We consider derivatives that maximize an investor's expected utility in the stochastic volatility model. We show that the optimal derivative that depends on the stock and its variance significantly outperforms the optimal derivative that depends on the stock only. Such derivatives yield a much...

Ziel dieses Beitrages ist es, die Zusammenhänge zwischen den Binomialmodellen der Operationsbewertung (Replikation bzw. Methode der risikoneutralen Wahrscheinlichkeiten) und dem Black/Scholes Modell aufzuzeigen und zu analysieren...

We introduce a new analytical approach to price American options. Using an explicit and intuitive proxy for the exercise rule, we derive tractable pricing formulas using a short-maturity asymptotic expansion. Depending on model parameters, this method can accurately price options with...

In this paper we construct arbitrage-free market models of stochastic volatility type for one stock, one bank account and a finite family of European call options with various strikes and maturities. We first introduce local implied volatilities and price level as market observables which...

In empirical modeling, there have been two strands for pricing in the options literature, namely the parametric and nonparametric models. Often, the support for the nonparametric methods is based on a benchmark such as theBlack-Scholes model with constant volatility. In this paper, we examine...

This paper investigates the impact of heterogeneous beliefs of professional investors on the currency options market. Using a unique data set with detailed information on the foreign-exchange forecasts of about 50 market participants over more than ten years, we construct an empirical proxy for...

In the existing literature on barrier options, much effort has been exerted to ensureconvergence through placing the barrier in close proximity to, or directly onto, thenodes of the tree lattice. In this paper we show that this may not be necessary toachieve accurate option price...

Financial models are largely used in option pricing. These physical models capture several salient features of asset price dynamics. The pricing performance can be significantly enhanced when they are combined with nonparametric learning approaches, that empirically learn and correct pricing...