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We analyze the joint convergence of sequences of discounted stock prices and Radon-Nicodym derivatives of the minimal martingale measure when interest rates are stochastic. Therefrom we deduce the convergence of option values in either complete or incomplete markets. We illustrate the general result by two main examples: a discrete time i.i.d. approximation(More)
We propose a new method to capture changes in hedge funds'exposures to risk factors, exploiting information from relatively high frequency conditioning variables. Using a consolidated database of nearly 15,000 individual hedge funds between 1994 and 2009, we …nd substantial evidence that hedge fund risk exposures vary signi…cantly across months. Our new(More)
We develop a new parametric estimation procedure for option panels observed with error. We exploit asymptotic approximations assuming an ever increasing set of option prices in the mon-eyness (cross-sectional) dimension, but with a fixed time span. We develop consistent estimators for the parameters and the dynamic realization of the state vector governing(More)
In recent years, numerous volatility-based derivative products have been engineered. This has led to interest in constructing conditional predictive densities and confidence intervals for integrated volatility. In this paper, we propose nonparametric estimators of the aforementioned quantities, based on model free volatility estimators. We establish(More)
In a financial market with one riskless asset and n risky assets following geometric Brownian motions, we solve the problem of a pension fund maximizing the expected CRRA utility of its terminal wealth. By considering a stochastic death time for a subscriber, we solve a unique problem for both accumulation and decumulation phases. We show that the optimal(More)
Forecast accuracy is typically measured in terms of a given loss function. However, as a consequence of the use of misspecified models in multiple model comparisons, relative forecast rankings are loss function dependent. This paper addresses this issue by using a novel criterion for forecast evaluation which is based on the entire distribution of forecast(More)