This paper surveys the most important developments in multivariate ARCH-type modelling. It reviews the model specifications, the inference methods, and the main areas of application of these models in financial econometrics.

We investigate intradaily seasonal patterns on the distribution of high frequency financial returns. Using quantile regression we show the expansions and shrinks of the probability law through the day for three years of 15 minutes sampled stock returns. Returns are more dispersed and less...

We show in this paper how, in a model of assets exchange in complete competitive markets, heterogeneity of the agent’s sub jective probabilities generates aggregate expenditures for Arrow-Debreu securities that have the gross substitutability property, with the consequences that competitive...

Traditionally share price returns and their variance have been explained by factors linked to the operations of the company such as systematic risk, corporate size and P/E ratios or by factors related to the influence of the macroeconomic environment. In these models, the institutional...

We propose a new dynamic model for volatility and dependence in high dimensions, that allows for departures from the normal distribution, both in the marginals and in the dependence. The dependence is modeled with a dynamic canonical vine copula, which can be decomposed into a cascade of...

A large number of parameterizations have been proposed to model conditional variance dynamics in a multivariate framework. This paper examines the ranking of multivariate volatility models in terms of their ability to forecast out-of-sample conditional variance matrices. We investigate how...

We consider the effect of asymmetric information on price formation process in a financial market where private information is held by a market maker. A Byesian game is proposed in which there is price competition between two market makers with two different information partition.

This paper proposes a class of asymmetric Autoregressive Conditional Duration models, which extends the ACD model of Engle and Russell (1997). The asymmetry consists of letting the duration process depend on the state of the price process in the beginning and at the end of the each duration. If...

In this paper, we apply a collection of parametric (Normal, Normal GARCH, Student GARCH, RiskMetrics and high-frequency duration models) and non-parametric (empirical quantile, extreme distributions models) Value-at-Risk (VaR) techniques to intraday data for three stocks traded on the New York...

In this paper, we focus on the trade and quote data for the IBM stock traded at the NYSE. We present two different framworks for analyzing this dataset. First, using regularly sampled observations, we characterize the intraday volatility of the mid-point of the bid-ask quotes by estimating GARCH...