References of "Bodson, Laurent"
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See detailDynamic Hedge Fund Style Analysis with Errors-in-Variables
Bodson, Laurent ULg; Hübner, Georges ULg; Coën, Alain

Conference (2008, June)

This paper revisits the traditional return-based style analysis (RBSA) in presence of time-varying exposures and errors-in-variables (EIV). We first apply a selection algorithm using the Kalman filter to ... [more ▼]

This paper revisits the traditional return-based style analysis (RBSA) in presence of time-varying exposures and errors-in-variables (EIV). We first apply a selection algorithm using the Kalman filter to identify the more appropriate benchmarks for the analyzed fund return. Then, we compute their corresponding higher moment estimated errors-in-variables, i.e. the measurement error series introducing the (cross) moments of order three and four. We adjust the selected benchmarks by subtracting their higher moments estimated EIV from the initial return series, to obtain an estimate of the true uncontaminated benchmarks. We finally run the Kalman filter on these adjusted regressors. Analyzing EDHEC alternative indexes styles, we show that this technique improves the factor loadings and permits to identify more precisely the return sources of the considered hedge fund strategy. [less ▲]

Detailed reference viewed: 52 (21 ULg)
Full Text
Peer Reviewed
See detailDynamic Hedge Fund Style Analysis with Errors-in-Variables
Bodson, Laurent ULg; Hübner, Georges ULg; Coën, Alain

Conference (2008, April)

This paper revisits the traditional return-based style analysis (RBSA) in presence of time-varying exposures and errors-in-variables (EIV). We first apply a selection algorithm using the Kalman filter to ... [more ▼]

This paper revisits the traditional return-based style analysis (RBSA) in presence of time-varying exposures and errors-in-variables (EIV). We first apply a selection algorithm using the Kalman filter to identify the more appropriate benchmarks for the analyzed fund return. Then, we compute their corresponding higher moment estimated errors-in-variables, i.e. the measurement error series introducing the (cross) moments of order three and four. We adjust the selected benchmarks by subtracting their higher moments estimated EIV from the initial return series, to obtain an estimate of the true uncontaminated benchmarks. We finally run the Kalman filter on these adjusted regressors. Analyzing EDHEC alternative indexes styles, we show that this technique improves the factor loadings and permits to identify more precisely the return sources of the considered hedge fund strategy. [less ▲]

Detailed reference viewed: 52 (16 ULg)
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See detailMean-Variance versus Mean-VaR and Mean-Utility Spanning
Bodson, Laurent ULg; Hübner, Georges ULg

in Gregoriou, Greg N. (Ed.) Stock Market Volatility Book (2008)

In this chapter, we contrast the optimal spanning properties of portfolios built under the traditional mean-variance (VAR) or mean-modified value-at-risk (MVaR) approaches with those created with the ... [more ▼]

In this chapter, we contrast the optimal spanning properties of portfolios built under the traditional mean-variance (VAR) or mean-modified value-at-risk (MVaR) approaches with those created with the linear-exponential (linex) utility function. Unlike asset allocation procedures that build on volatility or MVaR as a measure of risk and a single risk aversion parameter that characterizes investors, the use of linex utility introduces risk differentiation amongst investors and the risk-return relation of the optimal portfolio trades off between mean, variance, skewness and kurtosis. We identify efficient portfolios under the three competing frameworks and analyze their optimal allocations. [less ▲]

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See detailBel-20 Index (Brussels)
Bodson, Laurent ULg

in Wankel, Charles (Ed.) Encyclopedia of Business in Today's World (2008)

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See detailMarket Maker
Bodson, Laurent ULg

in Wankel, Charles (Ed.) Encyclopedia of Business in Today's World (2008)

Detailed reference viewed: 52 (8 ULg)
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See detailInternational Securities Identification Numbering (ISIN)
Bodson, Laurent ULg

in Wankel, Charles (Ed.) Encyclopedia of Business in Today's World (2008)

Detailed reference viewed: 30 (8 ULg)
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See detailA Comparison between Optimal Allocations Based on the Modified VaR and on a Utility-Based Risk Measure
Bodson, Laurent ULg; Coën, Alain ULg; Hübner, Georges ULg

in Gregoriou, Greg N. (Ed.) The VaR Modeling Handbook: Practical Applications in Alternative Investing, Banking, Insurance, and Portfolio Management Book (2008)

Many empirical analyses have demonstrated that some financial asset returns like those of hedge funds depart from the normal distribution. From this observation, several new risk measures have been ... [more ▼]

Many empirical analyses have demonstrated that some financial asset returns like those of hedge funds depart from the normal distribution. From this observation, several new risk measures have been created to take into consideration the skewness and the kurtosis of the return distributions. We propose in this chapter to present the impact of higher moments on the optimal portfolio allocation comparing two four-moment risk measures, namely a utility-based risk measure with the preference-free modified VaR (MVaR). [less ▲]

Detailed reference viewed: 79 (21 ULg)
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See detailAn X Ray of Money Market Fund Risks
Bodson, Laurent ULg; Debatty, Philippe; Masquelier, F.

in Treasury Management International Magazine (2008)

Detailed reference viewed: 37 (9 ULg)
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See detailLinearizing Option Returns for Portfolio and Risk Management
Bodson, Laurent ULg; Hübner, Georges ULg

Conference (2007, October 18)

This paper proposes a method to deduce the first four moments and the co-moments (with any other asset) of an option return. We consider the dynamics of an option-replicating portfolio of four basic ... [more ▼]

This paper proposes a method to deduce the first four moments and the co-moments (with any other asset) of an option return. We consider the dynamics of an option-replicating portfolio of four basic assets: the underlying, two long-term options and a zero coupon bond. This approach allows us to capture the moments up to order four of the underlying and to linearize the option return. A numerical example illustrates some of the features and applications of this model. [less ▲]

Detailed reference viewed: 37 (11 ULg)
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See detailDynamic Style Analysis with Errors in Variables
Bodson, Laurent ULg

Master of advanced studies dissertation (2007)

This paper revisits the traditional return-based style analysis (RBSA) in presence of time-varying exposures and errors in variables. We apply a selection algorithm using the Kalman filter to identify the ... [more ▼]

This paper revisits the traditional return-based style analysis (RBSA) in presence of time-varying exposures and errors in variables. We apply a selection algorithm using the Kalman filter to identify the more appropriate benchmarks and we compute their corresponding higher moment estimators (HME), i.e. the measurement error series introducing the (cross) moments of order three and four. Then, we retain the most significant HME and we add them to the selected benchmarks. Therefore, we obtain the most relevant benchmarks with none, some or all their HME as benchmarks explaining the analyzed fund return. We finally run the Kalman filter on the principal components of this set of selected benchmarks to avoid multicollinearity problems. Analysing EDHEC alternative indexes styles, we show that this technique improves the factor loadings and permits to identify more precisely the return sources of the considered fund. [less ▲]

Detailed reference viewed: 56 (6 ULg)
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See detailLinearizing Option Returns for Portfolio and Risk Management: A Tetranomial Approach
Bodson, Laurent ULg; Hübner, Georges ULg

Conference (2006, November 21)

This paper proposes a method to deduce the first four moments and the co-moments (with any other asset) of an option return. We consider the dynamics of an option-replicating portfolio of four basic ... [more ▼]

This paper proposes a method to deduce the first four moments and the co-moments (with any other asset) of an option return. We consider the dynamics of an option-replicating portfolio of four basic assets: the underlying, two long-term options and a zero coupon bond. This approach allows us to capture the moments up to order four of the underlying and to linearize the option return. A numerical example illustrates some of the features and applications of this model. [less ▲]

Detailed reference viewed: 47 (16 ULg)
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See detailAnalyse de l’intégration de produits dérivés dans un référentiel rendement-risque
Bodson, Laurent ULg

Master's dissertation (2006)

We present a model which aims at integrating derivatives into a portfolio management tool, taking into account the first four moments of the distributions of the assets it analyzes. We propose a new ... [more ▼]

We present a model which aims at integrating derivatives into a portfolio management tool, taking into account the first four moments of the distributions of the assets it analyzes. We propose a new approach by regarding any optional asset as a portfolio made up of four basic assets which duplicates perfectly its payments. In order to preserve the first four moments of the distributions of the basic assets, we build the quadrinomial trees of their future evolution. In addition to the tree of the underlying asset calibrated on its historical values and the tree of the riskless asset, we build the quadrinomial trees of two European-style puts to fill out our market (Ross, 1976). We force the risk-neutral probabilities to be nonnegative in order to correct the trees of the two additional options and exclude arbitrage opportunities created by their valuation using the Black and Scholes formula (1973). We build the quadrinomial tree of the optional asset according to these risk-neutral probabilities. We determine, starting from the trees produced, the sensitivities (deltas) of the optional asset with respect to each one of its basic assets over the first period of the tree. These values allow us to deduct the weight of each basic asset in the replication portfolio. We then obtain a linear function between the optional asset’s return and the returns of its basic assets. We calculate the moments and co-moments of the historical returns of each basic asset to establish the moments of the optional asset, and in addition its co-moments with the market. We then present a concrete implementation of the model and three of its potential applications: the calculation of the VaR of an optional asset, the creation of a portfolio with guaranteed capital and the integration of an optional asset into an unspecified portfolio. [less ▲]

Detailed reference viewed: 116 (12 ULg)