Robust optimization of conditional value at risk and portfolio selection

2008 ◽  
Vol 32 (10) ◽  
pp. 2046-2056 ◽  
Author(s):  
Anna Grazia Quaranta ◽  
Alberto Zaffaroni
Keyword(s):  
At Risk ◽  
Robust Optimization ◽  
Portfolio Selection ◽  
Value At Risk ◽  
Conditional Value At Risk

scholarly journals Robust Optimization-Based Commodity Portfolio Performance

2020 ◽  
Vol 8 (3) ◽  
pp. 54
Author(s):  
Ramesh Adhikari ◽  
Kyle J. Putnam ◽  
Humnath Panta
Keyword(s):  
At Risk ◽  
Robust Optimization ◽  
Value At Risk ◽  
Optimization Technique ◽  
Practical Importance ◽  
Optimization Techniques ◽  
Commodity Futures ◽  
Conditional Value At Risk ◽  
Holding Period ◽  
Mean Variance

This paper examines the performance of a naïve equally weighted buy-and-hold portfolio and optimization-based commodity futures portfolios for various lookback and holding periods using data from January 1986 to December 2018. The application of Monte Carlo simulation-based mean-variance and conditional value-at-risk optimization techniques are used to construct the robust commodity futures portfolios. This paper documents the benefits of applying a sophisticated, robust optimization technique to construct commodity futures portfolios. We find that a 12-month lookback period contains the most useful information in constructing optimization-based portfolios, and a 1-month holding period yields the highest returns among all the holding periods examined in the paper. We also find that an optimized conditional value-at-risk portfolio using a 12-month lookback period outperforms an optimized mean-variance portfolio using the same lookback period. Our findings highlight the advantages of using robust optimization for portfolio formation in the presence of return uncertainty in the commodity futures markets. The results also highlight the practical importance of choosing the appropriate lookback and holding period when using robust optimization in the commodity portfolio formation process.

Systemic Risk-Driven Portfolio Selection

2022 ◽  
Author(s):  
Agostino Capponi ◽  
Alexey Rubtsov
Keyword(s):  
At Risk ◽  
Portfolio Selection ◽  
Systemic Risk ◽  
Value At Risk ◽  
Global Financial Crisis ◽  
Risk Measures ◽  
Conditional Value At Risk ◽  
The Face ◽  
Financial Index ◽  
The Global Financial Crisis

How can we construct portfolios that perform well in the face of systemic events? The global financial crisis of 2007–2008 and the coronavirus disease 2019 pandemic have highlighted the importance of accounting for extreme form of risks. In “Systemic Risk-Driven Portfolio Selection,” Capponi and Rubtsov investigate the design of portfolios that trade off tail risk and expected growth of the investment. The authors show how two well-known risk measures, the value-at-risk and the conditional value-at-risk, can be used to construct portfolios that perform well in the face of systemic events. The paper uses U.S. stock data from the S&P500 Financials Index and Canadian stock data from the S&P/TSX Capped Financial Index, and it demonstrates that portfolios accounting for systemic risk attain higher risk-adjusted expected returns, compared with well-known benchmark portfolio criteria, during times of market downturn.

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