# Sébastien LaurentAix-Marseille Université | AMU · Graduate School of Management - IAE

Sébastien Laurent

PhD in Financial Econometrics

## About

103

Publications

23,285

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5,637

Citations

Citations since 2016

Introduction

Additional affiliations

September 2009 - present

September 2003 - August 2009

October 2001 - present

## Publications

Publications (103)

Deviations of asset prices from the random walk dynamic imply the predictability of asset returns and thus have important implications for portfolio construction and risk management. This paper proposes a real-time monitoring device for such deviations using intraday high-frequency data. The proposed procedures are based on unit root tests with in-...

Beta coefficients are the cornerstone of asset pricing theory in the CAPM and multiple factor models. This chapter proposes a review of different time series models used to estimate static and time-varying betas, and a comparison on real data. The analysis is performed on the USA and developed Europe REIT markets over the period 2009–2019 via a two...

The logarithmic prices of financial assets are conventionally assumed to follow a drift–diffusion process. While the drift term is typically ignored in the infill asymptotic theory and applications, the presence of temporary nonzero drifts is an undeniable fact. The finite sample theory for integrated variance estimators and extensive simulations p...

This paper proposes a new model with time-varying slope coefficients. Our model, called CHAR, is a Cholesky-GARCH model, based on the Cholesky decomposition of the conditional variance matrix introduced by Pourahmadi (1999) in the context of longitudinal data. We derive stationarity and invertibility conditions and prove consistency and asymptotic...

This paper shows that a large dimensional vector autoregressive model (VAR) of finite order can generate fractional integration in the marginalized univariate series. We derive high-level assumptions under which the final equation representation of a VAR(1) leads to univariate fractional white noises and verify the validity of these assumptions for...

In this paper, we show that despite the fact that Ornstein-Uhlenbeck (OU) processes fall within the general specification of asset price dynamics studied by Lee and Mykland (2008), the finite sample performance of their two tests for additive jumps is far from being satisfactory when the process deviates from the random walk, resulting in a strong...

We propose a bootstrap-based test of the null hypothesis of equality of two firms’ conditional risk measures (RMs) at a single point in time. The test can be applied to a wide class of conditional risk measures issued from parametric or semiparametric models. Our iterative testing procedure produces a grouped ranking of the RMs, which has direct ap...

An estimator of the ex-post covariation of log-prices under asynchronicity and microstructure noise is proposed. It uses the Cholesky factorization of the covariance matrix in order to exploit the heterogeneity in trading intensities to estimate the different parameters sequentially with as many observations as possible. The estimator is positive s...

The properties of dynamic conditional correlation (DCC) models, introduced more than a decade ago, are still not entirely known. This paper fills one of the gaps by deriving weak diffusion limits of a modified version of the classical DCC model. The limiting system of stochastic differential equations is characterized by a diffusion matrix of reduc...

This paper evaluates the most appropriate ways to model diffusion and jump features of high-frequency exchange rates in the presence of intraday periodicity in volatility. We show that periodic volatility distorts the size and power of conventional tests of Brownian motion, jumps and (in)finite activity. We propose a correction for periodicity that...

This paper evaluates the most appropriate ways to model diffusion and jump features of high-frequency exchange rates in the presence of intraday periodicity in volatility. We show that periodic volatility distorts the size and power of conventional tests of Brownian motion, jumps and (in)finite activity. We propose a correction for periodicity that...

This paper shows that large dimensional vector autoregressive (VAR) models of finite order can generate long memory in the marginalized univariate series. We derive high-level assumptions under which the final equation representation of a VAR(1) leads to univariate fractional white noises and verify the validity of these assumptions for two specifi...

Financial asset prices occasionally exhibit large changes. To deal with their occurrence, observed return series are assumed to consist of a conditionally Gaussian ARMA–GARCH type model contaminated by an additive jump component. In this framework, a new test for additive jumps is proposed. The test is based on standardized returns, where the first...

An estimator of the ex-post covariation of log-prices under asynchronicity and microstructure noise is proposed. It uses the Cholesky factorization on the covariance matrix in order to exploit the heterogeneity in trading intensity to estimate the different parameters sequentially with as many observations as possible. The estimator is guaranteed p...

We propose a widely applicable bootstrap based test of the null hypothesis of equality of two �firms' Risk Measures (RMs) at a single point in time. The test can be applied to any market-based measure. In an iterative procedure, we can identify a complete grouped ranking of the RMs, with particular application to �finding buckets of firms of equal...

Large one-off events cause large changes in prices, but may not affect the volatility and correlation dynamics as much as smaller events. In such cases, standard volatility models may deliver biased covariance forecasts. We propose a multivariate volatility forecasting model that is accurate in the presence of large one-off events. The model is an...

This paper investigates the causality between jumps in the exchange rate process and rumors of central bank interventions. Using the case of Japan, we analyze more specifically whether jumps trigger false reports of intervention (i.e. an intervention is reported whereas it did not occur). Intra-day jumps are extracted using a non-parametric techniq...

Large once-off events cause large changes in prices but may not affect volatility and correlation dynamics as much as smaller events. Standard volatility models may deliver biased covariance forecasts in this case. We propose a multivariate volatility forecasting model that is accurate in the presence of large once-off events. The model is an exten...

This chapter reviews the rapid advances in foreign exchange volatility modeling made in the last three decades. Academic researchers have sought to fit the three major characteristics of foreign exchange volatility: intraday periodicity, autocorrelation and discontinuities in prices. Early research modeled the autocorrelation in daily and weekly sq...

Using a reduced rank regression framework as well as information criteria, we investigate the presence of commonalities in
the intraday periodicity, a dominant feature in the return volatility of most intraday financial time series. We find that
the test has little size distortion and reasonable power even in the presence of jumps. We also find tha...

This article surveys the most important developments in volatility forecast comparison and model selection. We review a number of evaluation methods and testing procedures for predictive accuracy based on statistical loss functions. We also review recent contributions on the admissible form of loss functions ensuring consistency of the ordering whe...

IntroductionModelPrice Jump Detection Method
Simulation StudyComparison on NYSE Stock PricesConclusion

IntroductionGARCHStochastic VolatilityRealized VolatilityAcknowledgments

A complete guide to the theory and practice of volatility models in financial engineering Volatility has become a hot topic in this era of instant communications, spawning a great deal of research in empirical finance and time series econometrics. Providing an overview of the most recent advances, Handbook of Volatility Models and Their Application...

First, we investigate the minimal order univariate representation of some well known n-dimensionalconditional volatility models. Even simple low order systems (e.g. a multivariate GARCH(0,1)) forthe joint behavior of several variables imply individual processes with a lot of persistence inthe form of high order lags. However, we show that in the pr...

Quadratic Covariation is a popular descriptive measure for the volatil-ity of a multivariate price process. It is consistently estimated by the sum of outer products of high-frequency returns. This paper introduces the univariate and multivariate version of the Realized Outlyingness Weighted Quadratic Covariation (ROWQCov) as an estimator of the qu...

We determine the minimum univariate representation of some well known ndimensional conditional volatility models. Simple systems (e.g. a VEC(0,1)) for the joint behaviour of several variables generate individual processes with a lot of persistence, processes that can be erroneously considered as long memory models for the variance. We are also able...

This paper takes a new look at the relation between volume and realized volatility. In contrast to prior studies, we decompose realized volatility into two major components: a continuously varying component and a discontinuous jump component. Our results confirm that the number of trades is the dominant factor shaping the volume–volatility relation...

This paper addresses the question of the selection of multivariate GARCH models in terms of variance matrix forecasting accuracy with a particular focus on relatively large scale problems. We consider 10 assets from NYSE and NASDAQ and compare 125 model based one-step-ahead conditional variance forecasts over a period of 10 years using the model co...

A large number of parameterizations have been proposed to model conditional variance dynamics in a multivariate framework. However, little is known about the ranking of multivariate volatility models in terms of their forecasting ability. The ranking of multivariate volatility models is inherently problematic because it requires the use of a proxy...

This paper empirically investigates the induced effect of a more and less transparent central bank intervention (CBI) policy on rumors that can emerge. Using the case of Japan, we estimate a dynamic-probit model that explains the main determinants of false reports (i.e. falsely reported interventions) and anticipative rumors (i.e. rumors about futu...

This paper assesses the impact of G3 official central bank interventions on daily realized moments of DEM/USD exchange rate returns obtained from intraday data, 1989-2001. Event studies of the realized moments for the intervention day, the days preceding and following the intervention illustrate the shape of this impact. Rolling regressions results...

This paper takes a new look at the relation between volume and realized volatility. In contrast to prior studies, we decompose realized volatility into two major components: a continuously varying component and a discontinuous jump component. Our results confirm that the number of trades is the dominant factor shaping the volume-volatility relation...

Changes in variance, or volatility, over time can be modeled using the approach based on autoregressive conditional heteroscedasticity. Another approach is to model variance as an unobserved stochastic process. Although it is not easy to obtain the exact likelihood function for such stochastic variance models, they tie in closely with developments...

Opening, lunch and closing of financial markets induce a periodic component in the volatility of high-frequency returns. We show that price jumps cause a large bias in the classical periodicity estimators and propose robust alternatives. We find that accounting for periodicity greatly improves the accuracy of intraday jump detection methods. It inc...

Quadratic covariation is a popular descriptive measure for the volatility of a multivariate price process. It is consistently estimated by the sum of outer products of high-frequency returns. The proposed realized outlyingness weighted covariation (ROWCov) is a weighted sum of outer products of high-frequency returns and downweights returns that, b...

We propose three residual-based tests for conditional dynamic asymmetry. Estimation is performed under the null hypothesis of constant asymmetry of the innovations and, in a second step, the tests are performed either through a parametric model or a nonparametric method (runs). The working distribution is assumed to fall into the class of skewed di...

We propose three residual-based tests for conditional dynamic asymmetry. Estimation is performed under the null hypothesis of constant asymmetry of the innovations and, in a second step, the tests are performed either through a parametric model or a nonparametric method (runs). The working distribution is assumed to fall into the class of skewed di...

In the framework of encompassing regressions, the information content of the jump/continuous components of historical volatility is assessed when implied volatility is included as an additional regressor. The authors' empirical application focuses on daily and intradaily data for the S&P100 and S&P500 indexes, and daily data for the associated VXO...

We analyze and assess the impact of macroeconomic announcements on the discontinuities in many assets: stock index futures, bond futures, exchange rates, and gold. We use bi-power variation and the recently proposed non-parametric techniques of Lee and Mykland (2006) to extract jumps. Beyond characterizing the jump and cojump dynamics of many asset...

We analyse the relationship between interventions and volatility at daily and intra-daily frequencies for the two major exchange rate markets. Using recent econometric methods to estimate realized volatility, we employ bi-power variation to decompose this volatility into a continuously varying and jump component. Analysis of the timing and directio...

This paper empirically investigates the induced effect of a more and less transparent central bank intervention (CBI) policy on rumors that can emerge. Using the case of Japan, we estimate a dynamic-probit model that explains the main determinants of false reports (i.e. falsely reported interventions) and anticipative rumors (i.e. rumors about futu...

A large number of different parameterizations have been introduced to model conditional variance dynamics in a multivariate framework. A major problem with these models is the large number of parameters that have to be estimated and the many constraints, often difficult to make explicit, that have to be imposed to ensure semi-positive definiteness...

The predictability of stock returns in ten countries is assessed taking into account recently developed out-of-sample statistical tests and risk-adjusted metrics. Predictive variables in-clude both valuation ratios and interest rate variables. Out-of-sample predictive power is found to be greatest for the short-term and long-term interest rate vari...

The second alternative has been proposed by Andersen et al. (2003). In this case, a daily measure of variances and covariances is computed as an aggregate measure from intraday returns. More specifically, a daily realized variance for day t is computed as the sum of the squared intraday equidistant returns for the given trading day and a daily real...

This article assesses the impact of official FOREX interventions of the three major central banks in terms of the dynamics
of the currency components of the major exchange rates over the period 1989–2003. We identify the currency components of the
mean and volatility processes of exchange rates using the framework developed recently by Bos and Shep...

The purpose of this paper is to review and discuss the key improvements brought to OxGauss. Without having to install Gauss on his or her machine, the OxGauss user can run under Ox a wide range of Gauss programs and codes. Even with the consoleOx version (free for academics), Gauss codes can either be called from Ox programs or run and executed on...

The purpose of this paper is to review and discuss the key improvements brought to OxGauss. Without having to install Gauss on his or her machine, the OxGauss user can run under Ox a wide range of Gauss programs and codes. Even with the console Ox version (free for academics), Gauss codes can either be called from Ox programs or run and executed on...

This paper derives analytical expressions for the score of the APARCH model of Z. Ding et al. [J. Empir. Finance 1, 83–106 (1993)]. Interestingly, doing so we derive the analytical score of a broad range of GARCH models since the APARCH models nests at least seven specifications. The use of the APARCH model is now widespread in the literature. Howe...

Forecasts are an inherent part of economic science and the quest for perfect foresight occupies economists and researchers in multiple fields. The release of economic forecasts (and its revisions) is a popular and often publicized event, with a multitude of institutions and think-tanks devoted almost exclusively to that task. The European Central B...

We examine Italian inflation rates and the Phillips curve with a very long-run perspective, one that covers the entire existence of the Italian lira from political unification (1861) to Italy's entry in the European Monetary Union (end of 1998). We first study the volatility, persistence and stationarity of the Italian inflation rate over the long...

In this paper we model Value-at-Risk (VaR) for daily asset returns using a collection of parametric univariate and multivariate models of the ARCH class based on the skewed Student distribution. We show that models that rely on a symmetric density distribution for the error term underperform with respect to skewed density models when the left and r...

In this paper, we investigate the effect of central bank interventions on the weekly returns and volatility of the DEM/USD and YEN/USD exchange rate returns. In contrast with previous analyses, we allow for regime-dependent specifications and investigate whether official interventions can explain the observed volatility regime switches. It is found...

We put forward Value-at-Risk models relevant for commodity traders who have long and short trading positions in commodity markets. In a 5-year out-of-sample study on aluminium, copper, nickel, Brent crude oil and WTI crude oil daily cash prices and cocoa nearby futures contracts, we assess the performance of the RiskMetrics, skewed Student APARCH a...

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

In this paper, we estimate ARFIMA–FIGARCH models for the major exchange rates (against the US dollar) which have been subject to direct central bank interventions in the last decades. We show that the normality assumption is not adequate due to the occurrence of volatility outliers and its rejection is related to these interventions. Consequently,...

This paper studies and assesses the impact of G3 Central Bank interventions on the DEM/USD exchange rate properties using daily realized moments of exchange rate returns (obtained from intraday data) for the period 1989-2001. Event studies in terms of the realized moments for the intervention day, the days preceding and following the intervention d...

We show how the ARMA-Power GARCH model for the conditional mean and variance can be adapted to analyze times series data showing asymmetry. Dynamics is introduced in the location and the dispersion parameters of skewed location-scale distributions using the same type of structure found in the conditional mean and in the conditional variance in the...

We propose a practical and flexible method to introduce skewness in multivariate symmetric distributions. Applying this procedure to the multivariate Student density leads to a multivariate skew-Student density, in which each marginal has a specific asymmetry coefficient. Combined with a multivariate GARCH model, this new family of distributions is...

This tutorial documents G@RCH 2.3, an Ox package dedicated to the estimation and fore-cast of various univariate ARCH-type models in the conditional variance and an AR(FI)MA specification in the conditional mean. These ARCH processes include ARCH, GARCH, EGARCH, GJR, APARCH, IGARCH, FIGARCH, FIEGARCH, FIAPARCH and HYGARCH. These models can be estim...

We propose a practical and flexible solution to introduce skewness in multivariate symmetrical distributions. Applying this procedure to the multivariate Student density leads to a "multivariate skew-Student" density, for which each marginal has a different asymmetry coefficient. Similarly, when applied to the product of independent univariate Stud...