Curriculum vitae

Darolles Serge

Professeur
DRM

serge.darollesping@dauphinepong.fr
Tel : 01 44054784
Bureau : P608

Publications

Articles

Darolles S., Le Fol G., Mero G. (2017), Mixture of Distribution Hypothesis: Analyzing daily liquidity frictions and information flows, Journal of Econometrics

The mixture of distribution hypothesis (MDH) model offers an appealing explanation for the positive relation between trading volume and volatility of returns. In this specification, the information flows constitute the only mixing variable responsible for all changes. However, this single static latent mixing variable cannot account for the observed short-run dynamics of volume and volatility. In this paper, we propose a dynamic extension of the MDH that specifies the impact of information arrival on market characteristics in the context of liquidity frictions. We distinguish between short-term and long-term liquidity frictions. Our results highlight the economic value and statistical accuracy of our specification. First, based on some goodness of fit tests, we show that our dynamic two-latent factor model outperforms all competing specifications. Second, the information flows latent variable can be used to propose a new momentum strategy. We show that this signal improves once we allow for a second signal - the liquidity frictions latent variable - as the momentum strategies based on our model present better performance than the strategies based on competing models

Darolles S., Dudek J., Le Fol G. (2016), Gauging Liquidity Risk in Emerging Market Bond Index Funds, Annals of Economics and Statistics, 123/124, p. 247-269

ETFs and index funds have grown at very rapid rates in recent years. Originally launched totrack some large liquid indices in developed markets, they now also concern less liquid assetclasses such as emerging market bonds. Illiquidity certainly affects the quality of the replication,and in particular, liquidity might increase the tracking error of any index fund, i.e., thedifference between the fund and the benchmark returns. The tracking error is then the firstcharacteristic that investors consider when they select index funds. In this paper, we beginfrom the CDS-bond basis to simulate the tracking error (TE) of a hypothetical well-diversifiedfund investing in the emerging market bond universe. We compute the CDS-bond basis andthe tracking error for 9 emerging market sovereign entities: Brazil, Chile, Hungary, Mexico,Poland, Russia, South Africa, Thailand and Turkey. All of these countries are included inthe MSCI Emerging Market Debt in Local Currency index. Our sample period ranges fromJanuary 1, 2007 to March 26, 2012. Using a Regime Switching for Dynamic Correlations(RSDC) model, we show that the country-by-country tracking error is reduced by the diversificationat the fund level. Moreover, we show that this diversification effect is less effectiveduring crisis periods. This loss of diversification benefits is the main risk of index funds when they are designed to create a liquid exposure to illiquid asset classes

Darolles S., Francq C., Le Fol G., Zakoïan J-M. (2016), Intrinsic Liquidity in Conditional Volatility Models, Annals of Economics and Statistics, 123/124, p. 225-245

Until recently the liquidity of financial assets has typically beenviewed as a second-order consideration. Liquidity was frequently associatedwith simple transaction costs that impose - temporary if any- effect on assetprices, and whose shocks could be easily diversified away. Yet the evidenceespeciallythe recent liquidity crisis- suggests that liquidity is now a primaryconcern. This paper aims at disentangling market risk and liquidity riskin the context of conditional volatility models. Our approach allows theisolation of the intrisic liquidity of any asset, and thus makes it possible todeduce a liquidity risk even when volumes are not observed.

Darolles S., Gouriéroux C. (2015), Performance fees and hedge fund return dynamics, International Journal of Approximate Reasoning, -, -, p. -

A characteristic of hedge funds is not only an active portfolio management, but also the allocation of portfolio performance between different accounts, which are the accounts for the external investors and an account for the management firm, respectively. Despite lack of transparency in hedge fund market, the strategy of performance allocation is publicly available. This paper shows that, for the High-Water Mark Scheme, these complex performance allocation strategies might explain empirical facts observed in hedge fund returns, such as return persistence, skewed return distribution, bias ratio, or implied increasing risk appetite.

Darolles S., Le Fol G., Mero G. (2015), Measuring the Liquidity Part of Volume, Journal of Banking and Finance, 50, p. 92–105

Based on the concept that the presence of liquidity frictions can increase the daily traded volume, we develop an extended version of the mixture of distribution hypothesis model (MDH) along the lines of Tauchen and Pitts (1983) to measure the liquidity portion of volume. Our approach relies on a structural definition of liquidity frictions arising from the theoretical framework of Grossman and Miller (1988), which explains how liquidity shocks affect the way in which information is incorporated into daily trading characteristics. In addition, we propose an econometric setup exploiting the volatility-volume relationship to filter the liquidity portion of volume and infer the presence of liquidity frictions using daily data. Finally, based on FTSE 100 stocks, we show that the extended MDH model proposed here outperforms that of Andersen (1996) and that the liquidity frictions are priced in the cross-section of stock returns.

Darolles S. (2014), Evaluating UCITS Compliant Hedge Fund Performance, Bankers, Markets & Investors, 133, p. 11-22

Despite having registered significant investor appetite in recent years, empirical research on UCITS compliant hedge funds ("Newcits" or "Alternative UCITS") is a rare commodity. The major contribution of this paper is therefore to evaluate the performance of publicly regulated Alternative UCITS vehicles in comparison to traditional hedge funds. For the first time, a representative set of data has been analyzed on a period from June 2004 to May 2011. The results shed light on what really matters for investors: regulation, managerial skills and risk. We show that the UCITS regulatory constraints come at a cost to performance and that the impact of regulation differs from one strategy to another. We also find that the performance of Alternative UCITS is positively affected by the skill set of the manager. In particular, hedge fund experience is relevant when managing Alternative UCITS funds.

Darolles S., Le Fol G. (2014), Trading volume and Arbitrage, GSTF : Journal on Business Review, 3, 3, p. 30-39

Decomposing returns into market and stock specific components is common practice and forms the basis of popular asset pricing models. What about volume? Can volume be decomposed in the same way as returns? Lo and Wang (2000) suggest such a decomposition. Our paper contributes to this literature in two different ways. First, we provide a model to explain why volumes deviate from the benchmark. Our interpretation is in terms of arbitrage strategies and liquidity. Second, we propose a new efficient screening tool that allows practitioners to extract specific information from volume time series. We provide an empirical illustration of the relevance and the possible uses of our approach on daily data from the FTSE index from 2000 to 2002.

Darolles S., Vaissié M. (2012), The Alpha and Omega of Fund of Hedge Fund Added Value, Journal of Banking and Finance, 36, 4, p. 1067-1078

In spite of a somewhat disappointing performance throughout the crisis, investors are showing interest in hedge funds. Still, funds of hedge funds keep on experiencing outflows. Can this phenomenon be explained by the failure of fund of hedge fund managers to deliver on their promise to add value through active management, or is it symptomatic of a move toward greater disintermediation in the hedge fund industry? We introduce a return-based attribution model allowing for a full decomposition of fund of hedge fund performance. The results of our empirical study suggest that funds of hedge funds are funds of funds like others. Strategic allocation turns out to be a crucial step in the investment process, in that it not only adds value over the long-term, but most importantly, it brings resilience precisely when investors need it the most. Fund picking, on the other hand, turns out to be a double-edged sword.

Bialkowski J., Darolles S., Le Fol G. (2012), Reducing the risk of VWAP orders execution - A new approach to modeling intra-day volume, JASSA, 1, p. 12-18

This paper proposes a new dynamic approach to modelling intra-day trading volume based on factor models. It assumes that intra-day volume can be decomposed into two parts each predicted using separate time-series models. By enabling more accurate prediction of intra-day volume, this methodology allows for a significant reduction in the cost of executing Volume weighted Average Price orders.

Bialkowski J., Darolles S., Le Fol G. (2012), How to reduce the risk of VWAP orders execution ?, JASSA, 1

This paper proposes a new dynamic approach to modelling intra-day trading volume based on factor models. It assumes that intra-day volume can be decomposed into two parts each predicted using separate time-series models. By enabling more accurate prediction of intra-day volume, this methodology allows for a significant reduction in the cost of executing Volume Weighted Average Price orders.

Darolles S., Mero G. (2011), Hedge Fund Returns and Factor Models : A Cross-Section Approach, Bankers, Markets & Investors, 112, p. 34-53

This paper develops a dynamic approach for assessing hedge fund risk exposures. First, we focus on an approximate factor model framework to deal with the factor selection issue. Instead of keeping the number of factors unchanged, we apply Bai and Ng (2002) and Bai and Ng (2006) to select the appropriate factors at each date. Second, we take into account the instability of asset risk profile by using rolling period analysis in order to estimate hedge fund risk exposures. Individual fund returns instead of index returns are employed in the empirical application to better understand the covariation structure of the data: the common behavior of hedge fund returns is filtered not only from the past historical data (time- series dimension), but also from the cross-section of returns. Finally, we apply our approach to equity hedge funds and replicate the returns of the aggregated index.

Jay E., Duvaut P., Darolles S., Chretien A. (2011), Multifactor Models : Examining the potential of signal processing techniques, IEEE Signal Processing Magazine, 28, 5, p. 37-48

This article surveys the existing literature on the most widely used factor models employed in the realm of a financial asset pricing field. Through the concrete application of evaluating risks in the hedge fund industry, this article demonstrates that signal processing techniques are an interesting alternative to the selection of factors and can provide more efficient estimation procedure than classical techniques.

Darolles S., Fan Y., Florens J-P., Renault E. (2011), Nonparametric Instrumental Regression, Econometrica, 79, 5, p. 1541-1565

The focus of this paper is the nonparametric estimation of an instrumental regression function ? defined by conditional moment restrictions that stem from a structural econometric model E[Y-?(Z)|W]=0, and involve endogenous variables Y and Z and instruments W. The function ? is the solution of an ill-posed inverse problem and we propose an estimation procedure based on Tikhonov regularization. The paper analyzes identification and overidentification of this model, and presents asymptotic properties of the estimated nonparametric instrumental regression function.

Christian G., Darolles S. (2010), Conditionally fitted Sharpe performance with an application to hedge fund rating, Journal of Banking and Finance, 34, 3, p. 578–593

We define a battery of Sharpe performance measures, which differ by the information taken into account in their computation, but also by the potential use of the fund by the investor. Four advantages of Sharpe performance based rating are especially important for the investor. First, the performance measures correspond to the standard measures used for mutual funds and known by retail investors. Second, we can compare the numerical results, even if they are obtained with different assumptions. Third, the rankings are based on regression analysis and easy to compute. Fourth, we can easily use these performance measures in the design of an optimal basket of hedge funds. Finally, we can use the performance measures to partition the set of funds into homogenous segments.

Darolles S., Gouriéroux C., Jasiak J. (2009), L-performance with an application to hedge funds, Journal of Empirical Finance, 16, 4, p. 671– 685

This paper introduces a new parametric fund performance measure, called the L-performance. The L-performance is an alternative to the Sharpe performance, which is commonly used in practice despite its inability to account for skewness and heavy tails of unconditional return distributions. The L-performance improves upon the Sharpe measure in this respect. Technically, it resembles the Sharpe measure in that it is defined as a ratio of the first- and second-order moments, which are the trimmed L-moments instead of the conventional (power) moments. The trimming parameters allow for focusing the L-performance on specific risk levels of interest, according to financial risk criteria. For illustration, a set of L-performances is computed for a variety of hedge funds. The empirical study shows the use of L-performance for fund ranking and return smoothing (manipulation) control.

Bialkowski J., Darolles S., Le Fol G. (2008), Improving VWAP strategies: A dynamic volume approach, Journal of Banking and Finance, 32, 9, p. 1709-1722

In this paper, we present a new methodology for modelling intraday volume, which allows for a reduction of the execution risk in VWAP (Volume Weighted Average Price) orders. The results are obtained for all the stocks included in the CAC40 index at the beginning of September 2004. The idea of considered models is based on the decomposition of traded volume into two parts: one reflects volume changes due to market evolution; the second describes the stock specific volume pattern. The dynamic of the specific volume part is depicted by ARMA and SETAR models. The implementation of VWAP strategies allows some dynamic adjustments during the day in order to improve tracking of the end-of-day VWAP.

Darolles S., Gouriéroux C., Jasiak J. (2006), Structural Laplace Transform and Compound Autoregressive Models, Journal of Time Series Analysis, 27, 4, p. 477-503

This paper presents a new general class of compound autoregressive (Car) models for non-Gaussian time series. The distinctive feature of the class is that Car models are specified by means of the conditional Laplace transforms. This approach allows for simple derivation of the ergodicity conditions and ensures the existence of forecasting distributions in closed form, at any horizon. The last property is of particular interest for applications to finance and economics that investigate the term structure of variables and/or of their nonlinear transforms. The Car class includes a number of time-series models that already exist in the literature, as well as new models introduced in this paper. Their applications are illustrated by examples of portfolio management, term structure and extreme risk analysis.

Florens J-P., Gouriéroux C., Darolles S. (2004), Kernel-based nonlinear canonical analysis and time reversibility, Journal of Econometrics, 119, 2, p. 323–353

We consider a kernel-based approach to nonlinear canonical correlation analysis and its implementation for time series. We deduce a test procedure of the reversibility hypothesis. The method is applied to the analysis of stochastic differential equation from high-frequency data on stock returns.

Darolles S., Le Fol G. (2004), Nouvelles techniques de gestion et leur impact sur la volatilité, Revue d'économie financière, 74, p. 231-243

La gestion alternative s'est considérablement développée ces dernières années. Cependant l'impact sur les marchés et plus précisément sur la volatilité des marchés des nouvelles techniques de gestion qui l'accompagne est méconnu. Cet article se propose d'explorer le lien entre le développement de nouvelles pratiques de gestion et l'évolution de la volatilité, dont l'étape intermédiaire est l'étude du lien entre pratiques de gestion et volume.

New investment management techniques and their impact on volatility The growth of alternative investment has been considerable in recent years. However, the impact on markets or more precisely, on markets volatility, of the new induced management techniques is still not clear. In this article, we undergo such an analysis. We first link investment strategies to volume before analysing the volume-volatility relation.

Darolles S., Gouriéroux C. (2001), Truncated dynamics and estimation of diffusion equations, Journal of Econometrics, 102, 1, p. 1–22

We study inference on continuous-time processes from discrete data with a given time interval between consecutive observations, and propose a modification of the sieve estimation method based on the infinitesimal generator. Our approach consists on truncating the initial process to improve the estimationof the eigenfunctions at the boundaries of the set of admissible values. For diffusion processes, nonparametric estimationof the drift and volatility are derived. A prior truncation is also useful to eliminate in practice the specific dynamicsof extreme risks.

Gouriéroux C., Florens J-P., Darolles S. (2001), Factor ARMA representation of a Markov process, Economics Letters, 71, 2, p. 165–171

We decompose a stationary Markov process (Xt) as: View the MathML source, where the Zj's processes admit ARMA specifications. These decompositions are deduced from a nonlinear canonical decomposition of the joint distribution of (Xt, Xt-1).

Laurent J-P., Darolles S. (2000), Approximating payoffs and pricing formulas, Journal of Economic Dynamics and Control, 24, 11-12, p. 1721–1746

We use the ideas developed by Madan and Milne (1994. Mathematical Finance 3, 223-245), Lacoste (1996. Mathematical Finance 6, 197-213) to explore the optimality of polynomial approximations in pricing securities. In particular, we look at the approximations for security payoffs as well as the associated pricing formula in a L2 framework. We apply these ideas to two examples, one where the state variable follows an Ornstein-Uhlenbeck process and one based on Brownian motion with reflecting barriers, to illustrate the strengths and weaknesses of the approach.

Darolles S., Gouriéroux C., Le Fol G. (2000), Intraday Transaction Price Dynamics, Annales d'Economie et de Statistique, 60, p. 207-238

Les prix de transaction intrajournaliers présentent deuxcaractéristiques majeures : ils sont discrets en niveau et n'existent qu'à desdates de transaction aléatoires. Nous proposons une modélisation de ladynamique des prix de transaction prenant en compte ces deux aspects.Nous modélisons le processus de prix à l'aide d'une chaîne de Markov etintroduisons différents outils adaptés à l'étude de la dynamique, comme ladécomposition canonique, les mesures d'échelle et de vitesse. Cetteapproche est utilisée pour étudier les cours de transaction de l'action ElfAquitaine échangée à la Bourse de Paris.

High frequency transaction prices exhibit two major characteristics: they are discrete in level and only exist at random transactiondates. In this paper, we seek to model transaction price dynamics, takinginto account these two features. We specify the transaction price processas a Markov Chain with random transaction dates, and discuss varioustools for dynamic analysis like the canonical decomposition, the scale andspeed measures. The approach is applied to high frequency data on thestock Elf-Aquitaine traded on the Paris Bourse.

Ouvrages

Darolles S., Duvaut P., Jay E. (2013), Multi-factor models and signal processing techniques: application to quantitative finance, London ; Hoboken, NJ, ISTE ; J. Wiley, 184 p.

With recent outbreaks of multiple large-scale financial crises, amplified by interconnected risk sources, a new paradigm of fund management has emerged. This new paradigm leverages "embedded" quantitative processes and methods to provide more transparent, adaptive, reliable and easily implemented "risk assessment-based" practices. This book surveys the most widely used factor models employed within the field of financial asset pricing. Through the concrete application of evaluating risks in the hedge fund industry, the authors demonstrate that signal processing techniques are an interesting alternative to the selection of factors (both fundamentals and statistical factors) and can provide more efficient estimation procedures, based on lq regularized Kalman filtering for instance. With numerous illustrative examples from stock markets, this book meets the needs of both finance practitioners and graduate students in science, econometrics and finance.

Chapitres d'ouvrage

Darolles S., Gouriéroux C., Teiletche J. (2015), The Dynamics of Hedge Fund Performance, in Huynh V-N., Kreinovich V., Sriboonchitta S., Suriya K. (eds), Econometrics of Risk, Heidelberg, Springer, p. 85-113

The ratings of fund managers based on past performances of the funds and the rating dynamics are crucial information for investors. This paper proposes a stochastic migration model to investigate the dynamics of performance-based ratings of funds, for a given risk-adjusted measure of performance. We distinguish the absolute and relative ratings and explain how to identify their idiosyncratic and systematically persistent (resp. amplifying cycles) components. The methodology is illustrated by the analysis of hedge fund returns extracted from the TASS database for the period 1994-2008.

Darolles S., Dudek J., Le Fol G. (2014), Contagion in Emerging Markets, in Finch N. (eds), Emerging Markets and Sovereign Risk, Basingstoke (Publishing Building, Brunel Road, Houndmills, Basingstoke, Hampshire RG21 6XS), Palgrave Macmillan, p. XVI-298

Darolles S., Duvaut P., Jay E. (2013), Factor Models and General Definition, in Darolles S., Duvaut P., Jay E. (eds), Multi-factor models and signal processing techniques: application to quantitative finance, London ; Hoboken, NJ, ISTE ; J. Wiley, p. 1–21

This chapter introduces the common version of linear factor models and also discusses its limits and developments. It introduces different notations and discusses the model and its structure. The chapter lists out the reasons why factor models are generally used in finance, and further explains the limits of this approach. It also deals with the different steps in the building of factor models, i.e. factor selection and parameter estimation. Finally, the chapter gives a historical perspective on the use of factor models such as capital asset pricing model (CAPM), Sharpe's market model and arbitrage pricing theory (APT) in finance.

Darolles S., Duvaut P., Jay E. (2013), Factor Selection, in Darolles S., Duvaut P., Jay E. (eds), Multi-factor models and signal processing techniques: application to quantitative finance, London ; Hoboken, NJ, ISTE ; J. Wiley, p. 23–58

This chapter focuses on the empirical ad hoc approach and presents three reference models that are widely used in the literature. These models are all based on the factor representation, but highlight the nature of the factors to be used to explain specific asset class returns. In a section, the authors denote by eigenfactors the factors obtained from the observations using the eigenvector decomposition of the covariance matrix of the returns. The chapter describes some classical techniques, arising from the information theory. It provides complementary sections which provide some light on related problems to this approach such as the estimation of the covariance matrix of the data, the similarity of the approach with subspace methods and the extension of this approach to large panel data.

Darolles S., Duvaut P., Jay E. (2013), Least Squares Estimation (LSE) and Kalman Filtering (KF) for Factor Modeling: A Geometrical Perspective, in Darolles S., Duvaut P., Jay E. (eds), Multi-factor models and signal processing techniques: application to quantitative finance, London ; Hoboken, NJ, ISTE ; J. Wiley, p. 59-116

This chapter introduces, illustrates and derives both least squares estimation (LSE) and Kalman filter (KF) estimation of the alpha and betas of a return, for a given number of factors that have already been selected. It formalizes the "per return factor model" and the concept of recursive estimate of the alpha and betas. The chapter explains the setup, objective, criterion, interpretation, and derivations of LSE. The setup, main properties, objective, interpretation, practice, and geometrical derivation of KF are also discussed. The chapter also explains the working of LSE and KF. Numerous simulation results are displayed and commented throughout the chapter to illustrate the behaviors, performance and limitations of LSE and KF.

Darolles S., Duvaut P., Jay E. (2013), A Regularized Kalman Filter (rgKF) for Spiky Data, in Darolles S., Duvaut P., Jay E. (eds), Multi-factor models and signal processing techniques: application to quantitative finance, London ; Hoboken, NJ, ISTE ; J. Wiley, p. 117-132

This chapter presents a new family of algorithms named regularized Kalman Filters (rgKFs) that have been derived to detect and estimate exogenous outliers that might occur in the observation equation of a standard Kalman filter (KF). Inspired from the robust Kalman filter (RKF) of Mattingley and Boyd, which makes use of a l1-regularization step, the authors introduce a simple but efficient detection step in the recursive equations of the RKF. This solution is one means by which to solve the problem of adapting the value of the l1-regularization parameter: when an outlier is detected in the innovation term of the KF, the value of the regularization parameter is set to a value that will let the l1-based optimization problem estimate the amplitude of the spike. The chapter deals with the application of algorithm to detect irregularities in hedge fund returns.

Darolles S., Vaissié M. (2013), Regulation: Threat or Opportunity for the Funds of Hedge Funds Industry?, in Brown S., Gregoriou G. (eds), Reconsidering funds of hedge funds : the financial crisis and best practices in UCITS, tail risk, performance, and due diligence, Oxford, Academic Press, p. 481–493

A tidal wave of regulation is hitting financial markets worldwide as a result of the credit crisis of 2008-2009 and this time around the hedge fund world will not be immune. We argue in this chapter that, unlike conventional wisdom, regulation could be an opportunity for the funds of hedge funds (FoHFs) industry. The only necessary condition is fair treatment of hedge fund investments. We take the Solvency II framework as an example and show how the implementation of the granularity adjustment, first introduced for implementation in the Basel framework, makes it possible to take into account the diversification potential of FoHFs and in turn reconcile the outcome of the standard formula with empirical evidence.

Communications

Darolles S., Le Fol G. (2014), Trading Volume and Arbitrage,, THAILAND

Decomposing returns into market and stock specific components is common practice and forms the basis of popular asset pricing models. What about volume? Can volume be decomposed in the same way as returns? Lo and Wang (2000) suggest such a decomposition. Our paper contributes to this literature in two different ways. First, we provide a model to explain why volumes deviate from the benchmark. Our interpretation is in terms of arbitrage strategies and liquidity. Second, we propose a new efficient screening tool that allows practitioners to extract specific information from volume time series. We provide an empirical illustration of the relevance and the possible uses of our approach on daily data from the FTSE index from 2000 to 2002.

Darolles S., Dudek J., Le Fol G. (2014), Liquidity risk and contagion for liquid funds, 31st International French Finance Association Conference, AFFI 2014, Aix-en-Provence, FRANCE

Fund managers face liquidity problems but they have to distinguish the market liquidity risk implied by their assets and the funding liquidity risk. This latter is due to both the liquidity mismatch between assets and liabilities and the redemption risk due to the possible outflows from clients. The main contribution of this paper is the analysis of contagion looking at common market liquidity problems to detect funding liquidity problems. Using the CDS Bond Spread basis as a liquidity indicator and a state space model with time-varying volatility specification, we show that during the 2007-2008 financial crisis, there exist pure contagion effects both in terms of price and liquidity on the emerging sovereign debt market. This result has strong implication since the main risk for an asset manager is to get stuck with an unwanted position due to a dry-up of market liquidity.

Darolles S., Dubecq S., Gouriéroux C. (2014), Contagion Analysis In The Banking Sector, 31st International French Finance Association Conference, AFFI 2014, Aix-en-Provence, FRANCE

This paper analyses how an external adverse shock will impact the financial situations of banks and insurance companies and how it will diffuse among these companies. In particular we explain how to disentangle the direct and indirect (contagion) effects of such a shock, how to exhibit the contagion network and how to detect the "superspreaders", i.e. the most important firms involved in the contagion process. This method is applied to a network of 8 large European banks in order to analyze whether the revealed interconnections within these banks differ depending on the underlying measure of banks' financial positions, namely their market capitalization, the price of the CDS contract written on their default and their book value.

Darolles S., Gouriéroux C. (2014), The Effects of Management and Provision Accounts on Hedge Fund Returns - Part II: The Loss Carry Forward Scheme, Seventh International Conference of the Thailand Econometric Society, Chiang Mai, Thaïlande

In addition to active portfolio management, hedge funds are characterized by the allocation of portfolio performance between the external investors and the management firm accounts. This allocation can take different forms, such as the Loss Carry Forward scheme, and some of them can be coupled with performance smoothing techniques. This paper shows that this additional smoothing component might explain some empirical facts observed on the distribution and the dynamics of hedge fund returns.

Darolles S., Gouriéroux C. (2014), The Effects of Management and Provision Accounts on Hedge Fund Returns - Part I: The HighWater Mark Scheme, Seventh International Conference of the Thailand Econometric Society, Chiang Mai, Thaïlande

A characteristic of hedge funds is not only an active portfolio management, but also the allocation of portfolio performance between different accounts, which are the accounts for the external investors and an account for the management firm, respectively. Despite a lack of transparency in hedge fund market, the strategy of performance allocation is publicly available. This paper shows that, for the High WaterMark Scheme, these complex performance allocation strategiesmight explain empirical facts observed in hedge fund returns, such as return persistence, skewed return distribution, bias ratio, or implied increasing risk appetite.

Darolles S., Gagliardini P., Gouriéroux C. (2013), Survival of Hedge Funds: Frailty vs Contagion, 22nd Annual Meeting of the European Financial Management Association - EFMA 2013, Reading, Royaume-Uni

In this paper we examine the dependence between the liquidation risks of individual hedge funds. This dependence can result either from common exogenous shocks (shared frailty), or from contagion phenomena, which occur when an endogenous behaviour of a fund manager impacts the Net Asset Values of other funds. We introduce dynamic models able to distinguish between frailty and contagion phenomena, and test for the presence of such dependence effects, according to the age and management style of the fund. We demonstrate the empirical relevance of our approach by measuring the magnitudes of contagion and exogenous frailty in liquidation risk dependence in the TASS database. The empirical analysis is completed by stress-tests on portfolios of hedge funds.

Darolles S., Dudek J., Le Fol G. (2013), Liquidity Contagion. The Emerging Sovereign Debt Markets example, 30th International French Finance Association Conference, Lyon, FRANCE

Financial markets are today so interconnected that they are fragile to contagion. Massive investment funds with very short horizons in -and out- flows can generate contagion effects between markets. Since 2010, investors are willing to get a liquid exposure to the EMsovereign debt. As a consequence, some asset management firms started to propose products to track the performance of this asset class. However in that case, the fund manager faces a mismatch of liquidity between assets and liabilities and needs some tools to manage the liquidity of his investments. The main contribution of this paper is the analysis of contagion looking at common market liquidity problems to detect funding liquidity problems. Using the CDS Bond Spread basis as a liquidity indicator and a state space model with time-varying volatility specification, we show that during the 2007-2008 financial crisis, there exist pure contagion effects both in terms of price and liquidity on the emergings overeign debt market.This result has strong implication since the main risk for an asset manager is to get stuck with an unwanted position due to a dry-up of market liquidity.

Darolles S., Dudek J., Le Fol G. (2012), MLiq a meta liquidity measure, Computational and Financial Econometrics (CFE'12), Oviedo, SPAIN

The last crisis sheds light on the importance to consider liquidity risk in the financial industry. Indeed, liquidity had a predominant role in propagating the turmoil. In contrast, controlling for liquidity is a difficult task. The definition of liquidity links different dimensions that are impossible to fully capture together. As a consequence, there exist a lot of liquidity measures and we find in the literature some solutions to take into account more than one dimension of liquidity but also liquidity measures considering a long lasting liquidity problem. In this paper, we focus on drastic illiquidity events, i.e liquidity problems reported by several liquidity measures simultaneously. We propose a Meta-Measure of liquidity called MLiq and defined as the probability to be in a state of high liquidity risk. We use a multivariate model allowing to measure correlations between liquidity measures jointly with a state-space model that endogenously defines the illiquid periods.

Darolles S., Dudek J., Le Fol G. (2012), Liquidity Contagion. The Emerging Sovereign Debt Markets example, European Economic Association & Econometric Society, Malaga, SPAIN

Emerging economies have passed an important stress test during the period 2008-09 and are now the key drivers for global growth of the world economy. Financial markets are today so interconnected that they are fragile to contagion. The issue of financial contagion was historically concerning Emerging Markets (EM). These latter attract foreign investors and massive investments funds in -and out- flows on very short horizons can be a source of contagion effects between markets. The analysis of the sovereign debt markets and particularly related CDS markets is of interest since it is at the very center of a new phenomenon: banks are not anymore the main source of systemic risk but sovereign economies are. As foreign investors represent the most of the volume traded, capital flows in these markets should also impact FX market. Their analysis is thus also central to this study. Indeed, the main risk for an asset manager is to get stuck with unwanted sovereign debt due to a dry up of market liquidity. The main contribution of this paper is the analysis of contagion looking at common markets liquidity problems to detect funding liquidity problems. We use the Credit Default Swap bond spread basis and the deviations from the Covered Interest Parity as liquidity measures respectively for sovereign debt and FX markets. Moreover, we distinguish interdependence and pure contagion using a state-space model with a time-varying volatility specification and we apply it to both returns and liquidity indicators.

Darolles S., Le Fol G., Mero G. (2011), Tracking Illiquidities in Intradaily and Daily Characteristics, 28th annual International Conference of the French Finance Association, Montpellier, France

In this article, we distinguish between two types of liquidity problems called respectively liquidity frictions and illiquidity events. The first one is related to order imbalances that are resorbed within the trading day. It can be assimilated to "immediacy cost" and impacts the traded volume at the intraday and daily frequencies while affecting the price increments only at the intraday periodicity. The second one is inherent to the long lasting liquidity problems and is responsible for the time-dependence of the daily returns. We extend the MDHL framework of Darolles et al. (2010) to account for the presence of the illiquidity events. We then propose a two-step signal extraction formulation of the MDHL model in order to separate the two liquidity problem impacts on the daily returns and volume. We also provide, for a set of FTSE100 individual stocks, long lasting illiquidity indicators.

Gagliardini P., Gouriéroux C., Darolles S. (2011), Survival of Hedge Funds: Frailty vs Contagion, European Economic Association & Econometric Society, Malaga, Espagne

The rather short lifetimes of a majority of hedge funds and the reasons of their liquidation explain the interest of investors and academics in hedge fund survival analysis. In this paper we are interested in the dependence between liquidation risks of individual hedge funds. This dependence can either result from common exogenous shocks (frailty), or be due to contagion phenomena, which occur when an endogenous behaviour of a fund manager impacts the Net Asset Values of other funds. We introduce dynamic models able to distinguish between frailty and contagion phenomena, and to test for the presence and magnitude of such dependence effects, according to the age and management style of the fund.

Darolles S., Le Fol G., Mero G. (2011), When Market Illiquidity Generates Volume, First Meeting of the ANR Econom&Risk (Econometric Approaches for Risk Modeling), Orléans, FRANCE

We develop a model of the daily return-volume relationship which incorporates information and liquidity shocks. First, we distinguish between two trading strategies, information-based and liquidity-based trading and suggest that their respective impacts on returns and volume should be modeled differently. Second, we integrate the microstructure setting of Grossman-Miller (1988) with the information flow perspective of Tauchen-Pitts (1983) and derive a modified MDH model with two latent factors related to information and liquidity. Our model explains how the liquidity frictions can increase the daily traded volume, in the presence of liquidity arbitragers. Finally, we propose a stock-specific liquidity measure using daily return and volume observations of FTSE100 stocks.

Darolles S., Gouriéroux C., Gagliardini P. (2011), Survival of Hedge Funds: Frailty vs Contagion, International Conference on Stochastic Analysis and Applications, Hammamet, Tunisie

The rather short lifetimes of a majority of hedge funds and the reasons of their liquidation explain the interest of investors and academics in hedge fund survival analysis. In this paper we are interested in the dependence between liquidation risks of individual hedge funds. This dependence can either result from common exogenous shocks (frailty), or be due to contagion phenomena, which occur when an endogenous behaviour of a fund manager impacts the Net Asset Values of other funds. We introduce dynamic models able to distinguish between frailty and contagion phenomena, and to test for the presence and magnitude of such dependence effects, according to the age and management style of the fund.

Jay E., Duvaut P., Darolles S., Gouriéroux C. (2011), lq-regularization of the Kalman filter for exogenous outlier removal: application to hedge funds analysis, Fourth International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), San Juan, Porto Rico

This paper presents a simple and efficient exogenous outlier detection & estimation algorithm introduced in a regularized version of the Kalman Filter (KF). Exogenous outliers that may occur in the observations are considered as an additional stochastic impulse process in the KF observation equation that requires a regularization of the innovation in the KF recursive equations. Regularizing with a l1- or l2-norm needs to determine the value of the regularization parameter. Since the KF innovation error is assumed to be Gaussian we propose to first detect the possible occurrence of an exogenous impulsive spike and then to estimate its amplitude using an adapted value of the regularization parameter. The algorithm is first validated on synthetic data and then applied to a concrete financial case that deals with the analysis of hedge fund returns. The proposed algorithm can detect anomalies frequently observed in hedge returns such as illiquidity issues.

Gouriéroux C., Darolles S., Jay E., Duvaut P. (2011), lq-regularization of the Kalman filter for exogenous outlier removal: application to hedge funds analysis, 5th CSDA International Conference on Computational and Financial Econometrics (CFE'11), Londres, Royaume-Uni

A simple and efficient exogenous outlier detection & estimation algorithm introduced in a regularized version of the Kalman filter is presented. Exogenous outliers that may occur in the observations are considered as an additional stochastic impulse process in the observation equation of the Kalman filter that requires a regularization of the innovation in the recursive equations of the Kalman filter. Regularizing with a l1 or l2-norm needs to determine the value of the regularization parameter. Since the innovation error of the KF is assumed to be Gaussian we propose to first detect the possible occurrence of a non-Gaussian spike and then to estimate its amplitude using an adapted value of the regularization parameter. The algorithm is first validated on synthetic data and then applied to a concrete financial case that deals with the analysis of hedge fund returns. We show that the proposed algorithm can detect anomalies frequently observed in hedge returns such as illiquidity issues.

Documents de travail

Darolles S., Gouriéroux C., Jay E. (2012), Robust Portfolio Allocation with Systematic Risk Contribution Restrictions,, 48

The standard mean-variance approach can imply extreme weights in some assets in the optimal allocation and a lack of stability of this allocation over time. To improve the robustness of the portfolio allocation, but also to better control for the portfolio turnover and the sensitivity of the portfolio to systematic risk, it is proposed in this paper to introduce additional constraints on both the total systematic risk contribution of the portfolio and its turnover. Our paper extends the existing literature on risk parity in three directions: i) we consider other risk criteria than the variance, such as the Value-at-Risk (VaR), or the Expected Shortfall; ii) we manage separately the systematic and idiosyncratic components of the portfolio risk; iii) we introduce a set of portfolio management approaches which control for the degree of market neutrality of the portfolio, for the strength of the constraint on systematic risk contribution and for the turnover.

Autres publications

Darolles, S., Gouriéroux, C., (2015), Performance fees and hedge fund return dynamics , International Journal of Approximate Reasoning, Volume 65, October 2015, Pages 45–58

Darolles S., (2014), Special issue on hedge funds , guest editor for Bankers, Markets and Investors, Mars-Avril

Darolles, S ; Le Fol, G . Trading volume and Arbitrage. GSTF : Journal on Business Review. Volume 3. n° 3. 2014. pages 30-39

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