered from a set of market-available option data, as...

This paper tests empirically the recently proposed canonical least-squares Monte-Carlo (CLM) method for pricing American options. Market data used are daily last prices for the American style S&P 100 Index puts (OEX puts) and IBM puts from 30 July 2008 to 30 January 2009, the period of which...

This article constructs an entropy pricing framework by incorporating a set of informative risk-neutral moments (RNMs) extracted from the market-available options as constraints. Within the RNM-constrained entropic framework, a unique distribution close enough to the correct one is obtained, and...

We propose a new nonparametric method for valuing American options. We extract the risk neutral moments using a set of option data and incorporate them into the entropy framework as constraints to recover the risk-neutral pricing measure. With the recovered risk-neutral measure, we generate...

Recently, two types of innovative estimators of the quadratic variation (QV), namely RVB and RVQ estimators, are established in Yu (2020) for an asset's log-price process permitting time-varying spot volatility. Both RVB and RVQ utilize either higher-order- or cross-terms of log-return and hence...