Omega performance measure and portfolio insurance

Bertrand, Philippe; Prigent, Jean‐Luc

doi:10.1016/j.jbankfin.2010.12.001

Cited by 88 publications

(47 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To provide more meaningful tests of the MV optimal strategy using historical data, we turn to a bootstrap resampling approach. This type of procedure has been applied in numerous prior studies to assess the performance of investment strategies; some relatively recent examples include Sanfilippo (2003), Ledoit and Wolf (2008), Annaert et al (2009), Bertrand and Prigent (2011), and Cogneau and Zakamouline (2013).…”

Section: Bootstrap Resamplingmentioning

confidence: 99%

Robust Asset Allocation for Long-Term Target-Based Investing

Vetzal

2017

Int. J. Theor. Appl. Finan.

View full text Add to dashboard Cite

This paper explores dynamic mean-variance (MV) asset allocation over long horizons. This is equivalent to target-based investing with a quadratic loss penalty for deviations from the target level of terminal wealth. We provide a number of illustrative examples in a setting with a risky stock index and a risk-free asset. Our underlying model is very simple: the value of the risky index is assumed to follow a geometric Brownian motion diffusion process and the risk-free interest rate is specified to be constant. We impose realistic constraints on the leverage ratio and trading frequency. In many of our examples, the MV optimal strategy has a standard deviation of terminal wealth less than half that of a constant proportion strategy which has the same expected value of terminal wealth, while the probability of shortfall is reduced by a factor of two to three. We investigate the robustness of the model through resampling experiments using historical data dating back to 1926. These experiments also show much lower standard deviation and shortfall probability for the MV optimal strategy relative to a constant proportion strategy with approximately the same expected terminal wealth.

show abstract

Section: Bootstrap Resamplingmentioning

confidence: 99%

Robust Asset Allocation for Long-Term Target-Based Investing

Vetzal

2017

Int. J. Theor. Appl. Finan.

View full text Add to dashboard Cite

show abstract

“…Their difference in the Omega values becomes relatively small as L increases. Bertrand and Prigent (2006) demonstrate that a lower threshold level implies that the investors are more concerned with risk control, and a higher level means that they worry more about the return performance of the portfolio. The results suggest that the VBPI strategy is especially preferable for the more risk-averse investors and for the case of low rebalancing frequency.…”

Section: The Vbpi Strategy Versus the Cppi Strategymentioning

confidence: 92%

The effectiveness of the VaR-based portfolio insurance strategy: An empirical analysis

Jiang¹,

Ma²,

An³

2009

International Review of Financial Analysis

View full text Add to dashboard Cite

“…They found that overall, short positions can improve risk-return characteristics of a portfolio but mitigated this findings with the constraints involved in short positions that often carries additional constraints in terms of transactions costs and liquidity. Bertrand and luc Prigent (2011) analyzed the performance of two main portfolio insurance methods, the OBPI and CPPI strategies, using downside risk measures, thanks to Omega measure. They showed that CPPI strategies perform better than OBPI.…”

Section: Related Workmentioning

confidence: 99%