Discount rate changes, stock market returns, volatility, and trading volume: Evidence from intraday data and implications for market e ciency q

Journal of Banking & Finance 23 (1999) 897±924 www.elsevier.com/locate/econbase Discount rate changes, stock market returns, volatility, and trading volume: Evidence from intraday data and implications for market e ciency q Carl R. Chen *, Nancy J. Mohan, Thomas L. Steiner University of Dayton, Department of Economics and Finance, 300 College Park, Dayton, OH 45469-2251, USA Received 28 February 1997; accepted 24 August 1998 Abstract We examine the e ect of discount rate changes on stock market returns, volatility, and trading volume using intraday data. Equity returns generally respond negatively and signi cantly to the unexpected announcements; however, the e ect of expected changes on equity returns is insigni cant. Furthermore, our results indicate that equity prices respond to announcements within the trading period/hour after the information release. An indication of a return reversal is too small to cover the full transaction costs. Unexpected discount rate changes also contribute to higher market volatility although the volatility is short-lived. Similarly, unexpected changes in discount rates induce larger trading volume while expected changes do not. Abnormal trading volume occurs only in period t. Our results also support the notion that unexpected changes in the discount rates impact market returns irrespective of the Federal Reserve operating procedures. Ó 1999 Elsevier Science B.V. All rights reserved. JEL classi cation: G10; G14; E52 q An earlier version of the paper was presented at the 1996 Financial Management Association Meetings. The authors acknowledge the helpful comments of two anonymous referees. * Corresponding author. Tel.: 1 937 229 2418; fax: 1 937 229 2477; e-mail: chen@udayton.edu 0378-4266/99/$ ± see front matter Ó 1999 Elsevier Science B.V. All rights reserved. PII: S 0 3 7 8-4 2 6 6 ( 9 8 ) 0 0 1 1 8-6

898 C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 Keywords: Market e ciency; Discount rate; Public information; Volatility; Trading volume 1. Introduction We examine the impact on stock market returns, volatility, and trading volume of Federal Reserve discount rate changes. Unexpected Federal Reserve discount rate changes represent new public macroeconomic information that is a closely followed policy variable. An unexpected change in the discount rate may signal that the Federal Reserve is changing its federal fund rate in the foreseeable future which, in turn, may in uence a variety of other market interest rates. These interest rate changes a ect asset prices both through an impact on expected future cash ows and an impact on required rates of return used to discount these expected future cash ows to the present value. For example, a discount rate increase, ceteris paribus, decreases the expected future equity cash ows because rms must borrow at a higher cost. At the same time, the increase also raises the risk-free rate which, in turn, increases the required rate equity investors use to discount the future cash ows. As a result, an unexpected increase in market interest rates depresses equity prices, and, therefore, one would expect an unexpected change in the Federal Reserve discount rate to cause changes in equity prices. The primary objective of this study is to investigate the linkage between intra-day stock market price discovery (returns, volatility, and trading volume) and Federal Reserve discount rate change announcements which could be classi ed as either expected or unexpected public information depending on the nature of the announcements. Prior studies which have investigated discount rate changes include Roley and Troll (1984), Pearce and Roley (1985), Smirlock and Yawitz (1985), and Cook and Hahn (1988). Roley and Troll nd that market yields do not respond to discount rate changes before 1979, but interest rates, across the maturity spectrum, do respond after 1979. The authors suggest that the shifting relationship between the discount rate changes and the market yields is due to changes in Federal Reserve operating procedures. Pearce and Roley (1985) report identical results over the same sample period for stock returns. Smirlock and Yawitz (1985) classify discount rate changes as endogenous (expected) or exogenous (unexpected) and rea rm that interest rates and stock returns respond only to unexpected discount rate changes after 1979. However, Cook and Hahn (1988), focusing on interest rates rather than stock prices, argue that as long as market participants understand the signals

C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 899 contained in discount rate announcements and use them to revise their expectations of the future path of the federal funds rate, the Federal Reserve operating procedure is irrelevant. Moreover, they nd results in con ict to those of Smirlock and Yawitz partially due to di erent de nitions of the ``announcement day''. Controversy, therefore, persists. Our study investigates the stock market price discovery process associated with the discount rate changes, and it di ers from the prior research studies in several respects. First, we reinvestigate the question of whether the stock market responds to the discount rate changes employing intra-day data as opposed to daily data (close-to-close returns). Measuring stock returns over a more narrow time interval reduces the random variability of asset prices and, therefore, the power of the statistical tests are enhanced. Part of the controversy found in prior studies originated from the de nition of the ``announcement day''; therefore, the use of intra-day data can more accurately assess the impact of discount rate changes on equity prices, and the speed at which asset prices adjust to the discount rate changes. Smirlock and Yawitz (1985) conclude that equity prices adjust fully to the discount rate changes in no more than two days (inclusive of the announcement day), yet there is evidence that asset prices adjust to information more rapidly (e.g., Ederington and Lee, 1993). Second, we test the relationship between stock market volatility and the release of discount rate change information. Stock market volatility has drawn attention from the regulators and has been used by the academics to test market e ciency (Shiller, 1981). Is it private information or public information that causes market volatility? Third, we study the price formation process by examining the relationship between discount rate changes and trading volume. Does the announcement of public information such as the discount rate changes move stock prices with or without trading volume? Does public information generate trading only in the current period, or does it generate trading in both current and future periods more similar to the impact associated with private information? Moreover, observing price and volume together is more informative than observing price alone. For example, according to Blume et al. (1994), observing a high price alone (without trading volume) does not allow one to distinguish whether the price is high because of a high signal or because of an average signal with a high quality. Fourth, the intra-day data employed in this study covers a time span of 24 years (1973±1996), a longer period than employed by similar studies using daily data. Finally, we also study the impact of discount rate changes on utility stock returns. The remainder of the paper is organized as follows. Section 2 discusses data sources. Section 3 presents hypotheses and methodologies. Empirical results are presented and discussed in Section 4. A conclusion follows in Section 5.

900 C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 2. Data source and computations 2.1. Federal reserve discount rate changes The times and dates of the discount rate change announcements are obtained from the Dow±Jones News Retrieval Service, the Wall Street Journal Index, the Federal Reserve Bank of Richmond and the Federal Reserve Board in Washington, DC. 1 We classify types of discount rate changes, in accordance with Cook and Hahn (1988), as technical changes or policy changes. When the Federal Reserve Board changes the discount rate, it states the reason for its action in a press release. Technical (or expected) changes are de ned by when the discount rate is changed to realign it with market rates. On the other hand, the announcements that indicate the changes are to address the Federal ReserveÕs concern over the growth of money and credit, expected in ation rate, and economic activity, are classi ed as policy (or unexpected) changes. Announcements that contain both languages, following Cook and Hahn, are also classi ed as unexpected changes. Hereafter, we use the terms expected and unexpected changes to refer to technical and policy changes, respectively. The sampling period begins January 1973 and ends January 1996. In total, there are 68 discount rate change announcements ± 22 are expected changes and the remaining 46 are unexpected changes. Among the 68 announcements, 12 were made on the day before the market opened, 2 between eleven oõclock and twelve oõclock, 2 between twelve oõclock and one oõclock, 1 between one oõclock and two oõclock, 4 between two oõclock and three oõclock, 1 between three oõclock and four o'clock, 1 on Saturday, and 45 on the day after the market was closed. Regarding the day of the week, 5 announcements were made on Monday, 10 on Tuesday, 7 on Wednesday, 11 on Thursday, 34 on Friday, and 1 on Saturday. Among the 34 announcements made on Friday, 16 are increasing discount rates (bad news) and 18 are decreasing discount rates (good news). Table 1 tabulates the discount rate change announcements by day and by hour of the day. For the whole sample, Friday accounts for 50% of all announcements; the hours between the market close and the market open account for 68% of all announcements. For the unexpected discount rate changes, however, this statistic is reduced to 54%. Because the announcements seem to cluster around certain days (certain hours), and because business rms often engage in timing the release of information (Chen and Mohan, 1994), we conduct a simple test to see if the magnitude of the discount rate changes are 1 We thank Timothy Cook of the Federal Reserve Bank in Richmond for providing much of the announcement time data. Joe Coyne of the Federal Reserve Board is also acknowledged for providing recent announcement information.

C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 901 Table 1 Summary statistics Hour/day Monday Tuesday Wednesday Thursday Friday Saturday Total Panel A: For all 68 announcements, this table shows the announcements by day and by hour of the day Close 5 3 4 9 24 1 46 (68%) Open 0 2 1 2 7 0 12 (18%) Second 0 0 1 0 1 0 2 (3%) Third 0 0 0 0 2 0 2 (3%) Fourth 0 1 0 0 0 0 1 (1%) Fifth 0 2 2 0 0 0 4 (6%) Sixth 0 1 0 0 0 0 1 (1%) Total a 5 (7%) 9 (13%) 8 (12%) 11 (16%) 34 (50%) 1 (1%) Panel B: For the 46 unexpected discount rate change announcements, this table shows the announcements by day and by hour of the day Close 3 0 3 4 14 1 25 (54%) Open 0 2 1 1 7 0 11 (24%) Second 0 0 1 0 1 0 2 (4%) Third 0 0 0 0 2 0 2 (4%) Fourth 0 1 0 0 0 0 1 (2%) Fifth 0 2 2 0 0 0 4 (9%) Sixth 0 1 0 0 0 0 1 (2%) Total a 3 (7%) 6 (13%) 7 (15%) 5 (11%) 24 (52%) 1 (2%) Panel C: For the 22 expected discount rate change announcements, this table shows the announcements by day and by hour of the day Close 2 3 1 5 10 0 21 (95%) Open 0 0 0 1 0 0 1 (5%) Second 0 0 0 0 0 0 0 (0%) Third 0 0 0 0 0 0 0 (0%) Fourth 0 0 0 0 0 0 0 (0%) Fifth 0 0 0 0 0 0 0 (0%) Sixth 0 0 0 0 0 0 0 (0%) Total a 2 (9%) 3 (14%) 1 (5%) 6 (27%) 10 (45%) 0 (0%) a Percentage numbers are rounded.

902 C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 related to the timing of the announcements. Table 2 reports the ndings. In Panel A of Table 2, we test to determine whether the magnitude of the discount rate changes are di erent across the days of the week. None of the t-statistics are signi cant which implies that the magnitude of the discount rate changes are independent of the day of the week chosen to release this information. Panel B of Table 2 reports test results to determine whether the magnitude of the discount rate changes are di erent between three time frames: announcements made after the stock market is closed; announcements made before the market opens; and announcements made during the trading hours. Again, none of the t-statistics are signi cant which signals the lack of an association between the magnitude of the discount rate changes and the hour that the Federal Reserve chooses to release the information. 2.2. Stock market returns and trading volume Intra-day stock market returns are computed using the Dow±Jones Industrial Average Index and the Dow±Jones Utility Average Index obtained from various issues of the Wall Street Journal. The advantage of employing the Table 2 Magnitudes of the discount rate changes Day n Abs(discount rate change)% t-statistic Panel A: Day of the week a Monday 5 0.60 0.34 Tuesday 9 0.50 1.58 Wednesday 8 0.5938 0.29 Thursday 11 0.6364 0.77 Friday 34 0.5368 0.80 Saturday 1 1.0 na Total 68 0.5662 Panel B: Hour of the day b 1 46 0.5706 0.12 2 12 0.5417 0.59 3 10 0.5750 0.11 Total 68 0.5662 a This table reports the magnitudes of the discount rate changes. The magnitude is de ned as the average of the absolute value of the change in the discount rate. t-statistics compare the day of the week mean absolute change to the overall mean absolute change. The overall mean absolute change is 0.5662%. b This table reports the magnitudes of the discount rate changes. The magnitude is de ned as the average of the absolute value of the change in the discount rate. t-statistics compare the hour of the day mean absolute change to the overall mean absolute change. The hours are de ned as 1 for a after-market-close announcement, 2 for a before-market-open announcement, and 3 for announcements made during the trading hours. The overall mean absolute change is 0.5662%.

C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 903 Dow±Jones indices is due to the frequency of trading which means the indices are not likely to be a ected by the nonsynchronous trading problem often associated with smaller stocks. Stoll and Whaley (1990) document that the Major Market Index is less subject to nonsynchronous trading than the S&P 500 Index. 2 Market returns are computed for the period immediately following the announcement (t), ve periods afterwards t 1;... ; t 5, and four periods before the announcement t 1;... ; t 4. Daytime trading hours are de ned as trading periods. In cases where the announcement was made after the market closed, stock returns for period t are measured from the prior day close to the next day opening. Throughout the paper, we treat closeto-open as one trading period and avoid the use of the term ``hourly'' returns. The trading volume variable employed in our analysis is de ned as the New York Stock Exchange (NYSE) trading volume in the hour immediately after the announcement divided by the total NYSE outstanding shares during the month of the announcement. The purpose of this weighting procedure is obvious: the total number of shares listed on the stock exchange increases over time which generates more trading. Monthly outstanding shares serves as a su cient weight since the total number of shares outstanding does not change in any observable way between hours. NYSE trading volume is employed because the lack of intra-day Dow±Jones trading volume statistics. The data on hourly trading volume is taken from the Wall Street Journal, and the total shares outstanding are taken from various issues of the Survey of Current Business. 3 3. Hypotheses and methodology 3.1. Stock price changes and the speed of adjustment The linkage between information ow and asset returns has been a vital subject for nancial economics. 4 In this section, we specify tests which examine whether the discount rate change announcements a ect the stock market 2 Studies that employ Dow±Jones data include, but are not limited to, Lockwood and Linn (1990), and Gerety and Mulherin (1992). 3 Because the Survey of Current Business stopped publishing this data item in 1993, we thank the research department at the New York Stock Exchange for providing the additional monthly gures. 4 See Damodaran (1989), Penman (1987), and Thompson et al. (1987) for rm-speci c information; French and Roll (1986), and He and Wang (1995) for public vs. private information; Mitchell and Mulherin (1994), and Berry and Howe (1994) for total amount of information; French et al. (1989), Cutler et al. (1989), Harvey and Huang (1991), Ederington and Lee (1993), and McQueen and Roley (1993) for macroeconomic information.

904 C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 returns. Unexpected changes in the discount rate brings new information to the market which is anticipated to impact stock returns. To the extent that expected changes in the discount rate contain no new information and are already impounded in the stock values, we anticipate an insigni cant relationship between these expected changes and the stock returns. Furthermore, because the e cient market hypothesis implies that stock prices adjust to information rapidly, we also examine the e ciency of the market. Our null and alternative hypotheses can be speci ed as follows. Hypothesis 1A. Null: The unexpected discount rate change announcements have no impact on stock market returns. Alternative: Stock returns are inversely related to the unexpected changes in discount rates. Hypothesis 1B. Null: The expected discount rate change announcements have no impact on stock market returns. Alternative: Stock returns respond to the expected changes in discount rates. Hypothesis 2. Null: The market is e cient and, therefore, stock prices adjust to new information rapidly. Alternative: The market is not e cient; stock prices adjust to new information slowly and it is possible to generate abnormal pro ts from trading on such information. We estimate the parameters on four empirical models to test Hypotheses 1A, 1B and 2. These models are de ned by the following equations: R t i ˆ a b ddr t i l t i ; i ˆ 4;... ; 0;... ; 5; 1 R t i ˆ a b ddr ut i k ddr et i l t i ; i ˆ 4;... ; 0;... ; 5; 2 R t ˆ a b ddr ut k ddr et cd 1 dd 2 l t ; 3 R t ˆ a b ddr ut k ddr et cd 1 dd 2 pd 3 l t ; In these equations, R t and ddr t measure, at period t, the intra-day stock market returns and the changes in the Federal Reserve discount rates, respectively. Both basis point and percentage changes in discount rates are used to estimate Eq. (1)±(4). Further, Eq. (1) is estimated using the entire sample and re-estimated after partitioning the sample into unexpected and expected changes. Eq. (2) includes the regressors ddr ut and ddr et to capture the unexpected and expected discount rate change e ects in the same empirical model. D 1, in Eq. (3), is a dummy variable such that its value is 1 if the observation is in a period of decreasing discount rates and 0 otherwise, and D 2 is a dummy variable such that its value is 1 if the discount rate change represents a reversal and 0 otherwise. D 3, in Eq. (4), is a dummy variable with a value of 1 if 4

C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 905 the announcement of discount rate changes occur on Friday, 0 otherwise. We include this dummy variable in Eq. (4) for two reasons: (1) half of the announcements occur on Friday; (2) there is documented evidence of positive returns on Friday followed by negative returns on Monday. We do not investigate Monday separately because there were only 5 announcements made on Monday. 5 Eq. (1)±(4) di er based upon the control variables included and the eventtime-period studied. Eq. (1) o ers a simple test of whether the discount rate changes are inversely related to the intra-day stock returns while Eq. (2) tests whether the stock returns respond di erently to the unexpected and the expected discount rate changes. Because expected changes reveal no new information, ddr et should not be a signi cant factor. Eqs. (1) and (2) also allow for an examination of the speed of adjustment in stock returns. The results yield insight into the e ciency of the markets. For example, parameter estimates which are signi cant for time period t but insigni cant for other time periods would suggest full adjustment within one period. Eq. (3) controls for and examines whether: (1) nancial markets respond di erently to discount rate changes which represent a reversal in direction relative to the previous change in the discount rate and (2) does the market perceive rate increases as more or less signi cant than rate decreases? We test for a potential rate reversal e ect because a rate reversal signals a fundamental change in the economic condition, which may be more informative than a non-reversal change. We also test for a possible asymmetric information e ect in discount rate changes due to risk averse investors reacting di erently to ``good news'' and ``bad news''. Finally, Eq. (4) controls for and tests for a Friday e ect. 3.2. Stock market volatility Financial market volatility is important for investorsõ con dence, for portfolio selection, and for the pricing of both primary and derivative securities. In this section, we examine how market volatility responds to the discount rate changes. First, we examine if the arrival of public information causes market volatility. French and Roll (1986) conclude that variability in information ow is the major determinant of volatility, and that private information is the dominant factor. Harris (1986b), however, reasons that large price movements in the rst 45 minutes of the trading day are, in e ect, due to information which arrives while the market is closed. Adjusting for this e ect would reduce the 5 Because all Friday announcements were not made after the market close, we also employ a regression equation that allows us to control for the non-trading period returns. Results are reported in footnote 8.

906 C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 trading period variance and weaken the support for French and RollÕs (1986) private information hypothesis. Hypothesis 3 reexamines this issue. Hypothesis 3A. Null: Market volatility is not related to new public information such as unexpected discount rate change announcements. Alternative: Market volatility responds to the unexpected discount rate change announcements. Hypothesis 3B. Null: Market volatility is not related to existing public information such as expected discount rate change announcements. Alternative: Market volatility responds to the expected discount rate change announcements. To test Hypothesis 3, we employ the following regression equation: V t ˆ a b ddr ut 2 c ddr et 2 dd 2 l t ; All variables follow the same de nitions given in Eq. (1)±(4) except that now the dependent variable (V t ) is a measurement of market volatility. Following Ederington and Lee (1993), market volatility is measured by taking the absolute value of the di erence between the actual return R t i for an announcement (where i ˆ 4;... ; 5) and the mean return at period t i calculated using the t i period for each of the 68 discount rate announcement changes. That is, V t i;j ˆ jr t i;j R t i j for announcement j. A signi cant parameter estimate on the variable ddr 2 ut rejects the null hypothesis in support of Alternative 3A. Eq. (5) can test the U-shaped relationship between discount rate changes and market volatility. The relationship between market volatility and the discount rate changes is U-shaped if the magnitude of the discount rate change a ects the market volatility, irrespective the direction of the change. The exogenous variable ddr is squared to account for this assertion. The dummy variable D 2 is included to measure the e ect of a turning point in discount rate changes. Since the volatility of stock returns increases when the information arrives and, presumably, returns to normal when the information is fully analyzed and impounded in the stock prices, we also seek to examine the duration of the market volatility following the announcements of the discount rate changes. This sheds additional light on the market e ciency issue. 6 5 6 Empirical evidence regarding whether volatility remains high after the release of new information varies across di erent studies from several hours (Ederington and Lee, 1993) to several days (Patell and Wolfson, 1984).

Hypothesis 4. Null: The full information of the discount rate changes are quickly impounded in the stock price, and the market volatility is short-lived. Alternative: The market slowly incorporates the full information of the discount rate changes and volatility remains high for extended periods of time. To test Hypothesis 4, the following equation is employed. V t i ˆ a b ddr ut 2 c ddr et 2 dd 2 l t ; i ˆ 4;... ; 5: 6 All variables used in Eq. (6) have been previously de ned. 3.3. Trading volume C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 907 Although a number of analytical models suggest most trades in the nancial markets occur because of di ering beliefs (e.g., Admati, 1985), there is still debate over the issue of whether ``public information'' moves stock prices with trading or without trading. When French and Roll (1986) report that market volatility is greater during trading periods than during non-trading periods, the implication is that private information causes trading, while public information can be incorporated into asset prices without trading. Hasbrouck (1991) shares this same assumption. Alternatively, several theoretical papers have shown that unexpected public information leads to trading (e.g., Foster and Viswanathan, 1993; Kim and Verrecchia, 1991a,b). Moreover, Harris and Raviv (1993) argue that trading can occur in the absence of private information due to a di erencein-opinion. To examine the relationship between the discount rate changes and the trading volume, we de ne Hypothesis 5 as: Hypothesis 5. Null: Public information moves stock prices without trading. Alternative: Public information generates trading. To test Hypothesis 5, we employ Eqs. (7) and (8). Vol t i ˆ a bjddr ut j cjddr et j l t ; i ˆ 4;... ; 5; 7 Vol t ˆ a bjddr ut j cjddr et j kd 1 dd 2 l t : 8 All variables follow the same de nitions given in Eq. (1)±(4) except that now the dependent variable (Vol t ) is a measure of trading volume. Eq. (7) allows us to examine the impact of the public announcement on volume in the current period and subsequent periods (some contend that public information generates trading only in the current period, while private information generates trading in both the current and the future periods). Eq. (8) includes controls for whether the discount rate is increased or decreased (D 1 ), and whether a reversal occurred (D 2 ).

908 C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 4. Empirical results 4.1. Equity returns and discount rate changes Because we nd the results not to materially di er when we alternatively estimate the parameters for ddr t using basis point changes and percentage changes, Tables 3 and 4 present results from estimating Eq. (1)±(4) using only basis point changes. 7 Table 3 reports the results from estimating Eq. (1) using, in turn, the whole sample, the unexpected change sample, and the expected change sample; Table 4 reports results based upon Eq. (2)±(4). Tables 3 and 4, therefore, allow us to examine Hypotheses 1 and 2. In Table 3, the rst column reports results for all discount rate changes (unexpected and expected) over the ten event periods (from t 4 to t 5). The coe cient for ddr at time t (the trading period immediately following the announcement) is negative and signi cant at the one percent level which con rms evidence presented in prior studies that the discount rate changes are negatively correlated with equity returns. The magnitude of the parameter suggests that the stock returns decrease (increase) by 0.5% for every 10 basis points increase (decrease) in the discount rate. The R 2 of 34% is higher than that reported in Smirlock and Yawitz (1985). An examination of the coe cients for ddr for t 1 to t 5 reveals that the bulk of the e ect occurs during the rst period following the announcement although some reversal is observed in period t 2. The reversal is small ± 0.12% change in the stock returns for every 10 basis point changes in the discount rate (this point will be further elaborated upon later). Although the coe cient for period t 4 is negative and signi cant at the 5% level, no pattern of responses to the discount rate changes are observed before the information release. Furthermore, the correlation coe cient between R t and R t 4 is not statistically signi cant, therefore, the higher volatility seems to be due to unrelated events or due to uninformed trading associated with the upcoming news release. Columns 3 and 5 report results based upon partitioning the sample into unexpected and expected changes. Because only unexpected changes are regarded as new information, the signi cant coe cient for period t reported in Column 1 is anticipated to be driven by unexpected but not expected changes. The results reported in Column 3 are consistent with this conjecture. That is, the unexpected discount rate changes are associated with signi cant and negative changes in equity prices; the coe cients for the unexpected change sample other than for period t are generally not statistically signi cant except that a 7 Although parameter magnitudes vary between these two measures, the conclusions are not materially di erent. Smirlock and Yawitz (1985) also report similar results between these two measures.

C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 909 Table 3 Impact of discount rate changes on the Dow±Jones industrial index intra-day equity returns from 1973 to 1996 based on Eq. (1) Sample: Intra-day returns 1 2 3 4 5 6 Whole (N ˆ 68) R 2 Unexpected (N ˆ 46) R 2 Expected (N ˆ 22) R 2 Rt 4 0.0872 0.06 0.0571 0.03 0.1873 0.23 ( 2.07)** ( 1.10) ( 2.43)** Rt 3 0.0794 0.03 0.0348 0.01 0.1831 0.11 ( 1.45) ( 0.55) ( 1.60) Rt 2 0.0676 0.02 0.0979 0.04 0.0338 0.00 ( 1.05) ( 1.33) (0.25) Rt 1 0.0744 0.01 0.0185 0.00 0.2078 0.07 ( 0.73) ( 0.14) ( 1.22) Rt 0.5143 0.34 0.6440 0.50 0.2722 0.09 ( 5.85)*** ( 6.68)*** ( 1.45) Rt 1 0.0526 0.01 0.0433 0.01 0.0271 0.00 ( 0.75) ( 0.51) ( 0.20) Rt 2 0.1181 0.05 0.1704 0.10 0.0401 0.00 (1.87)* (2.15)** (0.36) Rt 3 0.0806 0.03 0.0322 0.02 0.1769 0.21 ( 1.52) ( 0.46) ( 2.29)** Rt 4 0.0741 0.02 0.0547 0.01 0.0670 0.02 ( 1.15) ( 0.67) ( 0.59) Rt 5 0.0627 0.01 0.0768 0.02 0.0966 0.02 ( 0.82) ( 0.86) ( 0.61) In this table, the dependent variable is the Dow±Jones industrial intra-day returns from 4 periods before (Rt 4) the announcement of discount rate change to 5 periods after (Rt 5) the announcement. Rt measures the stock returns of the trading period immediately after the information is released. The parameter estimates reported represent the coe cients on the regressor ddrt in Eq. (1). The equation is estimated for the whole sample (Column 1), the unexpected sample (Column 3), and the expected sample (Column 5). The sample period begins January 1973 and ends January 1996. Student t- statistics are in the parentheses and ***, **, and * denote signi cance at the 1%, 5% and 10% levels, respectively.

910 C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 Table 4 Impact of discount rate changes on the Dow±Jones industrial index intra-day equity returns from 1973 to 1996 based on Eq. (2)±(4) Hourly Returns 1 2 3 4 5 6 7 ddrut ddret D1 D2 D3 F-stat. R 2 Rt 4 0.0513 0.1631 1.46 0.08 ( 1.00) ( 2.16)** Rt 3 0.0333 0.1768 1.44 0.05 ( 0.50) ( 1.81)* Rt 2 0.1038 0.0089 0.64 0.03 ( 1.32) (0.08) Rt 1 0.0160 0.1976 0.65 0.02 ( 0.13) ( 1.07) Rt 0.6390 0.2510 4.25** 0.38 ( 6.09)*** ( 1.63) Rt 1 0.0504 0.0571 0.00 0.01 ( 0.58) ( 0.45) Rt 2 0.1653 0.0183 1.12 0.07 (2.14)** (0.16) Rt 3 0.0331 0.1808 1.63 0.06 ( 0.51) ( 1.91)* Rt 4 0.0623 0.0991 0.07 0.02 ( 0.78) ( 0.85) Rt 5 0.0667 0.0541 0.01 0.01 ( 0.71) ( 0.39) Rt 0.6901 0.2944 0.0692 0.1670 0.40 ( 2.87)*** ( 1.14) (0.25) (1.17) Rt 0.6605 0.2732 0.0455 0.1848 0.1083 0.40 ( 2.73)*** ( 1.05) ( 0.16) (1.28) (1.01) In this table, the dependent variable is the Dow±Jones intra-day returns from 4 periods before (Rt 4) the announcement of discount rate change to 5 periods after (Rt 5) the announcement. Rt measures stock returns for the period immediately after the information is released. Regressor ddrut measures unexpected changes in discount rates while ddret represents expected changes in discount rates, and they are derived by multiplying ddrt by a binary variable such that its value is 1 if discount rate change is policy (technical) oriented and 0 if technical (policy). D1 is a dummy variable which takes a value of 1 if the discount rate change occurred during periods of decreasing discount rates, and 0 during periods of increasing discount rates. Dummy variable D2 measures reversal in discount rate changes. Student-t statistics are in the parentheses and ***, **, and * denote signi cant at the 1%, 5%, and 10% levels, respectively. F-statistics test parameter equality of variables ddrut and ddret. ** denote signi cance at the 5% level.

C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 911 sign reversal occurs in period t 2 ± indication of a correction of an initial overreaction. The signi cant R t 4 in the whole sample equation is, therefore, driven by the expected change equation which is more consistent with the conjecture of an unrelated event. We also estimated the Pearson correlation coe cients between R t and R ti. None of the correlation coe cients are signi cant except that of t 2. Therefore, we conclude that no leakage of information is detected, but some correction of the initial overreaction to the unexpected changes in discount rate information is observed. Because the Dow±Jones Index consists of only very large blue chips, it is not likely that the reversal is caused by the nonsynchronous trading problem. The price reversal, however, does not necessarily constitute market ine ciency unless it generates abnormal pro t. The magnitude of the parameter suggests that stock returns change, on average, by 0.17% for every 10 basis point change in the discount rate. This magnitude does not appear to be pro table enough to cover all transaction costs which include brokerage fees and bid±ask spreads (bid±ask spread alone, on average, is 0.69% for large-cap stocks, see Reilly (1994)). The short-term price reversal is also found in Atkins and Dyl (1990); they conclude that it is not economically pro table after taking into account all transaction costs. Column 5 in Table 3 shows that the coe cient for the expected changes in the discount rates in period t is not signi cant, a nding consistent with prior studies that employed daily data. The coe cients for periods t 4 and t 3 are signi cant at the 5% level, but the lack of a pattern and the insigni cant cumulative returns leads us to conclude that these signi cant coe cients are probably induced by unrelated trading. This is particularly plausible because the changes in the discount rate is expected which should be fully anticipated by the market as evidenced by the insigni cant R t. Furthermore, our ndings of insigni cant return volatility and trading volume during these periods (reported in Tables 5 and 6) is consistent with this interpretation. Table 4 summarizes additional regression estimates based upon Eq. (2)±(4). Eq. (2) pools together the unexpected and expected changes while allowing for di erent coe cients on the two classes of discount rate changes. The variable ddr ut is derived by multiplying ddr t by a binary variable such that its value is 1 if the discount rate change is unexpected and 0 if the discount rate change is expected. A similar method is used to derive the variable ddr et. The results are basically consistent with those reported in Columns 3 and 5 of Table 3. That is, the unexpected discount rate changes are negatively and signi cantly associated with equity returns in period t. The coe cient for period t 2 is positive and signi cant ± suggesting some reversal of the initial response. The coe cient for the expected changes in discount rates in period t (in Column 2) is insigni cant, consistent with the results reported in Column 5 of Table 3. Column 6 of Table 4 reports F-statistics which test whether the parameters of the expected changes in the discount rates are equal to the parameters of the

912 C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 Table 5 Impact of discount rate changes on the Dow±Jones industrial index market volatility from 1973 to 1996 Market volatility (ddr ut ) 2 (ddr et ) 2 D 2 R 2 V t 4 0.0952 0.0309 0.1007 0.0990 (1.56) (0.44) (2.17)** V t 3 0.1394 0.1408 0.0940 0.0985 (1.76)* (1.55) (1.56) V t 2 0.0072 0.0845 0.0327 0.0114 (0.08) (0.77) ( 0.45) V t 1 0.3846 0.1963 0.0046 0.0769 (2.30)** (1.03) (0.04) V t 0.2637 0.2440 0.0824 0.0592 (1.67)* (1.34) (0.68) V t 1 0.0664 0.0664 0.0694 0.0255 ( 0.74) ( 0.65) (1.02) V t 2 0.0272 0.0711 0.0353 0.0144 ( 0.31) ( 0.71) ( 0.53) V t 3 0.0906 0.0171 0.0032 0.0239 (1.22) (0.20) (0.06) V t 4 0.0898 0.1044 0.0383 0.0252 ( 0.93) ( 0.94) ( 0.52) V t 5 0.1087 0.0775 0.0469 0.0205 (0.97) (0.60) (0.55) In this table, the dependent variable is a Dow±Jones Industrial Index intra-day market volatility measure de ned as the absolute value of the di erence in the intra-day return and the mean intraday return for the sample period from 1973 to 1996. To calculate the mean returns, only observations correspond to announcements periods are used. V t is the volatility measure on the period of the announcement. V t i is the volatility measure i period after the announcement. V t i is the volatility measure i period before the announcement. Exogenous variables are ddr 2 ut, ddr2 et, and D 2 which represent unexpected changes in discount rates squared, expected changes in discount rates squared, and dummy variable measuring the reversal of discount rate changes, respectively. Student-t statistics are in the parentheses, and ** and * denote signi cance at the 5% and 10% levels, respectively. unexpected changes in the discount rates. These results indicate that there is no di erence between these two parameters for any periods except that of period t. This reinforces our ndings in Columns 1 and 2 that equity returns respond only to unexpected changes in discount rates. The second to the last row of Table 4 reports the results from estimating Eq. 3. We added two additional exogenous variables to examine whether increasing the discount rates e ects equity prices di erently than decreasing the discount rates and whether the reversal of the discount rate changes e ect equity returns. It is evident that the coe cient of the unexpected discount rate changes remains highly signi cant and all other variables show no e ect on equity returns. More speci cally, the market does not perceive a rate increase

C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 913 Table 6 Impact of discount rate changes on trading volume from 1973 to 1996 Intraday volume abs(ddr ut ) abs(ddr et ) D 1 D 2 R 2 Vol t 4 5.4531 1.5621 0.03 (0.91) ( 0.24) Vol t 3 3.3329 1.0186 0.02 (0.56) ( 0.16) Vol t 2 4.8783 3.3947 0.01 (0.75) (0.48) Vol t 1 7.9668 6.0044 0.02 (0.88) (0.62) Vol t 25.5222 10.6145 0.08 (2.06)** (0.80) Vol t 1 7.0424 0.2424 0.03 (0.96) (0.03) Vol t 2 4.2012 3.7041 0.03 (0.60) ( 0.50) Vol t 3 3.3804 3.1814 0.03 (0.60) ( 0.53) Vol t 4 5.5179 2.7292 0.02 (1.11) (0.51) Vol t 30.1211 6.7732 21.8272 0.8763 0.29 (2.73)*** (0.57) (4.41)*** (0.13) In this table, the dependent variable is a measure of intra-day volume, which is calculated by dividing the NYSE intra-day volume by the total NYSE outstanding shares. Vol t measures the volume of the trading period immediately after the information is released. Regressor abs(ddr t )represent the absolute value of the discount rate changes. abs(ddr ut ) measures the absolute value of the unexpected changes in the discount rates, and abs(ddr et ) measures the absolute value of the expected discount rate changes. Sampling period begins January 1973 and ends January 1996. Student t-statistics are in the parentheses, and *** and ** denote signi cant at the 1% and 5% levels, respectively. to have di erential importance relative to a rate decrease; nor does the rate reversal convey more information. The last row of Table 4 reports results based upon Eq. (4). Dummy variable D 3 takes a value of 1 if the announcements were made on Friday, 0 otherwise. This allows us to test for a day-of-the-week e ect. The results show that unexpected changes remain highly signi cant, while neither the expected change e ect nor the Friday e ect are signi cant. Furthermore, because many of the Friday announcements and some of the weekday announcements were made after the market close, the returns associated with these announcements are, in e ect, returns during the non-trading periods. To control for this trading verses non-trading e ect, we employ regression analysis with dummy variables which control for this potential e ect.

914 C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 These empirical results, which are reported in footnote 8, continue to support our hypothesis. 8 These results are also consistent with the summary statistics reported in Tables 1 and 2 which show the magnitude of the announcements are not related to the timing of the announcement. One concern with the clustering of observations is that if the Federal Reserve made large discount rate change announcements after the market close, our results may be biased in favor of nding the relationship. To further alleviate this type of concern, we constructed 10 matching samples of close-to-open returns during non-announcement periods. The results show that the discount rate announcements have no impact on the returns for any of these 10 matching samples. Consequently, our ndings seem not to be dependent on the clustering of the timing of the announcements. Moreover, because we, in e ect, study the relationship between the magnitude of discount rate changes and stock returns (as oppose to announcement vs. no-announcement e ect), our results should not re ect spurious happenstance. 4.2. Market volatility and discount rate changes In recent years, the source of the market volatility has attracted substantial attention in the nancial literature. We continue this line of research by performing tests to examine Hypotheses 3A, 3B and 4 which address whether the discount rate change announcements contribute to market volatility and whether the market volatility persists. To test these hypotheses, we estimate Eqs. (5) and (6) and report the results in Table 5. In period t, the parameter estimate on the unexpected discount rate change e ect, (ddr ut ) 2, is positive and statistically signi cant at the 10% level. However, the expected discount rate changes show no causal relationship to the market volatility. Also, the dummy variable D 2, which measures the impact of discount rate change reversals, shows no e ect on market volatility at time t. 8 The following regression includes two additional dummy variables, D 4 and D 5, which have a value equal to 1 if the announcement was made after the close of trading on a weekday and on a Friday, respectively. They have a value of 0 otherwise. R t ˆ 0.7277 ddr ut 0.3109 ddr et 0.0717 D 1 +0.1365 D 2 0.2971 D 4 +0.1407 D 5, R 2 ˆ 0.43 ( 3.0) ( 1.2) ( 0.26) (0.95) ( 1.79) (1.24) In addition to this model, we also estimated two more regressions with the rst employing ``hourly'' returns (i.e., dividing the non-trading period returns by the number of hours during the non-trading periods), and the second adding a new dummy variable with a value equal to 1 if the announcement occurred during a period of economic expansion, 0 otherwise. Economic expansion (contraction) is de ned in accordance with the National Bureau of Economic Research. The rst test continues to provide support for our hypothesis that unexpected changes in the discount rate a ect stock returns, while expected changes do not. The second test shows that the economic cycle dummy variable is not statistically signi cant, and our original results are robust to this speci cation. These additional results are available from the authors.

C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 915 These ndings support the notion that unexpected public information does impact return variances (Harris, 1986b). Moreover, when public information announcements are anticipated which provides the market with no new information, the stock market volatility is una ected. We also nd that stock market volatility increases for the periods immediately preceding and after the announcement (periods t 1 and t). Moreover, the stock market volatility is sensitive to the unexpected changes in the discount rates; but not sensitive to the expected changes. Our ndings suggest that speculations about the rate changes, such as the timing of the changes and the magnitude of the changes, causes the market to react in the period immediately before the Federal Reserve announcement, and the reaction continues into the period after the Fed made the announcements. Market volatility in all other periods is not in uenced by the discount rate change announcement which lends support to the argument that the stock market incorporates discount rate change information within a short period of time. 9 Overall, our results in Table 5 are not consistent with Berry and Howe (1994) who nd that public information is not statistically related to price volatility. They acknowledge that combining market wide information and rm speci c information in their measurement could result in a ``wash out'' in the process of measuring aggregate returns. Our results, however, are supportive of Jones et al.õs (1994) ndings that public (versus private) information is the major source of shortterm return volatility. 4.3. Trading volume and discount rate changes In this section of the paper, we examine Hypothesis 5 which relates public information to trading. Because we have observed that the expected discount rate changes have an insigni cant impact on stock returns, the primary question addressed in this section is: does new (unexpected) public information move stock prices with or without trading? As an extension to this question, we also investigate: if trading occurs, does it occur only in the current period or also in the future periods (as one would expect in the case of private information)? We examine these issues by estimating Eqs. (7) and (8), and the results are reported in Table 6. Several conclusions can be drawn from Table 6: (1) Unexpected public information induces trading for the period immediately after the information is 9 Because we de ne volatility as the di erence between announcement jõs return and the mean returns of all announcements in period i, the estimated discount rate change impact is in e ect a measurement of the e ect of the magnitude of discount rate changes. We also calculate volatility by taking the di erence between announcement jõs return and the mean returns of all observations in period i ± announcement and non-announcement returns. The results, as expected are slightly stronger because it re ects both the magnitude e ect and the announcement e ect.

916 C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 released. The larger the magnitude of the discount rate changes, the heavier the trading. (2) As anticipated, expected discount rate changes, representing existing public information, have no impact on the trading volume for the current period nor for any other periods. (3) Public information induces trading only in the current period but not future periods. Therefore, the signi cant price changes in periods other than time t found in Tables 3 and 4 are less credible without the support of volume data. The volume results, therefore, tend to lend further support for the e cient market hypothesis. 10 (4) More trading has occurred during the decreasing discount rate periods than the increasing discount rate periods as evidenced by the signi cant parameter estimate for D 1. This result is related to Wood et al. (1985) who nd that the ratio of volume and price changes is higher for downsticks although others have found otherwise (Harris (1986a); also see Karpo (1987) for an overview of the relationship between price changes and volumes). Overall, our ndings that public information causes trading is more consistent with the arguments of Foster and Viswanathan (1993) and Harris and Raviv (1993). 4.4. Pre- and post-1979 debate Both Roley and Troll (1984) and Smirlock and Yawitz (1985) conjecture that the markets do not respond to discount rate changes before 1979 due to the di erent Federal Reserve operating procedures. 11 Cook and Hahn (1988), however, argue that as long as the market participants understand the signals contained in the discount rate announcements and use them to revise their expectations of the future path of the federal funds rate, the Federal Reserve operating procedure is irrelevant. Thus, they nd results in con ict to those reported in earlier studies. We re-examine Cook and HahnÕs (1988) ndings using higher frequency data. Our results are reported in Table 7. Panel A presents results of regressions based upon pre-1979 data and Panel B presents results based upon post-1979 data. From Panel A, it is clear that unexpected changes in the discount rates do have a negative e ect on equity returns while expected changes have no e ect. The unexpected changes in discount rates explain 32% of the equity price variation. This nding is more consistent with the arguments set forth in Cook and Hahn (1988) who conjecture that the Federal Reserve operating procedure is irrelevant and that the unexpected changes in discount rates do in uence T-bill rates. 10 In contrast to our ndings, Morse (1981) nds that abnormally high volume persists for sometime after earnings announcements. 11 For the relationship between discount rate policy and Federal Reserve operating procedures, see Hakkio and Pearce (1992).

C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 917 Table 7 Impact of discount rate changes on the Dow±Jones industrial index intra-day equity returns: Pre- 1979 vs. post-1979 results Intra-day returns ddr t ddr ut ddr et R 2 Panel A: Pre-1979 data R t (N ˆ 27) 0.3587 0.15 ( 2.11)* R t (N ˆ 14) 0.5284 0.32 ( 2.49)* R t (N ˆ 13) 0.1169 0.01 ( 0.38) R t (N ˆ 27) 0.4465 0.1709 0.17 ( 2.25)* ( 0.62) Panel B: Post-1979 data R t (N ˆ 41) 0.5342 0.37 ( 4.75)*** R t (N ˆ 32) 0.6514 0.52 ( 5.66)*** R t (N ˆ 9) 0.1100 0.01 ( 0.23) R t (N ˆ 41) 0.6514 0.2282 0.41 ( 5.05)*** ( 1.09) Panel C: Combined data Intra-day returns ddr ut ddr et ddr ut DUM ddr et DUM R 2 R t (N ˆ 68) 0.6864 0.2714 0.1808 0.0511 0.39 ( 5.52)*** ( 1.44) (0.74) (0.14) In this table, the dependent variable is the Dow±Jones intra-day returns (R t ). Regressors are changes in discount rates (ddr t ), unexpected changes in discount rates (ddr ut ), and expected changes in discount rates (ddr et ). When both ddr ut and ddr et are in the same regression, data are pooled and ddr ut (ddr et ) are derived by multiplying ddr t by a binary variable which takes a value of 1 or 0 depending on the types of discount rate changes. Variable DUM is a binary variable which takes a value of 1 or 0 depending on whether the discount rate changes occurred pre-1979 or post-1979. Student-t statistics are in the parentheses, and ***, ** and * denote signi cance at the 1%, 5%, and 10% levels, respectively. Panel B of Table 7 reports the results based upon post-1979 data. Again, these results support the contention that unexpected changes in discount rates a ect equity returns. All coe cients associated with unexpected discount rate changes are statistically signi cant at the one percent level and bear the right sign. Unexpected changes in the discount rate alone explains 52% of the variation in equity returns. Thus, the ndings reported in Roley and Troll (1984) and Smirlock and Yawitz (1985), both of which employ daily data (close-to-close), are questioned by the evidence found in this study. Finally, we combined all data but allow the slope coe cients of variables ddr ut and ddr et to re ect pre-1979 and post-1979 data. A binary variable (DUM) is

918 C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 de ned as either 1 or 0 depending upon whether the data corresponds to pre- 1979 or post-1979 periods. Therefore, the coe cients of variables ddr ut DUM and ddr et DUM measure the di erences in the slope coe cients between the two sub-periods for the unexpected and the expected changes in the discount rates, respectively. The results are reported in Panel C of Table 7. The unexpected changes in the discount rate in the pooled sample continue to be signi cant at the 1% level. None of the slope coe cient dummy Table 8 Impact of discount rate changes on the Dow±Jones utility index intra-day equity returns from 1973 to 1996 Hourly returns 1 2 3 4 5 6 ddr ut ddr et D 1 D 2 F-stat. R 2 R t 4 0.0038 0.0029 0.00 0.00 (0.07) (0.04) R t 3 0.0915 0.0938 0.00 0.09 ( 2.05)** ( 1.43) R t 2 0.0239 0.0321 0.01 0.01 ( 0.44) (0.40) R t 1 0.0066 0.2105 2.72* 0.06 (0.09) ( 1.96)** R t 0.5306 0.2363 3.01* 0.35 ( 5.61)*** ( 1.71)* R t 1 0.2982 0.1063 1.91 0.20 ( 3.85)*** ( 0.94) R t 2 0.1579 0.0122 3.01* 0.11 (2.89)*** (0.15) R t 3 0.0313 0.0018 0.18 0.01 ( 0.72) ( 0.03) R t 4 0.0084 0.0299 0.26 0.00 (0.20) ( 0.49) R t 5 0.0513 0.0116 0.22 0.02 ( 1.08) ( 0.17) R t 0.5329 0.2356 0.0046 0.0915 0.35 ( 2.44)** ( 1.01) ( 0.02) (0.71) In this table, the dependent variable is the Dow±Jones utility index intra-day returns from 4 periods before (R t 4 ) the announcement of discount rate change to 5 periods after (R t 5 ) the announcement. R t measures stock returns for the period immediately after the information is released. Regressors ddr ut measures unexpected changes in discount rates while ddr et represents expected changes in discount rates, and they are derived by multiplying ddr t by a binary variable such that its value is 1 if discount rate change is policy (technical) oriented and 0 if technical (policy). D 1 is a dummy variable which takes a value of 1 if the discount rate change occurred during periods of decreasing discount rates, and 0 during periods of increasing discount rates. Dummy variable D 2 measures reversal in discount rate changes. Student-t statistics are in the parentheses and ***, **, and * denote signi cance at the 1%, 5%, and 10% levels, respectively. F-statistics test parameter equality of variables ddr ut and ddr et. * denotes signi cance at the 10% level.

C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 919 variables are signi cant, which reinforces our ndings that the Federal Reserve operating procedures are irrelevant. 4.5. Some empirical results for the utility industry This section reports additional results for the utility industry. While the utility industry represents only one of the many segments of the equity market, it is generally believed to be more sensitive to changes in interest rates. Furthermore, this separate analysis is justi ed because the cost of equity plays an important role in the utility rate decision making, and because there exists the possibility that utility stocks may have a di erent investor clientele. Table 8 reports the empirical results of the impact of discount rate changes on the returns of utility stocks. The results can be summarized as: (1) Similar to the results on the industrial index, the unexpected discount rate changes a ect utility returns. (2) In addition to the reaction of equity prices to the discount rate changes in period t, a one period delayed response (in period t 1) is also observed. The magnitude of the cumulative parameters of time t and t 1 for the utility industry ( 0.8288) is slightly larger than that of the industrial index ( 0.8043) showing a greater sensitivity for the utility stocks. (3) A signi cant and positive sign for the two period ahead returns (R t 2 ) suggests a correction of a temporary overreaction. This nding is similar to that of the industrial sample although the correction seems to be stronger for the utility sample. It is also interesting to note that after the correction, the cumulative parameter estimates (from time t to t 2) for the utility index ( 0.67) is only slightly larger than the industrial index ( 0.64). (4) Although not as strong as the unexpected changes, the utility stock returns also react to the expected changes in period t and t 1. This e ect, however, disappears when both the trend and the turning point dummy variables are included in the equation (bottom line of Table 8). Furthermore, as Smirlock and Yawitz (1985) have pointed out, although discount rate changes for technical purposes is expected, the timing of the change is subject to uncertainty. Table 9 reports utility stock volatility as a result of changes in the discount rate. Signi cant and positive parameters are found in period t for the unexpected changes and in period t 1 for the expected changes. This roughly corresponds to the signi cant parameters found in Table 8 for the return equations, although volatility changes are more short-lived than the return changes. Overall, we nd utility stocks to have a slightly stronger reaction to changes in the discount rate. This can be seen from the lengthier response to the unexpected changes and some observable reaction to the expected changes in discount rates. The debate over the market e ciency pertinent to the utility industry can be traced back to the predictive ability of the Salomon Brothers Electric Utility Model (see Bower and Bower, 1984).

920 C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 Table 9 Impact of discount rate changes on the Dow±Jones utility index market volatility from 1973 to 1996 Market volatility (ddr ut ) 2 (ddr et ) 2 D 2 R 2 V t 4 0.0127 0.0150 0.0401 0.0083 (0.17) ( 0.17) (0.70) V t 3 0.0113 0.0185 0.0302 0.0161 (0.23) ( 0.32) ( 0.80) V t 2 0.1289 0.0293 0.0178 0.0693 (1.79)* ( 0.36) ( 0.32) V t 1 0.1422 0.2211 0.0122 0.0707 (1.49) (2.02)** (0.17) V t 0.3760 0.0103 0.0417 0.1086 (2.61)*** (0.06) (0.38) V t 1 0.0629 0.0113 0.0365 0.0110 (0.64) (0.10) ( 0.49) V t 2 0.0139 0.1686 0.0442 0.0973 (0.22) ( 2.31)** (0.91) V t 3 0.0464 0.0058 0.0060 0.0197 (1.01) ( 0.11) (0.17) V t 4 0.0197 0.0747 0.0440 0.0452 ( 0.42) ( 1.40) (1.24) V t 5 0.0792 0.1079 0.0243 0.0587 (1.39) (1.65) (0.56) In this table, the dependent variable is a Dow±Jones utility index intra-day market volatility measure de ned as the absolute value of the di erence in the intra-day return and the mean intraday return for the sample period from 1973 to 1996. To calculate the mean returns, only observations corresponding to announcements periods are used. V t is the volatility measure on the period of the announcement. V t i is the volatility measure i period after the announcement. V t i is the volatility measure i period before the announcement. Exogenous variables are (ddr ut ) 2, (ddr et ) 2, and D 2 which represent unexpected changes in discount rates squared, expected changes in discount rates squared, and dummy variable measuring the reversal of discount rate changes, respectively. Student-t statistics are in the parentheses, and ***, **, and * denote signi cance at the 1%, 5%, and 10% levels, respectively. We do not know the exact cause of this di erence in e ciency; however, we o er the possibility that it may be due to investor clientele e ects. There is evidence that the year-end stock market anomaly is attributed to the trading of individual investors who often are uninformed (Dyl and Maberly, 1992). To investigate the di erential investor clientele, we obtained institutional ownership data from Value Line for each of the 30 Dow±Jones industrial rms and the 15 Dow±Jones utility rms as de ned in the Daily Stock Price Record. The results are reported in Table 10. In 1985, institutional owners, who are considered more informed and rational, held 48.98% of the industrial rms, but only 32.26% of the utility rms. The di erence in this institutional ownership is statistically signi cant at the 1% level. Moreover,

C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 921 Table 10 Institutional ownership di erences between Dow±Jones industrial and utility rms Industry Mean Minimum Maximum t-statistics 1985 (3rd quarter) Industrial 48.98% 16.08% 65.80% 4.56 (0.00) Utility 32.26% 14.76% 58.59% 1995 (3rd quarter) Industrial 57.46% 30.97% 84.87% 4.78 (0.00) Utility 39.45% 29.09% 65.40% This table compares the institutional ownership di erences between the Dow±Jones industrial rms and the Dow±Jones utility rms. t-statistics test whether the mean institutional ownership between these two industries are di erent. p values are in the parentheses. although the percentage of institutional ownership increased for both types of rms by 1995, the di erence between the industrial rms (57.46%) and 12 utility rms (39.45%) continues to be statistically signi cant. 5. Conclusions This study examines the e ect of discount rate changes on equity returns, market volatility, and trading volume employing higher frequency (intra-day and close-to-open) data from 1973 to 1996. We are able to more accurately identify if and when the stock market responds to the release of the discount rate change information. More importantly, studying the market volatility and trading volume sheds additional light on the information literature. Our ndings can be summarized as follows: (1) Equity returns respond negatively and signi cantly to the unexpected announcements of discount rate changes, while the expected changes generally have no bearing on the equity returns. On average, stock returns change by 0.5% for every 10 basis point change in the discount rate. (2) Equity returns measured by the Dow±Jones industrial index respond rather rapidly to the unexpected announcement of discount rate changes. Within the trading period/hour after the information is released, the market impounds the information, although some evidence of a price reversal is observed. The size of the reversal, however, does not justify the total transaction 12 We also test the impact of discount rate changes on the utility returns partitioned into pre- 1979 and post-1979 sample. The results are comparable to that of the industrial stocks. That is, Federal Reserve operating procedure is irrelevant. Both pre-1979 and post-1979 data show a signi cant response of stock returns to changes in discount rates.

922 C.R. Chen et al. / Journal of Banking & Finance 23 (1999) 897±924 costs which include brokerage fees and bid-ask spreads. This result is stronger than that reported in Smirlock and Yawitz (1985) who contend that equity prices adjust to the announcements in approximately two days. Our interpretation of this nding is further supported by serial correlation tests. (3) When we break the sample into pre- and post-1979 subperiods to re-test the impact of the discount rate changes due to di erential Federal Reserve operating procedures, our evidence is supportive of the results reported in Cook and Hahn (1988). The unexpected discount rate changes have a negative and signi cant e ect on equity returns irrespective of Federal Reserve operating procedures. (4) For the utility industry, the negative e ect of discount rate changes lasts for two periods and a subsequent reversal is also observed. However, the overreaction and the subsequent correction is completed within three trading periods. These ndings seem to suggest that the utility industry stocks are slightly less e cient than the industrials. The results may be related to the investor clientele. We nd utility rms to have signi cantly lower percentages of institutional ownership than the industrial rms. (5) Not only a ecting equity returns, the unexpected discount rate changes also contribute to higher market volatility. These ndings are not supportive of French and RollÕs (1986) private information hypothesis and are in contrast to studies which found no relationship between public information arrival and market volatility (e.g., Berry and Howe, 1994). Our results, however, are supportive of Jones et al. (1994) ndings that public information, not private information, is the major source of return volatility. Our ndings of a shortlived market volatility suggests that the market incorporates information fully within a short period of time, which tends to lend more support for the e cient market hypothesis. (6) Unexpected discount rate changes also induce trading which is more supportive of the contention that public information causes price changes with trading (e.g., Harris and Raviv, 1993; Foster and Viswanathan, 1993) as oppose to the contention of French and Roll (1986) that private information causes trading. Increased trading volume due to unexpected public information, however, occurs only in the current period. References Admati, A., 1985. A noisy rational expectations equilibrium for multiasset securities markets. Econometrica 53, 629±57. Atkins, A.B., Dyl, E.A., 1990. Price reversals, bid±ask spreads, and market e ciency. Journal of Financial and Quantitative Analysis 25, 535±547. Berry, T., Howe, K.M., 1994. Public information arrival. Journal of Finance 49, 1331±1346. Blume, L., Easley, D., O'Hara, M., 1994. Market statistics and technical analysis: The role of volume. Journal of Finance 49, 153±181.

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