Hedge Funds Returns and Deviation from Normality During Crises

2010 ◽  
Author(s):  
François Desmoulins-Lebeault
Keyword(s):  
Hedge Funds ◽  
Hedge Funds Returns

Tracking hedge funds returns using sparse clones

2016 ◽  
Vol 266 (1-2) ◽  
pp. 349-371 ◽  
Author(s):  
Margherita Giuzio ◽  
Kay Eichhorn-Schott ◽  
Sandra Paterlini ◽  
Vincent Weber
Keyword(s):  
Hedge Funds ◽  
Hedge Funds Returns

Skewness in hedge funds returns: classical skewness coefficients vs Azzalini's skewness parameter

2010 ◽  
Vol 6 (4) ◽  
pp. 290-304 ◽  
Author(s):  
Martin Eling ◽  
Simone Farinelli ◽  
Damiano Rossello ◽  
Luisa Tibiletti
Keyword(s):  
Hedge Funds ◽  
Skewness Parameter ◽  
Hedge Funds Returns

scholarly journals Analysis of the dependence structure for time series of hedge funds returns

2021 ◽  
Author(s):  
He Zhu
Keyword(s):  
Time Series ◽  
Hedge Funds ◽  
Pearson Correlation ◽  
Tail Dependence ◽  
Dependence Structure ◽  
Kendall’S Tau ◽  
Multiple Strategies ◽  
Linear Relationships ◽  
Hedge Funds Returns ◽  
Dependence Measures

The aim of the thesis is to emphasize the different dependence measures beyond the well known Pearson correlation. The study is developed in the setting of a fund that deals with multiple strategies hedge funds under risk constraints. The relevance of our analysis is made clears by noticing that the Pearson correlation is sensitive only to linear relationships and it does not capture tail co-movements. Specifically, the dependence measures we focus are Kendall's tau, Spearman's rho and tail dependence. This thesis attempts to suggest some other solutions to an effective optimization that combines various fund strategies by using the aforementioned dependence measures.

Generalized runs tests to detect randomness in hedge funds returns

2015 ◽  
Vol 50 ◽  
pp. 608-615 ◽  
Author(s):  
Rania Hentati-Kaffel ◽  
Philippe de Peretti
Keyword(s):  
Hedge Funds ◽  
Hedge Funds Returns

scholarly journals Analysis of the dependence structure for time series of hedge funds returns

2021 ◽  
Author(s):  
He Zhu
Keyword(s):  
Time Series ◽  
Hedge Funds ◽  
Pearson Correlation ◽  
Tail Dependence ◽  
Dependence Structure ◽  
Kendall’S Tau ◽  
Multiple Strategies ◽  
Linear Relationships ◽  
Hedge Funds Returns ◽  
Dependence Measures

The aim of the thesis is to emphasize the different dependence measures beyond the well known Pearson correlation. The study is developed in the setting of a fund that deals with multiple strategies hedge funds under risk constraints. The relevance of our analysis is made clears by noticing that the Pearson correlation is sensitive only to linear relationships and it does not capture tail co-movements. Specifically, the dependence measures we focus are Kendall's tau, Spearman's rho and tail dependence. This thesis attempts to suggest some other solutions to an effective optimization that combines various fund strategies by using the aforementioned dependence measures.

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