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https://ssrn.com/abstract=1694442
 
 

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Risk-Reward Optimisation for Long-Run Investors: An Empirical Analysis


Manfred Gilli


Geneva School of Economics and Management (GSEM); Swiss Finance Institute

Enrico Schumann


AQ Investment AG

September 28, 2009

European Actuarial Journal, Vol. 1, No. 1 (supplement 2), pp. 303-327, 2011

Abstract:     
A common approach in portfolio selection is to characterise a portfolio of assets by a desired property, the reward, and something undesirable, the risk. These properties are often identified with mean and variance of returns, respectively, even though, given the non-Gaussian nature of financial time series, alternative specifications like partial and conditional moments, quantiles, and drawdowns seem theoretically more appropriate. We analyse the empirical performance of portfolios selected by optimising risk-reward ratios constructed from such alternative functions. We find that in many cases these portfolios outperform our benchmark (minimum-variance), in particular when long-run returns are concerned. We also find, however, that all the strategies tested (including minimum-variance) are sensitive to relatively small changes in the data. The main theme throughout our analysis is that minimising risk, as opposed to maximising reward, leads to good out-of-sample performance. Adding a reward-function to the selection criterion usually improves a given strategy only marginally.

Number of Pages in PDF File: 26

Keywords: Portfolio optimisation, Optimisation heuristics, Downside risk

JEL Classification: G11


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Date posted: October 20, 2010 ; Last revised: March 15, 2013

Suggested Citation

Gilli, Manfred and Schumann, Enrico, Risk-Reward Optimisation for Long-Run Investors: An Empirical Analysis (September 28, 2009). European Actuarial Journal, Vol. 1, No. 1 (supplement 2), pp. 303-327, 2011. Available at SSRN: https://ssrn.com/abstract=1694442

Contact Information

Manfred Gilli
Geneva School of Economics and Management (GSEM) ( email )
Bd du Pont d'Arve 46
Geneva 4, 1211
Switzerland
+41223798222 (Phone)
+41223798299 (Fax)
HOME PAGE: http://www.unige.ch/ses/metri/gilli/
Swiss Finance Institute ( email )
c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland
Enrico Schumann (Contact Author)
AQ Investment AG ( email )
Baarerstrasse 10
Zug, 6304
Switzerland
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