This paper is concerned with the issues of modeling and projecting the dynamics of volatility when a group of potentially useful predetermined variables is available. We predict realized volatility and value at risk (VaR) with a nested set of multiplicative error models for realized volatility....

In this paper we address the issue of forecasting Value-at-Risk (VaR) using different volatility measures: realized volatility, bipower realized volatility, two scales realized volatility, realized kernel as well as the daily range. We propose a dynamic model with a flexible trend specification...

AbstractThe following sections are included:OverviewThe Dodd-Frank Wall Street Reform and Consumer Protection ActEvaluation of the Dodd-Frank ACTMarket-Based Measures of Systemic RiskInterconnectednessStress TestsTransparencyNYU Stern Systemic Risk RankingsSystemic Risk MethodologySystemic Risk...

This work proposes novel network analysis techniques for multivariate time series. We define the network of a multivariate time series as a graph where vertices denote the components of the process and edges denote non-zero long run partial correlations. We then introduce a two step lasso...

Realized volatilities observed across several assets show a common secular trend and some idiosyncratic pattern which we accommodate by extending the class of Multiplicative Error Models (MEMs). In our model, the common trend is estimated nonparametrically, while the idiosyncratic dynamics are...

When observed over a large panel, measures of risk (such as realized volatilities) usually exhibit a secular trend around which individual risks cluster. In this article we propose a vector Multiplicative Error Model achieving a decomposition of each risk measure into a common systematic and an...

This work proposes novel network analysis techniques for multivariate time series. We define the network of a multivariate time series as a graph where vertices denote the components of the process and edges denote non zero long run partial correlations. We then introduce a two step LASSO...

Realized volatilities measured on several assets exhibit a common secular trend and some idiosyncratic pattern. We accommodate such an empirical regularity extending the class of Multiplicative Error Models (MEMs) to a model where the common trend is estimated nonparametrically while the...

This paper is concerned with the issues of modeling and projecting the dynamics of volatility when a group of potentially useful predetermined variables is available. We predict realized volatility and value at risk (VaR) with a nested set of multiplicative error models for realized volatility....