Department of Economics Working Paper Series. The Impact of Monetary Policy Surprises on Australian Financial Futures Markets

Transcription

1 Department of Economics Working Paper Series The Impact of Monetary Policy Surprises on Australian Financial Futures Markets Xinsheng Lu, Ying Zhou, and Mingting Kou 2013/01 1

2 The Impact of Monetary Policy Surprises on Australian Financial Futures Markets Author Names: Xinsheng Lu, Ying Zhou, Mingting Kou Xinsheng Lu Department of Economics and Finance, SEM, Tongji University, Shanghai, China Ying Zhou (corresponding author) Department of Economics, Auckland University of Technology, Auckland, New Zealand Postal Address: Private Bag 92006, Auckland 1142, New Zealand Tel: ext Fax: ying.zhou@aut.ac.nz Mingting Kou Business School, Datong University, China Abstract This paper investigates the impact of unanticipated Australian monetary policy changes on AUD/USD exchange rate futures, 3-year and 10-year Australian Treasury bond futures, during the period from January 1997 to April Our study contributes to the literature by using both 30-day and 90-day bank accepted bill (BAB) rates to disentangle anticipated from surprise cash rate target changes in the Australian money market, and by concurrently modelling the effects of monetary surprises and other key macroeconomic announcements in Australia. The empirical results suggest that the 30-day BAB rate is served as the best proxy for the expected monetary policy actions. Further, the effect of Australian monetary surprises on volatility of all futures instruments is significant and complete when other key macroeconomic announcements are considered simultaneously. Keywords: monetary policy surprises; financial futures; asset return volatility JEL classifications: C22, E44, G12, G14 2

3 1. Introduction The increasing interaction between financial markets and monetary policy is of great concern to investors, financial institutions, and monetary authorities. For financial market participants, assessing financial market responses to changes in monetary policy is essential to maximising the returns to portfolio and minimising the exposures to risk. Concomitantly, understanding the financial market reactions to the central bank s monetary policy stance enables central banks to learn the efficiency of the monetary transmission mechanism and to formulate effective monetary policy. The main objective of this paper is to investigate the impact of Australian monetary surprises on three important financial futures contracts, namely AUD/USD exchange rate futures, 3-year and 10-year Australian Treasury bond futures. The present research has several novel features. First, unlike many previous studies examining the overall impact of the RBA s cash rate announcement effect, this paper probes deeper into the unanticipated element of the announcement derived from 30-day and 90-day bank accepted bill (BAB) rates. Second, we use an extended threshold GARCH (T-GARCH) model to incorporate the effect of non-monetary announcements within the Australian economy. This makes a distinctive contribution to the literature, as very few of existing studies have actually explored the impacts of monetary surprises when other macroeconomic releases are also present, in particular in the Australian context 1. 1 The study carried out by Flannery and Protopapadkis (2002) examines the impact of the unanticipated component in 17 macroeconomic announcements on stock market return volatility in the US. However, the money aggregate rather than the Federal funds rate is selected as part of macro series announcements. Moreover, the announcement surprises in their study are based on market surveys rather than econometric models. 3

4 A third novel feature is that our model allows for the further exploration of the lagged effects of the cash rate target movements on financial futures markets. Finally, compared with existing studies, our data spans a much broader period from January 1997 to April This period covers RBA s policy communication procedures both pre-january 1998 and post- December 2007, as well as the Asian financial crisis and the more recent global financial crisis. Overall, our results indicate that, for the expected changes in Australian cash rate target, 30-day BAB rate is served as a better proxy than 90-day BAB rate. Further, the RBA s target rate news appears to have had a stronger impact on the AUD/USD exchange rate futures contract, which is consistent with the existing literature. In addition, when other key macroeconomic releases are incorporated, the effect of Australian monetary surprises on the volatility of all futures markets is found to be significant and complete. The rest of the paper is structured as follows. The next section gives a brief review of literature including their key findings. Section 3 discusses the methodology employed in our study. Section 4 provides the description of the data and the measurement of Australian cash rate surprises, and Section 5 reports the empirical results. Section 6 concludes the paper. 2. Literature Review Overall, there exists a large body of literature on how monetary policy announcements affect interest rates and stock markets. One strand of this literature is concerned with monetary news effects in the US market. In particular, since the work of Krueger and Kuttner 4

5 (1996) 2, a number of studies have used changes in the Fed funds futures contract rate to approximate the unexpected component of US monetary policy actions. Among many others, Poole and Rasche (2000) find that interest rates do not respond to the anticipated component of changes in the intended funds rate. Kuttner (2001) shows that the response of market interest rates to the surprise element of Fed policy is substantially stronger than its response to expected monetary policy actions, although such response does not apply to interest rates with a maturity beyond five years. Bonfim (2003) highlights the significance of monetary policy surprises in boosting stock market volatility, with unanticipated rises in Fed funds target rate exerting a larger impact on S&P volatility than unanticipated falls. Gulley and Sultan (2003) demonstrate that positive and negative changes in the Fed funds futures rate produce asymmetric effects on the stock market. Bernanke and Kuttner (2005) suggest a strong and consistent response of the stock market to monetary policy surprises, with an unexpected 25-basis-point rate cut typically associated with one percent increase in broad stock indexes. Although the prices of Fed funds futures contracts have been commonly selected to gauge monetary policy surprises in the US market, futures contracts over the monetary policy rates are not entirely available in the Australian market during our sample period from January 1997 to April According to Kearns and Manners (2006), the bank bill interest rates provide a good measure of monetary policy surprises for Australia. Further, Lu et al. (2009) utilises the 30-day bank bill rate as a proxy to identify the surprise element of Australian monetary policy. In the work of Kim and Nguyen (2008), the surprise component of Australian monetary announcement is equivalent to the difference between the actual rate 2 According to Krueger and Kuttner (1996), the Fed funds futures rate is served as an efficient predictor of the Federal funds rate changes. 5

6 change announced and the market-based expectations drawn from the financial press reports. More recently, Smales (2012) examines the reaction of Australian interest rate futures market to unanticipated changes in RBA monetary policy over the period , with the market expectations on RBA monetary policy decisions derived from short-end 30-day interbank futures 3. Another strand of literature endeavours to explain domestic stock market volatility by taking into account the influence of foreign news. Notably, Connolly and Wang (2003) study the impact of both domestic and foreign news on stock returns between the USA, Japan, and the UK. They argue that foreign macroeconomic news is a more important factor than domestic news in explaining domestic stock volatility. In an Irish context, Bredin et al. (2004, 2005) concentrate on the effect of US monetary policy surprises on Irish interbank rates and stock market volatility. Kim and Nguyen (2008) consider the impact of interest rate news from the RBA and the U.S. Fed on the Australia financial markets during the period from 1998 to 2006, and they find that the Fed s target rate surprises have reduced the volatility in the Australian markets. In addition, considerable efforts have also been devoted to exploring the impact of monetary policy shocks on foreign exchange markets. Newby (2002) finds that foreign exchange rates are hardly influenced by unexpected interest rate changes using a vector autoregressive approach. By introducing the 3-month Treasury bill rate as a measure of the unanticipated component of monetary policy action in Australia, Canada, and New Zealand, Zettelmeyer (2004) favours the conventional view of the exchange rate appreciation arising 3 However, the 30-day interbank futures data were not available until late Instead, 30-day and 90-day BAB rates are employed in our study to measure the expected changes in the RBA s target rate. 6

7 from contractionary monetary shocks. Using an event study with intraday data for Australia, Canada, New Zealand, and the United Kingdom, Kearns and Manners (2006) conclude that the extent to which monetary surprises affect the exchange rate is determined by the relevance of such surprises to the formulation of future monetary policy expectations. Kim and Nguyen (2008) show that the unexpected increase in the target rate appreciates the USD/AUD exchange rate in the sport and 1- and 3-month forward markets, although the news effect is stronger at the forward exchange rates. In general, it is evident from this review of the literature that relatively less work has been done on the response of Australian financial futures markets (in particular exchange rate futures) to unexpected monetary policy changes. In addition, none of the existing work has considered the potential effects of other macroeconomic releases within Australia. Our paper attempts to address this oversight and enrich the literature by investigating RBA s target rate news effect on the three classes of financial futures assets in Australia, including AUD/USD exchange rate futures, 3- and 10-year Treasury bond future contracts. To the authors best knowledge, our research represents the first attempt to model the combined effect of Australian monetary surprises and key macroeconomic announcements on Australian financial futures markets, with the surprise component of the RBA target rate changes derived from 30-day and 90-day bank accepted bill rates. 7

8 3. Methodology The methods used to measure the financial markets reactions to monetary policy changes mainly include the event-study approach 4 (see Cook and Hahn, 1989; Kuttner, 2001; Bonfim, 2003; Bernanke and Kuttner, 2005; and Lu et al., 2009), the vector autoregression (VAR) approach 5 (see Bernanke and Blinder, 1992; Thorbecke, 1997; and Bagliano and Favero, 1999), the identification through heteroskedasticity approach (see Rigobon, 2003; Rigobon and Sack, 2004; and Serwa, 2006), and the autoregressive conditional heteroskedasticity (ARCH) methodology developed by Engle (1982) and generalised by Bollerslev (1986). Since Bollerslev (1986), the generalised autoregressive conditional heteroskedasticity (GARCH) approach has been widely used for time series analysis of the financial market volatility (for example, see Li and Engle, 1998; and Fiser and Horvath, 2010). However, the basic GARCH (1,1) model implies a geometric decay in the volatility autocorrelation structure, which makes it difficult for the model to accommodate strong regular cyclical patterns often found around news disclosure days. 6 Another drawback of the standard GARCH model is that it can hardly capture the potential asymmetric leverage effect of negative shocks from various news announcements. Our study employs a methodology that allows for asymmetry while keeping the GARCH tractability. More specifically, we develop an extension of the T-GARCH model based on 4 According to Rigobon and Sack (2004), the event-study estimates contain biases when some important explanatory variables are ignored in the regression. Such biases often result in the underestimation of the policy effect on stock prices and the overestimation of the policy effect on Treasury yields. 5 Rudebusch (1998) finds that the VAR estimates of monetary policy surprises are neither precise nor correlated with funds rate shocks derived from forward-looking financial markets. 6 Ederington and Lee (2001) argue that the coefficients of past shocks estimated by the GARCH (1,1) model with high frequency data tend to underestimate the influence of the most recent and more distant return innovations and overestimate the influence of the shocks at the intermediate lags. 8

9 Zakoian (1994), in order to deal with the leverage effect of market volatility from negative shocks, and accommodate the regular cyclical patterns as well as the potential transitory component of return volatility on the announcement day. Further, enlightened by Ederington and Lee (2001) and Li and Engle (1998), we also take into account the effect of key macroeconomic announcements. These macroeconomic announcements include the growth rate of gross domestic product (GDP), the consumer price index (CPI), and the employment report (EMP) published by the Australian Bureau of Statistics (ABS). We consider Australian monetary policy surprises, in conjunction with other available information flows, using a single T-GARCH model as follows: R i,t = b i,0 + b i,1 R i,t-1 + b 2 M t + t (1) where t Φ t-1 ~N (0, h t ) h t,1 = ω + α t β h t-1 + γ I - t-1 t θ i M t-i (2) i 0 In equation (1), the dependent variable R i,t is the daily returns from the financial market i from day t-1 to day t. The explanatory variables include the daily returns of the financial asset on the previous day R i,t-1, and the unanticipated cash rate target changes M t. Equation (2) specifies the benchmark TGARCH (1,1) for conditional variance. Φ t-1 represents the information set available at the end of day t-1. In equation (2), I - t-1 is dummy variable, I - t-1 = 1 if t < 0, I - t-1 = 0 otherwise. Parameter α captures the ARCH effect while β captures the persistence in volatility. Parameter γ is used to catch the asymmetric effect of asset return volatility, and a significant γ implies that the negative innovation has a greater effect than the positive shocks. 9

10 In order to test the speed within which returns and volatility of financial markets incorporate the news content of the cash rate target changes, we assess the lagged effects of the cash rate target movements on interest rate and foreign exchange rate futures markets. Three-day lags are chosen, as we aim to find out whether the lagged effect of the cash rate target movements on the selected financial futures markets dies out within a three-day period. The contemporaneous and lagged effects of cash rate target surprises are captured by parameter θ i in equation (2), where i = (0, 1, 2, 3). Equations (1) and (2) can be used to both accommodate the cyclical patterns of monetary policy shocks, and address the potential asymmetric effect of negative shocks from various policy announcements. Thus, equations (1) and (2) are served as our benchmark model. Next, we move on to the joint effect of monetary policy releases and key macroeconomic news announcements on AUD/USD exchange rate futures, 3-year and 10-year Australian Treasury bond futures contracts. We are particularly interested in the relative importance of each information flow, as well as the interdependence and interaction of information flow in determining the daily return volatility. Three streams of information flow are considered, such as information flow of past volatility, information flow of monthly monetary policy review and release of the Reserve Bank s policy stance, and information flow of key domestic macroeconomic announcements. Thus, the extended variance equation can be specified as follows: 2 h t = ω + α t-1 + βh t-1 + γ I - t t-1 + θ i MD t-i + j 3 i 0 1 φ j A jt ( 3) where A jt refers to the scheduled macroeconomic announcement dummy for the growth rate of GDP, the consumer price index (CPI), and the employment report (EMP). A jt =1 if 10

11 announcement j is released on day t, and A jt = 0 otherwise. MD t is dummy variable for the monthly release of the Reserve Bank s monetary policy stance. MD t =1 for the first Tuesday of each calendar month on which the Reserve Bank announces its monetary policy, and MD t = 0 otherwise. 4. The Data 4.1. The RBA Cash Rate Target Announcements Australia monetary policy decisions, expressed in terms of the cash rate target, have been made progressively transparent since In January 1990, the RBA started to publicise changes in monetary policy. The RBA decides on the Cash Rate Target at regular board meetings held on the first Tuesday of each calendar month except January. Commencing January 1998, any changes in monetary policy decisions were announced in a media release at 9.30am (Australian EST) on the day immediately after the each meeting of the Board. However, prior to December 2007 media releases were issued only when the cash rate target was not left unchanged. Effective from February 2008, the media release is issued at 2.30pm on the day of the Board meeting, with the Board s decision taking effect from the following day. Appendix 1 shows the dates and movements of the RBA s cash rate target from January 1997 to April During the sample period, there are 37 monetary policy changes observed. The unexpected component of monetary policy changes is shown in columns (5) and (6), calculated by utilising 30-day and 90-day bank accepted bill rates respectively Financial Market Data 11

12 The financial market data for the present study consist of continuously compounded returns on three asset classes of AUD/USD exchange rate futures, 3- and 10- year Treasury bond futures. Daily data for the three futures instruments are obtained from the Sydney Futures Exchange (SFE). Daily percentage changes are used as returns for each security. The dataset covers the period from January 1997 to April [Insert Table 1] Table 1 summarises statistics on daily returns from the three series. It is shown that daily mean returns for all three futures instruments are positive. In addition, the sign of skewness for the 10-year Treasury bond futures appears to be positive, indicating that distribution of the series has a long right tail. On the contrary, the distribution of either AUD/USD exchange futures or 3-year Treasury bond futures has a long left tail. In other words, the distributions of all three series are typically non-symmetric. According to the reported kurtosis of all three series, the distribution for each series is leptokurtic and more peaked than normal distribution. Further, the reported probability for the Jarque-Bera test is zero for all series, suggesting that all three series are not normally distributed. It may be noted that the ADF test t-statistics is reported for the raw data series. Given that the ADF test critical value at the 1% level is , it is evident that the calculated t-statistics of all three variables are less than the ADF test critical value at the 1% significance level. Hence, the null hypothesis that any one series in this group has a unit root is rejected. All daily return series are stationary, and the means and autocovariances of the series are independent of time. Thus, the summary statistics shown in table 1 suggest that, along with an error distribution that allows for greater kurtosis than normal distribution, a model of GARCH-class is appropriate for our study. 12

13 4.3. The Measurement of the Cash Rate Surprises The effect of changes in the cash rate on asset prices is largely dependent upon the extent to which such changes convey new information about short-term or long-term monetary policy objectives. An important implication of efficient market and rational expectation hypotheses is that, in an efficient market, asset prices react immediately and unbiasedly to the unexpected component of information contained in the monetary policy announcement. We construct a measure of cash rate surprises based on changes in Australian bank accepted bill (BAB) rates. Three alternative techniques are developed to separate the unanticipated component from the entire cash rate announcements, which allows us to make meaningful comparisons. Our first approach utilises information contained in the Australian 30-day BAB rate. The rationale behind this technique is that the 30-day BAB rate is the most flexible short-end interest rate available in Australian money market, and the daily movements of the 30-day rate could reflect the influence of available information set on the changes of the cash rate target. Using 30-day BAB rate, we calculate the expected component of the cash rate target movement as follows: Δ R e crt, t = R 30d, t-1 R 30d, t-(j-1) (4) where ΔR e crt, t measures the expected change of the cash rate on day t, R 30d, t-1 is the 30-day BAB yield on the day before a cash rate target change, R 30d, t-(j-1) is the 30-day BAB yield on the day immediately after the previous target change made on day (t-j). Figure 1 illustrates the time line of Australian cash rate target announcements. Figure 1. Time line of Australian cash rate announcements 13

14 t-j t-(j-1) (t-1) t j days j is the number of days between two cash rate target changes Once the expected component of cash rate target change is known, the monetary surprises ΔR u crt,t can be calculated as the difference between the actual target changes R crt, t and anticipated target changes R e crt, t: ΔR u crt, t = Δ R crt, t - Δ R e crt, t (5) Our second approach adopts the Australian 90-day BAB rates to gauge the market s expectations of the likely changes in the cash rate target. The development of this model is based on previous finding by Kuttner (2001) that the 3-month Treasury bill yield in the US market fully reflects the changes in monetary policy target rate. The expected component of cash rate target movement ΔR e crt, t can be isolated using the following formula: ΔR e crt, t = R 90d, t-1 - R 90d, t-( j 1) (6) where R 90 d, t-1 is 90-day BAB yield on the day before a cash rate target change, R 90d, t-(j 1) is 90-day BAB yield on the day immediately after the previous target change made on day (t-j). The surprise content of the cash rate announcement ΔR u crt, t is derived from equation (5). Our third approach takes the entire cash rate in estimation, which is used merely for the purpose of making comparisons. 14

15 5. Empirical Results Our empirical results are obtained using equations (1), (2), and (3). More specially, equations (1) and (2) are used to estimate the impact of Australian monetary policy surprises on each of the three futures contracts, while equations (1) and (3) are used to estimate the combined impact of Australian monetary policy surprises and other four key macroeconomic announcements on each of the three futures contracts The RBA Cash Rate Target Announcements Table 2 reports the maximum likelihood estimates for AUD/USD futures market. The parameter γ is shown to be positive and significant at the 5% level in all three models, which suggests that the impact of past innovations on current volatility is asymmetric in the exchange rate futures market. [Insert Table 2] Columns (1) and (2) of Table 2 consist of the estimation results from our first approach of utilising the 30-day BAB rate. The contemporaneous impact of cash rate target announcements on volatility of AUD/USD futures market, captured by parameter θ 0, is negative and insignificant. The announcement effect on the exchange rate futures market volatility is incomplete, as the lagged effect captured by θ 1 on day 1 after the announcement day t is significant. Results obtained from using the 90-day BAB rate are reported in columns (3) and (4), showing that the impact of monetary surprises on AUD/USD futures market is not significant in this scenario. Moreover, monetary surprises always exert influences on the mean returns from the exchange rate futures market, regardless of whether 30-day or 90-day BAB rate changes is used as the proxy of the anticipated target changes. This is evidenced through a statistically significant parameter b 2 throughout Table 2. 15

16 Table 3 shows maximum likelihood estimation results obtained from T-GARCH model for 3-year Treasury bond futures markets. Parameter θ 0 is negative and significant at the 5% level for both Model 1 and Model 3, meaning that the RBA s monetary policy announcement plays an important role in smoothing the Treasury bond futures market and reducing return volatility. However, when the 90-day BAB rate is used in Model 2, the impact of monetary policy on 3-year Treasury bond futures market becomes insignificant. Further, the news effect of monetary policy announcement on market volatility is incomplete, as the lagged effect on day 1 and day 2 after the announcement day t, captured by θ 1 and θ 2 respectively, is significant in Model 1. Finally, a statistically significant parameter b 2 in both Model 1 and Model 2 suggests that the monetary surprises negatively affect the mean returns of the interest rate futures market. [Insert Table 3] Table 4 presents similar results for 10-year Treasury bond futures market. The effect of monetary surprises is significant at the 10% level using 30-day BAB rate in Model 1, and significant at the 5% level for Model 2 and Model 3. The effect of cash rate target announcements is incomplete on the announcement day in Model 1 and Model 3, as lagged effects are statistically significant at the 5% level. [Insert Table 4] 5.2. The RBA Cash Rate Target and Other Key Macroeconomic Announcements The combined effect of the monetary policy surprises and three macroeconomic announcements on the Australian financial futures markets is shown in Table 5. Parameter θ 0 is negative and significant at the 5% level for AUD/USD futures, confirming that the RBA s unexpected cash rate target announcement plays a key role in smoothing the volatility of the exchange rate futures, even when other key macroeconomic announcements are considered simultaneously. Monetary surprises are transmitted into these three futures markets 16

17 completely, since all parameters for the lagged effect of monetary policy announcements are insignificant at the 5% level. As shown by the parameter θ 2, CPI announcements tend to exert an influence over the volatility of AUD/USD future market and 3-year Treasury bond futures market. In addition, the announcements for the GDP growth rate (i.e. θ 1 ) do impact on the volatility of both 3- and 10-year Treasury bond futures markets, while employment reports (i.e. θ 3 ) produce no appreciable effect on the volatility of three financial futures markets. [Insert Table 5] 6. Concluding Remarks This paper investigates the effect of unanticipated monetary policy announcements and other macroeconomic releases on Australia foreign exchange futures and interest rate futures markets, using daily data for AUD/USD exchange rate futures, 3-year and 10-year Treasury bond futures contracts. Both 30-day BAB rate and 90-day BAB rate are used to gauge Australian monetary policy surprises. Consistent with Kim and Nguyen (2008), AUD/USD exchange rate futures contract are found to be strongly responsive to the unanticipated cash rate announcements. Such announcement effect is also seen on 3-year and 10-year Treasury bond futures markets, when the 30-day BAB rate is used to derive monetary policy surprises. Further, the RBA target rate announcement effect is complete on the announcement day for 3-year and 10-year bond futures markets, but not for AUD/USD futures market. The response of exchange rate futures market to monetary policy surprises appears to be sluggish. Although the degree of significance for the announcement effects depends on how the surprise element is measured, our empirical results suggest that the daily yield movements of the 30-day BAB rate outperform the 90-day BAB rate in measuring the expected monetary 17

18 policy actions. This can be explained by its shorter term to maturity and thus less information leaking. Using an extended threshold GARCH (T-GARCH) model, we have also studied the joint effect of monetary surprises and other key macroeconomic announcements on Australian financial futures markets. We find that when other key macroeconomic announcements are incorporated into a single T-GARCH model, the effect of monetary surprises on the volatility of all three financial futures instruments becomes significant and complete. Our findings suggest that the Reserve Bank s cash rate target announcements play a superior role in determining the price and volatility of the three financial futures instruments. 18

19 Table 1. Summary statistics on daily returns of AUD/USD exchange futures, 3-year and 10-year Treasury bond futures markets The table below reports descriptive summary statistics for three futures markets AUD/USD exchange futures (AUDF), 3-year and 10-year Treasury bond futures (TBF3y, TBF10y). µ is the mean and σ is the standard deviation. Skew is the coefficient of skewness, Kurt is kurtosis. ADF is t-statistics value for Augmented Dickey-Fuller test of unit root for all series. LB (10) is the value of Ljung-Box test of randomness for the 1 st through 10 th order autocorrelation, asymptotically distributed as χ 2 [10] under the null hypothesis that the series is white-noise process in which all autocorrelations be zero. Note that rejecting the null H 0 means accepting an alternative H 1 that at least one autocorrelation is not zero. The signs of ***, **, * indicate significance at the 1-, 5- and 10- percent level, respectively. AUDF TBF3Y TBF10Y µ Σ Skew Kurt ADF-t LB(10) *** *** 19

20 Table 2. The impact of cash rate target changes on AUD/USD futures market R i,t = b 0 + b 1 R i,t-1 + b 2 M t + t (1) where t Φ t-1 ~N (0, h t ), and h t,1 = ω + α t β h t-1 + γ I - t-1 t θ i M t-i (2) i 0 where R t is the daily return AUD/USD futures contract from day t-1 to day t. M t is unexpected cash interest rate changes. Parameter θ 0 captures the contemporaneous effect of cash rate target surprises. α captures the ARCH effect, β captures the persistence in volatility. The presence of leverage effect is tested by the hypothesis that the parameter γ < 0. The impact of past innovations on current volatility is asymmetric if γ 0. In Model 1, monetary policy surprises are calculated using 30-day BAB yield changes as the anticipated component of cash rate movements. In Model 2, monetary policy surprises are calculated using 90-day BAB yield changes. Model 3 utilises actual cash rate target changes. Panel A. Maximum likelihood parameter estimates for AUD/USD futures market. Model 1 with 30-day BAB Model 2 with 90-day BAB Model 3 actual target changes (1) (2) (3) (4) (5) (6) Coeff S. E. Coeff S. E. Coeff S. E. b b * * * b *** *** * ω *** *** *** α *** *** *** γ *** *** *** β *** *** *** θ *** θ *** θ θ *** 20

21 Panel B. Model diagnostics for standardised residuals Model 1 Model 2 Model 3 Mean S. D Skew Kurt LB(10) for Z i,t (0.863) (0.832) (0.884) LB(10) for Z 2 i,t (0.628) (0.707) (0.625) Notes: *denotes significance at 10%, **denotes significance at 5%, ***denotes significance at 1%. 21

22 Table 3. The impact of cash rate target changes on 3-year T-bond futures market R i,t = b 0 + b 1 R i,t-1 + b 2 M t + t (1) where t Φ t-1 ~N (0, h t ), and h t,1 = ω + α t β h t-1 + γ I - t-1 t θ i M t-i (2) i 0 where R t is the daily return 3-year T-bond futures contract from day t-1 to day t. M t is the unanticipated cash rate target changes. Parameter θ 0 captures the contemporaneous effect of cash target surprises. α captures the ARCH effect, while β captures the persistence in volatility. The presence of leverage effect is tested by the hypothesis that the parameter γ < 0. The impact of past innovations on current volatility is asymmetric if γ 0. In Model 1, monetary policy surprises are calculated using 30-day BAB yield changes as anticipated component of cash rate movements. In Model 2, monetary policy surprises are calculated using 90-day BAB yield changes as anticipated component of cash rate changes. Model 3 utilises actual cash rate target changes. Panel A. Maximum likelihood parameter estimates for 3-year Treasury bond futures market Model 1 with 30-day BAB Model 2 with 90-day BAB Model 3 actual target changes (1) (2) (3) (4) (5) (6) Coeff S. E. Coeff S. E. Coeff S. E. b b b *** *** ω 6.43E E-06** 8.44E E-06** 1.07E Eα *** *** *** γ β *** *** *** θ *** * *** θ *** θ *** θ Panel B. Model diagnostics for standardised residuals Model 1 Model 2 Model 3 Mean S. D Skew Kurt LB(10) for Z i,t (0.812) (0.884) (0.880) 22

23 LB(10) for Z 2 i,t (0.112) (0.164) (0.128) Notes: *denotes significance at 10%, **denotes significance at 5%, ***denotes significance at 1%. 23

24 Table 4. The impact of cash rate target changes on 10-year T-bond futures market R i,t = b 0 + b 1 R i,t-1 + b 2 M t + t (1) where t Φ t-1 ~N (0, h t ), and h t,1 = ω + α t β h t-1 + γ I - t-1 t θ i M t-i (2) i 0 where R i,t is the daily return 10-year T-bond futures contract from day t-1 to day t. M t is the unanticipated cash rate target changes. θ 0 captures the contemporaneous effect of cash target surprises. β captures the persistence in volatility, while α captures the ARCH effect. The presence of leverage effect is tested by the hypothesis that the parameter γ < 0. The impact of past innovations on current volatility is asymmetric if γ 0. In Model 1, monetary policy surprises are calculated using 30-day BAB yield changes as anticipated component of cash rate movements. In Model 2, monetary policy surprises are calculated using 90-day BAB yield changes as anticipated component of cash rate changes. Model 3 utilises actual cash rate target changes. Panel A. Maximum likelihood parameter estimates for 10-year T-bond futures market Model 1 with 30-day BAB Model 2 with 90-day BAB Model 3 actual target changes (1) (2) (3) (4) (5) (6) Coeff S. E. Coeff S. E. Coeff S. E. b b *** ** *** b * * ω 1.38E E- 06*** 1.68E E- 06*** *** α *** *** ** γ * ** β *** *** *** θ * *** *** θ θ θ ** *** 24

25 Panel B. Model diagnostics for standardised residuals Model 1 Model 2 Model 3 Mean S. D Skew Kurt LB(10) for Z i,t (0.340) (0.267) (0.054) LB(10) for Z 2 i,t (0.000) (0.000) (0.000) Notes: *denotes significance at 10%, **denotes significance at 5%, ***denotes significance at 1%. 25

26 Table 5. The impact of monetary surprises and key macroeconomic announcements on Australian financial futures markets R i,t = b 0 + b 1 R i,t-1 + b 2 M t + t (1) 2 h t = ω + α t-1 + βh t-1 + γ I - t t-1 + θ i MD t-i + j 3 i 0 1 φ j A j (3) where R i,t is the daily percentage changes of three futures returns from day t-1 to day t. M t is unexpected monetary policy changes derived from 30-day bank bill rate. A it stands for scheduled macroeconomic announcement dummies, representing the growth rate of gross domestic product (GDP), the consumer price index (CPI), and the employment report (EMP). A it =1 if announcement j is released in day t, and A it = 0 otherwise. MD t is the dummy variable for monthly monetary policy release of the Reserve Bank s policy stance. MD t =1 for the first Tuesday of each calendar month on which the Reserve Bank of Australia reviews its monetary policy, and MD t = 0 otherwise. Panel A. Maximum likelihood parameter estimates for the three futures markets AUD/USD futures 3-year bond futures 10-year bond futures Coeff S. E. Coeff S. E. Coeff S. E. b b ** b ** ω ** -3.07E E E E-05 α *** *** *** γ *** ** β *** *** *** θ ** E θ θ θ * φ *** *** φ *** *** φ E Panel B. Model diagnostics for standardised residuals AUD/USD 3-year bond 10-year bond Mean S. D Skew Kurt LB(10)forZ i,t 8.327(0.597) 4.886(0.899) 9.405(0.494) LB(10) for (0.236) (0.070) (0.000) 2 Notes: *denotes significance at 10%, **denotes significance at 5%, ***denotes significance at 1%. 26

27 Appendix 1 Dates and movements of the RBA s cash rate target (CRT) January April 2010 Date of Level in Change of Change in BAB yield Unexpected CRT (%) Changes CRT(%) CRT(%) 30-day BAB 90-day BAB from (3) from (4) (1) (2) (3) (4) (5) (6) 23/05/ /07/ /12/ /11/ /02/ /04/ /05/ /08/ /02/ /03/ /04/ /09/ /10/ /12/ /05/ /06/ /11/ /12/ /03/ /05/ /08/ /11/ /08/ /11/

28 06/02/ /03/ /09/ /10/ /11/ /12/ /02/ /04/ /10/ /11/ /12/ /03/ /04/ Notes: Column 1 is the level of CRT, Column 2 is changes in CRT, Columns 3 and 4 are changes in bank bill rates from the day after previous target change to the day before a target change, using the equation ΔR e crt, t =R 30 d, t-1 R 30 d, t- j + 1 where R 30 d, t-1 is 30-day (90-day) BAB yield on the day before a target change, R 30 d, t- j + 1 is 30-day (90-day) BAB yield on the day after the previous target change made on day (tj ). The monetary surprises in columns 5 and 6 are then calculated as the difference between the actual and anticipated target changes using the equation Δ R u crt, t = Δ R crt, t - Δ R e crt, t, therefore, Column (5) = (2)-(3); and (6) = (2)-(4). 28

29 References Bagliano, F. C. and Favero, C.A, Information from financial markets and VAR measures of monetary policy.european Economic Review, 43, Bernanke, B.S. and Blinder, A.S., The Federal funds rate and the channels of monetary transmission. American Economic Review, 82, Bernanke, B.S. and Kuttner, K.N., What explains the stock market s reaction to federal reserve policy? Journal of Finance, LX(3), Bollerslev, T., Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31, Bonfim, A. N., Pre-announcement effects, news effects, and volatility: monetary policy and the stock market. Journal of Banking and Finance, 27, Bredin, D., Gavin, C., and O Reilly, G., International monetary policy shocks and Irish market rates. Applied Economics Letters, 11, Bredin, D., Gavin, C., and O Reilly, G., US monetary policy announcements and Irish stock market volatility. Applied Financial Economics, 15, Connolly, R.A. and Wang, F.A., International equity market comovements: economic fundamentals or contagion? Pacific-Basin Finance Journal, 11,

30 Cook, T. and Hahn, T., The effects of changes in the Federal Funds rate target on market interest rates in the 1970s. Journal of Monetary Economics, 24, Ederington, L.H. and Lee, J.H., Intraday Volatility in Interest-rate and Foreign Exchange Markets: ARCH, Announcement, and Seasonality Effects. Journal of Futures Markets, 6, Engle, R.F., Autoregressive conditional heteroskedasticity with estimates of the variance of U.K. inflation. Econometrica, 50, Fiser, R. and Horvath, R., Central bank communication and exchange rate volatility: a GARCH analysis. Macroeconomics and Finance in Emerging Market Economies, 3, Flannery, M.J. and Protopapadakis, A.A., Macroeconomic factors do influence aggregate stock Returns. Review of Financial Studies, 15, Gulley, O.D. and Sultan, J., The link between monetary policy and stock and bond markets: evidence from the federal funds futures contract. Applied Financial Economics, 13, Kearns, J. and Manners, P., The impact of monetary policy on the exchange rate: a study using intraday data. International Journal of Central Banking, 2,

31 Kim, S-J. and Nguyen, D., The reaction of the Australian financial markets to the interest rate news from the Reserve Bank of Australia and the U.S. Fed. Research in International Business and Finance, 22, Krueger, J.T. and Kuttner, K.N., The Fed funds futures fate as a predictor of federal reserve policy. Journal of Futures Markets, 16, Kuttner, K.N., Monetary policy surprises and interest rates: evidence from the Fed funds futures market. Journal of Monetary Economics, 47, Li, L. and Engle, R., Macroeconomic announcements and the volatility of the treasury market. Working Paper No USA: University of California at San Diego. Lu, X., In, F., and Kou, M., The higher-frequency responses of Australian financial futures to unexpected cash rate announcements. Economic Record, 85, S22-S28. Newby, V.A., The effects of news on exchange rates when the risk premium is considered, Applied Financial Economics, 12, Poole, W. and Rasche, R.H., Perfecting the market s knowledge of monetary policy. Journal of Financial Services Research, 18, Rigobon, R., Identification through heteroskedasticity. Review of Economics and Statistics, 85,

32 Rigobon, R. and Sack, B., The impact of monetary policy on asset prices. Journal of Monetary Economics, 51, Rudebusch, G.D., Do measures of monetary policy in a VAR make sense? International Economic Review, 39, Sewa, D., Do emerging financial markets react to monetary policy announcements? Evidence from Poland. Applied Financial Economics, 2006, 16, Smales, L.A., RBA monetary policy communication: the response of Australia interest rate futures to changes in RBA monetary policy. Pacific-Basin Finance Journal, 20, Thorbecke, W., On stock market returns and monetary policy. Journal of Finance, 52, Zakoian, J.M., Threshold Heteroskedastic Models. Journal of Economic Dynamics and Control, 18, Zettelmeyer, J., The impact of monetary policy on the exchange rate: evidence from three small open economies. Journal of monetary Economics, 51,