IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Forecasting the intraday market price of money

Market efficiency hypothesis suggests a zero level for the intraday interest rate. However, a liquidity crisis introduces frictions related to news, which can cause an upward jump of the intraday rate. This paper documents that these dynamics can be partially predicted during turbulent times. A long memory approach outperforms random walk and autoregressive benchmarks in terms of point and density forecasting. The gains are particular high when the full distribution is predicted and probabilistic assessments of future movements of the interest rate derived by the model can be used as a policy tool for central banks to plan supplementary market operations during turbulent times. Adding exogenous variables to proxy funding liquidity and counterparty risks does not improve forecast accuracy and the predictability seems to derive from the econometric properties of the series more than from news available to financial markets in realtime.

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.

File URL: http://www.norges-bank.no/en/Published/Papers/Working-Papers/2011/WP-201106/
Download Restriction: no

Paper provided by Norges Bank in its series Working Paper with number 2011/06.

as
in new window

Length: 26 pages
Date of creation: 06 Jun 2011
Date of revision:
Handle: RePEc:bno:worpap:2011_06
Note: First version:
Contact details of provider: Postal: Postboks 1179 Sentrum, 0107 Oslo
Phone: +47 22 31 60 00
Fax: +47 22 41 31 05
Web page: http://www.norges-bank.no/
Email:


More information through EDIRC

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.:

as in new window
  1. Christian Kascha & Francesco Ravazzolo, 2008. "Combining inflation density forecasts," Working Paper 2008/22, Norges Bank.
  2. Anne Sofie Jore & James Mitchell & Shaun Vahey, 2008. "Combining Forecast Densities from VARs with Uncertain Instabilities," Reserve Bank of New Zealand Discussion Paper Series DP2008/18, Reserve Bank of New Zealand.
  3. Donald Robertson & Stephen Wright, 2012. "The Predictive Space, or, If x predicts y, what does y tell us about x?," Birkbeck Working Papers in Economics and Finance 1210, Birkbeck, Department of Economics, Mathematics & Statistics.
  4. Baglioni, Angelo & Monticini, Andrea, 2010. "The intraday interest rate under a liquidity crisis: The case of August 2007," Economics Letters, Elsevier, vol. 107(2), pages 198-200, May.
  5. Geweke, John & Amisano, Gianni, 2008. "Comparing and evaluating Bayesian predictive distributions of assets returns," Working Paper Series 0969, European Central Bank.
  6. Heider, Florian & Hoerova, Marie & Holthausen, Cornelia, 2009. "Liquidity hoarding and interbank market spreads: the role of counterparty risk," Working Paper Series 1126, European Central Bank.
  7. Angelo Baglioni & Andrea Monticini, 2013. "Why Does the Interest Rate Decline Over the Day? Evidence from the Liquidity Crisis," Journal of Financial Services Research, Springer, vol. 44(2), pages 175-186, October.
  8. Amit Goyal & Ivo Welch, 2004. "A Comprehensive Look at the Empirical Performance of Equity Premium Prediction," Yale School of Management Working Papers amz2412, Yale School of Management, revised 01 Jan 2006.
  9. Bhattacharya, Joydeep & Haslag, Joseph & Martin, Antoine, 2007. "Why Does Overnight Liquidity Cost More Than Intraday Liquidity?," Staff General Research Papers 13096, Iowa State University, Department of Economics.
  10. Enghin Atalay & Antoine Martin & James McAndrews, 2008. "The welfare effects of a liquidity-saving mechanism," Staff Reports 331, Federal Reserve Bank of New York.
  11. David Byers & James Davidson & David Peel, 1997. "Modelling Political Popularity: an Analysis of Long-range Dependence in Opinion Poll Series," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 160(3), pages 471-490.
  12. Martin, Antoine & McAndrews, James, 2008. "Liquidity-saving mechanisms," Journal of Monetary Economics, Elsevier, vol. 55(3), pages 554-567, April.
  13. Raffaella Giacomini & Halbert White, 2003. "Tests of Conditional Predictive Ability," Econometrics 0308001, EconWPA.
  14. Andrew Ang & Monika Piazzesi, 2001. "A No-Arbitrage Vector Autoregression of Term Structure Dynamics with Macroeconomic and Latent Variables," NBER Working Papers 8363, National Bureau of Economic Research, Inc.
  15. Graham Elliott & Thomas J. Rothenberg & James H. Stock, 1992. "Efficient Tests for an Autoregressive Unit Root," NBER Technical Working Papers 0130, National Bureau of Economic Research, Inc.
  16. Christian Huurman & Francesco Ravazzolo & Chen Zhou, 2010. "The power of weather," DNB Working Papers 236, Netherlands Central Bank, Research Department.
  17. Diebold, Francis X. & Li, Canlin, 2006. "Forecasting the term structure of government bond yields," Journal of Econometrics, Elsevier, vol. 130(2), pages 337-364, February.
  18. David C. Mills, Jr. & Travis D. Nesmith, 2007. "Risk and concentration in payment and securities settlement systems," Finance and Economics Discussion Series 2007-62, Board of Governors of the Federal Reserve System (U.S.).
  19. James D. Hamilton, 2007. "Daily Changes in Fed Funds Futures Prices," NBER Working Papers 13112, National Bureau of Economic Research, Inc.
  20. Martin, Antoine, 2004. "Optimal pricing of intraday liquidity," Journal of Monetary Economics, Elsevier, vol. 51(2), pages 401-424, March.
  21. Alain Durré & Stefano Nardelli, 2008. "Volatility in the Euro area money market: effects from the monetary policy operational framework," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 13(4), pages 307-322.
  22. Martin, Antoine & McAndrews, James, 2010. "A study of competing designs for a liquidity-saving mechanism," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1818-1826, August.
  23. Francis X. Diebold & Atsushi Inoue, 2000. "Long Memory and Regime Switching," NBER Technical Working Papers 0264, National Bureau of Economic Research, Inc.
  24. Furfine, Craig H, 2001. "Banks as Monitors of Other Banks: Evidence from the Overnight Federal Funds Market," The Journal of Business, University of Chicago Press, vol. 74(1), pages 33-57, January.
  25. Bech, Morten L. & Garratt, Rod, 2003. "The intraday liquidity management game," Journal of Economic Theory, Elsevier, vol. 109(2), pages 198-219, April.
  26. Gianni Amisano & Raffaella Giacomini, 2005. "Comparing Density Forecsts via Weighted Likelihood Ratio Tests," Working Papers ubs0504, University of Brescia, Department of Economics.
  27. Van Hoose, David D., 1991. "Bank behavior, interest rate determination, and monetary policy in a financial system with an intraday federal funds market," Journal of Banking & Finance, Elsevier, vol. 15(2), pages 343-365, April.
  28. Angelini, Paolo, 2000. "Erratum [Are Banks Risk Averse? Intraday Timing of Operations in the Interbank Market]," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 32(3), pages 442, August.
  29. James Mitchell & Stephen G. Hall, 2005. "Evaluating, Comparing and Combining Density Forecasts Using the KLIC with an Application to the Bank of England and NIESR 'Fan' Charts of Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 995-1033, December.
  30. Sowell, Fallaw, 1992. "Maximum likelihood estimation of stationary univariate fractionally integrated time series models," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 165-188.
  31. Michiel de Pooter & Francesco Ravazzolo & Dick van Dijk, 2010. "Term structure forecasting using macro factors and forecast combination," Working Paper 2010/01, Norges Bank.
  32. Angelini, Paolo, 1998. "An analysis of competitive externalities in gross settlement systems," Journal of Banking & Finance, Elsevier, vol. 22(1), pages 1-18, January.
  33. Robert F. Engle & Aaron D. Smith, 1999. "Stochastic Permanent Breaks," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 553-574, November.
  34. Dr. James Mitchell, 2005. "Evaluating, comparing and combining density forecasts using the KLIC with an application to the Bank of England and NIESR ÔfanÕ charts of inflation," NIESR Discussion Papers 777, National Institute of Economic and Social Research.
  35. Diebold, Francis X & Gunther, Todd A & Tay, Anthony S, 1998. "Evaluating Density Forecasts with Applications to Financial Risk Management," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 863-83, November.
  36. Berkowitz, Jeremy, 2001. "Testing Density Forecasts, with Applications to Risk Management," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(4), pages 465-74, October.
  37. Andrew W. Lo, 1989. "Long-term Memory in Stock Market Prices," NBER Working Papers 2984, National Bureau of Economic Research, Inc.
  38. Angelo Baglioni & Andrea Monticini, 2008. "The Intraday Price of Money: Evidence from the e-MID Interbank Market," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(7), pages 1533-1540, October.
  39. Ashley, R & Granger, C W J & Schmalensee, R, 1980. "Advertising and Aggregate Consumption: An Analysis of Causality," Econometrica, Econometric Society, vol. 48(5), pages 1149-67, July.
  40. Leeb, Hannes & P tscher, Benedikt M., 2005. "Model Selection And Inference: Facts And Fiction," Econometric Theory, Cambridge University Press, vol. 21(01), pages 21-59, February.
  41. Angelini, Paolo, 2000. "Are Banks Risk Averse? Intraday Timing of Operations in the Interbank Market," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 32(1), pages 54-73, February.
  42. Pesaran, M Hashem & Timmermann, Allan, 1995. " Predictability of Stock Returns: Robustness and Economic Significance," Journal of Finance, American Finance Association, vol. 50(4), pages 1201-28, September.
  43. Geetesh Bhardwaj & Norman Swanson, 2004. "An Empirical Investigation of the Usefulness of ARFIMA Models for Predicting Macroeconomic and Financial Time Series," Departmental Working Papers 200422, Rutgers University, Department of Economics.
  44. Celso Brunetti & Mario di Filippo & Jeffrey H. Harris, 2011. "Effects of Central Bank Intervention on the Interbank Market During the Subprime Crisis," Review of Financial Studies, Society for Financial Studies, vol. 24(6), pages 2053-2083.
  45. Antoine Martin & James McAndrews, 2008. "An economic analysis of liquidity-saving mechanisms," Economic Policy Review, Federal Reserve Bank of New York, issue Sep, pages 25-39.
  46. Pesaran, M. Hashem & Timmermann, Allan, 2007. "Selection of estimation window in the presence of breaks," Journal of Econometrics, Elsevier, vol. 137(1), pages 134-161, March.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:bno:worpap:2011_06. 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: ()

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.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.