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- W3122077475 abstract "(ProQuest: ... denotes formulae omitted.)1. IntroductionThe U.S. federal funds (fed funds) market is an interbank market for unsecured, mostly overnight loans of reserves held by banks at Federal Reserve Banks. It is an over-the-counter market where banks arrange trades either on their own on a bilateral basis or through brokers. Historically, the fed funds market has been a key financial market with major macro-economic and monetary policy implications. In particular, the average fed funds market rate, known as the effective fed funds rate, has substantial influence on the terms at which commercial banks lend to businesses and individuals. Furthermore, the Federal Reserve implements monetary policy by creating conditions under which fed funds trade around a specific target or within a target range set by the Federal Open Market Committee (FOMC).1The traditional source of data on the fed funds market is based on fed funds trades reported by the major fed funds brokers to the Federal Reserve Bank of New York (FRBNY). Using these data, various market-level interest rate statistics are calculated and published daily by the FRBNY. These statistics-in particular, the effective fed funds rate-are used widely by policymakers, financial market participants, and researchers in academia.An alternative source of data, used exclusively to conduct academic research, is inferred from algorithms based on the original work of Furfine (1999). Although there are now different versions of the original algorithm, they all seem to rely on the same principles. A number of recent empirical papers use a version of the Furfine algorithm's output to make important contributions. These papers assume, but do not formally test, the accuracy of the output of their algorithms. As we explain in more detail below, the main purpose of this article is to formally test these Furfine-based algorithms. Importantly, the results presented here do not extend to the traditional source of data collected by the FRBNY from the fed funds brokers. In particular, the results have no bearing on the ability of the Markets Group of the FRBNY to understand the fed funds market and to accurately calculate market-level measures, including the effective fed funds rate.In this study, we focus on the revised Furfine algorithm used by the Research Group of the FRBNY. This algorithm exploits the fact that privately traded fed funds transactions are often settled over the Fedwire® Funds Service (Fedwire), the large-value real-time payments settlement system operated by the Federal Reserve.2 As further explained in section 2, the algorithm searches all payments over Fedwire to identify the pairs of payments that look like fed funds loans. Specifically, the algorithm tries to identify first a sent payment from bank A to bank B on a given date for an amount that could reasonably constitute a loan principal, and then a return payment from bank B to bank A on the following day for an amount that could reasonably constitute the principal plus interest payment.If the algorithm correctly identifies fed funds transactions with sufficient accuracy, then its output could be useful to academic economists in studying the fed funds market. Indeed, it would provide data at the lowest level of aggregation (that is, individual transactions between specific pairs of banks) that could help shed light on the underpinnings of the U.S. fed funds market. The algorithm's output is especially attractive when trying to explain the behavior of the market during the 2008-09 financial crisis, as well as the specific role played by individual banks. Indeed, there has been a surge in the number of papers that use the algorithm's output (we found eleven papers written in the past two years; all are listed in the References section of this article).3An important question remains, however: To what extent does the algorithm identify individual fed funds transactions? …" @default.
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- W3122077475 date "2015-10-01" @default.
- W3122077475 modified "2023-09-28" @default.
- W3122077475 title "Challenges in Identifying Interbank Loans" @default.
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