The situation of a limited availability of historical data is frequently encountered in portfolio risk estimation, especially in credit risk estimation. This makes it, for example, difficult to find temporal structures with statistical significance in the data on the single asset level. By...

In this paper we propose a maximum entropy estimator for the asymptotic distribution of the hedging error for options. Perfect replication of financial derivatives is not possible, due to market incompleteness and discrete-time hedging. We derive the asymptotic hedging error for options under a...

We propose a consistent and computationally efficient 2-step methodology for the estimation of multidimensional non-Gaussian asset models built using Lévy processes. The proposed framework allows for dependence between assets and different tail-behaviors and jump structures for each asset. Our...

We investigate whether alternative asset classes should be included in optimal portfolios of the most prominent investor personae in the Behavioral Finance literature, namely, the Cumulative Prospect Theory, the Markowitz and the Loss Averse types of investors. We develop a stochastic spanning...

We introduce the selection of financial portfolios in a nonstationary Gaussian framework that assumes the price process to be modeled by a multifractional Brownian motion (mBm). This process captures the time-changing regularity of the sample paths as a result of the impact of the new...

This article presents a new approach for building robust portfolios based on stochastic efficiency analysis and periods of market downturn. The empirical analysis is done on assets traded on the Brazil Stock Exchange, B3 (Brasil, Bolsa, Balcão). We start with information on the assets from...

The problem of optimal portfolio choice is solved, in closed form, for an ambiguity averse investor who has access to stock and derivatives markets. The investor can have different levels of uncertainty about models for stock return and its stochastic volatility. Although both types of ambiguity...

In this paper we entertain a method of finding the most robust moving average weighting scheme to use for the purpose of timing the market. Robustness of a weighting scheme is defined its ability to generate sustainable performance under all possible market scenarios regardless of the size of...

We determine the optimal investment strategy for an ambiguity averse investor in a setting with stochastic interest rates. The investor is assumed to be ambiguous about the expected rate of return of both bonds and stocks, and may have different levels of ambiguity aversion about the two types...

In this paper we develop an asymptotic theory for the parametric GARCH-in-Mean model. The asymptotics is based on a study of the volatility as a process of the model parameters. The proof makes use of stochastic recurrence equations for this random function and uses exponential inequalities to...