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Assessing the quality of “Furfine-based” algorithms

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  • Olivier Armantier
  • Adam Copeland

Abstract

To conduct academic research on the federal funds (fed funds) market, historically one of the most important financial markets in the U.S., some empirical economists have used market level measures published by the Markets Group at the Federal Reserve Bank of New York (FRBNY). To obtain more disaggregate data, some researchers have relied on a separate source of information: individual transactions inferred indirectly from an algorithm based on the work of Furfine (1999). To date, however, the accuracy of this algorithm has not been formally established. In this paper, we conduct a test aimed at assessing the ability of the algorithm to identify correctly individual overnight fed funds transactions conducted by two banks, which are among the most active in the fed funds market. The results are discouraging. We estimate the average type I and type II errors from 2007 to 2011 to be 81% and 23%, respectively. Furthermore, we argue that these errors i) apply to almost half of the algorithm's output, ii) introduce systematic biases, and iii) may not subside when the algorithm's output is aggregated. Our results therefore raise serious concerns about the appropriateness of using the algorithm's output to study the fed funds market. Because the FRBNY Markets Group relies on a different source of data than the algorithm output, our results have no bearing on their understanding of the fed funds market and their calculation of market level measures, including the effective fed funds rate.

Suggested Citation

  • Olivier Armantier & Adam Copeland, 2012. "Assessing the quality of “Furfine-based” algorithms," Staff Reports 575, Federal Reserve Bank of New York.
  • Handle: RePEc:fip:fednsr:575
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    References listed on IDEAS

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    Cited by:

    1. Luca Arciero & Ronald Heijmans & Richard Heuver & Marco Massarenti & Cristina Picillo & Francesco Vacirca, 2016. "How to Measure the Unsecured Money Market: The Eurosystem’s Implementation and Validation Using TARGET2 Data," International Journal of Central Banking, International Journal of Central Banking, vol. 12(1), pages 247-280, March.
    2. Abbassi, Puriya & Bräuning, Falk & Fecht, Falko & Peydró, José-Luis, 2014. "Cross-border liquidity, relationships and monetary policy: Evidence from the Euro area interbank crisis," Discussion Papers 45/2014, Deutsche Bundesbank.
    3. Luca Arciero & Ronald Heijmans & Richard Heuver & Marco Massarenti & Cristina Picillo & Francesco Vacirca, 2014. "How to measure the unsecured money market? The Eurosystem�s implementation and validation using TARGET2 data," Questioni di Economia e Finanza (Occasional Papers) 215, Bank of Italy, Economic Research and International Relations Area.
    4. Mark Rempel, 2016. "Improving Overnight Loan Identification in Payments Systems," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(2-3), pages 549-564, March.
    5. Nellie Zhang, 2015. "Changes in Payment Timing in Canada’s Large Value Transfer System," Staff Working Papers 15-20, Bank of Canada.
    6. Q. Farooq Akram & Casper Christophersen, 2013. "Inferring interbank loans and interest rates from interbank payments - an evaluation," Working Paper 2013/26, Norges Bank.
    7. Edoardo Rainone, 2015. "Testing information diffusion in the decentralized unsecured market for euro funds," Temi di discussione (Economic working papers) 1022, Bank of Italy, Economic Research and International Relations Area.
    8. Carlos León & Jorge Cely & Carlos Cadena, 2016. "Identifying Interbank Loans, Rates, and Claims Networks from Transactional Data," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 85, pages 91-125, Julio - D.
    9. Quinn, Stephen & Roberds, William, 2014. "How Amsterdam got fiat money," Journal of Monetary Economics, Elsevier, vol. 66(C), pages 1-12.
    10. Anna Kovner & David R. Skeie, 2013. "Evaluating the quality of fed funds lending estimates produced from Fedwire payments data," Staff Reports 629, Federal Reserve Bank of New York.
    11. Ana Sofia Saldanha & Carla Soares, 2015. "The Portuguese money market throughout the crisis: What was the impact of ECB liquidity provision?," Economic Bulletin and Financial Stability Report Articles, Banco de Portugal, Economics and Research Department.
    12. Beltran, Daniel O. & Bolotnyy, Valentin & Klee, Elizabeth C., 2015. "Un-Networking: The Evolution of Networks in the Federal Funds Market," Finance and Economics Discussion Series 2015-55, Board of Governors of the Federal Reserve System (U.S.).
    13. Langfield, Sam & Liu, Zijun & Ota, Tomohiro, 2014. "Mapping the UK interbank system," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 288-303.
    14. Kuo, Dennis & Skeie, David R. & Vickery, James & Youle, Thomas, 2013. "Identifying term interbank loans from Fedwire payments data," Staff Reports 603, Federal Reserve Bank of New York, revised 01 Aug 2014.
    15. Edoardo Rainone, 2015. "Price transmission in the unsecured money market," IFC Bulletins chapters,in: Bank for International Settlements (ed.), Indicators to support monetary and financial stability analysis: data sources and statistical methodologies, volume 39 Bank for International Settlements.
    16. Q. Farooq Akram & Casper Christophersen, 2017. "Pricing in the Norwegian Interbank Market – the Effects of Liquidity and Implicit Government Support," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(2), pages 165-204, April.
    17. Garcia-de-Andoain, Carlos & Hoffmann, Peter & Manganelli, Simone, 2014. "Fragmentation in the Euro overnight unsecured money market," Economics Letters, Elsevier, vol. 125(2), pages 298-302.
    18. Bech, Morten L. & Bergstrom, Carl T. & Rosvall, Martin & Garratt, Rodney J., 2015. "Mapping change in the overnight money market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 44-51.

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    Keywords

    Banks and banking; Central ; Interest rates ; Federal Open Market Committee ; Stochastic analysis ; Equilibrium (Economics) ; Monetary policy;

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