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Implications of Nonlinear Dynamics for Financial Risk Management

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Author Info
Hsieh, David A.
Abstract

This paper demonstrates that when log price changes are not IID, their conditional density may be more accurate than their unconditional density for describing short-term behavior. Using the BDS test of independence and identical distribution, daily log price changes in four currency futures contracts are found to be not IID. While there appear to be no predictable conditional mean changes, conditional variances are predictable, and can be described by an autoregressive volatility model that seems to capture all the departures from independence and identical distribution. Based on this model, daily log price changes are decomposed into a predictable part, which is described parametrically by the autoregressive volatility model, and an unpredictable part, which can be modeled by an empirical density, either parametrically or nonparametrically. This two-step seminonparametric method yields a conditional density for daily log price changes, which has a number of uses in financial risk management.

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Publisher Info
Article provided by Cambridge University Press in its journal Journal of Financial and Quantitative Analysis.

Volume (Year): 28 (1993)
Issue (Month): 01 (March)
Pages: 41-64
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:cup:jfinqa:v:28:y:1993:i:01:p:41-64_00

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  1. Jose A. Lopez & Christian A. Walter, 2000. "Evaluating covariance matrix forecasts in a value-at-risk framework," Working Papers in Applied Economic Theory 2000-21, Federal Reserve Bank of San Francisco. [Downloadable!]
  2. William Fallon, 1996. "Calculating Value-at-Risk," Center for Financial Institutions Working Papers 96-49, Wharton School Center for Financial Institutions, University of Pennsylvania. [Downloadable!]
  3. John M. Maheu & Thomas H. McCurdy, 2001. "Nonlinear Features of Realized FX Volatility," CIRANO Working Papers 2001s-42, CIRANO. [Downloadable!]
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  4. Yi-Ting Chen & Chung-Ming Kuan, 2002. "Time irreversibility and EGARCH effects in US stock index returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 565-578. [Downloadable!]
  5. Cotter, John & Dowd, Kevin, 2007. "Estimating financial risk measures for futures positions: a non-parametric approach," MPRA Paper 3503, University Library of Munich, Germany. [Downloadable!]
  6. Peter F. Christoffersen & Francis X. Diebold, 1997. "How Relevant is Volatility Forecasting for Financial Risk Management?," Center for Financial Institutions Working Papers 97-45, Wharton School Center for Financial Institutions, University of Pennsylvania. [Downloadable!]
    Other versions:
  7. Torben G. Andersen & Tim Bollerslev, 1997. "Answering the Critics: Yes, ARCH Models Do Provide Good Volatility Forecasts," NBER Working Papers 6023, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  8. Evzen Kocenda, 2003. "An Alternative to the BDS Test: Integration Across The Correlation Integral," Econometrics 0301004, EconWPA. [Downloadable!]
    Other versions:
  9. John Cotter, 2004. "Realized volatility and minimum capital requirements," Money Macro and Finance (MMF) Research Group Conference 2003 20, Money Macro and Finance Research Group. [Downloadable!]
  10. Cotter, John, 2004. "Minimum Capital Requirement Calculations for UK Futures," MPRA Paper 3527, University Library of Munich, Germany. [Downloadable!]
  11. Jaehun Chung & Yongmiao Hong, 2007. "Model-free evaluation of directional predictability in foreign exchange markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(5), pages 855-889. [Downloadable!]
  12. Cotter, John & Longin, Francois, 2004. "Margin setting with high-frequency data," MPRA Paper 3528, University Library of Munich, Germany, revised 2006. [Downloadable!]
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