This paper examines the empirical performance of jump diffusion models of stock price
dynamics from joint options and stock markets data. The paper introduces a model with …

Which loss function should be used when estimating and evaluating option valuation
models? Many different functions have been suggested, but no standard has emerged. We …

Uncertainty on the choice of an option pricing model can lead to “model risk” in the valuation
of portfolios of options. After discussing some properties which a quantitative measure of …

Publisher Summary This chapter describes various Markov Chain Monte Carlo (MCMC)
methods for exploring the posterior distributions generated by continuous-time asset pricing …

Publisher Summary The stochastic discount factor methodology is the central tool in finance
to price assets and provides a natural framework to integrate contributions in discrete and …

We propose a probabilistic approach for estimating parameters of an option pricing model
from a set of observed option prices. Our approach is based on a stochastic optimization …

Carlsson and Fuller [C. Carlsson, R. Fuller, On possibilistic mean value and variance of
fuzzy numbers, Fuzzy Sets and Systems 122 (2001) 315–326] have introduced possibilistic …

In this paper, we consider the pricing of American options under a regime-switching double
Heston model, such that the interest rate and mean-reversion level parameters in both …

In an imcomplete information model, we show that investors' uncertainty about the drift of a
firm's fundamentals affects option prices through its affect on stock volatility and the …

We calibrate Heston stochastic volatility model to real market data using several optimization
techniques. We compare both global and local optimizers for different weights showing …