In this paper, we discuss the parameter estimation for a k-factor generalized long memory processwith conditionally heteroskedastic noise. Two estimation methods are proposed. The first method is based on the conditional distribution of the process and the second is obtained as an extension of...

This paper presents a theorical framework to model the evolution of a portfolio whose weights vary over time. Such a portfolio is called a dynamic portfolio. In a first step, considering a given investment policy, we define the set of the investable portfolios. Then, considering portfolio...

We propose a novel methodology for forecasting chaotic systems which is based on the nearest-neighbor predictor and improves upon it by incorporating local Lyapunov exponents to correct for its inevitable bias. Using simulated data, we show that gains in prediction accuracy can be substantial....

Operational risk management inside banks and insurance companies is an important task. The computation of a risk measure associated to these kinds of risks lies in the knowledge of the so-called loss distribution function (LDF). Traditionally, this LDF is computed via Monte Carlo simulations or...

In this paper, we provide a new dynamic asset pricing model for plain vanilla options and we discuss its ability to produce minimum mispricing errors on equity option books. The data set is the daily log returns of the French CAC40 index, on the period January 2, 1988, October 26, 2007. Under...

In a discrete time option pricing framework, we compare the empirical performance of two pricing methodologies, namely the affine stochastic discount factor and the empirical martingale correction methodologies. Using a CAC 40 options dataset, the differences are found to be small : the higher...

This paper aims to provide a dynamic analysis of the insurance linked securities index. We are discussing the behaviour of the index for three years and pointing out the consequences of some major events like Katrina or the last and current financial crisis. Some stylized facts of the index,...

Operational risk quantification requires dealing with data sets which often present extreme values which have a tremendous impact on capital computations (VaR). In order to take into account these effects we use extreme value distributions, and propose a two pattern model to characterize loss...

Are structural breaks models true switching models or long memory processes ? The answer to this question remain ambiguous. A lot of papers, in recent years, have dealt with this problem. For instance, Diebold and Inoue (2001) and Granger and Hyung (2004) show, under specific conditions, that...

In this paper, we propose an alternative approach to estimate long-term risk. Instead of using the static square root method, we use a dynamic approach based on volatility forecasting by non-linear models. We explore the possibility of improving the estimations by different models and...