Robust optimization of conditional value at risk and portfolio selection

Quaranta, Anna Grazia; Zaffaroni, Alberto

doi:10.1016/j.jbankfin.2007.12.025

Cited by 115 publications

(51 citation statements)

References 25 publications

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“…Therefore, mean-variance optimization is generally not used as academically intended, but instead to generate a somewhat unsatisfying set of rough takeaways that guide portfolio choice. Fortunately, the instability of mean-variance optimizations has been partially addressed through recommendations on shrinkage operators and random matrix theory (Jorion [1986], Plerou et al [2002], Sharifi et al [2004], Bai et al [2009]), robust optimizations (Ben-Tal and Nemirovski [1998], Quaranta and Zaffaroni [2008]), and incorporating market-derived parameter estimates.…”

Section: Asset Allocation Reviewmentioning

confidence: 99%

Flexible Indeterminate Factor-Based Asset Allocation

Blyth

Szigety²,

Xia³

2016

JPM

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Asset allocation represents a fundamental strategic decision for every institutional investor.Though many asset allocation approaches have been recommended and implemented in various forms, each has its own strengths and weakness. A careful review of current asset allocation frameworks provided motivation to design a hybrid approach that addresses many of these perceived individual shortcomings. Our guiding principle was to use several familiar elements to create a flexible process that incorporates less-quantifiable investment ideas around a rigorous foundation. The result, which we term Flexible Indeterminate Factor-based Asset Allocation (FIFAA), is an adaptive four-step asset allocation synthesis that remains quantitatively and theoretically well grounded. To achieve this goal, FIFAA overlays informed judgment about investment opportunities onto an objectively derived set of core factor exposures.ACKNOWLEDGEMENTS: The authors would like to thank the following people for valuable input and feedback:

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Section: Asset Allocation Reviewmentioning

confidence: 99%

Flexible Indeterminate Factor-Based Asset Allocation

Blyth

Szigety²,

Xia³

2016

JPM

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“…As indicated in the above, both variance and VaR are not good measures of risk. Therefore, similar to Quaranta and Zaffaroni [32] and Yao et al [33], we set up Mean-CVaR optimization framework of inventory portfolio from the perspective of long-term risk measure. After solving the optimization problem, we could set optimal portfolios, i.e., the efficient frontier.…”

Section: Mean-cvar Optimization Framework Of Inventory Portfoliomentioning

confidence: 99%

The Effects of Long Memory in Price Volatility of Inventories Pledged on Portfolio Optimization of Supply Chain Finance

He¹,

Wang²,

Xiang-lin³

2016

JMF

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Due to the illiquidity of inventories pledged, the essential of price risk management of supply chain finance is to long-term price risk measure. Long memory in volatility, which attests a slower than exponential decay in the autocorrelation function of standard proxies of volatility, yields an additional improvement in specification of multi-period volatility models and further impact on the term structure of risk. Thus, long memory is indispensable to model and measure long-term risk. This paper sheds new light on the impact of the existence and persistence of long memory in volatility on inventory portfolio optimization. Firstly, we investigate the existence of long memory in volatility of the inventory returns, and examine the impact of long memory on the modeling and forecasting of multi-period volatility, the dependence structure between inventory returns and portfolio optimization. Secondly, we further explore the impact of the persistence of long memory in volatility on the efficient frontier of inventory portfolio via a data generation process with different long memory parameter in the FIGARCH model. The extensive Monte Carlo evidence reveals that both GARCH and IGARCH models without accounting for long memory will misestimate the actual long-term risk of the inventory portfolio and further bias the efficient frontier; besides, through A sensitive analysis of long memory parameter d, it is proved that the portfolio with higher long memory parameter possesses higher expected return and lower risk level. In conclusion, banks and other participants will benefit from the long memory taken into the long-term price risk measure and portfolio optimization in supply chain finance.

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“…To this aim we formulate and solve a multistage stochastic programming problem which provides us with enough flexibility in the formulation of the objective function and of the constraints. To deal with uncertainty in optimization problems other approaches are possible and, in particular, we mention Robust Optimization and its application also to financial optimization problems (see, for example, [4][6] [23]). …”

Section: Literature Reviewmentioning

confidence: 99%

Dynamic Tracking Error with Shortfall Control Using Stochastic Programming

Barro

Canestrelli

2012

SSRN Journal

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In this contribution we tackle the issue of portfolio management combining benchmarking and risk control. We propose a dynamic tracking error problem and we consider the problem of monitoring at discrete points the shortfalls of the portfolio below a set of given reference levels of wealth. We formulate and solve the resulting dynamic optimization problem using stochastic programming. The proposed model allows for a great flexibility in the combination of the tracking goal and the downside risk protection. We provide the results of out-of-sample simulation experiments, on real data, for different portfolio configurations and different market conditions.

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Robust optimization of conditional value at risk and portfolio selection

Cited by 115 publications

References 25 publications

Flexible Indeterminate Factor-Based Asset Allocation

Flexible Indeterminate Factor-Based Asset Allocation

The Effects of Long Memory in Price Volatility of Inventories Pledged on Portfolio Optimization of Supply Chain Finance

Dynamic Tracking Error with Shortfall Control Using Stochastic Programming

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