IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v301y2001i1p457-472.html
   My bibliography  Save this article

One idea of portfolio risk control for absolute return strategy risk adjustments by signals from correlation behavior

Author

Listed:
  • Nishiyama, N.

Abstract

Absolute return strategy provided from fund of funds (FOFs) investment schemes is the focus in Japanese Financial Community. FOFs investment mainly consists of hedge fund investment and it has two major characteristics which are low correlation against benchmark index and little impact from various external changes in the environment given maximizing return.

Suggested Citation

  • Nishiyama, N., 2001. "One idea of portfolio risk control for absolute return strategy risk adjustments by signals from correlation behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 301(1), pages 457-472.
  • Handle: RePEc:eee:phsmap:v:301:y:2001:i:1:p:457-472
    DOI: 10.1016/S0378-4371(01)00411-3
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437101004113
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/S0378-4371(01)00411-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Danielsson, Jon & Morimoto, Yuji, 2000. "Forecasting Extreme Financial Risk: A Critical Analysis of Practical Methods for the Japanese Market," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 18(2), pages 25-48, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Valle, C.A. & Meade, N. & Beasley, J.E., 2014. "Absolute return portfolios," Omega, Elsevier, vol. 45(C), pages 20-41.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sofiane Aboura, 2014. "When the U.S. Stock Market Becomes Extreme?," Risks, MDPI, vol. 2(2), pages 1-15, May.
    2. Gencay, Ramazan & Selcuk, Faruk & Ulugulyagci, Abdurrahman, 2003. "High volatility, thick tails and extreme value theory in value-at-risk estimation," Insurance: Mathematics and Economics, Elsevier, vol. 33(2), pages 337-356, October.
    3. Danielsson, Jon & James, Kevin R. & Valenzuela, Marcela & Zer, Ilknur, 2016. "Model risk of risk models," Journal of Financial Stability, Elsevier, vol. 23(C), pages 79-91.
    4. Raymond Knott & Marco Polenghi, 2006. "Assessing central counterparty margin coverage on futures contracts using GARCH models," Bank of England working papers 287, Bank of England.
    5. Salhi, Khaled & Deaconu, Madalina & Lejay, Antoine & Champagnat, Nicolas & Navet, Nicolas, 2016. "Regime switching model for financial data: Empirical risk analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 148-157.
    6. Szymon Lis & Marcin Chlebus, 2021. "Comparison of the accuracy in VaR forecasting for commodities using different methods of combining forecasts," Working Papers 2021-11, Faculty of Economic Sciences, University of Warsaw.
    7. PICIU, Gabriela Cornelia, 2013. "Internal Rating – An Active Instrument In The Management Of Banking Risks. Case Study Bcr," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 17(2), pages 21-30.
    8. Luca Erzegovesi, 2002. "VaR and Liquidity Risk.Impact on Market Behaviour and Measurement Issues," Alea Tech Reports 014, Department of Computer and Management Sciences, University of Trento, Italy, revised 14 Jun 2008.
    9. Benjamin R. Auer & Benjamin Mögel, 2016. "How Accurate are Modern Value-at-Risk Estimators Derived from Extreme Value Theory?," CESifo Working Paper Series 6288, CESifo.
    10. Benjamin Mögel & Benjamin R. Auer, 2018. "How accurate are modern Value-at-Risk estimators derived from extreme value theory?," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 979-1030, May.
    11. Ramzi Nekhili & Jahangir Sultan, 2020. "Jump Driven Risk Model Performance in Cryptocurrency Market," IJFS, MDPI, vol. 8(2), pages 1-18, April.
    12. Dolores Furió & Francisco J. Climent, 2013. "Extreme value theory versus traditional GARCH approaches applied to financial data: a comparative evaluation," Quantitative Finance, Taylor & Francis Journals, vol. 13(1), pages 45-63, January.
    13. Araújo Santos, P. & Fraga Alves, M.I., 2012. "A new class of independence tests for interval forecasts evaluation," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3366-3380.
    14. Wagner, Niklas, 2005. "Autoregressive conditional tail behavior and results on Government bond yield spreads," International Review of Financial Analysis, Elsevier, vol. 14(2), pages 247-261.
    15. Degiannakis, Stavros & Floros, Christos & Dent, Pamela, 2013. "Forecasting value-at-risk and expected shortfall using fractionally integrated models of conditional volatility: International evidence," International Review of Financial Analysis, Elsevier, vol. 27(C), pages 21-33.
    16. Małgorzata Just & Krzysztof Echaust, 2021. "An Optimal Tail Selection in Risk Measurement," Risks, MDPI, vol. 9(4), pages 1-16, April.
    17. Huang, Dashan & Yu, Baimin & Fabozzi, Frank J. & Fukushima, Masao, 2009. "CAViaR-based forecast for oil price risk," Energy Economics, Elsevier, vol. 31(4), pages 511-518, July.
    18. Bekiros, Stelios D. & Georgoutsos, Dimitris A., 2005. "Estimation of Value-at-Risk by extreme value and conventional methods: a comparative evaluation of their predictive performance," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 15(3), pages 209-228, July.
    19. Lee, Tae-Hwy & Saltoglu, Burak, 2002. "Assessing the risk forecasts for Japanese stock market," Japan and the World Economy, Elsevier, vol. 14(1), pages 63-85, January.
    20. Sang Hoon Kang & Seong-Min Yoon, 2009. "Value-at-Risk Analysis for Asian Emerging Markets: Asymmetry and Fat Tails in Returns Innovation," Korean Economic Review, Korean Economic Association, vol. 25, pages 387-411.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:301:y:2001:i:1:p:457-472. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.