Newedge Research Chair

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Société Générale Prime Services (Newedge) "Advanced Modelling for Alternative Investments" Research Chair

The aim of the Société Générale Prime Services (Newedge) "Advanced Modelling for Alternative Investments" research chair is to develop advanced modelling techniques that can be used for alternative investment returns.

The research chair will expand the frontiers in alternative investment modelling techniques by enhancing the understanding of the dynamic and non-linear relationship between alternative investment returns and the returns on underlying fundamental systematic factors, and analysing the implications in terms of the management of portfolios including alternative investments

The chair is under the leadership of Lionel Martellini, director of EDHEC-Risk Institute.

Press release announcing the creation of the research chair: 25/06/09


Research output:

Alternative Equity Beta Investing: A Survey 
July 2015 
Noël Amenc, Felix Goltz, Véronique Le Sourd, Ashish Lodh 
Alternative equity beta investing has attracted increased attention within the industry recently. Though products in this segment currently represent only a fraction of overall assets, there has been tremendous growth recently in terms of both assets under management and new product development. In this context, EDHEC-Risk Institute carried out a survey among a representative sample of investment professionals to identify their views and uses of alternative equity beta. [Press release announcing the publication of the research: 30/07/15]

An Analysis of the Convergence between Mainstream and Alternative Asset Management 
February 2013 
Juha Joenväärä, Robert Kosowski 
This paper provides an academic analysis of the main techniques that are currently used by hedge fund managers and that could be transported to the mutual fund and alternative UCITS space in a straightforward manner so as to provide better forms of risk management in a regulated environment. It also examines the convergence between the mainstream and the alternative asset management industry by studying UCITS and non-UCITS hedge funds. [Press release announcing the publication of the research: 04/04/13]

Robust Assessment of Hedge Fund Performance through Nonparametric Discounting 
June 2012 
Caio Almeida, René Garcia 
This paper evaluates the performance of hedge funds through a new nonlinear risk adjustment of returns. The risk adjustment is such that it prices exactly the usual set of risk factors considered in the hedge fund literature. This nonlinear risk adjustment goes beyond the usual linear regression methodology used in many hedge fund performance papers, including nonlinear exposures based on option-like features. The approach proposed in this paper overcomes two important limitations of the linear methodology: it captures the nonlinear exposure of a hedge fund strategy to several risk factors, and it is not limited to nonlinear shapes resembling standard option payoff patterns. This methodology is applied to various hedge fund indices as well as to individual hedge funds, considering a set of risk factors including equities, bonds, credit, currencies and commodities. The main message that emerges from the analysis on the performance of hedge fund strategies is that exposure to higher-moment risks on the various factors matters. Analysing the performance of HFRI indices on primary strategies and sub-classes of primary strategies, the paper reports sizeable differences in performance, between the linear and the nonlinear risk adjustment. Most often the nonlinear risk adjustment reduces the performance but for some sub-classes it enhances their performance. It also shows how to conduct a risk analysis and provides an example where a change in a single risk factor can affect the average performance of funds when more robust risk adjustment is applied. [Press release announcing the publication of the research: 13/07/12]

Optimal Hedge Fund Allocation with Improved Estimates for Coskewness and Cokurtosis Parameters 
September 2010 
Asmerilda Hitaj, Lionel Martellini, Giovanni Zambruno 
This paper presents an application of the improved estimators for higher-order comoment parameters, recently introduced by Martellini and Ziemann (2010), in the context of hedge fund portfolio optimisation. It finds that the use of these enhanced estimates generates significant improvement for investors in hedge funds, and that it is only when improved estimators are used that portfolio selection with higher-order moments consistently dominates mean-variance analysis from an out-of-sample perspective. The results have important potential implications for hedge fund investors and hedge fund of funds managers who routinely use portfolio optimisation procedures incorporating higher moments. [Press release announcing the publication of the research: 04/11/10]

Improved Estimates of Higher-Order Comoments and Implications for Portfolio Selection 
February 2010 
Lionel Martellini, Volker Ziemann 
In the presence of non-normally distributed asset returns, optimal portfolio selection techniques require estimates for variance-covariance parameters, along with estimates for higher-order moments and comoments of the return distribution. This is a formidable challenge that severely exacerbates the dimensionality problem already present with mean-variance analysis. This paper extends the existing literature, which has mostly focused on the covariance matrix, by introducing improved estimators for the coskewness and cokurtosis parameters. We find that the use of these enhanced estimates generates a significant improvement in investors’ welfare. We also find that it is only when improved estimators are used that portfolio selection with higher-order moments dominates mean-variance analysis from an out-of-sample perspective. [Press release announcing the publication of the research: 13/10/10]

Passive Hedge Fund Replication – Beyond the Linear Case 
September 2009 
Noël Amenc, Lionel Martellini, Jean-Christophe Meyfredi, Volker Ziemann 
In this paper we extend Hasanhodzic and Lo (2007) by assessing the out-of-sample performance of various non-linear and conditional hedge fund replication models. We find that going beyond the linear case does not necessarily enhance the replication power. On the other hand, we find that selecting factors on the basis of an economic analysis can lead to a substantial improvement in out-of-sample replication quality, whatever the underlying form of the factor model. Overall, we confirm the findings in Hasanhodzic and Lo (2007)—the performance of the replicating strategies is systematically inferior to that of the actual hedge funds.


Related Research:

EDHEC-Risk Hedge Fund Reporting Survey 
November 2008 
Felix Goltz, David Schröder 
The objective of this survey is to shed light on current industry practices in order to establish an industry benchmark for hedge fund reporting in Europe. This research was produced with the support of Newedge.

EDHEC-Risk Funds of Hedge Fund Reporting Survey 
January 2005 
Noël Amenc, Philippe Malaise, Mathieu Vaissié 
The first study conducted worldwide comparing and contrasting suggestions from the industry (buy-side and sell-side) and academic recommendations on the sensitive issue of investor information.

EDHEC-Risk European Alternative Diversification Practices Survey 
December 2005
Noël Amenc, Walter Gehin, Jean-René Giraud, Lionel Martellini, Mathieu Vaissié 
A detailed assessment of current institutional practices in Europe, together with a summary of the research carried out by EDHEC-Risk Institute and by numerous professional and academic institutions on this topic. This survey was supported by Newedge (formerly Fimat).

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