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Hedge fund dynamic market sensitivity

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Abstract

Many hedge funds attempt to achieve high returns by employing leverage. However, it is difficult to track the degree of leverage used by hedge funds over time because detailed timely information about their positions in asset markets is generally unavailable. This paper discusses how to combine shrinkage variable selection methods with dynamic regression to compute and track hedge fund leverage on a time-varying basis. We argue that our methodology measures leverage as well as hedge fund sensitivity to markets arising from other sources. Our approach employs the lasso variable selection method to select the independent variables in equations of hedge fund excess returns. With the independent variables selected by the lasso method, a state space model generates the parameter estimates dynamically. The hedge fund market sensitivity indicator is the average of the absolute values of the parameters in the excess return equations. Our indicator peaks at the time of the Long Term Capital Management meltdown in 1998 and again at a critical time in the 2008 financial crisis. In the absence of direct information from hedge fund balance sheets, our approach could serve as an important tool for monitoring market sensitivity and financial distress in the hedge fund industry.

Suggested Citation

  • Jiaqi Chen & Michael Tindall, 2012. "Hedge fund dynamic market sensitivity," Occasional Papers 12-1, Federal Reserve Bank of Dallas.
  • Handle: RePEc:fip:feddop:2012_001
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    1. Getmansky, Mila & Lo, Andrew W. & Makarov, Igor, 2004. "An econometric model of serial correlation and illiquidity in hedge fund returns," Journal of Financial Economics, Elsevier, vol. 74(3), pages 529-609, December.
    2. Tobias Adrian, 2007. "Measuring risk in the hedge fund sector," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 13(Mar).
    3. Vikas Agarwal, 2004. "Risks and Portfolio Decisions Involving Hedge Funds," The Review of Financial Studies, Society for Financial Studies, vol. 17(1), pages 63-98.
    4. Patrick M McGuire & Kostas Tsatsaronis, 2008. "Estimating hedge fund leverage," BIS Working Papers 260, Bank for International Settlements.
    5. Markus K. Brunnermeier & Stefan Nagel, 2004. "Hedge Funds and the Technology Bubble," Journal of Finance, American Finance Association, vol. 59(5), pages 2013-2040, October.
    6. Gupta, Anurag & Liang, Bing, 2005. "Do hedge funds have enough capital? A value-at-risk approach," Journal of Financial Economics, Elsevier, vol. 77(1), pages 219-253, July.
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    Cited by:

    1. Jiaqi Chen & Michael Tindall, 2013. "Understanding hedge fund alpha using improved replication methodologies," Occasional Papers 13-2, Federal Reserve Bank of Dallas.
    2. François-Éric Racicot & Raymond Théoret, 2016. "The q-factor model and the redundancy of the value factor: An application to hedge funds," Journal of Asset Management, Palgrave Macmillan, vol. 17(7), pages 526-539, December.
    3. Boamah, Nicholas Addai, 2022. "Segmentation, business environment and global informational efficiency of emerging financial markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 52-60.
    4. repec:fip:feddop:2:x:1 is not listed on IDEAS

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