Long memory processes have been extensively studied over the past decades. When dealing with the financial and economic data, seasonality and time-varying long-range dependence can often be observed and thus some kind of non-stationarity can exist inside financial data sets. To take into account...

Controlling and managing potential losses is one of the main objectives of the Risk Management. Following Ben Ameur and Prigent (2007) and Chen et al. (2008), and extending the first results by Hamidi et al. (2009) when adopting a risk management approach for defining insurance portfolio...

In a Constant Proportion Portfolio Insurance (CPPI) framework, a constant risk exposure is defined by the multiple of the strategy. This article proposes an alternative conditional multiple estimation model, which is based on an autoregressive quantile regression dynamic approach. We estimate...

We present several estimates of measures of risk amongst the most well-known, using both high and low frequency data. The aim of the article is to show which lower frequency measures can be an acceptable substitute to the high precision measures, when transaction data is unavailable for a long...

The ultimate goal of risk management is the generation of efficient incomes. The objective is to generate the maximum return for a unit of risk taken or to minimise the risk taken to generate the return expected i.e. it is the optimisation of a financial institution strategy. Therefore, by...

Conditional dependence is expressed as a projection map in the trivariate copula space. The projected copula, its sample counterpart and the related process are defined. The weak convergence of the projected copula process to a tight centered Gaussian Process is obtained under weak assumptions...

This paper introduces two new commands, smpred and smmatch, that implement the statistical matching procedure proposed by Rubin (1986). The purpose of statistical matching in Rubin's procedure is to generate a single dataset from various datasets, where each dataset contains a specific variable...

We present a new recursive algorithm to construct vine copulas based on an underlying tree structure. This new structure is interesting to compute multivariate distributions for dependent random variables. We proove the asymptotic normality of the vine copula parameter estimator and show that...

In this paper, we present a new methodology based on vine copulas to estimate multivariate distributions in high dimensions, taking advantage of the diversity of vine copulas. Considering the huge number of vine copulas in dimension n, we introduce an efficient selection algorithm to build and...

Following Santos Silva and Tenreyro (2006), various studies have used the Poisson Pseudo-Maximum Likelihood to estimate gravity specifications of trade flows and non-count data models more generally. Some papers also report results based on the Negative Binomial estimator, which is more general...