Central bank communication and exchange rate volatility: a GARCH analysis

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  • This article was downloaded by: [York University Libraries]On: 24 November 2014, At: 03:58Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registeredoffice: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

    Macroeconomics and Finance inEmerging Market EconomiesPublication details, including instructions for authors andsubscription information:http://www.tandfonline.com/loi/reme20

    Central bank communication andexchange rate volatility: a GARCHanalysisRadovan Fier a & Roman Horvth ba Institute of Economic Studies, Charles University , Pragueb Czech National Bank and Institute of Economic Studies, CharlesUniversity , PraguePublished online: 08 Mar 2010.

    To cite this article: Radovan Fier & Roman Horvth (2010) Central bank communication andexchange rate volatility: a GARCH analysis, Macroeconomics and Finance in Emerging MarketEconomies, 3:1, 25-31, DOI: 10.1080/17520840903498099

    To link to this article: http://dx.doi.org/10.1080/17520840903498099

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  • RESEARCH ARTICLE

    Central bank communication and exchange rate volatility:a GARCH analysis

    Radovan Fisera and Roman Horvathb*

    aInstitute of Economic Studies, Charles University, Prague; bCzech National Bank and Instituteof Economic Studies, Charles University, Prague

    (Received 4 February 2009; accepted 14 June 2009)

    We examine the effects of the Czech National Bank communication, macro-economic news and interest rate differential on exchange rate volatility usinggeneralized autoregressive conditional heteroscedasticity model. Our resultssuggest that central bank communication has a calming effect on exchange ratevolatility. The timing of central bank communication seems to matter, too, asfinancial markets respond more to the communication before the policy meetingsthan after them. Next, macroeconomic news releases are found to reduceexchange rate volatility, while interest rate differential seems to increase it.

    Keywords: central bank communication; exchange rate; GARCH

    JEL classification: E52; E58; F31

    1. Introduction

    A considerable effort has been spent in last one or two decades to improve monetarypolicy transparency and to provide a clear communication of monetary policyactions in order to manage inflation expectations effectively. While the authoritativesurvey on central bank communication by Blinder et al. (2008) documents that theeffects of central bank communication on financial markets were examined in manydeveloped countries, the evidence on emerging market economies is rather scant.1

    In this paper, we aim to bridge this gap and study the impact of central bankcommunication on exchange rate volatility in one of the small open emergingeconomies, the Czech Republic.2 We chose the exchange rate market, as this marketis often of much greater importance than other segments of the financial markets forthe economic fluctuations in emerging economies. More specifically, we areinterested how the releases of oral and written policy statements by the centralbank (controlling for macroeconomic news and other factors) influence the exchangerate volatility using the generalized autoregressive conditional heteroscedasticity(GARCH) model. Additional hypothesis that we want to address in this short policypaper is whether the timing of central bank communication matters, i.e. whether thefinancial markets respond to the communication more strongly before the monetarypolicy meetings than after them (see Ehrmann and Fratscher 2007).

    *Corresponding author. Email: roman.horvath@cnb.cz or roman.horvath@gmail.com

    Macroeconomics and Finance in Emerging Market Economies

    Vol. 3, No. 1, March 2010, 2531

    ISSN 1752-0843 print/ISSN 1752-0851 online

    2010 Taylor & FrancisDOI: 10.1080/17520840903498099

    http://www.informaworld.com

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  • The paper is organized as follows. Section 2 introduces our empiricalmethodology and data. Section 3 presents the results. Concluding remarks follow.

    2. Data and empirical methodology

    We use daily data from 3 January 2005 to 14 February 2007, which makes 536observations. The use of daily data is justified if the main interest is to investigate theeffectiveness of central bank communication (Jansen and de Haan 2005) as well as bythe recent evidence suggesting that it may takes several days until news is fullyabsorbed by the financial markets (Evans and Lyons 2005). The source of centralbank communication and macroeconomic news variables is Reuters. Daily exchangerate and interest rate data are taken from the Czech National Bank (CNB).

    Our baseline specification is a GARCH(1,1)3 process for exchange rate returns,

    Dst m xt; 1

    s2t g1 g2x2t1 g3s2t1 fi

    Xn

    i1CBit r1newst r2intdifft ojt; 2

    st denotes the log of CZK/EUR.4 The constant term in Equation (1), m, shows the

    average rate of appreciation or depreciation. The error term, xt, of the meanEquation (1) is assumed to have a conditional variance, s2t , specified by Equation (2).The conditional variance equation includes in addition to the constant g1, ARCHterm xt71, and GARCH term s2t1, the variables capturing the effect of central bankcommunication, CBit, macroeconomic news, newst, and interest rate differential,intdifft.

    We use the following variables to assess the effect of central bankcommunication.

    commentt a dummy variable that takes a value of unity on days when a member of theCzech National Bank Board commented verbally on the price stability, economicoutlook, interest rates or exchange rate. The Board comprises of seven members, allwith equal weight in monetary policy rate setting process. The governor has a castingvote in case, when some members are missing at the monetary policy meeting and theirnumber is even.5

    timingt is defined as the product of commentt and variable , which is a categoricalvariable and takes value of 30 on the day of monetary policy meeting, 29 on the daybefore the meeting, 28 on two days before the meeting and so on. In consequence,comments closer to monetary policy meeting get greater weight.

    minutest is a dummy variable with unitary value on the day, when monetary policyminutes are published (this is typically 12 days after monetary policy meeting).

    It follows from the definition of our variables capturing the central bankcommunication that we focus on whether the central bank talked to the marketsthe rather than on interpreting the content of its communication. Therefore, thecentral bank communication variables are included only in the variance equationand exchange rate is assumed to follow random walk.

    Macroeconomic news, newst, is a dummy variable that takes a value of unity ondays, in which scheduled macroeconomic news is released. The macroeconomic newsdummy includes the releases of new data on the Czech producer and consumer price

    26 R. Fiser and R. Horvath

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  • indexes, gross domestic product (GDP) and balance of payments. Interest ratedifferential, intdifft, is a difference between Czech and the euro area money marketrate (1YPRIBOR and 1YEURIBOR, respectively).

    In case of tick-by-tick data, the impact of central bank communication andmacroeconomic news on exchange rate volatility should be non-negative, as the newinformation they contain affects the exchange rate return. However, in case of dailydata, the expected sign of these variables is not clear-cut and the existing literaturedocuments accordingly that they may both increase or decrease exchange ratevolatility (Jansen and de Haan 2005; Gabriel and Pinter 2006; Ehrmann andFratzscher 2007) according to whether it has a calming effect on the markets or not.Additionally, greater interest rate differential is likely to increase exchange ratevolatility (Kocenda and Valachy 2006). Larger differential may signal the lack ofsynchronization of the business cycle and subsequently monetary policy andexchange rate is thus more likely to adjust.

    Table 1. Descriptive statistics.

    st commentt timingt minutest newst intdifft

    Mean 28.99 0.11 2.32 0.05 0.21 70.46Median 28.78 0.00 0.00 0.00 0.00 70.36Maximum 30.56 1.00 29.00 1.00 1.00 0.40Minimum 27.42 0.00 0.00 0.00 0.00 71.17Standard deviation 0.83 0.32 6.69 0.21 0.41 0.40Skewness 0.25 2.43 2.68 4.30 1.42 0.35Kurtosis 1.70 6.90 8.57 19.44 3.00 2.50Jarque-Bera test 43.30 864.90 1332.00 7676.00 178.50 16.43

    [0.00] [0.00] [0.00] [0.00] [0.00] [0.00]Observations 536 536 536 536 536 536

    Notes: p-values are reported in the brackets. Exchange rate series in levels.

    Figure 1. Frequency of central bank communication.Note: Horizontal axis measure the days before monetary policy meeting. Vertical axis gives thefrequency.

    Macroeconomics and Finance in Emerging Market Economies 27

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  • Next, we present the descriptive statistics of key variables. Several issues arenoteworthy. Czech central bank communication occurs about every tenth day onaverage, while macroeconomic announcements are released more often (with themean of 0.21). Minutes occur monthly as the frequency of monetary policy meetingsis monthly in our sample period (as there are 22 business days on average per month,the mean is 0.05). Czech interest rates were on average nearly 0.5 percentage pointbelow the euro area during sample period.

    Figure 1 presents the frequency of central bank communication. As themonetary policy meeting is typically held on Thursday, the results indicate thatthe frequency of communication is much lower in the week the monetary policymeeting is held (see the frequencies on the days 13 in Figure 1). Thecommunication is the most intense from 10 to six days before the monetarypolicy meeting takes place. This finding is in line with evidence on the Bank ofEngland, European Central Bank and the US Federal Reserve (see Ehrmann andFratzscher 2007), where communication is more common as the meeting comescloser. On the other hand, in contrast to these central banks, we can see that theCzech central bank communication is not more frequent after the monetary

    Table 2. The effect of central bank communication on exchange rate volatility.

    Dst m xt

    s2t g1 g2x2t1 g3s

    2t1 fi

    Xn

    i1CBit r1newst r2intdifft ojt

    (1) (2) (3) (4) (5)

    m 70.000[0.00]

    70.000[0.00]

    70.000[0.00]

    70.000[0.00]

    70.000[0.00]

    g1 0.000***[0.00]

    0.000***[0.00]

    0.000***[0.00]

    0.000***[0.00]

    0.000***[0.00]

    g2 0.15***[0.05]

    0.15***[0.05]

    0.01[0.01]

    0.15*[0.08]

    0.15*[0.09]

    g3 0.60***[0.09]

    0.60***[0.10]

    0.95***[0.02]

    0.60***[0.15]

    0.60***[0.17]

    f1 (commentt) 73.37***[1.19]

    73.24**[1.31]

    f2 (timingt) 70.15**[0.07]

    70.16**[0.06]

    f3 (minutest) 4.78***[1.21]

    74.62**[2.33]

    74.80*[2.61]

    r1 73.66***[0.91]

    73.59*[2.18]

    70.99**[0.40]

    73.64**[1.85]

    73.57*[2.06]

    r2 1.81***[0.70]

    1.81[1.37]

    0.36***[0.19]

    1.86*[1.09]

    1.79[1.38]

    L-B(10), RES 12.84 12.77 13.01 12.85 12.96L-B(10), SQRES 10.59 11.79 9.03 13.43 12.44Schwartz inf. crit. 78.69 78.70 78.86 78.70 78.70

    N 536 536 536 536 536

    Notes: We report standard errors in parenthesis and Ljung-BoxQ-statistics of the 10th lag for standardizedand squared residuals. ***, **, and * denote significance at 1%, 5%, and 10%, respectively. The value off1, f2, f3, r1 and r2 are multiplied by 10

    6.

    28 R. Fiser and R. Horvath

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  • policy meeting. We suppose that this reflects the fact that the CNB puts a lot ofeffort in explaining their interest rate decision and risk scenarios at the pressconference just after the monetary policy meeting was held.

    3. Results

    Table 2 presents our results on the determinants of exchange rate volatility. We findthat that central bank communication tends to decrease exchange rate volatility, i.e.this supports the view that the central bank aims to decrease the noise in the financialmarkets (Blinder et al. 2008). The finding complies with Jansen and de Haan (2005)and Gabriel and Pinter (2006), who also find that the exchange rate volatility ofEUR/USD and HUF/EUR, respectively, is lower on the day when central bankcommunicates its views on the economy to the public.

    In addition, the results suggest that the timing of central bank communicationseems to matter too.6 Similarly, Ehrmann and Fratzscher (2007) study the timing ofcentral bank communication for the case of Bank of England, European CentralBank and the US Federal Reserve Bank. Despite defining the measure of timing ofcentral bank communication differently (primarily using various dummy variablesand interacting them with the model coefficients), their results suggest that the timingof communication is informative for a whole variety of financial assets including theexchange rate.

    We also find that the effect of central bank minutes is not clear, as the sign ofcoefficient differs across the specifications. The effect of macroeconomic news issomewhat surprising; it tends to decrease exchange rate volatility. This may reflectthe fact the there is higher uncertainty in emerging markets and news is likely to havecalming effect on the markets. Nevertheless, this effect is found also in some otherstudies in developed countries such as Kim et al. (2004), who report that DEM/USDexchange rate volatility decreases on the day the news on producer price index isreleased. Greater interest rate differential is fou...

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