Segmentation in the U.S. Dollar Money Markets
During the Financial Crisis
James J. McAndrews
May 19, 2009

Abstract
The U.S. dollar unsecured money market consists of two segments, Eurodollar deposits and federal funds purchases and sales. A previous study by Bartolini, Prati, andHilton showed that the two market segments were highly integrated for trades arranged
in New York in the period 2002-2004. Using another transaction-level dataset that
identi…es Eurodollar and fed funds trades, as well as the Libor panel of overnight interest rates, I …nd evidence of signi…cant rate di¤erences between the two market segments
during the …nancial crisis period beginning in August 2007. Furthermore, during thisperiod signi…cant di¤erences arose within the market segments. In general, the Liborrate is signi…cantly higher than the U.S. rates at times of market distress; moreoverthe interest rate changes between the two market segments became uncorrelated attimes. Central banks moved to make available o¢ cial U.S. dollar liquidity backstops
in London and other market centers. Evidence supports the hypothesis that access tothese sources of funding reduced the spread between the Libor and federal funds rates.

JEL classi…cation: G21, C78, L14
Keywords: Money market trading, market integration, federal funds, Eurodollar

Federal Reserve Bank of New York, 33 Liberty Street, New York, NY 10045, USA. The views expressed
here are those of the author and do not necessarily re‡ect those of the Federal Reserve Bank of New Yorkor of the Federal Reserve System. I thank Enghin Atalay, Ian Adelstein and Je¤rey Shrader for outstanding
research assistance. I also thank Florian Heider, Philipp Hartmann, Cornelia Holthausen, Joshua Rosenberg,
Michael Fleming, and participants in a seminar at the European Central Bank for comments.

1

Introduction

The U.S. dollar unsecured money market ties together lenders and borrowers of very shortterm credit. The market’s main maturity is of overnight duration, and the market has
both federal funds and Eurodollar deposit segments. These market segments are highly
integrated in normal times. How well integrated have they remained during the period of…nancial crisis starting in August 2007? This is an important question as both segments
are very large markets in which banks and other …nancial institutions manage their funding
resources. They are markets through which the monetary transmission mechanism operates
by manipulating the marginal cost of bank funding, the marginal source of which is overnightborrowing.
While the rates in the two markets are similar during normal times, the data reveal
extreme divergences in rates and the direction of rates during the period beginning in August
2007 and continuing through late 2008. The divergence between Libor rates set in London
and both New York Eurodollar rates and federal funds rates is much sharper than thedivergence between New York Eurodollar rates and federal funds rates (both of which are set
in the U.S.). This divergence suggests that either the time zone or geographical segmentationin the London and New York markets may be more important than the segmentation between
the Eurodollar and federal funds markets per se.
The breakdown in correlation between the Libor and fed funds rates suggests that theusual intermediation between the markets that keeps the two rates tethered to one anotherbroke down completely at times during the …nancial crisis. This divergence can serve as one
measure of the depth of the crisis, and re‡ects the di¢ culty of ensuring that the monetary
policy transmission mechanism functions adequately.
The …ndings of this study also suggest that increased access to o¢ cial sources of U.S.
dollar liquidity, in the form of the central bank liquidity swaps1 , has moderated the divergence1

Foreign exchange swap lines (FX swaps) were established with the Bank of England, Bank of

Canada, European Central Bank, and the Swiss National Bank on December 12, 2007 to provide a source of U.S. dollar funding to overseas banks.

1

The FX swaps have expanded in size

in Eurodollar and federal funds rates. This result suggests that term lending by central banks
can in‡uence and moderate divergences in overnight rates, improving the monetary policy
transmission process. This view widens the focus for implementation of monetary policy toinclude term markets, and to consider the time zones and jurisdictional di¤erences in money
markets.. If banks are uncertain regarding their future access to funding, a situation thatwas widespread beginning in August 2007, that can reduce the e¢ ciency of the overnightmarket as banks rely excessively on that market for the shortest of terms. Furthermore, evenvery similar market segments, but ones separated by geography and time zones, can become
distinct markets in times of crisis, requiring the monetary authority to conduct operations
in ways that more directly make funds available in the times and places in which markets
are active.
In the next section, I review the two segments of the money market. In section 3, I
describe data and the method used to identify the two segments.

In section 4, I present

a number of descriptive tables and charts that outline the relative behavior of the twomarket segments. In section 5, I present estimations that attempt to isolate various factorsthat account for the di¤erences observed between the two market segments, and section 6
concludes.

2

Fed funds and Eurodollar trades

The U.S. market for unsecured short-term loans consists of federal funds (or fed funds, forshort) trades (often called "purchases") and Eurodollar trades (often called "deposits"). Fed
funds trades, as we pointed out, are unsecured loans between banks that have accounts
at Federal Reserve Banks, which include domestic depository institutions, the branches offoreign banks, government-sponsored enterprises, foreign central banks, and monetary authorities. Fed funds trade daily on an overnight basis to assist banks in managing theirand number of participating Central Banks over the course of the program.

For more information,

see the following releases: http://www.federalreserve.gov/newsevents/press/monetary/20071212a.htm andhttp://www.federalreserve.gov/monetarypolicy/bst_liquidityswaps.htm

2

balance sheets, and, importantly for many of the banks, to maintain su¢ cient reserves on
average over a two-week reserve maintenance period to meet their reserve requirements.
Every day a bank’s normal business, including making payments on behalf of customers,causes in‡ows and out‡ows of balances in their Federal Reserve Bank accounts. To make useof any excess reserve balances to earn interest, or simply to make sure that their balances areboth positive and su¢ cient to meet their reserve requirements, banks can choose to either
sell or buy fed funds. Although participants in the fed funds market are domestic depository
institutions that can maintain accounts at the Federal Reserve Banks, some participants
choose to arrange their trades using correspondent banks, presumably because their scale ofoperation is so small.
Eurodollar trades are similar to fed funds trades, but are made among a di¤erent, but
overlapping, set of counterparties. European banks that maintain dollar liabilities trade
Eurodollar deposits. In addition, nondepository institutions, such as domestic …nance companies trade Eurodollars. Finally, deposit liabilities of domestic institutions that have set up
segregated sets of “foreign”accounts (so called International Banking Facilities) also qualify
as Eurodollars. For a fuller discussion of di¤erences and similarities between the markets
for federal funds and Eurodollars, see Bartolini et al. (2007). Some European banks, forexample, that maintain a branch in the U.S. could trade in both market segments, as candomestic banks that also maintain an International Banking Facility. Because of this partial overlap in the parent institutions of those eligible to participate in the di¤erent market
segments, arbitrage opportunities would work to make the two markets highly integrated.
A key di¤erence between fed funds trades and Eurodollar trades is that fed funds trades
can be settled directly between the borrower and lender using the Federal Reserve’s Fedwire
Funds Service. To make a Eurodollar trade, by contrast, some intermediary or correspondentbank or banks must be used to complete the transfer of dollar liabilities. The correspondents
often settle the Eurodollar trade by also using the Federal Reserve’s Fedwire Funds Service(although they can use other settlement methods as well, such as the CHIPS payment
system, or, if the two parties to the trade use the same correspondent bank, a book transfer

3

on the books of the correspondent bank). Using data from the transactions journal of theFedwire Funds Service, we identify overnight loans that are likely Eurodollar loans, and thosethat are likely fed funds loans, and investigate the interest rate di¤erentials between these
two segments. We utilize the distinction that Eurodollar loans are made via correspondentbanks (on the delivery side of the loan) with a much higher probability than are fed funds
loans.
In addition to utilizing the transaction-based interest rates generated from likely overnightmoney market trades on the Federal Reserve’s Fedwire Funds Service, I compare the transactionbased interest rates with those reported by the Libor panel of banks and published by the
British Bankers Association as the overnight, U.S. dollar Libor rate. Libor rates are indicative of the rates at which banks on the U.S. dollar Libor panel can borrow for an overnight
duration. The Eurodollar rates I calculate from the Fedwire Funds Service are trades typically arranged during the New York session (as trades arranged in London typically settle
either on correspondent banks’books, or via the CHIPS service). As a result, comparing Libor rates and the Eurodollar rates generated from transactions on the Fedwire Funds Service
allows one to determine the e¤ects of the time zone and geographical di¤erences (and here
geographical di¤erences also likely re‡ect di¤erences in the identities of borrowers, which we
don’t observe) on rates in the same market, namely the Eurodollar market.
Trading in the New York markets begins daily at about 8:00 (ET), when major New
York brokers begin receiving requests from customers to match orders to lend or bids toborrow funds (trades for Eurodollars also are made in London earlier in the U.S. day). The
market e¤ectively closes at 18:30, when the Federal Reserve’s large-value electronic payments
system, the Fedwire Funds Service, closes for the day, at which point it becomes impossible
for …nancial institutions to trade loans of federal funds for same-day settlement, the market
for Eurodollars e¤ectively winds down, and bank reserve holdings are …xed for the day.2
2

Technically, it is possible to execute and settle Eurodollar trades outside the United States after theclosing of the New York market, although the amount of Eurodollar trading is minimal after Eurodollar
settlement closes on Fedwire at 18:00, until markets in East Asia open several hours later.

4

Brokers often play the role of establishing contact between interested buyers and sellers ofshort-term loans. Trades are normally arranged anonymously between interested parties, andonly after the interest rate is agreed to by both parties is the borrower’s identity disclosed.
After that disclosure, and if the lender accepts to lend to the borrower (a decision usuallyconditioned on the presence of a predetermined credit line between the two parties), the tradeis deemed “executed”by the broker, and entered into a time-stamped record with informationon counterparts, amount traded, settlement and maturity dates, and an identi…er of whether
the trade was executed as a “federal funds”or a “Eurodollar”trade. Many trades are also
arranged directly between the two banks.
The next stage in the trading process is “settlement,” in which the loaned funds aredelivered by the lender to the borrower. Federal funds loans settle almost exclusively on the
Fedwire Funds Service. Fedwire settlement occurs when the lending institution instructs its
Reserve Bank to debit its reserve account and credit the reserve account of the borrowing
institution (via Fedwire). Fedwire provides near instantaneous, irrevocable settlement assoon as the payment instruction is received by the Federal Reserve Bank of the sender’s
district, provided that su¢ cient funds are available in the sender’s account. Fedwire also
handles the vast majority of short-term, unsecured, Eurodollar loans traded in the New York
market, with the residual settling on other systems, such as the Clearing House Interbank
Payments System (CHIPS), a private payment system. Eurodollar loans arranged in othermarket venues, such as London, tend more often to be settled on CHIPS.
At maturity, settlement of loan returns works almost identically to that of loan deliveries,
except that borrowing banks now act as “senders,”and are expected to instruct the Federal
Reserve to move balances out of their accounts and back into the accounts of lending banks(who now act as funds “receivers”), for an amount including both principal and due interest.

5

3

Data

Three interest rates are used in this study.

The easiest to describe is the overnight U.S.

dollar Libor rate as published by the British Bankers Association. The next two are rates
calculated from measures of federal funds trades and Eurodollar trades that are settled on
the Fedwire Funds Service, the Federal Reserve System’s large-value payment service. These
rates are described in more detail below.
Settlement data. The data we employ is gathered from the transactions journal of theFedwire Funds Service, the large-value payment system operated by the Federal Reserve,on which the vast majority of money market trading between U.S. institutions settles. The
data include information on senders’and receivers’identities, dollar amounts (in dollars andcents), and time stamps (in day/hour/minute/second format).
Using this data set, we …lter the data to identify likely overnight loans from Fedwire
payments. This technique was pioneered by Fur…ne (1999) and has been used in many
subsequent studies, including Fur…ne (2001, 2003, 2006), Demiralp et al. (2004), Millard
and Polenghi (2004), Ashcraft and Bleakley (2006), Ashcraft and Du¢ e (2007), and Hendry
and Kamhi (2007). The essence of these studies’methodology is to identify as overnight loans
all Fedwire payments that satisfy criteria such as matching bilateral payments (consisting ofa delivery of payments on one day, followed by a return of funds on the following businessday) for round dollar lots, in which return payments can be reasonably construed as including
principal plus due interest. See Fur…ne (1999) and Demilrap et al. (2004) for full descriptions.
Once we have the set of measured overnight loans, we classify them as likely federal funds
trades or likely Eurodollar trades. To do that, we make use of a prior study, that employed
another data set of overnight money market trades provided by a broker. After examiningthat data set, it became clear that a particular variable in the Fedwire Funds Service records
was highly predictive of whether an overnight loan was a federal funds trade or a Eurodollar
trade. Here we go into further detail on this method of classi…cation.

6

Trade data. Three previous studies, Bartolini et al (2005), Bartolini, Hilton and Prati(hereafter PBHP, forthcoming), and Bartolini, Hilton, and McAndrews (2007) use data
provided by a broker, BGC Brokers (formerly Eurobrokers), one of the four largest interbank
dollar brokers. The data include all federal funds trades during the sample period, as well
as all Eurodollar trades arranged by BGC Brokers’New York headquarters over the same
period. For each transaction we obtained amount traded, applicable interest rate, loandelivery date, term, trade completion time (in date/hour/minute/second format), and a‘federal funds’vs. ‘Eurodollar’identi…er.
The trade data consist of data on overnight interbank loans for 660 business days, fromFebruary 11, 2002, until September 24, 2004. No information on the institutions involved ineach trade was included.
Matching brokered trades with settlement orders In the study by Bartolini, Hilton,
and McAndrews (2007) the two sets of data, brokered trade data and Fedwire settlement
data, were matched. The set of matched trades consisted of approximately 38,000 trades
arranged between 2002 and 2004. The matching process is brie‡y described below:
For each brokered trade record, we searched for a Fedwire payment order that:
1. involved the same dollar amount speci…ed for the loan in the brokered trade record;
2. settled at any time after the execution time reported in the brokered trade record, but
before that day’s closing of Fedwire;
3. matched a payment order between the same two banks in the opposite direction on thefollowing business day, for an amount equal to the sum of the principal and interest
reported in the brokered trade record;
4. was uniquely matched, in the sense that no other Fedwire order also satis…ed 1, 2, and3, between the same or any other pair of banks.
The previous study recognized various potential biases with this matching process. The
algorithm yielded 38,358 uniquely matched records, each including information on trading,7

Fed Funds
Eurodollar
Total

Customer Non-Customer Total
1005
23579
24584
10886
2861
13747
11891
26440
38331

delivery, and return times, loaned amount, interest rate, a federal funds / Eurodollar identi…er, and information on trading counterparts.
Identifying Eurodollar loans in the Fedwire Transaction Journal A striking consistency was found in the matched data. When examining the matched trades, it is clear thatthose trades that contain a certain code in the Fedwire transactions journal on the delivery
leg of the loan are much more likely to be a Eurodollar trade. Speci…cally, for each Fedwire
payment, the sending bank enters a code on the payment message indicating whether thepayment is made on behalf of a customer. Of the 38,331 trades, approximately 36 percent
are identi…ed as Eurodollar trades by BCG Brokers.

Only 4 percent of the federal funds

1;005
loans were coded as having been initiated by a customer of the sending bank ( 24;584), while

79 percent of the Eurodollar loans were coded as customer loans ( 10;886).
13747
Consequently, using the customer code as a proxy for a Eurodollar loan will result in a
92 percent chance of correctly identifying Eurodollar loans ( 10;886), with an 8 percent chance
11;891of Type 1 error of counting fed funds loans as Eurodollars, and a 21 percent level of Type
2;861
2 error of falsely excluding Eurodollar loans counted as fed funds ( 13;747), if the matchedsample is representative of the population as a whole. By using the absence of a customer
code as a proxy for a fed funds loan we have an 89 percent chance of correctly identifying) with an 11 percent Type 1 error of counting Eurodollar loans as
a fed funds loan, ( 23;579
26;440
1;005
fed funds, and a 4 percent Type 2 error of incorrectly excluding fed funds loans ( 24;584).

Using this regularity in the data, I assign overnight transactions identi…ed on Fedwire to theEurodollar category if the sending institution has the transaction marker as one made on
behalf of a customer, and as a federal funds loans otherwise.
Finally, I use the Libor panel banks and their U.S. dollar overnight rate quotes to provide8an interest rate series indicative of rates on Eurodollar trades in London. I will compare
both the spreads between the New York Eurodollar rate and the transaction-based weighted
average federal funds rate, and the spread between the Libor rate and the transaction-based
weighted average federal funds rate.

4

Market Segmentation

It is useful to view some trends that can be observed in the market segments during thesample period. In Figure 1, the value of the trades in Eurodollar deposits and in fed funds(both from the Fedwire data) are shown in yellow and blue, respectively. There has been arapid rise in the values of Eurodollar trades conducted over the period, from an initial level ofapproximately $100 billion in 2001 to an amount in excess of $300 billion in the second halfof 2008, with a rapid rise occurring in August 2007. The value of federal funds transactions
increased as well but by a lesser amount, from around $150 billion to about $200 billion in
the second half of 2008. Values of both Eurodollar and fed funds trades have fallen sincelate 2008, with a signi…cant fall when the FOMC moved to the 0 to 25 basis point range forthe target federal funds rate in December 2008.
The next series of …gures show the extraordinary volatility that emerged in the rates ofthe market segments, starting on August 9, 2007. Figure 2 displays the di¤erences between
the three overnight interest rates used in this study and the daily e¤ective federal funds
rate as measured and publicly reported by the Markets Group of the Federal Reserve Bankof New York. The three rates are the U.S. dollar Libor rate, the fed funds rate (measured
as the weighted-average calculated from the Fedwire transactions journal extracts), and the
New York Eurodollar rate (measured as the weighted average rate as calculated from theFedwire transaction journal extracts, for the trades classi…ed as Eurodollars or fed funds).
As one can see, the rates became much more volatile beginning on August 9, 2007. It isespecially interesting to consider the di¤erences in these three rates when plotted versus thetarget federal funds rate (Figure 3) or the e¤ective federal funds rate (Figure 2).

9

When

plotted against the e¤ective rate (Figure 2), one can see that the Eurodollar rate moves with
the Libor rate (spiking when the Libor rate spikes) but with a reduced amplitude. Whenplotted against the target rate (Figure 3) one can see that the two "New York" session rates
move quite closely together, often moving away from the Libor rate, so that when the Liborrate spikes, the two other rates sink. I will discuss this geographical and time-zone variation
at greater length in the conclusion.
The next …gures, Figure 4-Figure 7, display the daily and the four-week average interest
rate spreads between Libor (Figures 4 and 5) and the weighted-average fed funds rate, andbetween the Eurodollar rate and the weighted average fed funds rate. The spreads are shownfor the whole period from January 1, 2001 through March 31, 2009, and for the more recent
sub-period from January 1, 2007 to March 31, 2009. The spike in the overnight Libor–fed
funds rate spread, which began abruptly on August 9, 2007 reached over 400 basis points
in September 2008, in the wake of the bankruptcy of Lehman Brothers Holdings Co. It hasremained volatile in most of the period since that initial spike, although more recently, since
the implementation of the 0 to 25 basis point range for the target federal funds rate, thevolatility has subsided.
For the Eurodollar–fed funds rate spread, a slightly di¤erent pattern emerges. First, thespread is much less volatile than the Libor–fed funds spread, never reaching the heights of
the Libor spread.

Second, the spread displays a persistent slump in the period following

the Lehman Brothers bankruptcy.
The Figures also show that the sample period used in the study of Bartolini, Hilton, andPrati, from 2002-2004 was characterized by a relatively less volatile spread between the rates
on Eurodollar and fed funds trades, and that the spread may have been relatively low duringthat period in comparison with both of the periods around 2000 and the most recent period.
These observations make our investigation of the whole sample of more interest.

104.0.1

Correlation breakdowns between rates

A clear way of measuring the level of dis-integration among the rates is to calculate thecorrelation between the di¤erent rates, both in their levels, and in their daily changes. A
series of …gures presents these correlations. All of the correlations are shown as smoothedmoving-averages of daily correlations measured over a 22 day moving window. The correlation on day t is the correlation between the two rates over the subsequent 22 (business) days.
Finally, this measure is smoothed by taking a 66-day, moving-average starting on date t.
The …rst two of these …gures, Figures 8 and 9, display the correlations between thechanges in the Eurodollar and fed funds rates, and the levels of Eurodollar and fed funds
rates, respectively. It is clear that these rates became less correlated during the sample, butboth their changes and levels maintained a correlation of approximately 0.7 throughout theperiod.
The next two …gures, Figures 10 and 11, display the correlations between U.S. Eurodollars
and the Libor rate. While the changes in these rates have maintained about a 0.8 correlationin the years from 2002 to 2007, they became much less correlated during the …nancial crisis,
falling markedly on August 9, 2007, and having 0.0 correlation in late 2008 following thebankruptcy of Lehman Brothers. Similarly, their levels (Figure 11) also became much lesscorrelated. In this …gure we can also see how they became much less correlated following
September 11, 2001, another period of unsettled money markets, and also a period in whichsigni…cant dollar liquidity was provided to U.S. banks, but not to banks in London.
Finally, in Figures 12 and 13 we see the correlations between the Libor and fed funds
rates. Again we see the correlation between their changes falling to zero around the periodof August 9, 2007, and to low levels (approximately 0.3) after the Lehman bankruptcy. Heretoo we see a sharp spike downward in the correlation around September 11, 2001.
These measurements show how unsettled these markets were, as well as pointing out
the lack of integration in the markets. A zero correlation in the rates in the two markets
suggest no integration, and with levels being only correlated at levels of 0.2 for a month-longperiod, it reinforces that conclusion. Such low levels of correlation in rates is a sign that11

the markets are segmented, that is, that funds are not ‡owing between markets well, andthat participants cannot easily arbitrage rate di¤erences between markets. An interestingand disturbing di¤erence between the correlations in the …nancial crisis, starting in August
2007 is that not only did the correlations between the levels of Libor and fed funds fall to
low levels, as occurred after September 11, 2001, but the correlation between the changes inrates fell to zero at times during the crisis.
The fall in the correlations between the changes in rates to zero or near zero (in addition
to the low correlation between the rates) is a clear sign of lack of integration between themarkets. When, after September 11, 2001, the correlation in rates fell to a low level (ofapproximately 0.4), that likely indicated an increase in the costs of intermediation between
the two markets. In the 2007-2008 crisis, in contrast, not only did the correlation in rates
fall, but in addition the correlation between changes in rates fell to zero or near zero. In
other words, although the rates might have been quite di¤erent on a particular day, the riseor fall in the rate in one market was just as likely to be accompanied by a change in rates
in the other market in the opposite direction. This indicates that market forces were notworking to intermediate rate di¤erences between markets. That high level of dysfunction in
overnight markets suggests a highly illiquid condition for many banks; a situation that likely
contributes to banks’needs to shed assets, as their ability to source funds in the market isimpaired.

5

Explanatory factors associated with rate spreads

In this section the pairwise spreads between the three rates are examined to determine thecontribution of various explanatory factors associated with the rates. I conduct estimations
that are very similar to the ones conducted by BHP (but using our settlement system data
to identify Eurodollar trades and federal funds trades, and using the Libor rate data, rather
than broker data). By using the Fedwire data, I am able to include a much longer sample
period, from January 1, 2001 to March 30, 2009. I …nd that the Eurodollar and federal funds

12

rates are very close to one another in the "baseline" period from 2001 through July 2007,
largely con…rming the results of BHP. These results suggest that the two market segments
were highly integrated over the baseline period. In addition, I use the Libor series to examinedi¤erences between the Libor rate and the fed funds rate, and to examine the di¤erences
between the London and New York Eurodollar markets.
Table 1 below shows the sample statistics of the three di¤erent data series used: theLibor rates, and the rates and values of the fed funds and Eurodollar trades derived fromthe Fedwire Funds Service. The fed funds trades are more numerous, accounting for larger
overall values lent, but are of smaller average size than the Eurodollar trades. The fed funds
rates calculated using these data fall within 3 tenths of a basis point of the e¤ective federal
funds rate as reported by the Federal Reserve Bank of New York.

The Eurodollar rate

displays a similar mean and standard deviation as the federal funds rates, with the averagerate lying just one basis point above the e¤ective federal funds rate. The Libor rate is bothmore volatile, with a higher standard deviation, as well as having a mean spread of 7 basis
points above the e¤ective federal funds rate.
Next we conduct estimations of the spreads using a similar method as that used in BHP.
We letLibor
t = rtrtf edf unds , where t is a daily index of time, and rtLibor is the Libor rateon day t, and rtf edf unds is the fed funds rate on day t. Similarly, we will consider two otherspreads,

0t= rtEurodollar

rtf edf unds , and00t= rtLibor

rtEurodollar .

We will consider theevolution of the spreads by the same model.

t =

where
and

t+

t t

t is a mean-zero, unit variance i.i.d. error term;t is the conditional mean oft;t is its conditional Exponential GARCH (EGARCH) volatility parameter.

Again, following BHP and standard EGARCH models of interest rates, we’ll include aP
set of n autoregressive terms in the equation for t , ni=1 i t i , and de…ne t as a functionof a distributed lag of a set of independent variables.
Our equations fort andt include a set of deterministic and stochastic factors that BHP

13

and other studies have identi…ed as determinants of overnight interest rate dynamics. We
include two sets of calendar date dummies,

ct andct to capture the e¤ect on rate behaviorof holidays, mid-months, month-ends, quarter-ends, FOMC meeting days, and some otherdays of predictable rate dynamics, such as the New York blackout of August 14, 2003, andSeptember 11, 2001, both of which interrupted federal funds trading.
To include the e¤ect of the required reserve regime in the United States, we include
dummies

dt anddt with dt = 1; :::; 10 identifying days in the reserve maintenance period.

Next, we include variables measuring the intraday cross-sectional variation in rates,
namely the standard deviation of the rates the Markets Group used to calculate the effective fed funds rate,panel,

Libor

desk

, and the standard deviation of the rates reported by the Libor, and the standard deviations of the fed funds and Eurodollar rates calculated
f edf unds

from the Fedwire Funds Service,,

Eurodollar.

To measure the unsettled trading in the markets during the crisis periods, we also estimate the model using dummy variables for the crisis periods. We use four such dummy
variables:
2008;

ElevatedLibor OIS SpreadP ostLehmanBrosBankruptcy

Interestonreserves, for the period from August 9, 2007 to September 15,, for the period from September 16, 2008 to October 8, 2008,, for the period from October 9, 2008 to December 4, 2008, andZeroto25rate,

for the period from December 5, 2008 to March 31, 2009.
Finally, to measure any possible e¤ects of the TAF3 and FX swaps, we include variables
that measure the outstanding dollar amounts of TAF borrowing and borrowing under theFederal Reserve’s swaps program,

T AF

, and

Swaps

. These programs could have di¤erente¤ects in the Libor, Eurodollar, and fed funds markets as the TAF credit was only directly
available to depository institutions in the U.S., while the borrowing under the swaps credit
was available only to depositories outside the U.S. in the countries in which the central bankparticipated in the swaps program. In addition, we include a full panel of dates for the TAF
3

The Term Auction Facility (TAF) began on the same day as the FX swaps to al-leviatethetermfunding

following:pressure

in

the

U.S.

For

more

information

on

the

facility,

http://www.federalreserve.gov/newsevents/press/monetary/20071212a.htm

http://www.federalreserve.gov/monetarypolicy/tafterms.htm

14

see
and

and swaps announcements, as well as dates for all the operations of the TAF and the swaps
program during the sample period.
The model was estimated using Stata, where the residuals were examined to select the
autoregressive structure, resulting in many autoregressive terms (as many as eight) being
included to eliminate any residual autocorrelation.
The results are summarized by presenting two speci…cations of the model, one in which
the rates are measured (as they are in the correlations presented above) using the Libor panel
convention in which the upper and lower quartiles of rates are excluded, and the reported rateis based on the trimmed mean of rates. For the Eurodollar and fed funds rates, I discarded
the upper and lower quartiles by value, so the top one-quarter of rates by total market value
and the bottom one-quarter of rates by total market value were discarded. Next, I report
the speci…cation where all the rates are included in the rate estimated, an untrimmed mean,in other words. Again, for the fed funds and Eurodollar rates, the mean is a value-weighted
average of rates.
The motivation for examining both the trimmed and untrimmed mean measures of rates
is suggested by examining Figures 14 and 15, which display both trimmed and untrimmedmeans for Libor and fed funds rates, respectively.

As can be seen, the untrimmed meanfor Libor moves systematically above the untrimmed mean starting in August 2007, which
presents quite a di¤erent pattern for fed funds, whose alternative mean estimates remainquite close throughout the period. This divergence between the untrimmed mean and thetrimmed mean for Libor suggests that they should be treated as a separate series.
The full results of the estimations are presented in a series of tables (Tables 3, 4, and5), but the estimates of special interest are summarized in Tables 2. Table 2 presents theestimated coe¢ cients for predictedt andt for themean and untrimmed mean equations and the

0

Libor
t = rtEurodollar
t = rtrtf edf unds both trimmed-

rtf edf unds equations. The …rst

two columns include two crisis period dummy variables, while the second and third columns
focus on the policy variables of TAF and the FX Swap program amounts.

In general,the predicted spreads in the Libor rates are signi…cantly higher than is the case for the15

Eurodollar rates, which are, on average less than a basis point di¤erent from the weightedaverage federal funds rate, while the Libor rate lies approximately 6 basis points above theweighted average federal funds rate. These levels suggest close, but not perfect integration.
BHP suggest that the cost of arranging an identical overnight trade is approximately 1.8
basis points for each leg of the trade. The estimated persistent di¤erences in Libor rates
are just above the amounts that would suggest that it would be pro…table, all else equal, toattempt to exploit these di¤erent rates; however, the persistence of di¤erent rates suggeststhat the costs could be somewhat higher than suggested by BHP. BHP were also using New
York broker data, and their results are more comparable to our Eurodollar rate series, which
estimates little di¤erence from fed funds rates in normal circumstances. In addition, theidentity of the counterparties makes many of the constituent trades that are represented bythese rates quite di¤erent across the market segments. Nonetheless, the close levels of thedi¤erent rates suggests signi…cant integration of the market segments, as does the similar
behavior across many of the other calendar and standard deviation variables in the model.
It is also striking how much closer the New York Eurodollar rates are to the fed funds rates
than are the Libor rates.
5.0.2

Crisis periods

Trimmed mean estimates The estimates in Table 2 suggest that the market disruptions
that occurred after August 2007 signi…cantly increased the level, and, in some cases, thevariability of the spread between the rates. Consider two major crisis periods, the "ElevatedLibor-OIS Spread Period", from August 7, 2007 to September 14, 2008, and the "Post
Lehman Bros. Bankruptcy Period," from September 15, 2008 to October 9, 2008, and focus
on the trimmed mean estimates.

In the Post Lehman Bros. Bankruptcy Period one cansee that the Libor-fed funds spread widened by 88 basis points, while volatility was slightly
reduced. In contrast the Eurodollar-fed funds spread did not change. A similar pattern held
for the Elevated Libor-OIS Spread Period, although with a smaller magnitude–the Libor-fed
funds spread widened by 4.6 basis points, and the volatility rose a bit.

16

The behavior fo the Eurodollar-fed funds spread was quite di¤erent, with no signi…cantdi¤erences in spread levels in these periods (although there was an increased volatility inthe Elevated Libor-OIS spread period). These measurements again con…rm that the New
York Eurodollar trades and fed funds trades never became as untethered from one anotheras was the case for Libor-fed funds. This fact suggests that the location and time zone oftrade matters sign…cantly in terms of willingness to transact, notwithstanding the type oftrade or intermediary, and perhaps matters even more in times of crisis.
Untrimmed mean estimates Recall Figure 14, which shows the signi…cant divergence
between the untrimmed and trimmed means in the Libor panel during the …nancial crisis.
During the crisis, the upper quartile of rates, which are not included in the trimmed mean
Libor, are so much higher than the remainder of the panel’s quotes that the averages sometimes diverge persistently by more than 200 basis points. Consider the estimated coe¢ cientsfor the Untrimmed Mean Estimates in Table 2. There, the Post Lehman Bros. Bankruptcy
Period suggests a 1680 basis point spread in the Libor-fed funds rates, with no change involatilities, while the spread between Eurodollars and fed funds actually falls by 40 basis
points. The Elevated Libor-OIS Spread Period, in contrast, does not raise the spreads.
These results suggest that the untrimmed Libor panel mean measures something quitedi¤erent to the trimmed-mean Libor rate. This is an important di¤erence when interpretingthe coe¢ cients for the TAF and Swap programs.
It appears that in the unsettled market periods the willingness, and perhaps the ability, to intermediate credit across these markets fell markedly, resulting in signi…cantly lessintegration across the markets.
Why is it the Libor market seems to pay higher rates, and have more variability in rates?
I o¤er two hypotheses.

First, depository institutions outside the U.S. do not face dollar

reserve requirements, but at the same time, are not able to take advantage of the demandsmoothing provided by the reserve maintenance periods. Second, the depository institutions
outside the U.S. do not have access in normal times to o¢ cial sources of U.S. dollars, such17

as the discount window of the Federal Reserve Banks. These features leave the depository
institutions with a greater level of liquidity risk and with demands for liquidity that are far
more inelastic than for a comparable U.S. based institution. As supply of funds is provided bybanks that have excess of funds, the elasticity of the supply of funds is in‡uenced by similar
forces as the demand, and is therefore also less elastic than for a comparable U.S. institution.
Consequently, one would expect the market to display a great deal more variability, and tohave higher interest rates. These features would likely be exaggerated in a crisis.
5.0.3

E¤ects of TAF and Swap Programs

Following the hypothesis that depository institutions outside the U.S. face more funding risk
as a result of not having access to o¢ cial sources of U.S. dollar funding, such as the discountwindow, it is important to test the e¤ect of the implementation of the TAF program, andthe FX swap programs that were instituted by the Federal Reserve and several other central
banks, including the Bank of England, the European Central Bank, the Swiss National Bankand the Bank of Japan. All of these jurisdictions contain banks active in the Eurodollar
market, whose quotes are likely re‡ected in the Libor rates.
Trimmed mean estimates We …nd that the FX swaps program lending had the e¤ect of
reducing the two spreads,Libort = rtrtf edf unds , and0Eurodollar
t = rtrtf edf unds , while the

TAF lending tended to widen them (the TAF coe¢ cient is positive, but insigni…cant for thetrimmed Libor-fed funds spread). For the Libor–fed funds spread, a billion dollars of lending
through the Swaps program tended to reduce the spread by 3 one-hundredths of a basis point,
so $400 billion of lending would be expected to reduce the spread by approximately 12 basis
points. Perhaps surprisingly, the two lending programs did not raise the variability of the
spreads, once the crisis periods are accounted for by their dummy variables. It is notablethat these e¤ects are seen, as these are overnight rate spreads, and the TAF program has
always lent only at either 28-day or 84-day terms (some of the lending in the swaps programs
was for overnight durations, for example, the Bank of England began lending overnight on

18

September 18, 2008). It is important that programs that o¤ered term …nancing, such as theTAF, a¤ected overnight rates. This is understandable as overnight rates are in‡uenced by
the availability of term …nancing to a bank: with term …nancing unavailable, a bank has ahigher willingness to pay for overnight funds.
A second set interesting …ndings in the estimations are the e¤ects of the TAF and FX
swaps programs on the00t= rtLibor

rtEurodollar spread.

Here we …nd that there was no

signi…cant e¤ect on the level of the spread between the two rates. These results are consistent
with the Libor and the Eurodollar borrowers having in common that they do not have directaccess to o¢ cial sources of funding. Consequently, the implementation of the TAF and FX
swaps program a¤ects their rates in the same manner, leaving their spread unchanged. This
impact occurs accross periods even though the rates behaved quite di¤erently in the crisis.
Untrimmed mean estimates The estimated coe¢ cients for the untrimmed means of
the spreads do not suggest that the FX swaps program reduced Libor-fed funds spreads; infact, the Libor-fed funds spread coe¢ cient is positive, suggesting that the spread widenedwith the increase in value lent through the swaps program. The coe¢ cient on the FX swaps
program for the Eurodollar-fed funds rates is negative, and for the TAF program positive.
Both are signi…cant, as was the case for the trimmed mean. These results suggest two points:…rst, the Eurodollar-fed funds rate spread has similar estimates for either the trimmed or
untrimmed mean, but those means do not vary from one another very much; second, theLibor-fed funds spread behaves di¤erently depending on whether we are using the trimmed
or the untrimmed means, which vary greatly for the Libor panel.
One interpretation of these results is that the Swaps program improved the liquidity of
the Libor market, resulting in lower rate spreads to fed funds for the majority of banks.
However, for banks whose borrowing costs were extremely high, possibly signalling credit
concerns, the Swaps program had no e¤ect on their borrowing rates in the market. Thatinterpretation would caution that care must be exercised when examining rate dynamics andthe o¢ cial programs. Another point is that the Libor panel rates are published daily. A

19bank with a self-announced high borrowing rate may not bene…t greatly in the market froman ample source of o¢ cial …nancing, as market counterparties can observe that its recent
borrowing rates were elevated. In general, it may be that the Swaps program improved
liquidity in the market generally (and certainly assisted banks in meeting commitments as
hundreds of billions of dollars were lent under the program) but may not have lowered themarket borrowing costs of banks whose borrowing costs might have some elevated concern
about credit risks re‡ected in their rates.
5.0.4

Other Results

The results of the estimation suggest that Libor rates are typically higher, although only a
few basis points higher, than federal funds rates (again, in normal market conditions). An
hypothesis for this persistently higher rate is that …rms in the Eurodollar market have lower
elasticity of both demand and supply. One source of the lower elasticity could arises from thelack of reserve requirements among Eurodollar borrowers and lenders. Absent the averaging
feature of reserve maintenance periods, banks face higher penalties (failing to repay a loan,
or denying a customer payment order, and the negative reputational e¤ects associated withbeing unable to meet commitments) than simply falling short of one’s required reserve forthe period, and therefore, their daily demand is likely less elastic than for a U.S. bank that is
subject to reserve requirements. Consequently, the banks in the Eurodollar market may face
both greater volatility in rates (which they do, since most volatility coe¢ cients are higher on
the reserve maintenance day variables) and higher rates, which compensate for the reduced
elasticity of supply. In order to lend funds banks must charge a slightly higher liquidity risk
premium, since they could …nd that they need the funds (with greater urgency than a U.S.
bank) later in the day.
Table 2 also shows results on the daily standard deviation of the fed funds and Liborrates, which generally shows that if the fed funds rates have a high standard deviation on aparticular day, that is, the rates are more highly dispersed, then the Libor and Eurodollar
to fed funds rate spreads are elevated, as is the volatility in the spread. So a high level of20

dispersion in rates, presumably when market participants either vary greatly or when theirperception of credit or liquidity risks vary, is correlated with a high average level of rates.
The full regressions, shown in Table 3, contained many other variables. One variable
that was included was the time di¤erence between New York and London, in an attempt todetermine if the time di¤erence (which varies from 4 to 6 hours) contributed to higher spreads.
This coe¢ cient was insigni…cant, so did not shed light on the source of the di¤erences.
An alternative speci…cation was tried in which a bank index of CDS prices was included
to control for the overall industry level of credit risks. However, it is not at all clear if one
wishes to control for credit risks in a speci…cation of the spread, as banks in both markets
are subject to credit risks (and the index does not properly distinguish between banks inthe London from New York, and is, indeed, a U.S. index). The results of this speci…cation
were not highly di¤erentiated from the basic speci…cation: the main di¤erence is that theTAF variable tended to raise the level of the Libor and Eurodollar spreads to fed funds moresigni…cantly than in the base speci…cation.
Many other variables were included in the estimation, including the announcement andoperation variables for TAF and Swaps. These variables had slight e¤ects, with the TAF
announcements associated with positive, but generally insigni…cant increases in spreads, andthe Swaps announcements associated with negative but insigni…cant changes in spreads.
Shown in Table 2 are the results for the Libor-Eurodollar spread, which is of some independent interest as it shows the di¤erence in rates on trades of the same type–namely,
overnight Eurodollar loans–but made in di¤erent trading centers, London and New York.
The results show that the New York Eurodollar rate fell away from the Libor rate during
the periods of market stress. Again, this could well be the result of all trades in New York,
both Eurodollars and fed funds, taking advantage of Open Market Desk moves to supply
liquidity after learning of very high London rates in the early morning hours New York time.
Another interesting result is that TAF and FX Swap program levels had no e¤ect on the
New York Eurodollar-Libor spread; this indicates that these programs a¤ected the banks inthose markets in a similar way, irrespective of the trading session in which they participated.

21

Consistent with previous studies, various calendar e¤ects were signi…cant, as were special
dates, such as the New York City blackout period in 2003.

6

Concluding remarks

The period of unsettled money markets beginning in August 2007 and continuing for morethan a year caused an extraordinary divergence in interest rates between two otherwise closely
integrated money markets, the Eurodollar and federal funds uncollateralized overnight interbank markets. I have examined the level and variability of these market segments over theperiod. Clearly, the crisis period caused signi…cant dis-integration of the market segments,
especially in the post Lehman Brothers Bankruptcy period. The divergence between the twomarkets was unprecedented in size over the preceding nine years. The Swaps and the TAF
programs to provide U.S. dollar funding to depository institutions both in the U.S. and inother nations had signi…cant e¤ects in the rate spreads, with the Swap program signi…cantly
reducing the rate spreads between Eurodollar rates and fed funds rates.
I have measured Eurodollar rates in two ways. The …rst is the Libor rate, published by
the British Bankers Association, and re‡ecting rates in London during the London trading
session. The second is derived from the Fedwire Transactions Journal, likely re‡ecting trades
arranged in New York during its trading session. Capturing these market segments allows
one to track the di¤erent behavior of the New York and London Eurodollar market, and we…nd that the New York market is more closely integrated with the fed funds market segment,
perhaps especially during crisis periods in dramatic contrast to the London market..
There are several explanations for why the New York Eurodollar market would be moreclosely integrated with the federal funds market than the London market. First, the timezone mismatch could cause signi…cant di¤erences. The implementation of open market operations during the U.S. trading day can in‡uence (and is designed to in‡uence) rates in
the U.S., but it occurs long after the London trading has wound down for the day. As an
example, consider a situation in which the London trading session faced high rates, resulting22

in a high Libor rate. When U.S. banks begin trading, and the Open Market Desk of theFederal Reserve Bank of New York canvasses dealers to determine market conditions, theymight …nd that rates are high. Consequently, the Desk might then decide to inject greater
quantities of liquidity than had rates been "soft." That would have the e¤ect of lowering
New York session rates, both Eurodollar and fed funds.

Second, the greater geographic

distance to London may impede the formation of relationships, and the revelation of information conducive to trading.

Finally, di¤erent counterparties in the di¤erent geographic

areas could explain di¤erences in rates.
The crisis caused an extraordinary divergence in rates between the two market segments,
as well as increases in variability of rates. These divergences played out di¤erently in New
York and London, however. In both Eurodollar markets the Swaps program tended to reducethe divergence in rates, suggesting that the program was e¤ective in reducing liquidity riskfor depository institutions outside of the U.S. that have U.S. dollar liabilities.

The TAF

program tended to be associated with a divergence in the rates, even though it o¤ered only
term funds to U.S. depositories. That result suggests term …nancing rates have a signi…cantin‡uence on overnight rates, a substitute source of funding for banks.
The results also highlight the extreme divergence within the Libor panel.

The upper

quartile of rates, which are the highest four rate quotes and which are excluded from thetrimmed mean calculation of the Libor rate, drifted far above the trimmed mean Liborrates, resulting in a persistently high divergence between the trimmed mean Libor rate, andthe rate found by averaging all 16 rate quotes of the panel. A similar divergence was notfound in the fed funds or New York Eurodollar rates when weighted by market value. Whenexamining the e¤ect of TAF and the FX Swaps program it was found that the spreads
measured in untrimmed means did not display the same consistent e¤ects, likely re‡ectingthat the central bank programs did not alter the market perceptions of counterparty credit
risk that the high-rate reporting banks likely su¤ered.
This period of heightened volatility in money market rates has been extraordinary. Although there have been short periods, such as the period following September 11, 2001, in

23

which the overnight U.S. dollar Libor and the fed funds rate levels became less correlated,such periods were not accompanied by a decline in the correlation between the changes inrates. This result suggests that in previous periods intermediation between the two markets
continued, but was somewhat more costly for banks to conduct. However, a rate rise in
one market would be correlated with a rate rise in the other. In the crisis period following
August 9, 2007, the correlation in levels fell, but, in addition, the correlation in changes inrates, the direction of rates, went to zero.

A rate rise in one market (whose rates werealready far apart) were just as likely to be accompanied by a decline as a rise in rates in
the other market, suggesting that any intermediation that was occurring was ine¤ective inaligning rates in the two market segments.

One conclusion might be that in a crisis, allmarkets are local.
With such a pronounced decline in market integration, monetary policy transmission isnegatively a¤ected. It is not surprising, given these circumstances, that central banks aroundthe world cooperated to …nd improved ways of delivering liquidity to banks in more direct
ways, in the places and times at which markets are active. Speci…cally, the Central Bank
Swaps program allowed banks outside of the U.S. to borrow dollars on a collateralized basis
from the ECB, BOE, SNB, BOJ, and other central banks, in their country at the normal
time of trading in the market. This approach to providing liquidity found a large demand
among banks, and, as the evidence here suggests, tended to narrow spreads in overnight rates
between London and New York, improving the basic transmission mechanism for monetary
policy.

24

References

Ashcraft, Adam, and Hoyt Bleakley (2006), “On the Market Discipline of InformationallyOpaque Firms: Evidence from Bank Borrowers in the Federal Funds Market” manuscript, University of Chicago.
Ashcraft, Adam, and Darrell Du¢ e (2006), “Systemic Illiquidity in the Federal Funds
Market,”American Economic Review, Papers and Proceedings, forthcoming.
Bartolini, Leonardo, Svenja Gudell, Spence Hilton, and Krista Schwarz (2005), “Intra-Day
Trading in the Overnight Federal Funds Market,” mimeo, Federal Reserve Bank of
New York.
Bartolini, Leonardo, Spence Hilton, and James McAndrews (2007), “Settlement Delays in
the Money Market,”Mimeo, Federal Reserve Bank of New York.
Bartolini, Leonardo, Spence Hilton, and Alessandro Prati (2007), “Money Market Integration,”Journal of Money, Credit, and Banking, forthcoming.
Demiralp, Selva, Brian Preslopsky, and William Whitesell (2004), “Overnight Interbank
Loan Markets,”manuscript, Board of Governors of the Federal Reserve.
Fur…ne, Craig (1999), “The Microstructure of the Federal Funds Market,”Financial Markets, Institutions & Instruments 8:5, pp. 24-44.
Fur…ne, Craig (2001), “Banks as Monitors of Other Banks: Evidence from the OvernightFederal Funds Market,”Journal of Business 74, pp. 33-55.
Fur…ne, Craig (2003), “Interbank Exposures: Quantifying the Risk of Contagion,”Journalof Money, Credit and Banking 35, pp. 111-128.
Fur…ne, Craig (2006), “The Costs and Bene…ts of Moral Suasion: Evidence from the Rescueof Long-Term Capital Management,”Journal of Business 79:2, pp. 593-622.
Hendry, Scott, and Nadja Kamhi (2007), “Uncollateralized Overnight Loans Settled in
LVTS,”Bank of Canada, Working Paper No. 2007-11.

Makrose, Sheri, Amadeo Alentorn, Stephen Millard, and Jing Yang (2006), “Designing
Large Value Payment Systems: An Agent-Based Approach,”Bank of England, working
paper.
Millard, Stephen, and Marco Polenghi (2004), “The Relationship Between the Overnight
Interbank Unsecured Loan Market and the CHAPS Sterling System,”Bank of England
Quarterly Bulletin, Spring, pp. 42-47.

26

Value in the Overnight Interbank Market
Eurodollar

FedFunds

400

USD Billions

300

200

100

0
1/1/01

1/1/03

1/1/05

1/1/07

1/1/09Figure 1

Spreads: Three Overnight Rates minus Markets Effective
Overnight LIBOR (USD)

W.A. FedFunds from Fedwire

W.A. Eurodollar from Fedwire

600

Basis Points

400

200

0

−200
1/1/07

10/1/07

Figure 2

7/1/084/1/09Difference Between Overnight Interbank
Borrowing Rates and Target Fed Funds Rate
Eurodollar (Fedwire Data)
Fed Funds (Markets)

LIBOR
Fed Funds (Fedwire Data)
100

0

-50

-100

1/1/07

4/1/07

7/1/07

10/1/07

1/1/084/1/08Sources: BBA, FRBNY

Figure 3
Overnight LIBOR (USD)− W.A. FedFunds Rate from Fedwire
Daily Value

Monthly Average

400

300

Basis Points

Basis Points

50

200

100

0
1/1/01

1/1/03

1/1/05

Source: MaPS staff calculations and Bloomberg

Figure 2

1/1/07

1/1/09

Overnight LIBOR (USD)− W.A. FedFunds Rate from Fedwire
Daily Value

Lehmanfailure400
Start offinancial
turmoil

Basis Points

300

Monthly Average

Interest
on reserves
begin
0-25bppolicy
rate

200

100

0
1/1/07

10/1/07

7/1/084/1/09Source: MaPS staff calculations and Bloomberg

Figure 3
W.A. Eurodollar Rate from Fedwire− W.A. FedFunds Rate from Fedwire
Daily Value

Monthly Average

Basis Points

50

0

−50

−100
1/1/01

1/1/03

1/1/05

Source: MaPS staff calculations

Figure 4

1/1/07

1/1/09

W.A. Eurodollar Rate from Fedwire− W.A. FedFunds Rate from Fedwire
Daily Value

Monthly Average

50

Basis Points

0

−50

−100
1/1/07

10/1/07

7/1/084/1/09Source: MaPS staff calculations

Figure 5

Correlation Between Changes in Eurodollar and Fed Funds
22-day correlation window, 66-day moving average
1.8.6

9 Aug 2007
.4

Lehman.2001jan1998

01jan2000

01jan2002

01jan2004

Source: FRBNY

Figure 8

01jan2006

01jan2008

01jan2010

Correlation Between Levels of Eurodollar and Fed Funds
22-day correlation window, 66-day moving average
1.8.6

9 Aug 2007
.4

Lehman.2001jan1998

01jan2000

01jan2002

01jan2004

01jan2006

01jan2008

01jan2010

Source: FRBNY

Figure 9

Correlation Between Changes in Eurodollar and LIBOR
22-day correlation window, 66-day moving average
1

Lehman.8.6.4

9 Aug 2007
.2001jan1998

01jan2000

01jan2002

01jan2004

Source: FRBNY

Figure 10

01jan2006

01jan2008

01jan2010

Correlation Between Levels of Eurodollar and LIBOR
22-day correlation window, 66-day moving average
1.8.6

9 Aug 2007
.4
.2

Lehman001jan1998

01jan2000

01jan2002

01jan2004

01jan2006

01jan2008

01jan2010

Source: FRBNY

Figure 11

Correlation Between Changes in Fed Funds and LIBOR
22-day correlation window, 66-day moving average
1

Lehman9 Aug 2007
.8
.6
.4
.2
0
01jan1998

01jan2000

01jan2002

01jan2004

Source: FRBNY

Figure 12

01jan2006

01jan2008

01jan2010

Correlation Between Levels of Fed Funds and LIBOR
22-day correlation window, 66-day moving average
1
.8
.6
.4
.2

9 Aug 2007

Lehman001jan1998

01jan2000

01jan2002

01jan2004

01jan2006

01jan2008

01jan2010

Source: FRBNY

Figure 13

Comparison of Trimmed and Untrimmed LIBOR Rates
8

6

4

2

0
1/1/07

10/1/07

7/1/08Trimmed Sample (8 bank)
Source: BBA and FRBNY

Figure 14

Untrimmed (16 bank)4/1/09

Comparison of Trimmed and Untrimmed Fed Funds Rates
6

4

2

0
1/1/07

10/1/07

Trimmed Sample

7/1/08Untrimmed

Source: FRBNY

Figure 15

4/1/09

Total Volume
Avg Daily Volume
Avg Daily Value
Mean Transaction SizeMedian Transaction Size

TABLE 1
Summary Statistics
Eurodollar
FedFunds
15841112867514954
1726$134,988,728,770$156,020,191,574$141,540,760$74,920,048

LIBOR$90,374,288$35,997,050

Avg Deviation from Target
0.011
0.003
0.072
High Deviation fromTarget
8.343
8.121
0.715
Avg Standard Deviation
0.107
0.101
0.799
Note: Data come from MaPS staff calculations and Bloomberg for the period 1/1/2001 8/8/2007.

TABLE 2Estimation Summary
Post Lehman Bros
Bankruptcy Period
Level
Volatility

Elevated Libor-OIS
Spread Period
Level
Volatility

Level

Volatility

Level

Volatility

Trimmed Mean
Coefficient Estimates
LIBOR-Fed Funds
Eurodollar-Fed Funds
LIBOR-Eurodollar

88.41***-6.89
64.47**-2.06***
0.43-1.98***

4.60***
0.35
2.32*

0.39***
1.20***
0.31**

0.013
0.009**
0.010

0.001
0.002
0.002

-0.03***-0.011**-0.013-0.001-0.005**-0.002Un-trimmed Mean
Coefficient Estimates
LIBOR-Fed Funds
Eurodollar-Fed Funds
LIBOR-Eurodollar

1680***-40.54***897.9***

0.13
-0.73
-0.56

2.74
-1.29**-2.04

0.12
1.08***
0.05-0.0140.020***
0.012

0.000
0.000
0.000

0.043*-0.019***0.058**-0.0010.002
0.000

Fed Funds Standard
Deviation

LIBOR Standard
Deviation

Level

Volatility

Level

Volatility

Trimmed Mean
Coefficient Estimates
LIBOR-Fed Funds
Eurodollar-Fed Funds
LIBOR-Eurodollar

15.66***
1.545***
14.42***

6.034***
4.944***
5.566***

0.15
0.01
0.188*

0.049**
0.02
0.042**

Un-trimmed Mean
Coefficient Estimates
LIBOR-Fed Funds
Eurodollar-Fed Funds
LIBOR-Eurodollar

7.307***
5.960***
0.13

4.452***
8.512***
2.877***-0.142*0.01-0.303***0.049***-0.02
0.077***

Note: Significance indicated by *** p<0.01, ** p<0.05, * p<0.1

TAF Levels

FX Swap Levels

TABLE 3
Estimation Results
Overnight LIBOR (USD) W.A. FedFunds Rate from
Fedwire-3.377***

Variance(Het)-0.381(0.31)

Overnight LIBOR (USD) W.A. Eurodollar Rate from
FedwireW.A. FedFunds Rate from
Fedwire - W.A. Eurodollar
Rate from Fedwire-3.047***

Variance(Het)-0.690***-0.435***

Variance(Het)-0.0951(0.24)(0.28)(0.23)(0.09)(0.25)

0.215

0.221

0.0173

0.214

0.093

0.185

(0.34)(0.22)(0.33)(0.22)(0.10)(0.24)-0.1870.249-0.397*0.253

0.150***-0.0925(0.24)(0.16)(0.22)(0.15)(0.06)(0.17)

1st of Month-0.990***-0.401*-0.906***-0.476**-0.149**0.315*(0.28)(0.21)(0.23)(0.21)(0.07)(0.17)

Last Day of Quarter

6.311***

0.760*

5.763***

0.527

0.449

0.63

(1.66)(0.40)(1.43)(0.37)(0.42)(0.41)

Maintenance Day=2

7.086**

0.517***

7.219**

0.759***-0.02130.524***(3.32)(0.18)(3.33)(0.18)(0.79)(0.17)

Variable
After a 3 Day Holiday
Before a 3 Day
Holiday
15th of Month

Maintenance Day=3
Maintenance Day=4

Mean

Mean

Mean

6.338*

6.560**-0.0838(3.32)(3.33)(0.79)

7.876**

0.320*

8.069**

0.621***

0.00241(3.32)(0.19)(3.33)(0.20)(0.78)(0.18)

Maintenance Day=5

7.250**

0.175

7.489**

0.259*-0.09020.278*(3.32)(0.16)(3.33)(0.15)(0.78)(0.17)

Maintenance Day=6

5.888*

0.407**

6.176*

0.746***-0.1630.319*(3.32)(0.17)(3.33)(0.17)(0.78)(0.16)

Maintenance Day=7

6.321*

0.255

6.475*

0.449***-0.0768

0.408**(3.32)(0.16)(3.33)(0.17)(0.78)(0.16)

5.922*

0.0412

6.199*

0.073-0.0727

0.363**(3.32)(0.17)(3.33)(0.17)(0.79)(0.17)

8.004**

0.586***

7.990**

0.896***

0.177-0.00668(3.33)(0.16)(3.33)(0.17)(0.79)(0.18)

Maintenance Day=10

7.403**

0.286*

7.462**

0.447***-0.00104

0.555***(3.33)(0.16)(3.33)(0.17)(0.79)(0.17)

Maintenance Day=1

6.180*

0.0402

6.321*

0.198-0.0578

0.394**(3.32)(0.16)(3.33)(0.17)(0.79)(0.17)

Last Day of Month1.079**

0.711***

1.121***

0.752***

0.06750.620***

Maintenance Day=8
Maintenance Day=90.304*(0.43)(0.22)(0.38)(0.21)(0.10)(0.22)

Penultimate Day ofMonth-0.2990.444*-0.2170.167

0.06750.131(0.30)(0.23)(0.25)(0.24)(0.07)(0.18)First Day of Quarter-0.597

0.661*

0.02490.599*-0.3360.432(0.93)(0.34)(0.83)(0.34)(0.26)(0.29)

2.149**

0.836***

2.048**

1.146***

0.103

0.0922(0.98)(0.30)(0.88)(0.30)(0.15)(0.37)

Penultimate Day of
Quarter

Day of FOMC
Meeting
Day After FOMC
Meeting
Day Before FOMC
Meeting
Blackout
11-Sep-01
Post Lehman Bros
Bankruptcy Period
Interest on Reserves
PeriodZero to 25 Basis
Points Target Period
Elevated Libor-OIS
Spread Period
Change in Target
Rate
Day After FifteenthMarkets Reported
Stdev

0.367

-0.487*0.498-0.586**0.0323-0.0469(0.39)(0.26)(0.37)(0.29)(0.09)(0.20)-0.693***-0.0725-0.523**-0.1040.0328-0.228(0.25)(0.21)(0.25)(0.23)(0.08)(0.18)

0.553

0.865***

0.486

1.092***

0.153

0.662***(0.47)(0.21)(0.44)(0.20)(0.09)(0.18)

29.17

4.432

-2.0390.77.860***

5.201(22.40)(19.70)(5.14)(5.13)(2.37)(3.95)-4.097*1.756***

2.22

1.925***

0.813

0.938**(2.49)(0.46)(2.02)(0.44)(4.39)(0.47)

88.41***-2.062***64.47**-1.975***-6.8860.427(16.70)(0.49)(25.40)(0.47)(5.28)(0.84)

12.94*

0.882

8.202

0.774

-0.03172.599***(7.56)(0.73)(8.11)(0.72)(2.26)(0.87)

4.35

0.431

-1.129

0.398

1.687

2.364***(5.97)(0.66)(6.21)(0.65)(2.16)(0.79)

4.595***

0.389***

2.321*

0.310**

0.347

1.202***(1.40)(0.13)(1.38)(0.13)(0.44)(0.20)-1.379-3.797**0.57(1.78)(1.83)(0.43)

0.547**

0.0233

0.282-0.0350.262***

0.268*(0.22)(0.18)(0.20)(0.18)(0.07)(0.15)

15.66***

6.034***

14.42***

5.566***

1.545***

4.944***(1.24)(0.36)(1.14)(0.32)(0.35)(0.37)

0.145

0.0491**0.188*

0.0420**0.01440.0177(0.10)
0.0252***(0.01)(0.02)(0.10)(0.02)(0.02)(0.03)-0.00146-0.0128-0.00228-0.0107**-0.00485**(0.00)(0.01)(0.00)(0.00)(0.00)

0.01320.000533

0.01040.00151

0.00918**0.00153(0.01)(0.00)(0.01)(0.00)(0.00)(0.00)

2.66-0.09371.963

0.01220.0697-0.488(2.45)(1.10)(2.36)(1.11)(0.77)(0.83)-0.987

0.491

-1.32

0.428

0.736

-0.871(3.56)(0.86)(3.43)(0.90)(1.18)(0.64)

1.412*

0.0874

0.903

0.166

0.223

-0.612**(0.73)(0.33)(0.74)(0.32)(0.24)(0.26)ECB Announcements-0.196-0.912***0.702-0.483-0.00967

0.502(0.55)(0.31)(0.62)(0.29)(0.40)(0.34)

Time Zone-0.115-0.206-0.194-0.0960.0188-0.299*(0.66)(0.19)(0.67)(0.17)(0.16)

Libor Panel Stdev
FX Swap Outstanding
TAF Outstanding
And 01FX Swap
Announcements
TAF Announcements

Constant

1.004

0.208

(0.17)-0.0975

Absolute Value of
Change in Target
Rate
ARMA

(0.98)(0.87)(0.84)

3.721***

3.716***

1.413**(0.64)(0.66)(0.70)

ARCH

ARMA

ARCH

ARMA

0.602***

0.609***

0.394***(0.02)
0.0671***(0.02)(0.02)(0.02)-0.0395*

0.0447**(0.02)(0.02)

0.0306*0.0291*0.0595***(0.02)(0.02)(0.02)

Fourth Lag

0.00880.00910.0101(0.01)(0.01)(0.02)

Fifth Lag

0.0295***0.0364***0.00672(0.01)(0.01)(0.02)

Sixth Lag

-0.00395-0.00789

0.0168(0.01)(0.01)(0.02)

0.000672

0.00951

0.00545(0.01)(0.01)(0.01)

0.00860.01480.0348**(0.01)(0.01)First Lag of Dep. Var.

Second Lag
Third Lag

Seventh Lag
Eighth Lag

ARCH(0.02)

theta

0.0962***(0.04)(0.04)(0.04)

kappa

0.505***

0.563***

0.397***(0.06)(0.06)(0.06)

lambda0.473***

0.513***

0.301***(0.02)(0.02)(0.04)

Observations

2025

2025

0.0829**

2025

2025

Note: Standard errors in parentheses, p-values given by (*** p<0.01, ** p<0.05, * p<0.1).

0.0834**2026

2026