Analysts are accustomed to using prices for the information they contain. A stock price, for
example, can be thought of as an expected value of future cash flows. Each futures price …

This paper establishes a novel model-free representation of the risk-neutral density in terms
of market-observed options prices by combining exact series representations of the Dirac …

The departure in modelling terms from the log-normal distribution for option pricing has been
largely driven by empirical observations on skewness. In recent years, the Weibull and …

This study develops a truncated Gram–Charlier expansion (TGCE) option pricing model,
which simultaneously considers the skewness, kurtosis and essentially truncated (bounded) …

Christoffersen and Goncalves (2005) study the effect of parameter estimation error in
computing value-at-risk and expected shortfall through commonly used methods including …

Risk preference functions across the wealth domain are estimated from option prices and
asset realized returns using:(a) a semiparametric probability model, the Edgeworth Series …

This thesis comprises three studies on extracting the information embedded in option prices.
In Chapter One, we propose a new predictor to forecast US real economic activity (REA) by …

Los modelos implícitos constituyen uno de los enfoques de valoración de opciones
alternativos al modelo de Black-Scholes que ha conocido un mayor desarrollo en los …

The risk-neutral density function (RND) is a fundamental concept in mathematical finance
and is heavily used in the pricing of financial derivatives. The estimation of a well-behaved …

This thesis examines and compares the performance of the parametric mixture model and
the two nonparametric, kernel regression and neural network models, with the intention of …