Portfolio value-at-risk forecasting with GA-based extreme value theory

Lin, Ping-Chen; Ko, Po-Chang

doi:10.1016/j.eswa.2008.01.086

Cited by 43 publications

(18 citation statements)

References 19 publications

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“…Efficient portfolios constructed using the minimum VAR strategy were also found to yield performance closer to that expected compared to portfolios selected using the mean-variance model (Durand, Gould & Maller 2011). Using Genetic Algorithm to construct the mean-VAR efficient frontier for listed Taiwanese stocks, robust optimisation results were obtained (Lin & Ko 2009) and it was found that investors might inefficiently allocate their wealth if the decision was based on the mean-variance model (Tsao 2010).…”

Section: Figurementioning

confidence: 91%

Asset Allocation: Analysis of Theory and Practice in the Australian Investment Management Industry

Santacruz

2014

SSRN Journal

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Section: Figurementioning

confidence: 91%

Asset Allocation: Analysis of Theory and Practice in the Australian Investment Management Industry

Santacruz

2014

SSRN Journal

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“…However, most discussions in literatures of risk management (Pennings & Smidts, 2000;Iversen, Mathiassen, & Nielson, 2004;Benaroch, Lichtenstein, & Robinson, 2006;Dewan & Ren, 2007;Gefen, Wyss, & Lichtenstein, 2008;Berkowits, Christoffersen, & Pelletier, 2009;Lin & Ko, 2009;Roisenberg, Schoeninger, & da Silva, 2009) do not seem to generalize to present a systematical way of designing such a SSS.…”

Section: Model Risk and System Flexibility Requirementmentioning

confidence: 93%

A systematic design for coping with model risk

Yang

Tsaih

Hsieh

2011

Expert Systems with Applications

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“…Financial market risk measurement methods include sensitivity analysis [5], volatility [6], pressure experiment [7], extreme value theory, and VaR (Value at Risk) [8; 9]. Value at Risk (VaR), as a tool and method of risk measurement and control, plays a more important role in risk management decisions in financial institutions in recent years [10].…”

Section: Introductionmentioning

confidence: 99%

Statistical assessment on CVaR publications in management innovation

Mei-qin

Penghui

2014

2014 IEEE Workshop on Electronics, Computer and Applications

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CVaR (Conditional Value at Risk) model has been used in management innovation during all the last two decades, and its research outcomes have been increasing steadily since the year of 2000. CVaR was hence an important and hot topic in past 22 years and there were lots journal papers listed in several subject categories in WoS online databases. In this paper, the subjects' categories, top productive countries or institutes, fruitful authors, citations as well as publications' most frequently used author keywords, most frequently used keyword plus were analyzed respectively on total published papers scale. Environmental Science & Ecology, Engineer and Cardiovascular System were the main subjects of CVaR outcomes. It is still in its fast increasing stage during its life circle of production, and more scholars pay attention to CVaR research nowadays. Risk, risk-factors and disease were the most frequently used keywords. The USA had an apparent advantage in both quantity and quality of CVaR research. Research productivity in P.R. China produced a high amount of papers with little citations and citations per paper reflecting heed for important. In addition, the USA was located in the center of the international collaboration networks and almost all the top productive institutes such as the University Texas and Harvard University. Through the global analysis of the develop trends on CVaR research it will give us a clearly view and a deep understanding for future management innovation.

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Portfolio value-at-risk forecasting with GA-based extreme value theory

Cited by 43 publications

References 19 publications

Asset Allocation: Analysis of Theory and Practice in the Australian Investment Management Industry

Asset Allocation: Analysis of Theory and Practice in the Australian Investment Management Industry

A systematic design for coping with model risk

Statistical assessment on CVaR publications in management innovation

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