It is well known that non-normality plays an important role in asset and risk management. However, handling a large number of assets has long been a challenge due to the curse of dimensionality. We describe a statistical technique, which we call Moment Component Analysis (MCA), that extends...

This paper introduces and analyzes a procedure called Testing-Based Forward Model Selection (TBFMS) in linear regression problems. This procedure inductively selects covariates that add predictive power into a working statistical model before estimating a final regression. The criterion for...

We propose a model to forecast very large realized covariance matrices of returns, applying it to the constituents of the S&P 500 on a daily basis. To address the curse of dimensionality, we decompose the return covariance matrix using standard firm-level factors (e.g., size, value and...

The last regulation of the Fundamental Review of the Trading Book (FRTB) proposed to replace the Incremental Risk Charge (IRC) with the Default Risk Charge (DRC). Since, many studies were implemented to give the adequate model and the impact of this change. As we know in the modeling area, we...

We focus on two particular aspects of model risk: the inability of a chosen model to fit observed market prices at a given point in time (calibration error) and the model risk due to recalibration of model parameters (in contradiction to the model assumptions). In this context, we follow the...

Specification tests are developed for the conditional distribution of a dependent process {X_i} in a family of nonlinear time-series models. The family includes several Generalized AutoRegressive Conditional Heteroscedastic [GARCH] models that are widely used in finance and economics. Such tests...

The Central Bank of Morocco has been working on developing a Forecasting and Policy Analysis System (FPAS) to support a gradual move toward a more flexible exchange rate regime and the eventual adoption of a full-fledged inflation-targeting (IT) regime. At the center of the FPAS is a quarterly...

When workers have incomplete information about their ability, they can learn about this ability by searching for jobs, both while employed and unemployed. Search outcomes yield information for updating the belief about the ability which affects optimal search decisions in the future. Firms...

The present book is concerned with spatial interaction modelling. In particular, it aims to illustrate, through a collection of methodological and empirical studies, how estimation approaches in this field recently developed, by including the tools typical of spatial statistics and spatial...

The focus is on cross-sectional dependence in panel trade flow models. We propose alternative specifications for modeling time invariant factors such as socio-cultural indicator variables, e.g., common language and currency. These are typically treated as a source of heterogeneity eliminated...