IDEAS home Printed from https://ideas.repec.org/p/ctc/serie1/def010.html
   My bibliography  Save this paper

Forecasting the intraday market price of money

Author

Listed:
  • Andrea Monticini

    (Dipartimento di Economia e Finanza, Università Cattolica del Sacro Cuore)

  • Francesco Ravazzolo

    (Norges Bank and BI Norwegian Business School)

Abstract

Central banks' operations and eciency arguments would suggest that the intraday interest rate should be set to zero. 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. Long memory approaches or a combination of them to account for model uncertainty outperform random walk, autoregressive and moving average benchmarks in terms of point and density forecasting. The relative accuracy is higher when the full distribution is predicted. We also document that such statistical accuracy can provide economic gains in investment strategies based on lending in the intraday market.

Suggested Citation

  • Andrea Monticini & Francesco Ravazzolo, 2014. "Forecasting the intraday market price of money," DISCE - Working Papers del Dipartimento di Economia e Finanza def010, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    • Handle: RePEc:ctc:serie1:def010
    as

    Download full text from publisher

    File URL: http://dipartimenti.unicatt.it/economia-finanza-def010.pdf
    File Function: First version, 2014
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Martin, Antoine & McAndrews, James, 2008. "Liquidity-saving mechanisms," Journal of Monetary Economics, Elsevier, vol. 55(3), pages 554-567, April.
    2. 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.
    3. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    4. 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.
    5. 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.
    6. Angelini, Paolo, 1998. "An analysis of competitive externalities in gross settlement systems," Journal of Banking & Finance, Elsevier, vol. 22(1), pages 1-18, January.
    7. Raffaella Giacomini & Halbert White, 2006. "Tests of Conditional Predictive Ability," Econometrica, Econometric Society, vol. 74(6), pages 1545-1578, November.
    8. Heider, F. & Hoerova, M. & Holthausen, C., 2009. "Liquidity Hoarding and Interbank Market Spreads : The Role of Counterparty Risk," Discussion Paper 2009-40 S, Tilburg University, Center for Economic Research.
    9. John C. Williams & John B. Taylor, 2009. "A Black Swan in the Money Market," American Economic Journal: Macroeconomics, American Economic Association, vol. 1(1), pages 58-83, January.
    10. Berkowitz, Jeremy, 2001. "Testing Density Forecasts, with Applications to Risk Management," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(4), pages 465-474, October.
    11. 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.
    12. Anne Sofie Jore & James Mitchell & Shaun P. Vahey, 2010. "Combining forecast densities from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 621-634.
    13. 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;Western Finance Association, vol. 44(2), pages 175-186, October.
    14. 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.
    15. McAndrews, James & Sarkar, Asani & Wang, Zhenyu, 2017. "The effect of the term auction facility on the London interbank offered rate," Journal of Banking & Finance, Elsevier, vol. 83(C), pages 135-152.
    16. Olivier Blanchard, 2009. "The Crisis: Basic Mechanisms and Appropriate Policies," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 10(01), pages 3-14, April.
    17. Geweke, John & Amisano, Gianni, 2010. "Comparing and evaluating Bayesian predictive distributions of asset returns," International Journal of Forecasting, Elsevier, vol. 26(2), pages 216-230, April.
    18. James D. Hamilton, 2009. "Daily Changes in Fed Funds Futures Prices," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(4), pages 567-582, June.
    19. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    20. Caporin, Massimiliano & Preś, Juliusz, 2012. "Modelling and forecasting wind speed intensity for weather risk management," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3459-3476.
    21. Leeb, Hannes & Pötscher, Benedikt M., 2005. "Model Selection And Inference: Facts And Fiction," Econometric Theory, Cambridge University Press, vol. 21(1), pages 21-59, February.
    22. 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," National Institute of Economic and Social Research (NIESR) Discussion Papers 253, National Institute of Economic and Social Research.
    23. Bhattacharya, Joydeep & Haslag, Joseph H. & Martin, Antoine, 2009. "Why does overnight liquidity cost more than intraday liquidity?," Journal of Economic Dynamics and Control, Elsevier, vol. 33(6), pages 1236-1246, June.
    24. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    25. Antoine Martin & James J. McAndrews, 2008. "An economic analysis of liquidity-saving mechanisms," Economic Policy Review, Federal Reserve Bank of New York, vol. 14(Sep), pages 25-39.
    26. 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.
    27. 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 863-883, November.
    28. 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.
    29. Christian Kascha & Francesco Ravazzolo, 2010. "Combining inflation density forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 231-250.
    30. Diebold, Francis X. & Inoue, Atsushi, 2001. "Long memory and regime switching," Journal of Econometrics, Elsevier, vol. 105(1), pages 131-159, November.
    31. Ángel León & Francis Benito & Juan Nave, 2006. "Modeling The Euro Overnight Rate," Working Papers. Serie AD 2006-11, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    32. Bech, Morten L. & Garratt, Rod, 2003. "The intraday liquidity management game," Journal of Economic Theory, Elsevier, vol. 109(2), pages 198-219, April.
    33. Amisano, Gianni & Giacomini, Raffaella, 2007. "Comparing Density Forecasts via Weighted Likelihood Ratio Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 177-190, April.
    34. Linzert, Tobias & Abbassi, Puriya, 2011. "The effectiveness of monetary policy in steering money market rates during the recent financial crisis," Working Paper Series 1328, European Central Bank.
    35. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 4, pages 135-196, Elsevier.
    36. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    37. 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 442-442, August.
    38. 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, September.
    39. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    40. Capistrán, Carlos & Timmermann, Allan, 2009. "Forecast Combination With Entry and Exit of Experts," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 428-440.
    41. 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.
    42. Mills Jr., David C. & Nesmith, Travis D., 2008. "Risk and concentration in payment and securities settlement systems," Journal of Monetary Economics, Elsevier, vol. 55(3), pages 542-553, April.
    43. 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.
    44. 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.
    45. Ravazzolo Francesco & Vahey Shaun P., 2014. "Forecast densities for economic aggregates from disaggregate ensembles," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(4), pages 1-15, September.
    46. Michiel De Pooter & Francesco Ravazzolo & Dick van Dijk, 2010. "Term structure forecasting using macro factors and forecast combination," International Finance Discussion Papers 993, Board of Governors of the Federal Reserve System (U.S.).
    47. Ang, Andrew & Piazzesi, Monika, 2003. "A no-arbitrage vector autoregression of term structure dynamics with macroeconomic and latent variables," Journal of Monetary Economics, Elsevier, vol. 50(4), pages 745-787, May.
    48. Brousseau, Vincent & Manzanares, Andrés, 2005. "A look at intraday frictions in the euro area overnight deposit market," Working Paper Series 439, European Central Bank.
    49. Michael J. Fleming & Warren B. Hrung & Frank M. Keane, 2010. "Repo Market Effects of the Term Securities Lending Facility," American Economic Review, American Economic Association, vol. 100(2), pages 591-596, May.
    50. Bhardwaj, Geetesh & Swanson, Norman R., 2006. "An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 539-578.
    51. Selva Demiralp & Òscar Jordà, 2002. "The announcement effect: evidence from open market desk data," Economic Policy Review, Federal Reserve Bank of New York, vol. 8(May), pages 29-48.
    52. 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.
    53. Ashley, R & Granger, C W J & Schmalensee, R, 1980. "Advertising and Aggregate Consumption: An Analysis of Causality," Econometrica, Econometric Society, vol. 48(5), pages 1149-1167, July.
    54. 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.
    55. Pesaran, M Hashem & Timmermann, Allan, 1995. "Predictability of Stock Returns: Robustness and Economic Significance," Journal of Finance, American Finance Association, vol. 50(4), pages 1201-1228, September.
    56. Martin, Antoine, 2004. "Optimal pricing of intraday liquidity," Journal of Monetary Economics, Elsevier, vol. 51(2), pages 401-424, March.
    57. Jurgilas, Marius & Zikes, Filip, 2012. "Implicit intraday interest rate in the UK unsecured overnight money market," Bank of England working papers 447, Bank of England.
    58. 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.
    59. Ruilin Zhou, 2000. "Understanding intraday credit in large-value payment systems," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 25(Q III), pages 29-44.
    60. Enghin Atalay & Antoine Martin & James J. McAndrews, 2008. "The welfare effects of a liquidity-saving mechanism," Staff Reports 331, Federal Reserve Bank of New York.
    61. Huurman, Christian & Ravazzolo, Francesco & Zhou, Chen, 2012. "The power of weather," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3793-3807.
    62. Suresh Sundaresan & Zhenyu Wang, 2009. "Y2K Options and the Liquidity Premium in Treasury Markets," Review of Financial Studies, Society for Financial Studies, vol. 22(3), pages 1021-1056.
    63. 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.
    64. 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," National Institute of Economic and Social Research (NIESR) Discussion Papers 253, National Institute of Economic and Social Research.
    65. G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
    66. Suresh Sundaresan & Zhenyu Wang, 2009. "Y2K Options and the Liquidity Premium in Treasury Markets," Review of Financial Studies, Society for Financial Studies, vol. 22(3), pages 1021-1056, March.
    Full references (including those not matched with items on IDEAS)

    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. repec:ctc:serie1:def10 is not listed on IDEAS
    2. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    3. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2010. "Combining predictive densities using Bayesian filtering with applications to US economics data," Working Paper 2010/29, Norges Bank.
    4. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    5. Puriya Abbassi & Falko Fecht & Johannes Tischer, 2017. "Variations in Market Liquidity and the Intraday Interest Rate," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(4), pages 733-765, June.
    6. Christian Pfister, 2018. "(Real-)Time Is Money," Working papers 675, Banque de France.
    7. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    8. 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.
    9. Billio, Monica & Casarin, Roberto & Ravazzolo, Francesco & van Dijk, Herman K., 2013. "Time-varying combinations of predictive densities using nonlinear filtering," Journal of Econometrics, Elsevier, vol. 177(2), pages 213-232.
    10. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combining Predictive Densities using Nonlinear Filtering with Applications to US Economics Data," Tinbergen Institute Discussion Papers 11-172/4, Tinbergen Institute.
    11. Davide Pettenuzzo & Francesco Ravazzolo, 2016. "Optimal Portfolio Choice Under Decision‐Based Model Combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1312-1332, November.
    12. Anne Sofie Jore & James Mitchell & Shaun P. Vahey, 2010. "Combining forecast densities from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 621-634.
    13. Knut Are Aastveit & Karsten R. Gerdrup & Anne Sofie Jore & Leif Anders Thorsrud, 2014. "Nowcasting GDP in Real Time: A Density Combination Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(1), pages 48-68, January.
    14. Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2018. "Combined Density Nowcasting in an Uncertain Economic Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 131-145, January.
    15. Bjørnland, Hilde C. & Ravazzolo, Francesco & Thorsrud, Leif Anders, 2017. "Forecasting GDP with global components: This time is different," International Journal of Forecasting, Elsevier, vol. 33(1), pages 153-173.
    16. Ravazzolo Francesco & Vahey Shaun P., 2014. "Forecast densities for economic aggregates from disaggregate ensembles," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(4), pages 1-15, September.
    17. Dr. James Mitchell, 2009. "Measuring Output Gap Uncertainty," National Institute of Economic and Social Research (NIESR) Discussion Papers 342, National Institute of Economic and Social Research.
    18. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2017. "Density Forecasts With Midas Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(4), pages 783-801, June.
    19. Garratt, Anthony & Mitchell, James & Vahey, Shaun P., 2014. "Measuring output gap nowcast uncertainty," International Journal of Forecasting, Elsevier, vol. 30(2), pages 268-279.
    20. 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;Western Finance Association, vol. 44(2), pages 175-186, October.
    21. Huurman, Christian & Ravazzolo, Francesco & Zhou, Chen, 2012. "The power of weather," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3793-3807.

    More about this item

    Keywords

    interbank market; intraday interest rate; forecasting; density forecasting; policy tools.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E4 - Macroeconomics and Monetary Economics - - Money and Interest Rates
    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:ctc:serie1:def010. 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: Simone Moriconi (email available below). General contact details of provider: https://edirc.repec.org/data/dscatit.html .

    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.