Multifractality and value-at-risk forecasting of exchange rates
This paper addresses market risk prediction for high frequency foreign exchange rates under nonlinear risk scaling behaviour. We use a modified version of the multifractal model of asset returns (MMAR) where trading time is represented by the series of volume ticks. Our dataset consists of 138,418 5-min round-the-clock observations of EUR/USD spot quotes and trading ticks during the period January 5, 2006 to December 31, 2007. Considering fat-tails, long-range dependence as well as scale inconsistency with the MMAR, we derive out-of-sample value-at-risk (VaR) forecasts and compare our approach to historical simulation as well as a benchmark GARCH(1,1) location-scale VaR model. Our findings underline that the multifractal properties in EUR/USD returns in fact have notable risk management implications. The MMAR approach is a parsimonious model which produces admissible VaR forecasts at the 12-h forecast horizon. For the daily horizon, the MMAR outperforms both alternatives based on conditional as well as unconditional coverage statistics.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 401 (2014)
Issue (Month): C ()
|Contact details of provider:|| Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/|
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Waszczuk, Antonina, 2013. "A risk-based explanation of return patterns—Evidence from the Polish stock market," Emerging Markets Review, Elsevier, vol. 15(C), pages 186-210.
- Thomas Lux, 2006.
"The Markov-Switching Multifractal Model of Asset Returns: GMM Estimation and Linear Forecasting of Volatility,"
wp06-19, Warwick Business School, Finance Group.
- Lux, Thomas, 2008. "The Markov-Switching Multifractal Model of Asset Returns: GMM Estimation and Linear Forecasting of Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 194-210, April.
- Lux, Thomas, 2004. "The Markov-switching multi-fractal model of asset returns: GMM estimation and linear forecasting of volatility," Economics Working Papers 2004,11, Christian-Albrechts-University of Kiel, Department of Economics.
- Lux, Thomas, 2006. "The Markov-Switching Multifractal Model of asset returns: GMM estimation and linear forecasting of volatility," Economics Working Papers 2006,17, Christian-Albrechts-University of Kiel, Department of Economics.
- Laurent Calvet & Adlai Fisher, 2002. "Multifractality In Asset Returns: Theory And Evidence," The Review of Economics and Statistics, MIT Press, vol. 84(3), pages 381-406, August.
- Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-55, January.
- Laurent Calvet & Adlai Fisher, 1999.
"Forecasting Multifractal Volatility,"
New York University, Leonard N. Stern School Finance Department Working Paper Seires
99-017, New York University, Leonard N. Stern School of Business-.
- Laurent Calvet, 2000. "Forecasting Multifractal Volatility," Harvard Institute of Economic Research Working Papers 1902, Harvard - Institute of Economic Research.
- Laurent E. Calvet, 2004. "How to Forecast Long-Run Volatility: Regime Switching and the Estimation of Multifractal Processes," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 2(1), pages 49-83.
- Jeremy Berkowitz & James O'Brien, 2002. "How Accurate Are Value-at-Risk Models at Commercial Banks?," Journal of Finance, American Finance Association, vol. 57(3), pages 1093-1111, 06.
- Aktham I. Maghyereh & Haitham A. Al-Zoubi, 2008. "The tail behavior of extreme stock returns in the Gulf emerging markets: An implication for financial risk management," Studies in Economics and Finance, Emerald Group Publishing, vol. 25(1), pages 21-37, March.
- Mulligan, Robert F. & Koppl, Roger, 2011. "Monetary policy regimes in macroeconomic data: An application of fractal analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(2), pages 201-211, May.
- Yi Xue & Ramazan Gencay, 2009.
"Trading Frequency and Volatility Clustering,"
Working Paper Series
31_09, The Rimini Centre for Economic Analysis, revised Jan 2009.
- James McCulloch, 2012. "Fractal Market Time," Research Paper Series 311, Quantitative Finance Research Centre, University of Technology, Sydney.
- R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
- Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-62, November.
- King, Michael & Sarno, Lucio & Sojli, Elvira, 2010. "Timing exchange rates using order flow: The case of the Loonie," Journal of Banking & Finance, Elsevier, vol. 34(12), pages 2917-2928, December.
- Xu, Zhaoxia & Gençay, Ramazan, 2003. "Scaling, self-similarity and multifractality in FX markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 323(C), pages 578-590.
- Kiani, Khurshid M., 2011. "Relationship between portfolio diversification and value at risk: Empirical evidence," Emerging Markets Review, Elsevier, vol. 12(4), pages 443-459.
- Bollerslev, Tim, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
Journal of Econometrics,
Elsevier, vol. 31(3), pages 307-327, April.
- Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- Pierre Giot, 2005. "Market risk models for intraday data," The European Journal of Finance, Taylor & Francis Journals, vol. 11(4), pages 309-324.
- Lobato, I.N. & Savin, N.E., 1996.
"Real and Spurious Long Memory Properties of Stock Market Data,"
96-07, University of Iowa, Department of Economics.
- Lobato, Ignacio N & Savin, N E, 1998. "Real and Spurious Long-Memory Properties of Stock-Market Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 261-68, July.
- I.N. Lobato & N.E. Savin, 1996. "Real and Spurious Long Memory Properties of Stock Market Data," Econometrics 9605004, EconWPA, revised 26 Sep 1996.
- Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
- Sottile, Pedro, 2013. "On the political determinants of sovereign risk: Evidence from a Markov-switching vector autoregressive model for Argentina," Emerging Markets Review, Elsevier, vol. 15(C), pages 160-185.
- Hull, Matthew & McGroarty, Frank, 2014. "Do emerging markets become more efficient as they develop? Long memory persistence in equity indices," Emerging Markets Review, Elsevier, vol. 18(C), pages 45-61.
- Georges Dionne & Pierre Duchesne & Maria Pacurar, 2005.
"Intraday Value at Risk (IVaR) Using Tick-by-Tick Data with Application to the Toronto Stock Exchange,"
Cahiers de recherche
- Dionne, Georges & Duchesne, Pierre & Pacurar, Maria, 2009. "Intraday Value at Risk (IVaR) using tick-by-tick data with application to the Toronto Stock Exchange," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 777-792, December.
- Sensoy, A., 2013. "Generalized Hurst exponent approach to efficiency in MENA markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 5019-5026.
- Nekhili, Ramzi & Altay-Salih, Aslihan & Gençay, Ramazan, 2002. "Exploring exchange rate returns at different time horizons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 313(3), pages 671-682.
- Wei Sun & Svetlozar Rachev & Frank J. Fabozzi, 2009. "A New Approach for Using Lévy Processes for Determining High-Frequency Value-at-Risk Predictions," European Financial Management, European Financial Management Association, vol. 15(2), pages 340-361.
- McCulloch, James, 2012. "Fractal market time," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 686-701.
When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:401:y:2014:i:c:p:71-81. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)
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 references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.