# Anticipated and Repeated S hocks in Liquid Markets *

Dong Lou London School of Economics d.lou@lse.ac.uk

Hongjun Yan Yale School of Management hongjun.yan@yale.edu
Jinfan Zhang Yale School of Management jinfan.zhang@yale.edu

This Draft: March 1 , 201 1

* We thank Viral Acharya, Nick Barberis, Mikhail Chernov, Greg Duffee, Darrell Duffie, Michael Fleming, David Goldreich, Robin Greenwood, Peter Kondor, Arvind Krishnamurthy, Andrew Metrick, Lasse Pedersen, Christopher Polk, Tyrone Smith, Jeremy Stein, Dimitri Vayanos, Lei Xie, Tong Yu, and seminar participants at UC Irvine, LSE, Yale, and Econometric Society Meetings for helpful comments. We are also grateful to Pengjie Gao, Andrea Vedolin, and Tong Yu for t heir generous help with some of the data used in this paper. Lou acknowledges financial support from the Paul Woolley center at the London School of Economics. Yan received support from a Whitebox Advisors research grant administered through the Yale Inter national Center for Finance. Please direct all correspondence to Hongjun Yan.

# Anticipated and Repeated Shocks in Liquid Markets

Abstract
We show that Treasury security prices in the secondary market decrease significantly before auctions and recover shortly after. Hence, Treasury security prices tend to be lower on auction days, implying a large issuance cost for the Treasury Department, which is estimated to be 9

- 18 basis points of the auction size (amounts to over half a billion dollars for issuing Treasury notes in 2007). These results appear to be consistent with the hypothesi s of dealers’ limited risk

- bearing capacity and the imperfect capital mobility of Treasury investors, highlighting the important role of capital mobility even in the most liquid financial markets.

JEL Classification Numbers: G12. Keywords : Liquidit y, Slow

- moving capital, Supply s hocks , Treasury auction

.1 I. Introduction In this paper, we empirically examine how anticipated and frequently repeated supply shocks are absorbed in liquid financial markets. In particular, we examine the price impact of Treasury security auctions on the secondary Treasury , repo , and equity market s
. This may appear as a surprising agenda : T reasury auctions are conducted every month , of which the exact dates and amounts are announced in advance , s o these events are largely anticipated. G iven the depth and liquidity of the U.S. Treasury, repo, and equity markets , o ne might expect no appreciable price impacts from anticipated supply shocks. 1 In sharp contrast to this conventional view , our evidence reveals significant price effects in all three markets around Treasury auctions

. S pecifically, w e find that Treasury auctions exert significant price pressure in the secondary Treasury market during the 5 to 10 days leading up to the se auctions and that this price pressure gradually dissipates in the subsequent 5 to 10 days. An efficient way to detect this price dip and recovery pattern is to compare T reasury returns around auctions: For example, t he 5

- day cumulative return of a n on
- the

- run 2

- year T reasury note before the subsequent 2

- year note auction is, on average, 8.89 ( t = 2.93) basis points low er than the 5

- day post

- auction return of the same security

. 2 Similar ly , this 5

- day return difference is, on average, 22.54 ( t =3.67) basis points for 5

- year notes, and 23.84 ( t =1.78) basis points for 10

- year notes. These results suggest that , even in the most liquid financial markets like the Treasury market, capital has limited mobility and cannot instantly absorb anticipated and frequently repeated supply shocks.
T he findings have important economic implications

. First of all , they suggest that the cost of security issuance borne by the Treasury D epartment is an order of magnitude larger than previous ly estimate d auction markups in the literature , which compares the auction price with a benchmark price on the auction day , and often finds the markup to

1 In 2008, the total size of Treasury securities outstanding is $10 trillion (from Treasury Department website), the total U.S. stock market capitalization is $14 trillion (from CRSP), and the estimated size of the repo market is over $10 trillion (Gorton and Metrick (2010)).

2 An on

- the

- run Treasury security is the most recently issued security of a given maturity. The first off

- the

run and the second off

- the

- run securities are t he second and third most recently issued securit ies of a given maturity, respectively.2 be around 1 basis point of the auction size. 3 Our findings suggest that , because of the price impact of T reasury auctions , the se benchmark prices on auction days are already depressed. Therefore , while th e traditional app roach is appropriate for measuring auction markups , it does not reflect the total issuance cost borne by the Treasury Department

. To incorporate price impacts into our cost measure, we take the average price in the secondary Treasury market on the t th day before and the t th day after each auction as the benchmark price, with t ran g ing from 1 to 10. 4 That is, our measure reflects the amount of money the Treasury Department could have saved were it able to issue Treasury notes at the secondary market pri ces several days before and after auctions. For t

=5, for example, our estimates of Treasury issuance costs for 2

- , 5

- , and 10

- year notes are 9.07, 16.81, and 18.43 basis points of the auction size, respectively. According to these estimates, the total cost of issuing Treasury notes alone in 2007 is $643 million. This cost is likely to be substantially higher in the near future when the U.S. faces an unprecedented budget deficit. While it is by no means clear whether part of the estimated cost can be saved t hrough better designs of the Treasury selling mechanism, recognizing such cost is a necessary first step to understand and improve it s efficiency. 5 Second, our findings suggest that the frictions behind investors’ slow response s to demand/supply shocks are of first

- order importance even in the most liquid financial markets

. A simple long

- short strategy that exploits th es e large and reoccurring swings in Treasury returns around auction days yields a Sharpe ratio higher than many well

- known asset pricing anomalies , such as currency carry trade s and price momentum

. For example, by going short in the on
- the

- run 2

- year note and long in a duration

- matched portfolio comprising the on

- the

- run 6

- month Treasury bill and 10

- year note during the 10 days before each 2

- year note auction, and holding reversed positions during the 10 days after, an investor can achieve a n annualized Sharpe ratio of 1.08. In comparison, the Sharpe ratio s are around 0.59

– 0.95 for currency carry trade s , and 0.47

– 0.75 for price m omentum

3 See, for example, Nyborg and Sundaresan (1996 ) and Goldreich (2007).

4 This is likely a conservative estimate since the auctioned security will become “on

- the

- run” in a few days and should be worth more than the soon

- to

- become

- off

- the

- run note, as suggested by the well

- known on

- the

run
- off

- the

- run phenomenon (e.g., Amihud and Mendelson (1991), Krishnamurthy (2002) )

. 5 Motivated by our empirical evidence, Jin and Yan (2011) analyzes a model of optimal security selling mechanism when capital is slow

- moving.3 strategies in the U.S. stock market

. 6 Interestingly, w hile the bid

- ask spread drops substantially throughout our sample period , the Sharpe ratio of our strategy increases over time . I n the last 10 years of our sample, 1998

- 2008, the Sharpe ratio reaches 1.44 ; e ven after accounting for the bid

- ask spread, it remains close to 1

. In addition, th e documented return pattern implies large swings in bond premium around auction days each month. Even our most conservative estimate implies that the post

- auction an nualized bond premium is 2.3% higher than its pre

- auction counterpart. This difference is economically significant given that the unconditional bond premium is only 1.4% in our sample, thus posing a big challenge for asset pricing models

. Finally, the shock s analyzed here are small relative to the size of Treasury markets

. In the last 10 years, the average auction size of Treasury notes is merely 0.3% of the Treasury market size. 7 I f one takes into a ccount the amount of T reasury securities maturing in each month , the net supply shock is even smaller . In addition, the timing and size of Treasury auctions are announced in advance, making Treasury auctions a clean setting to analyze capital mobility

. Our evidence that markets are unable to quickly absorb t hese anticipated small shocks, repeatedly , suggests that capital mobility is perhaps more limited than previously thought even in these most developed financial markets. 8 I t therefore seems reasonable to expect capital immobility to play an even bigger rol e in less liquid markets, such as corporate bond and structured product markets

. The documented return pattern is consistent with the interpretation that Treasury auctions exert temporary price impacts in secondary Treasury markets. 9 More precisely, the underlying mechanism has two ingredients

. First, primary dealers have limited risk

bearing capacity. According to the U.S. Treasury selling mechanism, primary dealers are

6 See, e.g., Brunnermeir, Nagel, and Pedersen (2009), Lustig, Roussanov, and Verdelhan (2009) , Asness, Moskowitz, and Pedersen (2008) , and Burnside, Eichenbaum, Kle shc helski, and Rebelo (2010)

. 7 In contrast, the demand shocks analyzed in Shleifer (1986) are close to 3% of the shares outstanding.

8 In a recent study, Fleckenstein, Longstaff , and Lustig (2010) provide another piece of evidence on the imperfection of the Treasury markets: The prices o f nominal Treasury bonds and TIPS appear to be inconsistent with inflation swap markets and imply large mispricing.

9 An alternative interpretation is that Treasury auctions have information contents. Although Treasury
a uctions are fully anticipated, their outcomes are likely to contain information about economic conditions. However, if uncertainty about these auctions is resolved gradually in the days leading to these auctions, the pre
- auction Treasury returns should be higher than post

- auction ones, opposite to the find ings

.4 expected to participate actively and to submit competitive bids in all Treasury auctions

. 10 With limited risk

- bearing capacity, these primary dealers usually need to hedge part of the risk they expect to acquire by short selling similar securities in the secondary market before auctions

. Consistent with this interpretation, we find that the price impact on the second market is more pronounced when the total risk expected to be acquired by primary dealers is larger , for instance, when the auction size is larger and in period s with higher implied Treasury return volatilit ies

. The above limited

- risk

- bearing

- capacity idea alone , however, is unlikely to explain the whole phenomenon: P rimary dealers ’ short selling in secondary Treasury markets would not have a price impact , were there enough end

- investors to step in and provide liquidity. This point is particularly important since a large amount

– sometimes even larger than the offering amount

– of Treasury securities are maturing around these auctions. 11 In other words, end

- investors do h ave e nough capital to absorb the supply. F or primary dealers’ shorting to have a material price impact , end

- investors’ capital has to be slow

- moving

. Major investors in Treasury markets are indeed likely un responsive to transient demand/supply shocks

. Although the total size of Treasury securities outstanding is around $10 trillion, o ver 40% of them are nonmarketable and held by Federal Government

a ccounts. 12 The Federal Reserve holds another 8% to 9%, most of which is obtained through noncompetitive bid s at auctions. “Private holdings” constitute the rest , of which f oreign investors and s tate and local government s account for more than half. While there

are no publicly available data on these private holdings , it seems reasonable to expect that many of them do not have the intention, or resources, to engage in short

- term arbitrage trades. In addition , insurance companies and bond mutual funds , which account for

10 According to Administration of Relationships with Primary Dealers , available from the website of the Federal Reserve Bank of New York, http://www.ny.frb.org/markets/pridealers_policies.html , “Primary dealers are also required to participate in all auctions of U.S. government debt and to make reasonable markets for the Ne w York Fed when it transacts on behalf of its foreign official account

- holders.” According to Fleming (2007), primary dealers alone purchased 70.9% of Treasury securities sold to the public (and another 21.6% on behalf of their institutional clients) during July 30, 2001 to December 28, 2005

. 11 For example, on June 1, 2004, the Treasury Department issued around $25 billion 2

- year note s, but there were $27 billion worth of Treasury securities maturing on the previous day.

12 The data on the own ership of Treasu ry securities are from http://fms.treas.gov/bulletin/index.html

.5 around 13% of private holdings , are also likely to be unresponsive to the temporary pr ice movements around auctions. For example , we find 70% of the insurance companies in the U.S. make less than 5 trades a year in Treasury markets. Index bond mutual funds, due to concerns of tracking errors, are likely to avoid newly issued securities befo re they are included in the indices they are tracking. 13 In other words, rather than exploiting the yield changes around auctions, index funds might be part of the cause of the documented phenomenon. Moreover, a ctive bond mutual funds are likely constrained by their investment capital , as w e find that mutual fund investors only gradually move their capital into bond mutual funds after Treasury auctions.
Our interpretation has a number of further predictions. First, it implies that repo rates tend to be lower before auctions . Recall that primary dealers need to short in the secondary Treasury market prior to auctions. To take short positions, they need to borrow Treasury securities through “reverse repo” transactions. In these trans actions, primary dealers essentially lend to their counterparties and take Treasury securities as collateral, which they short

- sell in secondary markets. Primary dealers’ strong demand for these transactions implies that they would be willing to accept low er interest rates in the ir lending, leading to lower repo rates before auctions. Since this hedging activity is expected to last only for a few days, its impact should be stronger for overnight repo rates than for long

- term repo rates. Consistent with this conjecture, we find that the average overnight general

- collateral repo rates during the 5 days before 2

- year note auctions is 6.75 ( t =4.83) basis points lower than that during the 5 day s after. The pattern for one

- week term repo rates is slightly weaker, with a rate differential of 4.39 ( t =4.36) basis points , while that for

one
- month repo rates is virtually absent. Second, since off

- the

- run notes are close substitutes to on

- th e
- run o nes, our interpretation impl ies that the price impact around auctions should also arise for off

- the

run securities. Indeed, w e find that the return pattern of off

- the

- run notes is almost identical to that of on

- the

- run notes. Third, auction s of Treasury securit ies with one maturity should also affect prices of other maturiti es, and the impact should be stronger if

13 Many fixed

- income indices usually adjust their composition at the end of each month. For example, Barclays US Treasury Bond Index adju sts its composition on the last calendar day of each month; see, https://ecommerce.barcap.com/indices

.6 the maturit y differen tial is smaller. Consistent with this prediction , w e find a similar price pattern of 10

- year notes around both 2

- year and 5

- year note auctions , when there is no 10

- year note auction in surrounding days. Moreover, relative to 2

- year note auctions, 5

- year note auctions have a much stronger price impact on 10

- year note s
. F inally , since Treasury yields affect the discount and borrowing rates in other financial markets, one might expect the Treasury yield movements around auctions to also affect prices in other markets, such as the equity market. To our surprise, we find very large equity price movements around Treasury auctions: T he average cumulative return of the value

- weighted CRSP index in the 5 day s before 2

- year note auctions is 49 ( t =3.11) basis points lower than that after these auctions. Put differently , in the past three decades, the average stock market return is negative during the 5 days before 2

- year note auctions, and is more than twice the unconditional average during the 5 days after . We further show that this return pattern is not driven by calendar

- time effects (e.g., turn

- of

- the

month, turn

- of

- the

- year effects). While the stock return pattern is potentially consistent with our over all interpretation, the exact underlying mechanism for such a large price impact remains unclear

. The rest of the paper is organized as follow s : Section II reviews the related literature and Section III describes the data

. Section I V analyzes the impacts of Treasury auctions on the secondary T reasury market. Section V presents the interpretation and further analysis implied by the interpretation. Sections V I and V I I analyze the impact on the repo and stock markets , respectively. Secti on V I II concludes.
II. Related Literature
Our paper is related to the literature on the price impact of supply/demand shocks

. Since the seminal paper by Shleifer (1986 ), there has been a proliferation of research examining the impact of uninformative demand due to index re

- compositions on stock prices, e.g., Greenwood (2005), Mitchell, Pulvino, and Stafford (2004 ), Wurgler and Zhuravskaya (2002), Kaul, Mehrotra, and Morck (2000).
A related literature examines the price impact of institutional capital flows, e.g., Coval and Stafford (2007) , Frazzini and Lamont ( 2008 ) , and Lou (20 10 ). The contribution7 of our paper lies in that we provide evidence in very liquid financial markets in a setting where the shocks are both anticipated and frequently repeated

. This unique feature highlights the first

- order importance of frictions to our understanding of the overall financial markets

. In a related study, Fleming and Rosenberg (2007) show that the primary dealers reduce their positions prior to auctions to make room for absorb ing the issuance of Treasury securities, and interpret the price appreciation during the subsequent week as a compensation for dealers to take the risks associated with their inventory changes. Greenwood, Hanson, and Stein (2010) show t hat corporations respond to the supply shocks of Treasury securities by filling the resulting maturity gap, thus acting as macro liquidity providers. More recently, Krishnamurthy and Vissing

- Jorgensen ( 2010 ) show that changes in the supply of U.S. Treasury securities have large effects on a variety of yield spreads. Our paper, i n contrast , examines Treasury auctions’ price impact in the secondary Treasury market s , both before and after auctions, as well as their spillover effects both across maturities and across markets

. Another subtle but important feature is that the Treasury supply analyzed in our paper is not net supply, and so our focus is on the frictions for the new securities to “ work their way to the end

- investors. ” Our results highlight the key role of not only dealers’ limited risk

- bearing capacity , but also, more importantly, end

- investors’ slow

- moving capital

. Hence, o ur study contributes to the

r ecent literature that begins to appreciate the importance of limitations in capital mobility (e.g. , Mitchell, Pedersen , and Pulvino ( 2007 ) , Acharya, Shin, and Yorulmazer ( 2009 ), He and Xiong ( 2009 ), Duffie ( 2010 ) , Malliaris and Yan ( 2010 ) )

. III. Data
A. Institutional background of T reasury auctions
In our sample period of 1980

- 2008 , the U.S. Treasury Department auctioned , on average, $2.35 trillion worth of securities each year ; the total amount auctioned was $6.7 trillion in 2008

. The participants of these auctions include primary dealers, institutional investors, foreign central banks, the Federal Re serve, and a small number of individual investors. The Treasury Department usually schedule s the auction date s several months in advance and announces the auction size several days before each auction. Immediately after the8 announcement, dealers and investors in the Treasury market start to trade forward contracts on the soon

- to

- be

- issued Treasury security in the “when

- issued” market. In each auction, primary dealers and other competitive bidders submit sealed bids of rate

- q uantity pairs that specify the amount to be purchased at each minimum yield. Two auction mechanisms have been employed in Treasury auctions: multiple

- price and single

- price auctions. Under both mechanisms, the clearing price is identified by equating the a ggregate demand submitted by competitive bidders to the total issue amount minus the total demand from noncompetitive bidders (i.e., those who submit market orders )

. The difference between the two mechanisms lies in that, while in multiple

- price auctions, competitive bidders pay for their allocated shares at their submitted rates, in single

- price auctions, all winning bidders pay the same price. While almost all Treasury auctions in the 1980s were m ultiple

- price auctions, the single

- price mechanism is the dominant form in the more recent two decades. 14
B. Data sample
From the U

. S

. Treasury D epartment website, w e collect detailed information regarding individual auctions for Treasury note s , with maturities ranging from 2 to 10 years. Such information includes the auction date, issue date, auction mechanism, bids submitted, total tender amount received, total tender amount accepted, l owest and highest winning rates , etc . Our sample spans from Janua ry 1980 to June 2008 , d uring which period 2

- year Treasury notes are issued on a monthly basis and 10

- year notes are issued on a quarterly basis. The issu ing frequency of 5

- year notes varied a few times in this period. In total, we have 33 2 2

- year note auct ions , 210 5

- year note auctions, and 132 10

- year note auctions. 15 We then match our auction data with the CRSP daily U

. S

. Treasury database to obtain daily Treasury security price s and carr ied interest s
. Throughout our analysis, we use the average of the bid and ask prices from CRSP as our measure of clean price s
.

14 For more detailed discussions of these two auction mechanism s see, e.g., Goldreich (2007).

15 The Treasury also issued 3

- , 4

- , and 7

- year notes roughly at a quarterly frequency. Their issuance, however, was interrupted in the period of 1998

- 2003 for 3

- year notes , 1990

- 2008 for 4

- year notes, and 1993

- 2008 for 7

- year notes.9 We supplement our Treasury auction and yield data with f ive additional data

sources. First, we obtain daily repo rates from Bloomberg. Second , to examine insurance companies’ trading activities in Treasury markets, we get their trading records from the ir annual reports to National Association of Insurance Commissioners (NAIC). In particular, Schedule D of the se report s includes trades by insura nce companies in each year and their holding s at the end of the year. 16 Third, we obtain daily stock return s from the CRSP daily stock files. Fo u rth , we collect from TrimTabs , for the period of 1998

- 2008, daily investment flows to three major mutual fund classes: bond mutual funds, equity funds, and hybrid funds. Finally , from Mueller, Vedolin , and Yen (2011), we obtain the daily model

- free estimates of maturity

- weighted implied volatility of nearest

- to

- ex piry at

- the

money options on the 30

- year, 10

- year, and 5

- year Treasury securities.
Table I presents some descriptive statistics of our sample

. P anel A reports the summary statistics associated with Treasury a uctions, and Panel s B and C report those for all other main variables. T he average size of Treasury auction s across all maturities is well over $10 billion. The average daily Treasury note return ranges from 1.9 6 (for 2

- year note s) to 2.31 (for 10

- year notes) basis points. T he average daily return of the value

- and equal

- weighted CRSP indices and the value

- weighted S&P 500 index are 4.45, 8.15, and 3.53 basis points, respectively. T he average daily flow s to bond, equity , and hybrid mutual funds reported by TrimTab s are 0.4,

- 0.92, and

- 0.19 basis points per day. 17 Finally, the average maturity

- weighted Treasury

- auction implied volatility is around 8% in our sample.
IV. Price Impact on Secondary Markets To analyze the impact of Treasury auctions on the secondary Treasury market, w e first examine yield s
- to

- maturity of 2

- year notes, the most frequently issued Treasury notes , around subsequent 2

- year note auctions

. Specifically, for each 2

- year note auction, we calculate daily yield s to maturity of the on
- the

- run 2

- year note during both the 10 days before and 10 days after the auction and compare them with the yield on the auction

16 See Jiang, Yan , and Yu (201 0) for detailed descriptions of this dataset.

17 See Edelen and Warner (2001) and Greene and Hodges (2002) for a description of the construction of flows and its pote ntial issues.10 day

. 18 Since there is a 2

- year note auction almost every month i n our sample , the se 20

- day event window s around auctions cover virtually all trading days in our sample period.
The pattern in Treasury yields around auctions can be easily seen in Figure 1. The upper
- left panel plots the time series average of Y( t )

- Y(0), wh ere Y( t ) is the yield of the

on
- the

- run 2

- year note o n day t and Y( 0 ) is the yield of the same security on the auction day

. There is a clear inv erted

- V shaped pattern : yields tend to go up before auctions and then decrease after ward

. More detail ed results are presented in Table I I : The yield differences, Y( t )

- Y(0), are negative in the entire 20

- day event window surrounding each auction, and are statistically significant in the 4 days immediately before the auctions and 6 day s after the auctions. More specifically, the yield of 2

- year notes increases , on average, by 2.53 basis poi nts during the 5

- day period before the auctions, but decrease s by 2.32 basis points during the 5

- day period after ward

. These results suggest that 2

- year note auctions exert temporary price pressure on the existing 2

- year notes ; secondary market prices are lower on auction days than in surrounding days. An other way to see this price impact is to compare 2

- year note returns before and after these auctions. This approach effectively integrates the pre

- and post

auction impacts into one measure and so increases the statistical power in detecting such price impact. As shown in Table III , t he return of the on
- the

- run 2

- year note on the day prior to the subsequent auction is, on average, 3.68 basis points lower than the return of the same note on the day immediatel y after the auction, with a t

- statistic of 3. 90 . The return difference is positive and statistically significant in the entire 20

- day window: The average cumulative retur n during the 10 days after auction s is 9.20 basis points higher than that during the 10 days before, with a t

- statistic o f 2. 02

. The return differen tial achieves its maximum on day 6 , with a point estimate of 10.2 basis points and a t

- statistic of 3. 62

. The documented yield and return pattern around subsequent auctions is not un ique to 2

- year notes . A very similar pattern exists for other maturities. For example, as shown in Table II, the yield of the on
- the

- run 5

- / 10

- year notes increases by 2. 67 / 1.57 basis points

18 We track the same 2

- year note throughout the 20

- day window around each auct ion, even though this security becomes off

- the

- run immediately after the auction.11 during the 5 day s before auctions, and decreases by 2. 73 / 2.00 basis points in the 5 day s after. Moreover, as shown i n Table III, the cumulative 5

- day return of the on

- the

- run 5

- year Treasury note before a 5

- year note auction is, on average, 22.54 ( t =3.67) basis points lower than the 5

- day return of the same note aft er the auction. This return difference is 23.84 ( t =1.78) basis points for 10

- year notes.
A. Economic significance
T h e temporary movement s in Treasury yields around subsequent auction s have a number of important implications. First, they r epresent a substantial issuance cost borne by the Treasury Department , which has been largely ignored in prior literature. Second, they impl y a potentially large trading profit, even after taking into account transaction costs. Finally, these large swings in avera ge Treasury returns provide u seful guidance for future asset

- pricing models. We examine these issues in more detail in this section

. A.1. Large issuance cost s I n prior literature , Treasury auction markup s are usually measured as the difference between the auction price and some benchmark traded price on auction day s (e.g., the secondary market price or the forward price in the when

- issue market) . While this is perhaps a clean measure of auction underpricing du e to winner’s curse , it does not reflect the total cost borne by the Treasury Department , as o ur previous results suggest that the secondary market prices on auction days have already been driven down by these auctions

. To take into account the price pressure effect resulting from Treasury auctions, we take as the benchmark price the average secondary Treasury market price s around each auction (rather than on the auction day)

. We then calculate the amount of money the Treasury Department could have sav ed were it able to issue Treasury notes at this benchmark price

. We n ote that t his is likely a conservative estimate since the auctioned securit y will become “on

- the

- run” in several days and should be worth more than the

soon
- to

- be

- off

- the

- run security in the secondary market , as suggested by the well

- known

on
- the

- run
- off

- the

- run phenomenon (e.g., Amihud and Mendelson (1991), Krishnamurthy (2002)). Table IV shows that Treasury issues notes at yields that are significantly higher than those in the secondary market. Panel A report s Y ( A )

− Y � ( t ) , where Y ( A ) is the12 auction yield and Y � ( t ) is the average of the on
- the

- run note yield s on the t th d ay before and t th d ay after the auction, w ith t ranging from 1 to 10. The results suggest that auction yields are significantly higher than yields in the secondary market around auctions

. Take 2

- year notes , for example: the yield difference measure, Y ( A )

− Y � ( t ) , for t = 1, 5, and 10

are 3

. 63 ( t =5.77) , 4.90 ( t =4 .62 ), and 5.05 ( t =3.42) basis points, respectively

. The results are similar for 5

- and 10

- year notes. For t equal to 5, the yield difference is 4.04 ( t =4.70) basis points for 5

- year notes and 2.66 ( t =3.12) basis points for 10

- year notes. Based on these yield differences, w e further compute the implied cost borne by the Treasury Department both as a fraction of total issuance size and in dollar terms. As shown in Panel B , based on the yield difference for t=5, the issuance cost s f or 2

- , 5

- , and 10

- year note s are 9.07, 16.81, and 18.43 basis points of the au ction size , respectively. These figures translate into large dollar amounts. For 2007 , the last full year in our sample, the implied total cost of issu ing Treasury notes amounts to $649 million. Based on the yield difference Y ( A )

− Y � ( t ) , for t ≥ 8, the implied costs are well above $7 00 million.
While i t is by no means clear how part of the above estimated issuance cost can be saved through better designs of the Treasury issuance mechanism, recognizing this cost is undoubtedly a n essential first step to assess and improv e the efficiency of the mechanism. Motivated by our empirical results, Jin and Yan (2011) analyze a model of security issuance when issuance has a price impact in the secondary market. In particular , they analyze the potential benefits and costs when the seller increases the frequency of auctions and hence reduce the lumpiness of the supply shocks.
A.2. Trading profit s The documented return pattern around Treasury auctions also impl ies potentially large trading profits . For example, to take advantage of the price movements around 2

- year note auctions that happen almost every month in our sample , one can short the on

- the

run 2

- year note in the t days before each auction , and long a duration

- matched portfolio comprising the on

- the

- run 6

- month T

- bill and 10

- year note t o hedge out the interest rate risk

. The n one can switch to the reversed positions , long the 2

- year note and short the 6

- month bill and 10

- year note, in the t days after the auction

. As shown in Table V, t his simple long

- short portf olio generates significant profits. Panel A reports the results based13 on the full sample

. T he portfolio return is significant and positive for all t ranging from 1 to 10, with 9 out of the 10 return estimates being significant at the 1% level. For t =10, for instance, the average return of th is trading strategy is 8.62 ( t =3.65) basis points , with a n annualized Sharpe ratio of 1.08. For reference , the Sharpe ratio s for currency carry trade s and stock price m omentum are around 0.59

- 0.95 and 0.47

- 0.75 , respectively (s ee, e.g., Brunnermeir, Nagel, and Pedersen (2009), Lustig, Roussanov, and Verdelhan (2009) and Asness, Moskowitz, and Pedersen (2008)).

T he strategy requires large turnover: one needs to complete two “round trips” each month for both their long and short positions , and hence to pay twice the bid

- ask spread s
. T o examine whether transaction cost s have a material impact on the documented trading profits, we start by exploiting time

- series variations in bid

- ask spread s in our sam ple period

. We estimate from the CRSP dataset that t he average bid

- ask spread for 2

- year on
the

- run note s drops from 9 basis points in the first 10 years of our sample to 1.7 basis points in the last 10 year s , a general trend consistent with prior evidence based on various data sources (e.g., Amihud and Mendelson (1991) , Jegadeesh (1993), Fleming (2003))

. If trading costs play a significant role in explaining our return pattern , we would expect to observe a decreasing trend in the profitability of th is stra tegy. However, as shown in Panel B of Table V, t he average return s to our simple strategy in the last 10 years of the sample are similar in economic magnitude to those based on the full sample , and with a much higher Sharpe ratio

. Take t =10 , for example : the annualized Sharpe ratio of the strategy in the last 10 years is 1.44 , compared with 1.08 achieved in the full sample.
To more directly assess the Sharpe ratio net of transaction cost s , we take bid

- ask spread estimates from Fleming (2003), who calculat es daily interdealer bid

- ask spreads for

on
- the

- run Treasury securities using firm/market quotes from GovPX for the period of December 1996 to March 2000. 19 Based on these estimates, the overall bid

- ask spread for our long

- short portfolio is 1.46 basis points. 20 Since our trading strategy requires two

19 It has been noticed that the CRSP indicative bid

- ask spread data has various problems, especially for the early sample period (see, e.g., Duffee (1996)).

20 Fleming (2003) shows that the average bid

- ask spread s for 10

- year, 2

- year , and 6

- month Treasury securities are 2.44, 0.66, and 0.37 basis points , respectively. According to our duration estimates, the hedge portfolio has 20% in 10

- year note s and 80% in 6

- month T

- bill s
. T hus the bid

- ask spread for the whole portfolio is 0.66+2.44 × 0.2+0.37 × 0.8=1.46 basis point s .14 round trips each month, the total transaction cost is 35.04 (=1.46 × 2 × 12 ) basis points per year. In other wo rds, after taking into account transaction costs, the Sharpe ratio of the strategy is still as high as 0.95 during the last 10 years of our sample

. A.3. Implication s for theoretical models The large Sharpe ratio of our trading strategy calls for a search for additional risk factors that the strategy may be exposed to and , perhaps more likely, t he trading frictions beyond bid

- ask spread s (e.g., the cost of shorting Treasury securities) that may prevent arbitrageurs from exploit ing this opportunity. Moreover, the large swings in Treasury returns between the pre

- and post

- auction periods pose a significant challenge to asset

- pricing models

. Our most conservative estimate, based on the entire 20

- day window around each auction , implies an increase in annualized expected 2

- year note return by 2.3% from the pre

- auction to post

- auction period. For re ference, the average 2

- year note return premium (over 3

- month T

- bill returns) is 1.4% in our sample. This result is hard to explain by existing asset

- pricing theories, especially g iven the recurring natur e of this phenomenon

. B. Robustness The phenomenon documented here is not unique to on

- the

- run securities

. As shown in the lower row of Figure 1 , t he yield pattern for off

- the

- run notes is almost the same as that for the on

- the

- run securities. We repeated the analysis in Tables II and III for off

- the

- run

n otes and get very similar results

. W e also conduct a number of additional tests to examine the robustness of our results . First, we repeat our analysis on three subsamples : 1980

- 1990, 1991

- 2000, and 2001

- 2008

. The main results hold for all subsamples and appear to be stronger for the more recent two decades

. Second , since auction s usually take place in the middle of a day , it is unclear whether the return on the auction day itself should be classified as pre

- auction or p ost

- auction. We repeat our analysis by excluding auction day returns and the results are by and large unchanged . Finally, since Treasury securities accumulate interest payments on each calendar day (rather than trading day), we accordingly adjust for the e ffect of weekends and holidays on our return pattern s . The results , omitted for brevity, are virtually identical to those reported in Tables II and III.15 V. Interpretations
It seems natural to try to link this phenomenon to the information contents in auctions. Although the date and amount of auctions can be almost perfectly anticipated, auction outcome s , such as the bid

- to

- cover ratio and coupon rate , are likely to be informative signal s about the Treasury markets and the overal l economic conditions

. I f the uncertainty about auctions is resolved gradually during the days leading to these auctions, we should expect that the average Treasury returns before auctions be higher than those after . This prediction, however, is opposite t o what we find in the data

. A more plausible interpretation is that Treasury auctions exert significant temporary price impact s in secondary Treasury markets. A telltale sign of this interpretation is that there is a strong return reversal in Treasury returns around a u ctions

. For the portfolio examined in Table V, for example, the correlation between the 10

- day pre
- a u ction return and the 10

- day post

- a u ction return is 0.22, with a p
- value of 0.002. This implies return reversal in 2

- year note s since the strategy is short in the 2

- year note before auctions, but is long in the 2

- year note after auctions. More precisely, our interpretation has two ingredients

. First, primary dealers have limited risk

- bearing capacity. In the U.S. Treasury market , primary dealers are expected to pa rticipate actively in all auctions and submit meaningful bids. Put differently , primary dealers are expect ed to acquire large positions in the se auctioned securities. Due to limited risk

- bearing c apacity, the dealers need to hedge this to

- be

- acquired large exposure by sho r t ing similar securities in the secondary Treasury market as well as shorting in the when

- issued market

. Th ese short

- selling activities exert significant downward pressure on secondary market prices

. 21
The second ingredient of our interpretation is that end

- investors in Treasury markets are likely constrained from providing liquidity instantly. This point is particularly important since a large amount

– relative to auction size

– of Trea sury securities are also maturing around auctions , indicating that end

- investors indeed have enough capital to

21 Primary dealers’ short selling in the when

- issued market can also depress spot Treasury prices, if the counterparties with long positions in the when

- issued marke t hedge their exposure in the secondary Treasury market.16 absorb the supply shock from these auctions . For primary dealers’ shorting activities to have a ny significant price impact , end

- investors’ capital has to be slow moving. Our interpretation has a number of further implications, which we explore next.
A. Limited r isk

- bearing c apacity Primary dealers’ limited risk

- bearing capacity has the following two additional predictions. First, given the similarities among Treasury notes across maturities, the price pressure resulting from Treasury auction s of one maturity should naturally spill over to Treasury securities with different maturities, and this impact should be stronger if the maturity di fferen tial is smaller. Second, the price impact of Treasury auctions should be stronger when the total risk expected to be acquired by primary dealers is higher; for instance, when the auction size is larger and in periods with higher implied Treasury retu rn volatilities.
To test the first prediction , we examine the yield patterns of 10

- year notes around 2

- and 5

- year note auctions

. We explicitly exclude observations where there is a 10

- year note auction within 10 days of a 2

- or 5

- year note auction, to ensure that we are not picking up the effect of own auctions. 22 Consistent with our prediction , Table V I show s that an inverted V

- shaped yield pattern also arises for 10

- year notes around 2

- or 5

- year note auction s
. 10

- year note yields increase significantly before both 2

- and 5

- year note auctions and decrease after ward . Not surprisingly , because of the large difference in maturity between 2

- year and 10

- year notes, the yield change resulting from 2

- year note auctions is small, hovering around one basis point , and is statistically significant in only a few days surrounding auction day s
. In contrast , 5

- year note auctions have a much stronger impact on 10

- year yields

. T he m agnitude of the impact is around 3 basis points , and 6 out of the 10 point estimates are significant at the 5% level

. In test ing the second prediction , w e conduct a simple time

- series regression

. T he dependent variable is the cumulative return of the long

- short portfolio defined in Table V during the 20

- day wi ndow around auctions , which is meant to measure the price impact of

22 This requirement significantly limits our potential choices of combinations. For example, we cannot examine the yield patterns of 2

- year notes around auctions of 5

- and 10

- year note auctions, as there are only a small number of 5

- and 10

- year note auctions that are not within one week of any 2

- year note auction.17 Treasury auctions

. The independent variables include the offeri ng size and Treasury options implied return volatilities , both of which reflect the risk primary dealers are expected to acquire at auctions

. W e use Mueller, Vedolin , and Yen (2011)’s model

- free estimates of maturity

- weighted average implied volatilities of nearest

- to

- expiry at

- the

money options on the 30

- year, 10

- year, and 5

- year Treasury securities at the end of the previous month

. The results are similar if we use different weights (e.g., equal weights). We also include year fixed effect s to de

- trend offering size. T he r esults are summarized in Table V II

. Consistent with the prediction , we find that the price impact of Treasury auctions is substantially more pronounced when the offering size is larger and when the Treasury market is more volatile. Specifically, as shown in Panel A , the coefficient estimate on offering size is 4.58 ( t =1.71) and that on the implied volatility is 1.68 ( t

=2.28)

. In other words, one
- standard

- deviation increase s in offering size and Treasury options implied volatility lead to 1.79 ( = 4.58 × 0.39) and 2.94 ( = 1.68 × 1.75) basis points increases in the long

- short portfolio return.
The marginal significance of offering size is likely due to the fact that auctions of other maturities also occur in the vicinity of 2

- year note auctio ns
. For instance, in a large part of our sample, there is a 5

- year note auction within a few days following each 2

- year note auction. D ue to the across

- maturity spillover effect ( Table V I ) , these 5

- year note auctions can mitigate (or sometimes strengthen) the price impact of 2

- year note auctions

. To better capture the price effect of Treasury auctions of all maturities , we construct a measure of “offering size imbalance , ” OSI ( t ) , which is defined as the logarithm of the aggregate offering amount from all Treasury note auctions of any maturity during the t days prior to the day in question ( i.e., day 0) minus that during the t days following day 0

. The idea is that if more Treasury securities are auctione d in the next few days, the price pressure implies a low return today. On the other hand, if more securities are auctioned in the previous a few days, the recovery from that price pressure implies a high return for today. That is, our price pressure interp retation implies a positive coefficient on OSI ( t )

. To address time variation s in expected bond returns, we use the daily 2

- year note return minus the average 2

- year return in the surrounding 20 day s as the dependent variab le. 23

23 Alternatively, we also use unadjusted daily return s as the dependent variable with and without month

fixed effect s
. The results remain similar.18 Consistent with our prediction , as shown in Panel B, the coefficient s estimates on OSI ( t ) are significant ly positive

. F or example, the coefficient is 0. 0 29 ( t =2.79) for OSI ( 5 ) , and 0. 0 46 ( t = 3.83 ) for OSI ( 10 )

. Put differently, an increase in OSI ( 5 ) by the average size of a 2

- year note auction (i.e., $20 billion) is associated with an increase in daily 2

- year note returns of 0.69 (=0.029 × log(20B)) basis points

. Taken together, the evidence lend s further support to our hypothesis that, due to limited risk

- bearing capacity, primary dealers hedge the risk they are expected to acquire at auctions by short selling similar securities , and thus causing downward price pressure in secondary market s before auctions

. In addition, such price impact is more pronounced for Treasury securities with closer maturities to those auctioned securities , when the auction amount is larger, and when Treasury markets are more volatile

. B. Slow

- moving e nd

- investors The second ingredient in our interpretation is end

- investors’ slow responses to transitory yield changes in the Treasury market. Major investors in Treasury markets are indeed likely to be unresponsive to transient demand/supply shocks. According to data compiled by the Treasury Department , although the to tal size of the Treasury securities outstanding is around $10 trillion toward the end of our sample, over 40% of them are nonmarketable and held by Federal Government accounts

. The Federal Reserve holds another 8% to 9% of outstanding Treasury securities, most of which is obtained through noncompetitive bid s at auctions. Given the mandates of the Federal Reserve, it is unlikely that either would respond to transient movements in Treasury yield s
. “Private holdings” account for the rest , of which s tate and lo cal governments and f oreign investors hold more than half

. While there are no publicly available data on these investors’ trading behavior , it seems reasonable to expect that many of them do not have the intention, or resources, to adjust their positions on a daily basis to exploit the opportunity from transitory price movements. In addition, we have two pieces of further evidence on the slow responses of two other major investors in Treasury securities. First, insurance companies collectively hold about $ 1 60 billion of Treasury securities at the end of our sample , which amounts to 3.3 % of the private holdings. W e gather data on their trading and holding s from Schedule D of19 their reports to National Association of Insurance Companies (NAIC). Our analyses suggest that insurance companies trade very infrequently in the Treasury market . For example, close to 70% of all insurance companies make less than five trades , and in any given year , around 14% of them do not make any trade. While this finding is consist ent with insurance companies’ general objective to maintain a low turnover , it suggests that insurance companies are unlikely to absorb sudden supply changes in the Treasury market

. Second, w e also examine the behavior of bond mutual funds. At the end of our sample, b ond mutual funds collectively hold close to 500 billion dollars ’ worth of Treasury securities, which accounts for around 10 % of all private holdings

. Index bond mutual funds are likely to avoid newly issued securities due to concerns of tracki n g errors. Many fixed

- income indi ces usually adjust their composition at the end of each month. As a result , index bond mutual fund managers are likely to be reluctant to purchase the new securities before they are included in the indices they are tracking

. In other words, rather than exploiting the yield changes around auctions, index fund might be part of the cause of the phenomenon

. For active bond mutual funds, while we do not directly observe their trading, we gauge their ability to absorb sudden increase s in Treasury supply by examining their capital flow patterns around Treasury a uctions

. Specifically, we obtain a daily series of total net assets and investment returns for three fund classes

– bond funds, equity funds, and hybrid funds (which inv est in both bonds and equities) , from TrimTabs. We then compute the daily investment flow to each fund class in day t as the percentage change in total net assets from t

- 1 to t , after adjusting for the investment return in day t

. Similar to the tests for b ond return patterns around auctions , we compare the difference between the cumulative capital flow to each fund class dur in g the t days subsequent to an au ction and the cumulative flow during the t days prior to the auction. W e focus on 2

- year Treasury note auctions in this test since the flow data are not availab le before 1998 and there are too few observations for other maturities in the post

- 1998 period.
T he results are shown in Table V II I. Columns 1 and 2 present the flow pattern for bond mutual funds around 2

- year note auctions. Overall, t here are significantly larger capital inflows to bond mutual funds after Treasury auctions than before these auctions.20 The difference in cumulative cap ital flows to bond funds keeps drifting up ward after the auction day and peaks on days 9 and 10. D uring the 10 days after a 2

- year note auction, the cumulative capital inflow to bond mutual funds is about 16 ( t =3.0 2) basis points higher than that during th e 10 days prior to the auction. For reference, the average daily flow to bond mutual funds in our sample period is only 0 .4 basis points each day

. The evidence that investors move their capital into bond mutual funds at a higher rate after Treasury auctions than before these auctions suggests that mutual fund investors are slow in reallocating their capital across asset classes , perhaps due to limited attention. 24 Consistent with this view, i n f urther analyses , we find that capital flows to equity and hybrid mutual funds after auctions are generally lower than those before auctions , albeit with marginal statistical significan ce
. VI. The Impact on Repo Markets Our interpretation also implies that auctions may exert a large impact on the repo markets. Recall that, anticipating the large positions that they will assume at auctions, primary dealers would short in the secondary market to hedge the risk. T o take short positions, they need to borro w Treasury securities through “reverse repo” transactions, which is essentially primary dealers lending cash to their counterparties and taking Treasury securities as collateral , so they can sell those Treasury securities short. From the perspective of the ir counterparties, th ese are repo transaction s . Naturally, p rimary dealers have stronger incentives to initiate these reverse
- repo transactions shortly before Treasury auctions than in other periods

. As a result , they would be willing to accept lower interest rate s in these transactions , leading to lower repo rates before auctions. Moreover, since this hedging activity is expected to last only for a few days, the impact should be stronger f or overnight repo rates than for long

- term repo rate s
. To test this idea, we obtain daily data on overnight, one

- week, and one

- month repo rates from Bloomberg. Since our prediction is that repo rates decrease before auctions due to the scarcity of Treasury security collaterals, our analysis is focused on general

- collateral

24 The evidence does not pin down how investors are attracted to bond mutual funds after auctions. It could be that investors have more expos ure to media coverage about Treasury securities around auctions, which induces them to i nvest. Alternatively, some institutional investors may prefer to keep a low turnover and adjust their positions infrequently. The higher yields around auctions can only attract these institutional investors slowly over time.21 repo rates, which are the interest rates in repo contracts backed by Government General Collaterals. Since t he repo data are available only for the post

- 1992 period, we center our analysis around the most frequent 2

- year note auctions for statis tical power reasons
. W e compare the average repo rates after 2

- year note auction s with those before. The results are reported in Table I X

. Consistent with our prediction, repo rates in the p re
- auction period are significantly low er than those in the p ost

- auction period

. For example , as shown in c olumn s 1 and 2 , the average overnight repo rate during the 10 days before auctions is, on average, 3.47 basis points lower tha n during the 10

- day period after the auctions, with a t

- statistic of 2.21. This rate di fferential is positive for the entire 20

- day window around auction days and reaches its maximum on day 5, with a point estimate of 6. 75 basis points and a t

- statistic of 4.83

. There is a similar but slightly weaker pattern in one
- week term repo rate s ( c olumns 3 and 4) . For example, the average 5

- day p re
- auction one
- week rate is 4. 39 ( t =4.36) basis points lower than that during the post

- auction 5

- day period. T his pattern almost completely disappears for one

- month term repo rates , for which most of the point estimates are indistinguishable from 0 . Th ese results are consistent with the hypothesis that primary dealers hedg e their risk in the a few days before Treasury auctions, and thus driv e down short

- term repo rates. We also repeat our analysis on rever se repo rates. Since t he relationship between repo and reverse repo rates are similar to that between bid and ask prices , the results based on reverse repo rates , omitted for brevity, are almost identical to those based on repo rates

. VII. The Impact on Stock Returns
M ore broadly, since Treasury yields are the basis for pricing assets in other financial markets, and given the magnitude of fluctuations in Treasury yields around auctions , one may expect these Treasury auctions to also significantly affect the pri ces in other markets, such as the U.S. equity market. We examine three market indices : the value

- weighted CRSP index , the equal

- weighted CRSP index , and t he value

- weighted S&P 500 index

. For each index , w e compute ∆ CR ( t ) , the cumulative market return during the t days after each auction minus that during the t days before the auction. The results are reported in Table X

. Column s 1 and 2 present the average of ∆ CR ( t ) based on the value

- weighted CRSP index around 2

- year Treasury note auctions

. ∆ CR ( t ) is significantly positive f or all22 t ranging from 4 to 9 , and peaks on day 6

. For example , ∆ CR ( 5 ) is 49 ( t = 3

. 11) basis points ; that is, the cumulative CRSP value

- weighted market return in the 5 days after a 2

- year Treasury note auction is , on average, 49 basis points higher than that during the 5 days before these auctions. This is a substantial difference since the unconditional expected return of the value

- weighted CRSP index is 4.45 basis points per day

. In other words, the annualized expected return in the 5 days before each auction is

- 1.1% , while that based on the 5 days after an auction is 23.4%. This return pattern is similar for equal

- weighted CRSP returns , as reported in columns 3 and 4. Interestingly, this return pattern also arises for the value

- weighted S&P 500 index ( c olumns 5 and 6 ) , suggesting the observed phenom en on is not driven by small stocks only.
Th e stock return effect documented here is not specific to 2

- year note auctions. In unreported analysis, we find a similar stock return pattern around 5

- year note auctions

. but due to substantial reduction in sample size, the estimate based on 10

- year auctions is statistically insignificant. To analyze the price impact resulting from T reasury auctions of all maturities simultaneously , we conduct a similar analysis to that reported in Panel B of Table V II

. Specifically, we regress excess daily stock market returns on offering size imbalance . Our results, omitted for brevity, show that stock returns tend to be higher (lower) if more Treasury notes are auctioned in the previous (subsequent) 5 to 10 days. We also consider a number of alternative explanations for the stock return pattern. First, one might sus pect that the higher post

- auction returns are compensation for higher volatility. However, w e find that stock market returns , based on all three market indices,

are slightly more volatile before Treasury auctions than after , thus inconsistent with this hyp othesis. In addition, our findings can not be attributed to previously known calendar

time return effects such as turn

- of

- the

- month and turn

- of

- the

- year effects. W e exclude all Treasury auctions from our analyses that take place between the 25 th of a month to the 5 th of the following month , or in the first or last month of a year , and the results are very similar.
One possible interpretation of our finding is that the temporary drop in Treasury prices before auctions induce s some investors, such as asset allocation mutual funds and hedge funds, to move their capital from th e equity market to the Treasury market. Such23 cross
- market arbitrage trades can then lead to a temporary price effect in the equity market. While d irect tes ts of this mechanism , which require detailed daily trading data of hedge funds and mutual funds in both markets, are not feasible, we provide some circumstantial evidence consistent with this hypothesis

. In unreported analysis , we find that the stock return pattern is substantially stronger among stocks with higher idiosyncratic volatilities, higher effective bid

- ask spreads, and higher institutional ownership. While this interpretation is potentially consistent with our findings, the exact underlying mechanism for such a large price impact remains unclear.
VIII. Conclusion Our empirical evidence suggests that anticipated and frequently repeated supply shocks such as Treasury auctions can have first

- order impact s on the secondary T reasury , repo , and equity ma rket s
. These results suggest significant issuance costs borne by the Treasury Department , which are an order of magnitude larger than the estimated auction markups in prior literature. F or instance, the esti m a ted cost of issuing T r easury notes alone is over half a billion doll a rs in 2007. Our results further call for theoretical and empirical studies to analyze and improve the efficiency of the Trea sury security

- selling mechanism in settings in which anticipated supply shocks can affect market prices.
Ou r results also pose significant challenges to existing asset

- pricing theories and suggest that market frictions are playing an important role even in the most liquid and well

- developed financial markets . Hence, explicitly modeling the risk

- bearing capacity of broker

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– 608.26 Table I

. Summary Statistics Panel A reports the summary statistics of Treasury note a uctions

. Maturity is the number of years to maturity of a Treasury note . Under A uction T ype , “Multiple” denotes a multiple

- price auction and “ Single ” denotes a single

- price auction. No. of Issues is the total number of issues in our sample

. Amount is the face value issued at each auction. Bid

- to

- Cover Ratio is the ratio of total value bid in an auction to the total face value issued to all competitive bidders. Auction Y ield is the maximum winning yield for a single

- price auction, and is the weight ed

- average yield based on the amount issued at each winning yield for a multiple

- price auction

. Panel B reports the summary statistics for Treasury notes and stocks. d aily return is the change in daily price levels including coupon distributions. duration is the modified duration (expressed in years) of the on

- the

- run security on the subsequent auction day

. vwght daily return is the value

weighted portfolio return, and ewgh t daily return is the equal

- weighted portfolio return

. The sample period for Panels A and B is January 1980 to June 2008

. Panel C reports the summary statistics for other data. Treasury options implied volatility is the model

free maturity

- weighted implied volatility of nearest

- to

- expiry at

- the

- money options on the 30

- year, 10

- year, a nd 5

- year Treasury securities from January 198 2 to June 2008

. daily flow is the daily percentage flow to mutual funds from January 1998 to June 2008

. The sample period for repo rates is from January 1992 to June 2008

. Yields, returns , and daily flows are expressed in basis points.

Panel A: Summary statistics of Treasury auctions (1980

- 2008) Maturity Auction No. of Amount ($ Billions) Bid

- to

- Cover Ratio Auction Yield (%) Type Issues Mean Std ev Mean Std ev Mean Std ev 2 Multiple 150 10.13 3.24 2.68 0.56 9.26 2.59 2 Single 182 22.93 6.21 2.61 0.4 5.09 1.28 2 Total 332 17.13 8.16 2.64 0.48 6.36 2.62 5 Multiple 64 7.66 2.41 2.78 0.49 8.78 2.61 5 Single 146 14.83 2.84 2.57 0.38 4.68 0.66 5 Total 210 12.64 4.27 2.63 0.43 7.01 2.86 10 Multiple 75 9.92 3.65 2.44 0.34 7.76 3.19 10 Single 57 13.03 4.01 2.38 0.43 5.29 0.64 10 Total 132 11.27 4.1 2.41 0.38 7.57 3.1427 Panel B: Summary statistics of Treasury notes and stocks (1980

- 2008) Variables Mean Standard Deviation 25 th Median 75 th Summary statistics of Treasury note returns (basis point) daily return (2

- year) 2.85 16

. 24

- 4.24 2.34 9.63 daily return (5

- year) 3.33 34.48

- 13

. 65 3.08 20.58 daily return (10

- year) 3.36 49

. 75

- 23.16 3.33 30.45 Summary statistics of Treasury note durations (year) duration (2

- year) 1.78 0.07 1.74 1.79 1.83 duration (5

- year) 4.16 0.27 4.04 4.19 4.34 duration (10

- year) 6.98 0.88 6.40 7.07 7.74 Summary statistics of stock returns (basis point) CRSP vwght daily return 4.45 105.70

- 42.39 7.71 54.01 CRSP ewght daily return 8.15 82.99

- 24.17 14.52 47.10 SP500 vwght daily return 3.53 111.69

- 48.26 4.81 56.90

Panel C: Other data Summary statistics of Treasury options implied volatilities ( % ) (19 82

- 2008) Implied Volatility 8

. 00 1

. 75 6.99 7.75 8.82 Summary statistics of daily mutual fund flows (basis point) (1998

- 2008) daily flow to bond funds 0.40 15.31

- 3.24

- 0.02 3.33 daily flow to equity funds

- 0.92 10.27

- 5.09

- 1.72 1.87 daily flow to hybrid funds

- 0.19 11.06

- 3.95

- 0.06 3.49 Summary statistics of General Collateral Repo rate s ( % ) (1992

- 2008)

o ver night 3.97 1.63 2.90 4.49 5.31

o ne w eek 3.96 1.63 2.92 4.53 5.30

o ne m onth 3.97 1.63 2.90 4.52 5.3028 Table II

. Treasury Yields A round Subsequent Auctions This table reports the time

- series average of Y ( t )

− Y ( 0 ) , which is the yield of an on
- the

run n
- year Treasury note ( n =2,5,10) on day t (where t ranges from

- 10 to 10) minus the yield of the same note on the day when a subsequent n
- year note auction is conducted

. (More precisely, the note is on

- the

- run before the auction and becomes off

- the

- run after the auction.) T he sample period is from January 1980 to June 2008. All y ields are expressed in basis points. T

- statistics are based on standard errors that are Newey

- W est adjusted up to 12 lags , and are reported in parenthese s. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively.

T reasury yields around subsequent auctions : Y ( t )

− Y ( 0 ) 2

- year notes 5

- year notes 10

- year notes t Mean t

- v alue Mean t

- v alue Mean t

- v alue

- 10

- 1.16 (

- 0.59)

- 2.68 * (

- 1.87 )

- 0.79 (

- 0.39 )

- 9

- 1.82 (

- 0.98)

- 2.50 (

- 1.6 0)

- 2.14 (

- 1.21 )

- 8

- 2.86 (

- 1.5 0 )

- 3.35** (

- 2.43 )

- 1.64 (

- 0.95 )

- 7

- 3.04* (

- 1.68)

- 2.61* (

- 1.95 )

- 0.10 (

- 0.06 )

- 6

- 2.64* (

- 1.83)

- 2.07 (

- 1.54 )

- 1.03 (

- 0.71 )

- 5

- 2.53* (

- 1.5 0 )

- 2.67** (

- 2.5 0)

- 1.57 (

- 1.11 )

- 4

- 2.81* (

- 1.77)

- 2.96*** (

- 3.08 )

- 2.76* * (

- 2.02 )

- 3

- 3.01** (

- 2.21)

- 1.56* (

- 1.8 0)

- 2.25* * (

- 2.04 )

- 2

- 2.06** (

- 2.03)

- 0.64 (

- 1.14 )

- 0.41 (

- 0.52 )

- 1

- 1.77*** (

- 3.18) 0.30 ( 0.67 )

- 0.78 (

- 1.2 0) 1

- 0.36 (

- 1.11)

- 0.77 ** (

- 2.02 )

- 0.56 (

- 1.21 ) 2

- 0.67 (

- 1.09)

- 1.74*** (

- 2.88 )

- 1.23 (

- 1.4 0) 3

- 0.87 (

- 0.97)

- 2.46*** (

- 2.97 )

- 1.87 * (

- 1.7 0) 4

- 1.92* (

- 1.94)

- 1.96** (

- 2.37 )

- 2.01 (

- 1.62 ) 5

- 2.32* * (

- 2.18)

- 2.74** * (

- 2.63 )

- 2.00 (

- 1.51 ) 6

- 3.19** (

- 2.61)

- 2.11 (

- 1.58 )

- 1.48 (

- 1.32 ) 7

- 2.93* * (

- 2.14)

- 2.75 (

- 1.58 )

- 2.78 * (

- 1.7 0) 8

- 2.77 (

- 1.6 0 )

- 3.41** (

- 2.1 0)

- 3.42* (

- 1.9 0) 9

- 3.19* (

- 1.74)

- 3.09* (

- 1.95 )

- 4.47** (

- 2.07 ) 10

- 3.91** (

- 2.13)

- 2.95* (

- 1.88 )

- 4.68** (

- 2 .00) No. Obs. 332 210 13229 Table III

. Treasury Returns A round Subsequent Auctions This table reports the time

- series average of ∆ CR ( t ) , which is the cumulative return of

an on
- the

- run n
- year Treasury note ( n =2,5,10) during the t days after a subsequent n
year note auction minus the cumulative return of the same n
- year note during the t days before the auction, where t ranges from 1 to 10. (More precisely, the note is on

- the

run before the auction and becomes off

- the

- run after the auction.) The sample period is from January 1980 t o June 2008. All r eturns are expressed in basis points. T

- statistics are based on standard errors that are Newey

- West adjusted up to 12 lags, and are reported in parentheses . ***, **, and * indicate significance levels of 1%, 5%, and 10%, respective.

Treasury note returns around subsequent a uctions : ∆ CR ( t ) 2

- year notes 5

- year notes 10

- year notes t Mean t

- v alue Mean t

- v alue Mean t

- v alue 1 3.68*** ( 3.9 0) 1.98 ( 0.99 ) 8.61 ( 1.53 ) 2 3.54** ( 2.21 ) 9.94*** ( 4.03 ) 10.87 ( 1.13 ) 3 6.15** ( 2.42 ) 16.86*** ( 4.28 ) 26.37** ( 2.31 ) 4 8.66*** ( 2.87 ) 20.86*** ( 4.34 ) 31.61*** ( 2.75 ) 5 8.89*** ( 2.69 ) 22.54*** ( 3.67 ) 23.84* ( 1.78 ) 6 10.20*** ( 3.62 ) 17.12** ( 2.07 ) 16.44 ( 1.31 ) 7 9.42*** ( 2.63 ) 21.21** ( 2.2 0) 17.44 ( 1.01 ) 8 9.61** ( 2.28 ) 27.59*** ( 3.01 ) 30.4* ( 1.67 ) 9 9.08** ( 2.23 ) 22.85** ( 2.43 ) 40.68** ( 2.02 ) 10 9.20** ( 2.02 ) 22.77** ( 2.53 ) 32.45 ( 1.39 ) No. Obs. 332 210 13230 Table IV

. Cost s of Issuing Treasury Notes Panel A of this table presents the time

- series average of Y ( A )

− Y � ( t ) , where Y ( A ) is the auction yield of the newly issued Treasury notes, and Y � ( t ) is the average of the yield of the on

- the

- run n
- year note ( n =2,5,10) on day t before the subsequent auction and the yield of the same note on day t after the auction , with t ranging from 1 to 10. (More precisely, the note is on

- the

- run before the auction and becomes off

- the

- run after the auction.) The a uction y ield is the maximum winning yield for single

- price auctions, and is the weighted

- average yield based on the amount issued at each w inning yield for multiple

- price auctions

. The sample period is from January 1980 to June 2008. Yields are expressed in basis points. Panel B of t his table presents the estimated cost of issuing Treasury notes. The percentage cost is calculated as the produ ct of Y ( A )

− Y � ( t ) and the duration of the notes and is expressed in basis points . The dollar amount cost is based on the Treasury securities issuance in 2007 , the last full year in our sample , and is expressed in millions

. T

- statistics based on standard errors that are Newey

- West adjusted up to 12 lags , are reported in parenthese s. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively

.

Panel A: Yield difference Y ( A )

− Y � ( t ) 2

- year notes 5

- year notes 10

- year notes t Mean t

- v alue Mean t

- v alue Mean t

- v alue 1 3.63*** ( 5.77 ) 1.58** ( 2.6 3) 1.36* ( 1.84 ) 2 3.90*** ( 5.40 ) 2.52*** ( 3.65 ) 1.52 ( 1.58 ) 3 4.50*** ( 5.07 ) 3.42*** ( 4.36 ) 2.84** ( 2.26 ) 4 4.84*** ( 4.88 ) 3.86*** (4.52 ) 3.19*** ( 3.13 ) 5 4.90*** ( 4.62 ) 4.04*** ( 4.70 ) 2.66*** ( 3.12 ) 6 5.33*** ( 5.98 ) 3.44*** (3. 3 4 ) 2.21** (2.34) 7 5.42*** ( 5.17 ) 3.95*** ( 3.01 ) 2.43* ( 1.65 ) 8 5.38*** ( 4.18 ) 4.69*** ( 3.82 ) 3.59* ( 1.90 ) 9 5.03*** ( 3.82 ) 4.06*** ( 3.41 ) 4.39** (2. 07 ) 10 5.05*** ( 3.42 ) 4.05*** ( 3.59 ) 3.85* (1.71 ) No. Obs. 332 210 13 231 Panel B: Cost s of i ssuance b as ed on the a verage y ield on d ay s
- t and t 2

- year notes 5

- year notes 10

- year notes All notes
t Percentage (basis point s ) Amount (Millions) Percentage (basis point s ) Amount (Millions) P ercentage (basis point s ) Amount (Millions) Amount (Millions) 1 6.72 172 6.57 103 9.42 79 354 2 7.22 185 10.48 164 10.53 88 437 3 8.33 213 14.23 222 19.68 165 600 4 8.95 229 16.06 251 22.11 186 665 5 9.07 232 16.81 262 18.43 155 649 6 9.86 252 14.31 223 15.32 129 604 7 10.03 257 16.43 256 16.84 141 654 8 9.95 255 19.51 304 24.88 209 768 9 9.31 238 16.89 263 30.42 256 757 10 9.34 239 16.85 263 26.68 224 72632 Table V

. Hedge Portfolio Returns This table presents HRet ( t ) , the cumulative return to a hedge strategy from t days before an auction to t days after , where t ranges from 1 to 10 . On the t th day before each auction , we construct a hedge portfolio by going short in the on
- the

- run 2

- year note, and going l ong in a duration

- matched portfolio of the on
- the

- run 6

- month T

- bill and 10

- year note. We hold this hedge p ortfolio until the auction day, and then reverse our positions: We now go l ong in the same 2

- year note (which just becomes the first off

the

- run note ) and go short in the duration

- matched portfolio of the on
- the

- run 6

- month T

- bill and on
- the

- run 10

- year note. We h old this portfolio unti l the t th day after the auction

. The full sample period is from January 1980 to June 2008. Returns are expressed in ba sis points. Sharpe Ratio is the annualized Sharpe ratio for this trading strategy. T

- statistics based on standard errors that are Newey

- West adjusted up to 12 lags , and are reported in parenthes e s. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively

.

Panel A: Hedge portfolio returns HRet ( t ) Panel B: Hedge portfolio returns HRet ( t ) in the full sample (1980

- 2008) in the period of 1998

- 2008 t Mean t

- v alue Sharpe R atio t Mean t

- v alue Sharpe Ratio 1 1.04* ( 1.67 ) 0.34 1

- 0.4 0 (

- 0.47 )

- 0.14 2 2.40*** ( 2.89 ) 0.66 2 1.37 ( 1.6 0 ) 0.5 0 3 4.41*** ( 3.35 ) 0.94 3 2.61*** ( 2.68 ) 0.84 4 4.96*** ( 3.3 0 ) 0.98 4 4.15*** ( 4.01 ) 1.05 5 5.87*** ( 3.1 0 ) 0.95 5 4.78*** ( 3.48 ) 1.06 6 6.39*** ( 3.95 ) 1.05 6 6.85*** ( 4.66 ) 1.32 7 8.17*** ( 4 .0 0 ) 1.2 0 7 8.02*** ( 5.14 ) 1.56 8 8.10*** ( 3.88 ) 1.12 8 7.62*** ( 4.64 ) 1.41 9 8.24*** ( 3.6 0 ) 1.08 9 8.13*** ( 5.08 ) 1.44 10 8.62*** ( 3.65 ) 1.08 10 8.52*** ( 4.95 ) 1.44 No. Obs 319 No. Obs 11633 Table V I

. On

- t he

- Run 10

- Year Treasury Yields A round 2

- and 5

- Year Auctions This table reports the time

- series average of Y ( t )

− Y ( 0 ) , which is the yield of an on

- the

run 10

- year Treasury note on day t (where t ranges from

- 5 to 5) minus the yield of the same note on the day when a subsequent n
- year note ( n =2,5) auction is conducted

. (More precisely, the note is on

- the

- run before the auction and becomes off

- the

- run after the auction.) We exclude 2

- and 5

- year no te auctions that are within one week of any 10

- year note auction. The sample period is from January 1980 to June 2008. All y ields are expressed in basis points. T

- statistics based on standard errors that are Newey

- West adjusted up to 12 lags , and are repor ted in parenthes e s. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively.

10

- year Treasury yields around 2

- and 5

- year note auctions: Y ( t )

− Y ( 0 ) around 2

- year note auctions around 5

- year note auctions t Mean t

- v alue Mean t

- v alue

- 5

- 1.48 (

- 1.50)

- 2.71** (

- 2.26)

- 4

- 1.44 (

- 1.61)

- 2.89** (

- 2.51)

- 3

- 1.41* (

- 1.72)

- 1.57 (

- 1.60)

- 2

- 0.96 (

- 1.63)

- 0.69 (

- 1.00)

- 1

- 1.20*** (

- 2.70) 0.01 (0.01) 1

- 0.74* (

- 1.93)

- 0.22 (

- 0.42) 2

- 0.44 (

- 0.67)

- 2.12*** (

- 2.98) 3 0.23 (0.22)

- 3.08*** (

- 4.18) 4

- 0.68 (

- 0.60)

- 2.31*** (

- 2.90) 5

- 0.8 (

- 0.61)

- 3.22*** (

- 3.00) No. Obs. 275 14434 T able V II

. The Effect of Dealer s’ Risk

- Bearing Capacity and Auction Size This table presents the effect of d ealers’ risk

- bearing capacity and auction size on Treasury security return s around subsequent auctions. T he dependent variable in Panel A , H Ret ( 10 ) , is described in Table V

. Offering Amount is the logarithm of the amount in dollars offered by the Treasury Department in the 2

- year note auction. I mplied V

olatility is the model

- free maturity

- weighted implied volatility of nearest

- to

- expiry at

the

- money options on the 30

- year, 10

- year, and 5

- year Treasury securities at the end of the previous month

. The dependent variable in Panel B is the daily return of on

- the

- run 2

- year Treasury notes, adjusted by the average daily return in the 20

- day windows surrounding it. OSI ( t ) is the logarithm of the aggregate offering amount from all Treasury note auctions of any maturity type during the t days prior to the return date minus that during the t days subsequent to the return date. The sample period is January 1982 to June 2008 for Panel A and is January 19 8 0 to June 2008 Panel B

. T

statistics based on standard errors that are Newey

- West adju sted up to 12 lags , and are reported in parenthese s. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively.

Panel A: Dependent Variable = H Ret ( 10 ) Coefficient ( *100 00 ) t

- v alue Offering Amount 4 .58 * (1. 71 ) Implied Volatility 1 .68 * * ( 2

. 28 )

Panel B: Dependent Variable = daily 2

- year note return Coefficient (*1 0 0 00) t

- v alue Dependent Variable = daily 2

- year note return OSI ( 5 ) 0

. 0 2 9* ** ( 2

. 79 )
Dependent Variable = daily 2

- year note return OSI ( 10 ) 0

. 0 46 ** * ( 3

. 83 )35 Table VIII

. Daily Mutual Fund Flows A round Treasury Auctions This table reports the time

- series average of ∆ FLOW ( t ) , which is the cumulative daily investment flows during the t days subsequent to a 2

- year Treasury note auction minus that during the t days prior to the auction, where t ranges from 1 to 10. The sample period is from January 1998 to June 2008. We examine capital flows to three types of mutual funds: bond mutual fun ds, equity mutual funds, and hybrid mutual funds. T

statistics based on standard errors that are Newey

- West adjusted up to 12 lags , and are reported in parenthes e s. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively.

Mutual fund flows around 2

- year Treasury note auctions: ∆ FLOW ( t ) bond funds equity funds hybrid funds t Mean t

- v alue Mean t

- v alue Mean t

- v alue 1

- 0.03%** (

- 2.22) 0.00% (

- 0.37)

- 0.03%*** (

- 2.60) 2

- 0.02% (

- 1.11) 0.01% (0.52)

- 0.02% (

- 1.58) 3 0.03%** (2.03)

- 0.01% (

- 0.32)

- 0.02% (

- 1.21) 4 0.05%*** (3.01)

- 0.01% (

- 0.55)

- 0.01% (

- 0.73) 5 0.06%*** (3.06)

- 0.02% (

- 0.84)

- 0.03% (

- 1.32) 6 0.14%*** (2.82)

- 0.03% (

- 1.30)

- 0.05%* (

- 1.86) 7 0.15%*** (2.87)

- 0.03% (

- 1.05)

- 0.05%* (

- 1.81) 8 0.15%*** (2.95)

- 0.02% (

- 0.89)

- 0.05%* (

- 1.74) 9 0.16%*** (3.15)

- 0.03% (

- 1.05)

- 0.04% (

- 1.14) 10 0.16%*** (3.02)

- 0.04% (

- 1.29)

- 0.09%** (

- 2.16) No. Obs. 120 120 12036 Table IX

. Repo R ate s A round Treasury Auctions This table reports the time

- series average of ∆ Repo ( t ) , which is the average repo rate during the t days subsequent to a 2

- year Treasury note auction minus that during the t days prior to the auction, where t ranges from 1 to 10. The sample period is from January 1992 to June 2008. All r epo contracts are backed by Government General Collaterals. Repo r ates are expressed in basis points. T

- statistics based on standard errors that are Newey

- West adjusted up to 1 2 lags , and are reported in parenthese s. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively.

Average r epo rate around auctions: ∆ Repo ( t ) Overnight One

- week One

- month t Mean t

- v alue Mean t

- v alue Mean t

- v alue 1 1.38 (0.99) 1.33 (1.50)

- 0.70* (

- 1.65) 2 3.69** (2.39) 2.43*** (2.72) 0.11 (0.27) 3 5.09*** (3.29) 3.78*** (3.84) 0.78 (1.62) 4 6.53*** (4.53) 4.47*** (4.31) 1.11* (1.78) 5 6.75*** (4.83) 4.39*** (4.36) 1.41** (2.03) 6 6.50*** (4.67) 3.94*** (3.80) 1.08 (1.30) 7 5.85*** (4.26) 3.41*** (3.22) 0.81 (0.86) 8 4.85*** (3.49) 2.78** (2.28) 0.43 (0.37) 9 4.13*** (2.79) 2.19 (1.59) 0.11 (0.08) 10 3.47** (2.21) 1.68 (1.10)

- 0.19 (

- 0.12) No. Obs. 198 198 19837 Table X

. Stock Market Returns A round Treasury Auctions
This table reports the time

- series average of ∆ CR ( t ) , which is the cumulative return of the stock market during the t days after a 2

- year Treasury note auction minus the cumulative return of the stock market during the t days before the auction, where t ranges from 1 to 10. T hree types of market returns are examined here : the value

weighted CRSP return, equal

- weighted CRSP return, and value

- weighted S&P500 index return. The sample period is from January 1980 to June 2008. All returns are expressed in basis points. T

- statistics based on standard errors that are Newey

- West adjusted up to 12 lags , and are reported in parenthese s. ***, **, and * indicate significance level s of 1%, 5%, and 10%, respectively.

Stock m arket ret urns around 2

- year note auctions: ∆ CR ( t ) value

- weight ed CRSP equal

- weight ed CRSP value

- weight ed S & P500 t Mean t

- v alue Mean t

- v alue Mean t

- v alue 1

- 0.07% (

- 0.90) 0.04% (0.70)

- 0.10% (

- 1.17) 2 0.03% (0.33) 0.35%*** (4.93)

- 0.06% (

- 0.49) 3 0.16% (1.27) 0.44%*** (4.88) 0.07% (0.54) 4 0.33%** (2.35) 0.39%*** (3.69) 0.28% * (1.86) 5 0.49%*** (3.11) 0.50%*** (4.04) 0.41%** (2.50) 6 0.52%*** (3.03) 0.65%*** (4.71) 0.40%** (2.28) 7 0.48%*** (2.57) 0.79%*** (5.14) 0.32% * (1.68) 8 0.46%** (2.31) 0.73%*** (4.19) 0.30% (1.49) 9 0.45%** (2.19) 0.65%*** (3.52) 0.31% (1.46) 10 0.29% (1.30) 0.55%*** (2.71) 0.13% (0.57) No. Obs. 332 332 33238 Figure 1

. Treasury Yields A round Auctions S olid lines in these figures correspond to the time

- series average of Y ( t )

− Y ( 0 ) , which is the yield of the n
- year Treasury note ( n =2,5,10) on day t (where t ranges from

- 5 to 5 ) minus the yield of the same note on the day when a subsequent n
- year note auction is conducted

. (More precisely, the n ote is on

- the

- run before the auction and becomes off

the

- run after the auction.) The dotted lines are the 95% confidence interval. The top three figures are for on

- the

- run Treasury notes, and the bottom three figures are for the first off

- the

- run notes. The sample period is from January 1980 to June 2008. All yields are expressed in basis points.