ࡱ> 23e[  bjbj zjj4lxxxX@```4!!!h!dR"}=#$"$$$&&&<<<<<<<$? %A|"=`&%&&&"=*$$7=***&8$`$<*&<**2r<8TH`8$# 5=!&^88,M=0}=82A&(A8* conditional time-varying interest rate risk premium: Evidence from the TREASURY BILL futures market Alan C. Hess And Avraham Kamara School of Business Administration University of Washington Seattle, WA 98195 June 28, 2002 We thank Jefferson Duarte, Wayne Ferson, Francis Longstaff, Andrew Siegel and participants of the Pacific Northwest Finance Conference for comments. We thank the Chicago mercantile Exchange for kindly providing data. Please direct correspondence to Professor Avraham Kamara, University of Washington Business School, Box 353200, Seattle, WA 98195-3200. Tel. (206) 543-0652; Fax. (206) 685-9392; Email: kamara@u.washington.edu. conditional time-varying interest rate risk premium: Evidence from the TREASURY BILL futures market Abstract Existing studies of the term structure of interest rates often use spot Treasury rates to represent default-free interest rates. However, part of the premium in Treasury rates is compensation for the risk that short-sellers may default. Since Treasury bill futures are default-free they provide cleaner data to estimate the interest rate risk premium. The mean excess return in default-free Treasury bill futures is zero. This suggests that the interest rate risk premium could be economically negligible. We find that although the mean unconditional premium is zero, futures returns contain economically and statistically significant time varying conditional interest rate risk premiums. The conditional premium depends significantly positively on its own conditional variance and its conditional covariance with the equity premium. The conditional premium is large in the volatile 1979-1982 period, but small afterwards. Introduction Do investors receive a premium for bearing interest rate risk? If they do, is the premium constant or does it vary systematically with other economic variables? The pure expectations hypothesis of the term structure says that the risk premium is zero, while the expectations hypothesis says that if there is a risk premium it is constant through time (Campbell 1986). There is empirical evidence that part of the risk premium that researchers have found using spot Treasury rates is not an interest rate risk premium. Much of this evidence comes from the Treasury bill market. Fried (1994) concludes that using the term structure of spot yields alone may be inappropriate in addressing some questions related to the term structure. (p. 70). Kamara (1988, 1997) finds that forward rates implied by secondary market Treasury bill yields contain a premium for the risk that short sellers may default. Consequently, time variation in the spot Treasury term structure results from time variation in both nominal risk-free interest rates and short-sellers default premiums. Longstaff (2000) presents evidence that at the very short end of the yield curve the pure expectations hypothesis holds. He found that the differences between averages of overnight repo rates and term repo rates for maturities of one week to three months were economically and statistically insignificant. Longstaff used repo rates in his study to avoid the liquidity and secondary market default risk premiums that may be in interest rates on spot-traded Treasury bills. In this study we estimate unconditional and conditional term premiums using Treasury bills futures returns. Like Longstaff we avoid counting secondary market liquidity and default risk premiums as term premiums. Futures rates should provide cleaner data for studying the term premium. In contrast to the secondary Treasury market, futures markets have clearing associations that employ safeguards that virtually eliminate default on futures contracts. Telser and Higinbotham (1977)), Edwards (1983), and Brennan (1986) provide theoretical motivation for using futures rates instead of implied forwards rates to avoid the default risk inherent in implied forward rates. MacDonald and Hein (1989) and Kamara (1990) find that Treasury bill futures rates are significantly more accurate predictors of future spot rates than are implied forward rates. Poole (1978) argues that it is probably not necessary to make any allowance for term premiums when using futures rates to gauge market expectations of futures spot rates (p. 63). The mean Treasury bill futures excess return is economically negligible and statistically indistinguishable from zero. Hence, our unconditional tests cannot reject the pure expectations hypothesis, which postulates that term premiums are zero. This contrasts with the term structure literature that uses spot Treasury rates, but is consistent with Longstaffs (2000) findings using repo rates. Zero mean unconditional interest rate risk premiums need not imply that the interest rate risk premium is zero. The conditional interest rate risk premium can vary through time and be nonzero at each point in time, even when the mean unconditional premium is indistinguishable form zero. Hodrick (1987) reports such findings for currency premiums. we investigate conditional one- and two-factor equilibrium models of the interest rate risk premium. The one-factor model predicts that the interest rate risk premium depends on its conditional variance. Affine models of the term structure (e.g., Cox, Ingersoll, and Ross, 1985) suggest that the term premium is positively related to interest rate volatility. Fama (1976), Shiller, Campbell, and Schoenholtz (1983), Engle, Lilien, and Robins (1987), and Klemkosky and Pilotte (1992), among others, document empirically that the interest rate risk premium in spot Treasury rates is related to interest rate variance. Our conditional two-factor equilibrium model, which is motivated by CAPM-based models with non-tradable claims (Mayers 1972; Stoll 1979; and Hirshleifer 1988) and an intertemporal capital asset pricing model (Merton 1973), postulates that an assets risk premium also depends on its conditional covariance with the equity market risk premium. We design our empirical tests so that the futures risk premium and the term premium are identical. We find that futures returns contain a significant time varying conditional interest rate risk premium that depends positively on its conditional variance. In the two-factor model, the premium also depends positively on its conditional covariance with the equity premium. Longstaff (2000) tests 1-day to 3-month term premiums, whereas we test 3-6 months term premiums. We find, similar to Longstaff, that our unconditional tests support the pure expectations hypothesis. However, unlike Longstaff, our conditional tests reject the expectations hypothesis theory of the term structure. Our conditional tests also reject the affine models of the term structure of Vasicek (1977) and Cox, Ingersoll, and Ross (1985). Our results also shed light on the wider debate about whether commodity and financial futures prices contain risk premiums. Studies of futures markets, for example, Dusak (1973), Carter, Rausser and Schmitz (1983) and Bessembinder (1992) reach conflicting conclusions regarding the existence of risk premiums in futures prices. We find that the conditional premiums in Treasury bill futures prices are substantial in 1979-1982 a period of very volatile interest rates, but are small afterwards. Section 2 presents our empirical results and Section 3 our conclusions. 2. Empirical evidence The Treasury bill futures contract calls for delivery of a 3-month (13-week) Treasury bill with one million dollars face value. We study the excess return on a long position in the Treasury bill futures contract over a quarterly horizon that begins exactly 13 weeks before the futures delivery day and ends on the futures delivery day. It is important to notice that we design our tests such that our investment period always ends on the futures delivery date. Consequently, the uncertainty for our investors comes entirely from uncertainty regarding the interest rate on the spot 3-month Treasury bill on the delivery date. This is exactly the uncertainty faced by investors who buy six-month spot Treasury bills 3 months before the futures delivery date, and sell them in the spot market on the futures delivery date. Hence, in our tests, the futures risk premium is also the term premium. This is an important point in our empirical design. To clarify, consider an economy with the following three securities today: Spot 3-month Treasury bills, spot 6-month Treasury bills, and a futures contract calling for delivery, 3 months from today, of one 3-month Treasury bill. Assume that all three securities have a face value of one dollar. Investors who wish to invest for 3 months can choose one of the following strategies: Today, buy spot 3-month Treasury bills at a cost of P3,0 per unit. After 3-months, redeem the bills for their face value. This is the riskless strategy. Let rf denote the rate of return on this strategy. Today, buy spot 6-month Treasury bills at a cost of P6,0 per unit. After 3-months, sell them as 3-month bills for the spot price of P3,1 per unit. The excess return on this strategy is  EMBED Equation.3 . Today, buy one Treasury bill futures contract today with a contract price of F0. After 3-months, pay F0, accept delivery of the 3-month bill, and immediately sell it for P3,1. In addition, because the futures position does not require any initial cash flow, invest today F0 in strategy 1 as well. The excess return on Strategy 3 is  EMBED Equation.3 . The excess return on strategy 2 is one measure of the term premium. The excess return on strategy 3 is the futures risk premium. Strategies 2 and 3 contain the same risk the uncertain price of $P3,1. Hence, when investors hold the Treasury bill futures contract to delivery, the futures risk premium and the term premium are one and the same. 2.1. Data We assembled a sample of spot and futures rates on three-month Treasury bills from 1976 through 1998. The spot rates are bid discount rates from the daily quote sheets of the Federal Reserve Bank of New York. The Treasury bills futures contract, which began trading in 1976, expires on a quarterly basis (March, June, etc.). The futures rates are settlement discount rates on the nearest-maturity futures contracts observed exactly thirteen weeks before their delivery dates. We collected the futures rates from various issues of the International Monetary Market Yearbook and from data kindly provided by the Chicago Mercantile Exchange. Futures contracts are marked-to-market daily. As a result, the Treasury bill futures rate is less than its corresponding forward rate by what is termed a convexity adjustment (see Hull, 1999, p.108). The daily marking-to-market resets the value of the futures contract to zero each day. Consequently, in equilibrium, the futures rate must equal the risk neutral expectations of the underlying spot rate on the futures delivery date (see Grinblatt and Jegadeesh, 1996, for a formal derivation). Our paper tests the expectations hypotheses and the possible risk premium in the Treasury bill futures market. Consequently, the absence of convexity in futures rates actually makes our tests cleaner than tests using forward interest rates. Put differently, the risk premium estimated using forward bill rates includes a convexity bias, whereas the risk premium estimated using futures bill rates does not. This difference could be important when interest rates are volatile because, like the term premium, the convexity bias is related to the variance of short-term interest rates (Campbell, 1986). Let Rfut denote the realized excess rate of return on a long position in the Treasury bill futures contract. Recall that P3,1 denotes the realized 3-month Treasury bill spot price on the delivery day of the futures contract, and F0 denotes todays (13 weeks before the delivery date) futures price. Then, for our quarterly horizon, Rfut = (P3,1 (F0)/F0. 2.2. Unconditional tests Existing term structure studies (e.g., Fama, 1984) document large term premiums in spot Treasury bill rates. However, Poole (1978), Kamara (1998, 1997), Fried (1994) and Longstaff (2000) argue that this is a premium for secondary market default and liquidity risks and not only for interest rate risk. Poole (1978), Kamara (1998, 1997), Fried (1994) advance that Treasury bill futures rates are more adequate measures of interest rate risk premiums. As an unconditional test of the expectations hypothesis, Table 1 shows that the mean, annualized Treasury bill futures excess return is 0.0007 (i.e., 7 basis points) per year, with a t-statistic of 0.42, and a p-value of 0.68. Thus, the mean unconditional interest rate risk premium is economically small and statistically indistinguishable from zero. Stated alternatively, futures rates are unbiased forecasts of future spot rates. Thus, the results of the unconditional test using futures excess returns are consistent with the pure expectations hypothesis. For comparison, Table 1 also shows summary statistics for excess returns on Strategy 2 above, of buying spot 6-month Treasury bills and selling them after 3-months (denoted R6m3). The average excess return is 50 basis points with a p-value of 0.007, which suggests that there is a significant, economically and statistically, positive term premium. Hence, the results of the unconditional test using spot excess returns reject the pure expectations hypothesis. Even though the mean futures term premium is zero, the dashed line in Figure 1 shows that the futures excess return varies considerably over time, and is sometimes very large, especially in the Federal Reserves alternative monetary regime that ran from late 1979 through late 1982. We now explore the question of whether despite having zero mean unconditional premium, Treasury bill futures rates contain time varying conditional interest rate risk premiums. 2.3 Conditional univariate tests Economic theory (e.g., Cox, Ingersoll and Ross, 1985) and empirical studies (e.g. Fama, 1976; Shiller, Campbell, and Schoenholtz, 1983; Engle, Lilien, and Robins, 1987; and Klemkosky and Pilotte, 1992), suggest that the term premium is positively related to interest rate volatility. We test this relation using  EMBED Equation.2  (1) The realized risk premium, Rfut, is the expected risk premium, which is a linear function of its conditional variance,  EMBED Equation.3 , plus a random error,  EMBED Equation.3 . Eq. (1) also provides a test of the term structure models of Vasicek (1977) and Cox, Ingersoll, and Ross (1985). Vasicek (1977) postulates that (1 = 0, so that the term premium is constant, whereas the affine model of Cox, Ingersoll, and Ross (1985) postulates that (0 = 0, so that the term premium is proportional to its variance. We estimate eq. (1) assuming that the time varying conditional volatility of Treasury bill rates follows the square root augmented GARCH(1,1) process proposed by Gray (1996) and Bekaert, Hodrick, and Marshall (1997).  EMBED Equation.2  (2) GARCH models explicitly model the time varying conditional variances by an autoregressive moving average process of past squared shocks. In GARCH-M models, the conditional mean (risk-return) model, the error term and the conditional variance model are estimated jointly. The square root augmented GARCH(1,1) adds an interest rate level effect, as in the square root process of Cox, Ingersoll and Ross (1985), to the GARCH effects. This helps to accommodate the considerable shift in interest rate volatility during the 1979-1982 monetary regime. Table 2 reports estimates of the GARCH-M model. The middle column reports the coefficients estimated using futures rates to measure the term premium. The key result is that the estimated value of  EMBED Equation.3 , the coefficient of interest rate volatility, is significantly positive with a serial correlation and heteroskedasticity corrected p-value of near zero. Thus, based on this estimate, the conditional interest rate risk premium in the Treasury bill futures market covaries positively with its conditional time-varying variance. This model rejects the expectations hypothesis of the term structure, which requires that if there is an interest rate risk premium it is constant. Eq. (1) also provides a test of affine term structure models. The Vasicek (1977) model predicts that (1 = 0, whereas the Cox, Ingersoll, and Ross (1985) model predicts that (0 = 0. Using the futures data we reject the Vasicek (1977) model, but cannot reject the Cox, Ingersoll, and Ross (1985) model. The estimated values of a1, a2 and a3 support the assumption that the conditional variance follows an autoregressive moving average process of squared shocks. The estimates of each of the GARCH terms are significant at conventional levels. Furthermore, the interest rate level effect, a3, is significantly positive with a serial correlation and heteroskedasticity consistent t-statistic greater than 4. During periods of historically high interest rates, interest rate volatility is also high, as is the term premium. The solid line in Figure 1 plots the estimated time varying conditional risk premium. The estimated conditional risk premium is substantial from late 1979 to late 1982, but is small before and afterwards. One possible explanation for the large premiums in 1979-1982 is the high leverage of futures contracts. (For example, initial margins in 1982 were equivalent to a price change of about 0.40%.) It is also useful to note that the corresponding riskless returns (on the underlying bill) were unusually high and unusually volatile during 1979-1982, fluctuating between 7-17%. Given our sample size, it is possible, however, that the coefficients in Table 2 are not estimated with sufficient precision to make reliable inferences regarding their exact magnitude. One finding, which can be seen by comparing the solid and dashed lines in Figure 1, is the different patterns of the conditional risk premiums and realized excess returns in the 1979-1982 sub-period. While the expected premiums are positive and economically significant, the mean realized premium in 1979-1982 is economically and statistically negligible (about minus 3 basis points). The realized excess returns are those earned by investors (speculators) who bought the futures contracts and held them to delivery 3 months later. The different plots suggest that long speculators were often surprised by the realizations of subsequent interest rates in 1979-1982. Because the 1979-1982 regime is a short and unprecedented period this finding should not be viewed as evidence of market inefficiency. Speculators may not have had enough time to learn and form rational expectations. Moreover, it is important to remember that we use the entire sample period of 1976-1998 in estimating the parameters of the model. Still, it is well established that interest rate volatility was substantially higher in 1979-1982 than in 1976-1978 and 1983-1998. Consequently, any model that postulates that the interest rate risk premium depends positively on its variance would imply significant interest rate risk premiums in 1979-1982. For comparison, the right-hand column of Table 2 reports our estimated coefficients of the GARCH-M model of the term premium using R6m3 to measure the premium. The inferences differ little from those based on futures rates. The main exception is that the intercept is now economically and statistically significant (35 basis points, with a near zero, serial correlation and heteroskedasticity consistent, p-value). Thus, using R6m3, we reject both affine term structure models of Vasicek (1977) and Cox, Ingersoll, and Ross (1985). Post-1982 evidence. Because interest rates were substantially more volatile during 1979-1982 than subsequently, it is possible that the finding of a volatility-related, time-varying term premium is attributable solely to this subset of the data. To check this, we estimated the univariate GARCH-M model using data for 1983-1998. Table 3 reports the results. Note first that the estimated coefficient of the term premium on its volatility has decreased from 10.35 in the entire 1976-98 sample to 0.18 in the post-1982 sub-sample. Thus, when the volatility of interest rates decreased, the covariance of the term premium with interest rate volatility decreased relatively more. If we view the regression coefficient as the price per unit of risk, and the regressor as the amount of risk, the results indicate that the price of risk was smaller in the post-1982 sub-sample. The price of risk apparently decreased when the amount of risk decreased. While smaller, the coefficient of volatility is statistically significant with a p-value of 0.0006. Thus, even in the post-1982 sub-sample, the data are inconsistent with the expectations hypothesis. There appears to be a time-varying interest rate risk premium in Treasury bill futures rates.  To summarize, we find that although the mean unconditional interest rate risk premium measured using futures rates is indistinguishable from zero, futures prices contain significant time varying conditional term premiums that relate significantly positively to their time varying conditional variance. This relation is similar to the one found in studies investigating spot Treasury quotes [e.g., Fama (1976), Shiller, Campbell, and Schoenholtz (1983), Engle, Lilien, and Robins (1987), and Klemkosky and Pilotte (1992)]. Consequently, our empirical evidence using futures rates strengthens our confidence in the spot market evidence that Treasury rates contain interest rate risk premium that covary positively with interest rate variance. Investigating 1-day to 3-month repo rates Longstaff (2000) finds that unconditional and conditional tests cannot reject the pure hypothesis term premium. Investigating the futures term premium, measured as the (6-to-3-month) difference between the futures rate and the subsequently observed spot rate, we also find that unconditional tests cannot reject the pure expectations hypothesis. However, unlike Longstaff, we find that the conditional futures term premium covaries significantly through time with its volatility. Thus, Treasury bill futures data reject the expectations theory of the term structure. The conditional term premium in the Treasury bill futures market is neither zero nor is it constant. It also raises the possibility that the repo term premium in Longstaff (2000) may be related to the volatility of the overnight repo rates. 2.4 Bivariate conditional tests The univariate tests reported above assumed that the risk premium depends only on its underlying volatility. Yet, two important asset pricing theories advance that the risk premium in futures prices should also be related to the covariance of its return with some real variable, such as the equity market risk premium, rather than to just the variance of its return. In this section we attempt to gain further insights into the determinants of the term premium by estimating a two-factor asset-pricing model. The first strand of equilibrium asset pricing models, include Mayers (1972), Stoll (1979) and Hirshleifer (1988). These CAPM-based models assume that some claims are non-tradable and that participation in futures markets is limited because of significant entry costs. They postulate that the equilibrium futures risk premium depends on the covariance of its return with the equity market risk premium, in addition to its residual (non-market) risk. The residual risk is the component of the risk premiums variance that remains after accounting for the covariance between the futures risk premium and the equity markets risk premium. Thus, they postulate the following conditional two-factor model  EMBED Equation.2  (3) Here,  EMBED Equation.2  is the conditional covariance between futures and equity markets excess returns. The two-factor model extends the one-factor model by adding a risk premium that depends on the conditional covariance with the equity premium. The second strand of equilibrium asset pricing models that postulate the relation described by eq. (3) is a two-factor version of Mertons (1973) intertemporal capital asset pricing model. The model advances that the equilibrium risk premium of any asset includes a premium for systematic-market risk, as in the static CAPM. For futures risk premiums, this component depends linearly on the covariance of the futures risk premium with the equity market risk premium. In addition, Merton (1973) advances that the risk premium of any asset also depends linearly on its covariances with the state variables that determine the stochastic investment opportunity set. The two-factor version of Mertons (1973) model assumes that a single state variable fully describes the stochastic investment opportunity set. Merton suggests using a (Treasury) security whose return is perfectly negatively correlated with the future riskless (in terms of default) interest rate as a single (instrumental) variable representing shifts in the investment opportunity set (p. 879). Since the long futures position in our sample is held to delivery, Rfut is perfectly negatively correlated with the three-month Treasury bill rate. Hence, Rfut can proxy for that single state variable, and a two-factor Mertons model also implies the linear risk-return relation described in eq. (3). Both strands of equilibrium models above hypothesize that (2, the coefficient of the systematic risk premium component in (3), is positive. Let Rm denote the quarterly excess return on the equity market portfolio. We measure it as the return on the Standard and Poors 500 portfolio minus the riskless return on the corresponding Treasury bill. The dates of the equity excess returns exactly match the dates of the futures excess returns. Standard and Poors 500 data are from the Center for Research in Security Prices (CRSP). To estimate eq. (3) one must specify an empirical model for the conditional covariance of futures and equity risk premiums. We base the equity excess return specification on the empirical findings of Glosten, Jaganathan and Runkle (1993) and Scruggs (1998):  EMBED Equation.2  (4)  EMBED Equation.2  (5) The equity excess return, Rm, depends on its time varying conditional variance,  EMBED Equation.2 , and on Rb, the 3-month Treasury bill yield. Fama and Schwert (1977), Campbell (1987), Ferson (1989), Glosten, Jaganathan and Runkle (1993) and Scruggs (1998) report a strong negative empirical relation between the equity market monthly risk premium and the nominal Treasury bill yield. The GARCH(1,1)-M specification of  EMBED Equation.2 is augmented to include the 3-month Treasury bill yield. Campbell (1987), Glosten, Jaganathan and Runkle (1993) and Scruggs (1998) also report a strong positive empirical relation between the volatility of the equity market excess returns and the nominal Treasury bill yield. Lastly, to make the estimation tractable we assume, similar to Scruggs (1998), that the conditional correlation between the two residuals is constant.  EMBED Equation.2  (6) We continue to assume that the conditional futures variance follows the square root augmented GARCH(1,1)-M process as in the one-factor case. Table 4 presents estimates of the conditional two-factor, bivariate GARCH-M model. The interest rate risk premium continues to depend significantly positively on its conditional variance. In addition, the estimate of (2 is significantly positive. Hence, we also find a positive empirical relation between the term premium and its conditional covariance with the equity premium. These results reject the expectations hypothesis of the term structure, which requires that if there is a risk premium that it is constant. While not reported, for brevity, the plot of the conditional futures risk premium estimated using the two-factor model is similar to the plot of the conditional futures risk premium estimated using the one-factor model, which is shown in Figure 1. The results regarding the conditional equity risk premium are consistent with existing literature (e.g., Scruggs, 1998). The equity excess return relates significantly positively to its conditional variance, and significantly negatively to the Treasury bill yield, at less than a 0.00001 level in each case. In addition, we also find a significant positive relation between the conditional variance of the equity premium and the nominal Treasury bill yield. 3. Summary The literature (Poole, 1978; Kamara, 1998, 1997; Fried, 1994; and Longstaff, 2000) suggests that the spot Treasury bill term premiums are biased estimates of the interest rate risk premium because they also include premiums for liquidity risk and for the risk that short sellers will default. In contrast, term premiums estimated using futures rates are more adequate measures of interest rate risk premiums because they do not include any default premium. Moreover, because the daily marking-to-market of futures contracts resets their value to zero each day, futures rates do not include a convexity bias, and must be equal, in equilibrium, to the risk neutral expectations of the underlying spot rate on the futures delivery date (Grinblatt and Jegadeesh, 1996). We have presented an investigation of the expectations hypothesis of the term structure and the possible risk premiums using futures Treasury bill rates. The pure expectations hypothesis says that futures rates equal expected future spot rates. Unconditional tests are consistent with the pure expectations hypothesis. The three-month futures rate is an unbiased forecast of the future spot rate. In contrast, unconditional spot (only) term premium contain economically and statistically significant premiums. Conditional tests of the futures term premium, however, reject the expectations hypothesis. They reveal that futures rates contain a conditional risk premium that varies systematically through time. The conditional futures premium covaries positively with the volatility of interest rates. This result holds over our entire sample, 1976-1998, and over the post-1982 sub-sample, albeit with far small coefficients. In addition, the conditional futures premium also covaries positively with the return on the stock market. Our conditional tests also reject the affine term structure models of Vasicek (1977), which predicts that the term premium is constant, and Cox, Ingersoll, and Ross (1985), which predicts that the term premium is an affine function of interest rate volatility. Investigating 1-day to 3-month repo rates Longstaff (2000) finds that unconditional and conditional tests cannot reject the pure hypothesis term premium. Whereas, we find that the conditional term premium in the Treasury bill futures market is neither zero nor is it constant. Our test use different conditioning information. An interesting question for future research is whether there are time-varying term premiums in 1-day to 3-month repo rates if the volatility of interest rates and their covariance with the equity market are used as conditioning variables. Table 1. Annualized Term Premium Measured Using Treasury Bill Futures and Spot Rates, 1976-1998Rfut - Futures term premiumR6m3 - Spot term premiumMean0.0007 (7 bps)0.0050 (50 bps)Standard Error 0.01620.0173T-stat0.41812.7556P-value0.67680.0071Rfut is the annualized futures quarterly excess return. R6m3 is the annualized quarterly excess return from buying the 6-month spot bill and selling it 3 months later. Table 2. Univariate interest rate level augmented GARCH-M model for the Treasury bill time varying conditional interest rate risk premium, 1976-1998.  EMBED Equation.2   EMBED Equation.2 CoefficientEstimated Coefficients using Futures Rates (p-value)Estimated Coefficients using Spot Rates (p-value)(00.0003 (0.5569)0.0035 (0.0000)(110.3596 (0.0000)9.2284 (0.0000)a10.9153 (0.0000)0.9397 (0.0000)a20.0464 (0.0001)(0.0018 (0.6881)a30.0003 (0.0000)0.0003 (0.0000)Test a1=a2=0Rejected at significance level 0.00000000.Rejected at significance level 0.00000000.Rfut is the annualized futures quarterly excess return. Rb,t is the 3-month spot Treasury bill yield at the beginning of the period. R6m3 is the annualized quarterly excess return from buying the 6-month spot bill and selling it after 3 months. Heteroskedasticity and autocorrelation consistent two-tailed p-values are in parentheses. Table 3. Univariate interest rate level augmented GARCH-M model for the Treasury bill futures time varying conditional interest rate risk premium, 1983-1998.  EMBED Equation.2   EMBED Equation.2 Coefficient Estimated Coefficient (p-value)(0(0.0003 (0.0000)(10.1760 (0.0006)a1-0.1290 (0.0000)a20.0032 (0.0000)a30.0007 (0.0000)Rfut is the futures quarterly excess return, in percent. Rb,t is the 3-month spot Treasury bill yield at the beginning of the period. Heteroskedasticity and autocorrelation consistent two-tailed p-values are in parentheses. Table 4. Bivariate interest rate level augmented GARCH-M model for the Treasury bill futures interest rate risk premium, 1976-1998.  EMBED Equation.2   EMBED Equation.2   EMBED Equation.2   EMBED Equation.2   EMBED Equation.2 CoefficientEstimated Coefficient (p-value)CoefficientEstimated Coefficient (p-value)(0(0.0011 (0.0633)(0(2.5878 (0.0000)(15.1920 (0.0000)(1108.8657 (0.0000)(2184.5353 (0.0000)(2(83.5364 (0.0000)a11.1583 (0.0000)b00.0243 (0.0000)a2(0.0062 (0.8908)b10.0049 (0.0024)a30.0002 (0.0000)b20.0172 (0.0000)c10.0057 (0.0000)b30.7412 (0.0000)Rfut and Rm are the futures and equity quarterly excess returns. Rb,t is the 3-month spot Treasury bill yield at the beginning of the period. Heteroskedasticity and autocorrelation consistent two-tailed p-values are in parentheses. References Anderson, Ronald W., and Danthine, Jean-Pierre, 1983, Hedger diversity in futures markets, Economic Journal 93, 370-389. Bekaert, Geert, Hodrick, Robert J., and Marshall, David A., 1997, On biases in tests of the expectations hypothesis of the term structure of interest rates, Journal of Financial Economics 44, 309-348. Berndt, E. 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Fama, Eugene F., and Schwert, William G., 1977, Asset returns and inflation, Journal of Financial Economics 5, 115-146. Ferson, Wayne E., 1989, Changes in expected security returns, risk, and the level of interest rates, Journal of Finance 44, 1191-1217. Fried, Joel, 1994, U.S. Treasury bill forward and futures prices, Journal of Money Credit and Banking 26, 55-71. Glosten, Lawrence R., Ravi, Jaganathan, and David E., Runkle, 1993, On the relation between the expected value and the variance of the nominal excess return on stocks, Journal of Finance 48, 1779-1801. Gray, Stephen F., 1996, Modeling the conditional distribution of interest rates as a regime-switching process, Journal of Financial Economics 42, 27-62. Grinblatt, Mark, and Jegadeesh, Narasimhan, 1996, The relative price of Eurodollar futures and forward contracts, Journal of Finance, 51, 1499-1522. Hirshleifer, David, 1988, Residual Risk, Trading costs, and commodity futures risk premia, Review of Financial Studies 1, 173-193. Hodrick, Robert J., 1987, The empirical evidence on the efficiency of forward and futures foreign exchange markets (Harwood Academic Publishers; New York, NY). Hull, John C., 2000, Options, futures and & other derivatives, 4th ed. Prentice-Hall, Upper Saddle River, NJ. Kamara, Avraham, 1988, Market trading structure and asset pricing: Evidence from the Treasury bill markets, Review of Financial Studies 1, 357-375. Kamara, Avraham, 1990, Forecasting accuracy and development of a financial market: The Treasury bill futures market, Journal of Futures Markets 10, 397-405. Kamara, Avraham, 1997, The relation between default-free interest rates and expected economic growth is stronger than you think, Journal of Finance 52, 1681-1694. Keynes, John M., 1930, A Treatise on money, vol. 2, 135-44 (MacMillan, London, England). Klemkosky, Robert C., and Eugene A. Pilotte, 1992, Time-varying term premia in U.S. Treasury bills and bonds, Journal of Monetary Economics 30, 87-106. Lauterbach, Beni, 1989, Consumption volatility, production volatility, spot-rats volatility, and the returns on Treasury bills and bonds, Journal of Financial Economics 24, 155-179. Longstaff, Francis A., 2000, The term structure of very short-term rates: New evidence for the expectations hypothesis, Journal of Financial Economics 58, 397-415. MacDonald, S. Scott, and Hein, Scott E., 1989, Futures and forward rates as predictors of near-term Treasury bill rates, Journal of Futures Markets 9, 249-262. Mayers, David, 1972, Non-marketabe assets and capital market equilibrium under uncertainty. In Studies in the Theory of capital markets, edited by Michael Jensen, pp. 223-248. Prager: New York. Merton, Robert C., 1973, An intertemporal capital asset pricing model, Econometrica 41, 867-887. Press, William H., Flannery, Brian P., Teukolsky, Saul A., and Vetterling, William T., 1986, Numerical Recipes (Cambridge University Press, New York, NY). Poole William, 1978, Using T-bill futures to gauge interest-rate expectations, Economic Review, Federal Reserve Bank of San Francisco, September, 63-75. Richard, Scott, F., and Sundaresan, M., 1981, A continuous time equilibrium model of forward prices and futures prices in a multigood economy, Journal of Financial Economics 9, 347-371. Scruggs, John T., 1998, Resolving the puzzling intertemporal relation between the market risk premium and conditional market variance: A two-factor approach, Journal of Finance 53, 575-603. Shiller, Robert J., John Y. Campbell, and Kermit L. Schoenholtz, 1983, Forward rates and future policy: Interpreting the term structure of interest rates, Brookings Papers on Economic Activity, 1, 173-217. Stoll, Hans R., 1979, Commodity Futures And Spot Price Determination And Hedging In Capital Market Equilibrium, Journal of Financial and Quantitative Analysis 14, 873-894. Telser, Lester G., and Higinbotham, Harlow N., 1977, Organized futures markets: Costs and benefits, Journal of Political Economy 85, 969-1000. Vasicek, Oldrich, 1977, An equilibrium model of the term structure, Journal of Financial Economics 5, 177-188.  EMBED Excel.Chart.8 \s   The two strategies are not exactly equivalent because of trading frictions, default risk, and the daily marking-to-market of futures contracts (Cox, Ingersoll and Ross, 1981; Richard and Sundaresan, 1981; Kamara, 1988). For simplicity, the example above ignores those differences. We will, however, address the effects of marking-to-market below.  Our sample ends in 1998 because trading in Treasury bill futures contracts fell dramatically in the late 1990s. Nineteen ninety-eight seems the last year when the contract was still sufficiently liquid to avoid stale prices. For example, in our data, the trading volume and open interest for the March 1995 contract are 7,194 and 15,520 contracts, respectively; but, trading volume and open interest for the September 1998 contract are 722 and 3267 contracts. Our last observation (on December 1998 for the March 1999 contract) has a trading volume of only 74 contracts and an open interest of 1,500 contracts. We repeated all our tests without it. Our conclusions are unaffected.  Starting with the June 1993 contract, the delivery date of the futures contract moves within the delivery month. (The purpose is to maximize the number of bills available for delivery and reduce the likelihood and severity of possible squeezes.) As a result, one-half of our observations after 1982 overlap by one week (1/13 of an interval). We address this issue by correcting the standard errors in all the regressions below for serial-correlation of, at least, first-order.  Our calculations of returns account for the fact that Treasury trades settle one day after the trade day. We also adjust futures returns.  The hedging pressure literature that began with Keynes (1930) also advances that the futures risk premium depends on the variance of the interest rate. Hedging pressure models (e.g., Anderson and Danthine, 1983), however, distinguish between hedgers (agents who trade in both the underlying asset and the futures market) and speculators (agents who face an infinite cost of entry into the underlying cash market). As a result, the futures risk premium depends on the net hedging position. We do not test these models because there are no net hedging data for the Treasury bill futures market for large periods in our sample. Moreover, the existing data suggest that hedgers in the Treasury bill futures market are almost always net short.  Recent affine term structure models (e.g., Duarte, 2002) allow both (0 and (1 to be significant.  The constant term is omitted because the square root process introduces a de facto intercept (Gray, 1996, p. 49.)  We calculated quasi-maximum likelihood estimates and standard errors in two stages using the RATS software. First, we calculated maximum likelihood estimates using the Berndt, Hall, Hall and Hausman (1974) algorithm. This yields consistent estimates, but the standard errors need to be adjusted (Bollerslev and Wooldridge, 1992). We then calculated quasi-maximum likelihood estimates and serial correlation and heteroskedasticity-consistent standard errors using the Broyden, Fletcher, Goldfarb and Shanno algorithm (Press et. al., 1986). We iterated the two procedures until we achieved convergence of both the estimates and the log-likelihood function.  We also tested and could not reject the null hypothesis that a higher order GARCH process is not needed.  Cox, Ingersoll, and Ross (1985) also postulates that the conditional variance is a function of the contemporaneous interest rate level only, so that the GARCH terms should be zero. We reject the joint hypothesis a1 = a2 = 0 at a near zero level. But, our conditional variance specification uses the lagged interest rate level.  We also repeated our tests for the entire sample in two ways. First, we repeated the tests, by adding products of the intercept and each of the variables in the term premium and conditional variance equations by a dummy variable that equals one during 1979-1982 and zero otherwise. Second, we tested other GARCH specifications (e.g., Engle and Bollerslev, 1986 and Engle, Lilien, and Robins, 1987). Our conclusions are unaffected. The conditional interest rate risk premium in the Treasury bill futures market covaries positively with its conditional time-varying variance during our entire sample period; and the estimated coefficient of the term premium on its volatility is significantly higher in 1979-1982 than in the rest of sample period.  Lauterbach (1989) finds that spot Treasury term premiums depend on conditional volatilities of consumption and production in 1964-1979, but do not depend on them in the post-1979 period.  We also tested a model with an asymmetric variance term following Glosten, Jaganathan and Runkle (1993) but could not reject the null hypothesis of symmetry. Scruggs (1998) also finds that when the conditional equity variance depends on the Treasury bill yield, the estimate of the asymmetric term is indistinguishable from zero.  For a discussion of Multivariate GARCH models, see for example, Engle and Kroner (1995). 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2 W2 2 > 2 2 2 2 Bcm,P 2 Bt,Y 2 B-,k 2 B1, 2 @c2, 2 X2, 2 Bt,Y 2 BL-,k 2 B1, 2 @2, 2 l!t,Y 2 !-,k 2 9"1, 2 M&2, 2 !)b,P 2 *t,YSymbolww w - 2 E ` 2 ` 2 ` 2 T'`Symbolww w - 2 Bw-Symbolww w - 2  e 2 e & "System`w 'pЃw-WWOWWOWWOWWOWWOWWOWWOWWOWWOW FMicrosoft Equation 3.0 DS Equation Equation.39q}$II hm2 Lb {\hb {^<  .1  @`&  & MathTypepTimes New Roman wEquation Native A@_991060200@WFsސsސOle BPIC VYCLMETA ECompObjXZ\fObjInfo[^Equation Native _ - 2 `@h 2 `a 2 `b 2 `WhTimes New Roman w - 2 'fi 2 m 2 @ fi 2 / tY 2 m 2 YtY 2 >fi 2 -m 2 tY 2 ,P 2  ,P 2 ,P 2 ,P 2 ',PSymbolww w - 2 `= 2 `+ 2 `` 2 ``Symbolww w - 2  - 2 - 2 -Times New Roman w - 2 3 2 3 2 T 1 2 ~1 2 3 2 1Times New Roman w - 2 `  (` 2 `  (` 2 `E) ` 2 `|+ 2 ` c`Symbolww w - 2 `c e 2 `)e & "System`w 'pw-WWOWWOWWOWWOWWOW FMicrosoft Equation 3.0 DS Equation Equation.39qՀ$vIpI hfm,t=c1 "hf,t "hm,t L + +^?  .1  &` & MathTypeTimes New Romant w_1086068839^FppOle bPIC ]`cLMETA eH - 2 @h 2 Ea 2 ObTimes New Romant w - 2 Q'f2Y 2 QtY 2 Q fY 2 Q tY 2 QfmY 2 QtY 2 Q,P 2 Qd ,P 2 Q,PTimes New Romant w - 2 B(~ 2 )|Times New Romant w - 2 C#2 2 12 2 1 2 Q 1 2 C 2 2 Q1m 2 C2Symbolwwt w - 2 = 2 &+ 2 ` 2 ` 2 M`Symbolwwt w - 2 Q - 2 Qa-2Symbolwwt w - 2  e 2 eTimes New Romant w - 2 y  ` 2 &+ 2 q d`2 I7982Times New Romant w - 2 1 2 rtY 2 -k 2 Q1 & "System`wt 'pذw-Times New Romant w FMicrosoft Equation 3.0 DS EqCompObj_afObjInfobEquation Native _10848878342xeFuation Equation.39qul Ri,t e = 0+1"hf,t2+f,t,              i=fut, 6m3Ole PIC dgLMETA HCompObjfhfL + +^?  .1  &` & MathTypeTimes New Romant w - 2 @h 2 Ea 2 ObTimes New Romant w - 2 Q'f2Y 2 QtY 2 Q fY 2 Q tY 2 QfmY 2 QtY 2 Q,P 2 Qd ,P 2 Q,PTimes New Romant w - 2 B(~ 2 )|Times New Romant w - 2 C#2 2 12 2 1 2 Q 1 2 C 2 2 Q1m 2 C2Symbolwwt w - 2 = 2 &+ 2 ` 2 ` 2 M`Symbolwwt w - 2 Q - 2 Qa-2Symbolwwt w - 2  e 2 eTimes New Romant w - 2 y  ` 2 &+ 2 q d`2 I7982Times New Romant w - 2 1 2 rtY 2 -k 2 Q1 & "System`wt 'pذw-Times New Romant w FMicrosoft Equation 3.0 DS Equation Equation.39q hf,t2ObjInfoiEquation Native _992963085lFOle =a1"f,t"12 + a2"hf,t"12+ a3"R b,t"1L + +^?  .PIC knLMETA HCompObjmofObjInfop1  &` & MathTypeTimes New Romant w - 2 @h 2 Ea 2 ObTimes New Romant w - 2 Q'f2Y 2 QtY 2 Q fY 2 Q tY 2 QfmY 2 QtY 2 Q,P 2 Qd ,P 2 Q,PTimes New Romant w - 2 B(~ 2 )|Times New Romant w - 2 C#2 2 12 2 1 2 Q 1 2 C 2 2 Q1m 2 C2Symbolwwt w - 2 = 2 &+ 2 ` 2 ` 2 M`Symbolwwt w - 2 Q - 2 Qa-2Symbolwwt w - 2  e 2 eTimes New Romant w - 2 y  ` 2 &+ 2 q d`2 I7982Times New Romant w - 2 1 2 rtY 2 -k 2 Q1 & "System`wt 'pذw-Times New Romant w FMicrosoft Equation 3.0 DS Equation Equation.39qz՜$vIpI Rfut,t e = 0+1"hf,t2+f,tEquation Native _992963299jGsFOle PIC ruLL + +^?  .1  &` & MathTypeTimes New Romant w - 2 @h 2 Ea 2 ObTimes New Romant w - 2 Q'f2Y 2 QtY 2 Q fMETA HCompObjtvfObjInfowEquation Native Y 2 Q tY 2 QfmY 2 QtY 2 Q,P 2 Qd ,P 2 Q,PTimes New Romant w - 2 B(~ 2 )|Times New Romant w - 2 C#2 2 12 2 1 2 Q 1 2 C 2 2 Q1m 2 C2Symbolwwt w - 2 = 2 &+ 2 ` 2 ` 2 M`Symbolwwt w - 2 Q - 2 Qa-2Symbolwwt w - 2  e 2 eTimes New Romant w - 2 y  ` 2 &+ 2 q d`2 I7982Times New Romant w - 2 1 2 rtY 2 -k 2 Q1 & "System`wt 'pذw-Times New Romant w FMicrosoft Equation 3.0 DS Equation Equation.39qz$vIpI Rfut,t e = 0+1"hf,t2+2"hfm,t+f,tL + +^?  .1  &` &_1084968076zFOle PIC y|LMETA H      !"#$%&'()*+,-./012478;>?@ACDEFGHIKLMNOPQSTUVX MathTypeTimes New Romant w - 2 @h 2 Ea 2 ObTimes New Romant w - 2 Q'f2Y 2 QtY 2 Q fY 2 Q tY 2 QfmY 2 QtY 2 Q,P 2 Qd ,P 2 Q,PTimes New Romant w - 2 B(~ 2 )|Times New Romant w - 2 C#2 2 12 2 1 2 Q 1 2 C 2 2 Q1m 2 C2Symbolwwt w - 2 = 2 &+ 2 ` 2 ` 2 M`Symbolwwt w - 2 Q - 2 Qa-2Symbolwwt w - 2  e 2 eTimes New Romant w - 2 y  ` 2 &+ 2 q d`2 I7982Times New Romant w - 2 1 2 rtY 2 -k 2 Q1 & "System`wt 'pذw-Times New Romant wCompObj{}fObjInfo~Equation Native F_991051262F FMicrosoft Equation 3.0 DS Equation Equation.39q*@  eh  ef,t  e2=a  e1  e"  ef,t"1  e2 + a  e2  e"h  ef,t"1  e2+ a  e3  e"R  eb,t"1 Lb {\hb {^<  .1  @`&  & MathTypepTimes New Roman w - 2 `@h 2 `a 2 `Ole PIC LMETA CompObj3fb 2 `WhTimes New Roman w - 2 'fi 2 m 2 @ fi 2 / tY 2 m 2 YtY 2 >fi 2 -m 2 tY 2 ,P 2  ,P 2 ,P 2 ,P 2 ',PSymbolww w - 2 `= 2 `+ 2 `` 2 ``Symbolww w - 2  - 2 - 2 -Times New Roman w - 2 3 2 3 2 T 1 2 ~1 2 3 2 1Times New Roman w - 2 `  (` 2 `  (` 2 `E) ` 2 `|+ 2 ` c`Symbolww w - 2 `c e 2 `)e & "System`w 'pw-WWOWWOWWOWWOWWOW FMicrosoft Equation 3.0 DS Equation Equation.39q|$vIpI hf,m=c1 "hf,t "hObjInfo5Equation Native 6_1086707142!F$`R&Ole 9m,t  !FMicrosoft Excel ChartBiff8Excel.Chart.89qOh+'0HPp BA Computer ServicesBA Computer ServicesPRINTfCompObj:bObjInfo<Workbook45[      !"#$%&'()*+,-./0156789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~;Y4 2    g ''   Arialw@) IwIw0-Arialw@# IwIw0-------- Arialw@& IwIw0---"System 0-'- g -'- g --  $  - 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