A number of studies on the S&P 500 index options market claim that the no arbitrage assumption cannot be rejected for this market because either the martingale restriction defined in Longstaff (1995) cannot be rejected by the data, or, even when it is rejected, a large proportion of the...

We test the accuracy and hedging performance of the deltas given by a range of nonparametric measure changes. The nonparametric models accurately estimate deltas across a number of asset price dynamics. The optimal nonparametric measure change displays superior estimation bias, which depends on...

Haley and Walker (2010) present the Euclidean and Empirical Likelihood nonparametric option pricing models as alternative tilts to Stutzer's (1996) Canonical pricing method. We empirically test the comparative strengths of each of these methods using a large sample of traded options on the...

The aim of this paper is to determine whether forward-looking option-implied returns forecasts lead to better out-of-sample portfolio performance than conventional time series models. We consider a simple two-asset setting with a risk-free asset and the S&P 500 index the risky asset with monthly...

Alcock and Carmichael (2008) introduce a nonparametric method for pricing American style options that is derived from the canonical valuation developed by Stutzer (1996). While the statistical properties of this nonparametric pricing methodology have been studied in a controlled simulation...

In this paper we solve the discrete time mean-variance hedging problem when asset returns follow a multivariate autoregressive hidden Markov model. Time dependent volatility and serial dependence are well established properties of financial time series and our model covers both. To illustrate...

We find that option-implied information such as forward-looking variance, skewness and the variance risk premium are sensitive to the way the volatility surface is constructed. For some state-of-the-art volatility surfaces, the differences are economically surprisingly large and lead to...

This paper presents the first comparison of the accuracy of density forecasts for stock prices. Six sets of forecasts are evaluated for DJIA stocks, across four forecast horizons. Two forecasts are risk-neutral densities implied by the Black-Scholes and Heston models. The third set are...

We propose a novel method of estimating default probabilities using equity option data. The resulting default probabilities are highly correlated with estimates of default probabilities extracted from CDS spreads, which assume constant recovery rates. Additionally, the option implied default...

Least-squares methods enable us to price Bermudan-style options by Monte Carlo simulation. They are based on estimating the option continuation value by least squares. We show that the Bermudan price is maximized when this continuation value is estimated near the exercise boundary, which is...