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MONETARY POLICY ANNOUNCEMENTS AND STOCK REACTIONS:

AN INTERNATIONAL COMPARISON

Shen Wang and David G Mayes

University of Auckland

Abstract

This article investigates the impact of domestic monetary policy rate announcements on the stock

markets of New Zealand, Australia, the United Kingdom and the euro area, using event-study

methods to identify stock price reactions to the unanticipated/surprise component of announcements.

As Australia and New Zealand did not reach the zero bound we investigate whether there is an

impact from the global financial crisis on stock market reactions that can be distinguished from the

asymmetric reactions to surprises that characterise the business cycle. We find that the euro area

and the UK both show a financial crisis effect but behaviour in New Zealand and Australia does not

change. We conduct robustness checks and explore confounding factors, especially the impact of

guidance from central banks that prepares markets for policy rate changes.

We have two main aims in this article: first to see whether the financial crisis has affected how stock

prices respond to policy surprises. There is some evidence from the UK (Gregoriou et al., 2009) that

stock price responses became significantly positive during the financial crisis, which implies a striking

change in behaviour. We therefore extend the existing literature to Australia and New Zealand because

these two countries did not reach the zero bound for nominal interest rates and, hence used

conventional policy throughout the crisis period. Beyond short run measures to ensure adequate

liquidity, they did not employ quantitative easing or credit easing in addition to interest rate policy. We

also include the UK and the euro area, which did reach the zero bound, as comparators.

The nature of the likely change in behaviour in a crisis is not completely obvious. It is usually

thought that in a crisis people become much more risk averse. This could mean therefore that they

become more sensitive to monetary policy surprises, particularly negative ones. However, it is also

thought that as monetary policy approaches the zero bound it becomes less effective, because people

can see that conventional monetary policy will soon reach its limits. A negative shock could then

simply accelerate the onset of the belief about policy ineffectiveness and hence show a weakened

response in stock prices. As a by-product of this analysis we also get to test whether the experience

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recorded for the US, the UK and the euro area in normal times can be extended to Australia and New

Zealand.

Secondly, we seek to substantiate the evidence that the response of markets to monetary policy

surprises varies over the course of the business cycle. There is good evidence that monetary policy

responses to asset prices are themselves asymmetric (Mayes and Viren (2011) for the euro area;

D Agostino et al. (2005) for the US) but little in the reverse direction, although Anderson et al. (2007)

find that stock price responses to positive macroeconomic news, including that from interest rates, is

positive in expansions and negative in contractions.1 Simply put, it is normally thought, on the basis of

previous evidence (Bernanke and Kuttner, 2005; Bohl et al., 2008; Bredin et al., 2007a,b; Honda and

Kuroki, 2006 and Wongswan, 2005), that if there is a positive interest rate surprise this will encourage

markets to fear that there is more adverse information available to the central bank than they had

thought existed and hence the stock price response would be negative. However, in uncertain times

such a surprise might lead markets to believe that policy will be more conducive to steady growth in

the future, as the central bank appears more determined to maintain price stability than was previously

thought. Montagnoli and Mayes (2011) for example show that central banks themselves tend to set

policy differently under greater uncertainty.2 The previous discussion of the influence of the global

financial crisis suggests that the reaction of markets may be different in the down and up phases of the

cycle as well as during uncertainty which is usually associated with turning points.

There is extensive evidence that, in addition to affecting inflation and the real economy,

monetary policy has a clear impact on stock prices (and on house prices) (Iacovello and Minetti, 2003,

2008). Since stock prices are forward looking that influence will come through news and monetary

policy surprises. The reaction to news will incorporate the change the central bank is expected to make

in the settings of policy in the light of that same news. Thus when monetary policy decisions are

announced, what will move stock prices is announcements that are different from those expected. All

of the countries in our sample implement a form of inflation targeting, although this is not how euro

area policy is described by the Eurosystem, and try to make their policy predictable. However, they

typically only announce policy decisions at scheduled meetings. Some countries also offer a projection

1 See also Boyd et al. (2005) for an asymmetric stock price response to labour market news. They find a positive response to bad news and expansions and a negative response in contractions. This they argue is because of the expected response of monetary policy. 2 They consider the Czech, Swedish and UK central banks as these have the longest history of recording perceived uncertainty.

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of how the policy rate might be expected to evolve in the future in the light of current information and

expected future events. In our sample this is only the case in New Zealand.

Although there is wide debate about the appropriateness of reacting to asset price changes,

including stock prices,3 it is clear that monetary policy does indeed also respond to them in practice

(see Mayes and Viren, 2011, for the case of the euro area and Miller et al., 2002 for the US).4 The

relationship is therefore bi-directional. For market participants, changes in monetary policy have

implications for effective investment and risk management decisions. For central banks, an

understanding of the links between monetary policy and asset prices is fundamental, as has been

demonstrated with unwelcome clarity in the present global financial crisis. They need to understand

both how they can influence stock prices and how that influence impacts on inflation and financial

stability. Our analysis here focuses on how stock markets react to policy surprises. To some extent

monetary policy makers do deliberately seek to surprise markets if conventional policy setting does not

appear to shifting expectations as anticipated. For example, in a crisis interest rates might well be

reduced rather further than appears necessary from pre-crisis behaviour, simply to ensure that markets

get the message that the central bank intends to move firmly to head off any prospect of deflation. By

definition such steps are rare or they would get built into what is expected and no longer be a surprise.

They also do not constitute any attempt to move asset prices by some particular amount.

In common with most studies of announcement affects we apply event-study methods (Bernanke

and Kuttner, 2005) as this enables us to identify the behaviour of stock prices around the specific time

of the announcement and to filter out other extraneous sources of price changes. We are somewhat

restricted in our data as we require on the one hand daily stock prices and on the other a sustained

period where a country has applied a similar monetary policy regime and announced its decisions in the

form of a policy interest rate setting. In the case of euro area we are of course limited by the period of

its existence, however, in the case of New Zealand we are more limited than might be expected, as

although it was the earliest adopter of inflation targeting and was very transparent in its decision

making from as early as 1989, most of the early policy setting was indicative, backed up by the threat

of changes in the quantity of overnight money. Although the target was consistently the 90-day

Treasury Bill rate, this was not the instrument and the policy is aptly described Open Mouth

Operations (Guthrie and Wright, 2000; Mayes and Riches, 1996). It is only since April 1999 that New

3 Bernanke and Gertler (2001), Cechetti et al. (2000), Filardo (2000), Goodhart and Hofmann (2000) 4 Rigabon and Sack (2003) show that a rise in the S&P500 index increases the probability of a monetary policy tightening at the next FOMC meeting in the US.

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Zealand has used the overnight cash rate (OCR) as its explicit policy variable. Similarly the UK has

only been using the Repo rate as its main instrument since 1997. However this gives us 119

observations up until interest rates fell to the zero bound in the present crisis.5

As the global financial crisis is not yet over, more complex changes in behaviour may well

emerge. At this stage, however, monetary policy makers may wish to reflect on whether changes in the

reaction to policy surprises in a crisis have any implications for policy.

In the rest of the article, Section 1 explains the model and the methodology applied. Section 2

considers the issues posed by our data on the four monetary regimes: New Zealand, Australia, the UK,

and the euro area. In Section 3, we discuss the results. Section 4 concludes.

1. The Model and Methodology

Two main approaches have been used to estimate the impact of monetary policy announcements:

event-study (Bernanke and Kuttner, 2005) and identification-through-heteroskedasticity developed by

Rigobon and Sack (2004). In the event-study approach, the returns of stock indices for a short window

of time round the announcement are regressed against the surprise components of policy rate changes.

The regression coefficient measures the magnitude and direction of the response. Expected policy

changes are usually included in the regression in case expectations are not fully acted upon.6 Under the

identification-through-heteroskedasticity approach, the response of asset prices to policy rate changes is

identified based on the increase in the variance of policy shocks that occurs on days of monetary policy

announcements. The identification-through-heteroskedasticity approach is not appropriate here, since it

does not allow us to test the effects of the financial crisis and the business cycle. Hence we follow

Bernanke and Kuttner (2005) in using an event study. By way of reassurance Rosa (2009) suggests, in

a comparison of the two methods, that the event-study approach is to be preferred. However, the

support is not universal, as Kholodilin et al. (2009) argue that there is downward bias in the event-study

approach in the case of the euro area.

An important concern with the event-study method is the problem of endogeneity, namely the

possibility that the policy interest rate decision itself is affected by recent movements in stock prices.7

5 In the euro area interest rates did not fall to zero but effectively reached a lower bound as the ECB was not willing to accept deposits at zero interest rates. 6 Clearly if rational expectations are the basis of the model then the coefficient on the expected policy change will be zero but there is always the possibility of consistent departures from this in practice. 7 See, for example, Rigobon and Sack (2003) and D Agostino et al. (2005). Also see Mayes and Viren (2011) for an asymmetrical response of monetary policy to asset prices/inflation risks.

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In any case, other variables may have an impact on both the policy interest rate and stock prices,

thereby distorting the estimates of a model that just considered the influence from monetary policy to

prices. Previous studies have addressed the problem by using a short event window of one day or less.

With a short event window, the joint effect of stock prices on monetary policy is minimised as it is very

unlikely that the policy rate decision would be affected by any stock price changes that occurred earlier

during the announcement day.8 The omitted variable problem is also reduced, and any confounding

news release on the announcement days can be controlled for using dummy variables. The ideal

solution is to use high frequency intra-day data9; however, as such data are not available, especially for

New Zealand and Australia, we use an event window of one day.

1.1 Baseline Model

We can express the relationship between monetary policy and stock prices using the following model

(Bernanke and Kuttner, 2005),

rt = a + b PRe t + c PRu

t + Xtd +

t (1)

where rt refers to the one-day return of a stock index on announcement day t, and PR refers to the

policy rate, e denoting the expected change and u the unexpected change. X is a vector of all the other

identifiable factors, other than policy rate changes, which affect the announcement day returns. t is the

announcement day. a, b, c and d are parameters and

is the residual.

Stock prices are forward looking and should therefore be taking account not simply of all the

known factors that will influence returns but all of the expected future events as well. Monetary policy

decisions, which follow an announced timetable, will form part of that expectation. Thus if

expectations are correct the expected change, PRe, should have no observable impact on returns on

the day it is announced. It is only when the policy rate announced is different from that expected that

returns will be affected; i.e. it is the surprise element in policy that moves prices. We should therefore

find that b is not significantly different from zero.

Clearly the way in which expectations are measured will be crucial to the determination of the

surprise. We assume that the price of policy-rate based futures contracts will be a reasonable measure

of what the market expects. Futures are not traded in the policy rates themselves but in closely related

90 day market rates. Therefore we use the 90-day Bank Bill rates instead of the official cash rate (OCR)

8 It would only be where there is an emergency monetary policy committee meeting to handle a rapid threat to financial stability that such a result might occur and that is not a characteristic of our dataset. 9 See Farka (2009)

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for New Zealand and the cash rate (CR) for Australia.10 In the case of the UK and the euro area we use

the 3-month LIBOR and the 3-month EURIBOR respectively, instead of the Repo Rate/Official Bank

Rate11 and the Main Refinancing Rate12.

The surprise component is calculated as the one-day change in the futures implied rate:13

PRu t = f m, t

f m, t-1 (2)

where f m, t refers to the futures rate on the announcement day (month m, day t) 14. The expected

component of the rate change is then:

PRe t = PR t

PRu t, (3)

except for the euro area where it is calculated as PRe t = PR t+1

PRu t due to the fact that the daily

EURIBOR is released before the policy rate announcement. The drawback of this approach is that if

the expectation is mismeasured then so also will be the surprise. This could result in biased estimates.15

An alternative expectation might be derived from surveys of market analysts shortly before the

announcement, although it is difficult to get consistent data across the whole time period. Jensen et al.

(1996) and Patelis (1997) have also found clear linkages between monetary policy indicators and stock

returns in a different framework. However, these alternative measures would not be high frequency and

measure expectations on the day of the announcement. It will also be difficult to get equivalent

measures from the four countries. Rosa and Verga (2007) show that it is possible to construct an index

from the ECB s use of code words, particularly in their post-decision press conference which give good

predictability of the nature of the next monetary policy decision. Indeed they suggest that the index

they build from these statements and a simple Taylor rule can improve on futures markets as a forecast

of the actual interest rate change if they are combined. This suggests that measures of expectations

through futures might be inefficient. Despite this, Rosa (2008) argues that the Federal Reserve is more

predictable, although it offers far less explanation of its actions than the ECB. Moreover, on Rosa s

data, which cover the period from 1999 through to mid-2006, the Federal Reserve has a greater impact

on the yield curve through monetary policy surprises than does the euro area for any given surprise.

10 Guender and Rimer (2008) spell out the determinants of the 90-day rate and the implementation of monetary policy in New Zealand. 11 The Repo Rate served as the policy rate during 1997-2005; it was replaced by the Official Bank Rate in 2006. 12 See Gregoriou et al. (2009) for the use of LIBOR and Bohl et al. (2008) for the use of EURIBOR. 13 Kuttner (2001) is usually credited with being the first to adopt this approach. 14 The implied futures rate is calculated as 100 minus the daily settlement price. 15 The evidence is somewhat mixed. Chernenko et al. (2004) present evidence that forward and future prices are generally not pure measures of market expectations as they are heavily affected by the presence of risk premia. However, Piazzesi and Swanson (2008) find that, although excess returns on federal funds rate futures in the US have been positive on average and strongly countercyclical, monetary shocks generated from daily futures prices are robust to time-varying risk premia.

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(We follow up one specific suggestion in Rosa (2008) by seeing whether the indication given by the

Reserve Bank of New Zealand on the path of future interest rate decisions has an impact

see Section

3.2.1.)

Calculating stock returns from the daily price data is straightforward, using continuous

compounding:

r = ln (Pn+1/ Pn) (4)

where Pn is the closing stock price on day n. There is however an element of choice over which index

to use in measuring the overall market, hence in all cases except New Zealand where there is no

obvious substitute covering the data period, we re-estimate using an alternative market index for each

country. This will act as a check on the robustness of the results. The aggregate stock indices are:

NZXALL of New Zealand, S&P/ASX 200 and FTSEAU of Australia, FTSE100 and FTSEUK of the

United Kingdom, and EUROSTOXX50 and EUROSTOXX of the euro area.

1.2 Asymmetry

The baseline model assumes that the response of stock prices to monetary policy surprises does not

vary according to other factors. However, there are several reasons for suggesting that reactions to

monetary policy may not be symmetric over the economic cycle. Economic behaviour is itself not

symmetric over the course of the cycle. Mayes and Viren (2011) show with European data that there

are two main asymmetries. The best known instance is the Phillips curve. In the up phase of the cycle,

falls in unemployment are associated with increasingly large increases in inflation. In the down phase

of the cycle the curve is much flatter and the same proportionate change in unemployment is associated

with little decrease in inflation. Secondly the relationship between employment and output also varies

across the cycle. The falls in employment (rise in unemployment) associated with falling or slowing

growth are larger than the subsequent rises in employment (falls in unemployment) when output

regains the same levels. Thus the economic downturn results in a permanent reduction in employment

compared to output. An alternative explanation would explain the same results in terms of changes in

the behaviour of productivity (as in the real business cycle literature for example).

Basistha and Kurov (2008) and Farka (2009) show that US stocks respond much more strongly

when economic performance is weak (recessions or easing cycles of monetary policy). Mayes and

Viren (2011) also show that the response of monetary to assets prices varies over the course of the

cycle, which might have a further impact on both the estimates and the responsiveness of stock prices

to monetary policy surprises. Surprises to shift asset prices might also be used both as the cycle nears

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its peak or trough as policy seeks to moderate the cycle. We follow the earlier work in Mayes and

Viren in using a threshold approach to allowing behaviour to vary across the phases of the business

cycle. The nature of the asymmetry may well be more complex but the limited amount of data

precludes many more sophisticated approaches to estimation than this two regime model.

However, a second type of asymmetry which may exist among the stock responses is asymmetry

due to the sign of the surprise rate change. Markets may respond differently when the surprise is

positive rather than negative; for example, if investors are conservative, they may tend to react more

strongly to bad news than to good news. We therefore also test for this type of asymmetry as well. Of

course the two forms of asymmetry may be interrelated. Bad news in the down phase of the cycle may

generate a more heavily downward shift in stock prices than if it were to occur in the up phase. The

response to positive news may be similarly asymmetric but there is no clear prior reason to expect that

the degree of asymmetry should be the same for positive and negative shocks.

To take account of the business cycle effect, we use the threshold regression approach (Teräsvirta

and Granger, 1993; Tong, 1983), which effectively allows all the coefficients to vary between the up

and down phases of the cycle by including the dummy variable CONTRACT, which equals to 1 for all

observations that fall into the contraction periods determined using OECD s business cycle turning

points, and zero otherwise. This variable is also interacted with the expected and surprise monetary

policy changes.

The same approach is used to test for asymmetry in respect to the response to positive rather than

negative surprises. We use negative surprises as the base case and include a dummy variable

POSITSURP, which equals 1 when the surprise is positive and 0 otherwise. These extra variables and

those discussed later in the context of crises and robustness tests form part of the X vector in the

formulation of the relationship shown in (1).

1.3. The impact of the global financial crisis

Although crises could be treated simply as just a business cycle with a deeper trough, there are reasons

for suggesting that they engender a quantitatively different response. Crises engender fear and an

element of panic that may be absent in a more gentle recession where financial variables do not form

part of the problem in themselves. The global financial crisis has had widespread negative impacts on

financial markets, hence changes in responses to monetary policy can be expected. The crisis effect has

documented by Gregoriou et al. (2009) for the UK, where there is a dramatic shift in stock price

responses, from significantly negative during the pre-crisis period to highly positive during the crisis.

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They argue that the finding highlights the inability of monetary policy-makers to reverse, via interest

rate cuts, the negative trend observed in stock prices after the onset of the credit crisis. This change in

sign would be quite a dramatic departure for stock price reactions.

However, due to the severity of the global financial crisis, some central banks have been faced

with the zero bound problem in exercising monetary policy. This is seen most obviously in the UK s

Official Bank Rate. From March 2009 onwards, the OBR has remained at 0.5%. The euro area has

been similarly constrained since May 2009. Once the policy rate has reached, or is close to, the zero

bound, the behaviour of the stock market can be expected to be different. Traditional models, such as

the event-study approach used here, can only reflect upside changes, since no further downward

adjustment is possible in either market expectations or the policy rate. Therefore, the zero bound

period also contributes to the difference in behaviour observed during the crisis.

An obvious extension in the crisis period would be to try to take account of the impact of

quantitative easing. However there is no obvious mapping of the quantitative changes and the interest

rate changes so we would not be able to compare crisis and non-crisis periods directly.16 It is also not

quite clear how the futures market would behave in the two periods. Futures can reflect the existence of

what are effectively negative interest rates.

The euro area s response to the crisis has been a little different from that of the Bank of England

but it also effectively hit the zero bound in that any further interest rate reduction would have removed

any remuneration on deposits. However, a further facet which might make the responses during the

financial crisis period different is that central banks have been responding simultaneously to threats to

financial stability and price stability, yet their range of monetary tools to do so is limited and such

measures will have impacts on both objectives. This may therefore increase the uncertainty about what

the measures are intended to achieve and indeed about what they may achieve. This in turn therefore

may alter the response of stock prices to monetary policy innovations in the crisis period. In the case of

the euro area, interest rates were raised in the first part of 2011 (outside the data period) by the

minimum 25 basis points but without withdrawing the liquidity measures that are assisting European

commercial banks and effectively the troubled governments of Greece, Portugal and Ireland since it is

government bonds that the ECB takes as collateral. There is thus no neatness to the policy regime,

which complicates our ability to investigate the period.

16 Clearly we might be able to construct some sort of expectational variable concerning the size of quantitative easing on each announcement day but it is not immediately apparent how that or the surprise would be translated into interest rate space.

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Since neither Australia nor New Zealand came close to the zero bound nor did they have to do

anything much in the way of extraordinary measures other than a temporary guarantee for new

wholesale borrowing by the banks, we are able to see whether behaviour was different in the financial

crisis from other periods.

To account for the effect of the financial crisis on the stock responses, we effectively divide our

sample into two by introducing a dummy variable CRISIS, which equals to 1 for the crisis period and 0

otherwise. CRISIS is interacted with the expected change and surprise change variables in equation (1),

to form two additional dummy variables in the new regression. Hence all of the parameters are

permitted to be different in the two periods. We tried some experimentation to see how the crisis period

should be defined, as its intensity varied and in some regions the full force of the crisis did not come

through until the collapse of Lehman Brothers in September 2008. We tried altering the onset date over

the plausible range and found that the collapse of Lehman Brothers made the best threshold date for the

euro area, whereas in the UK it makes sense to date it from August 2007 and the problems with

Northern Rock. For Australia and New Zealand, the different dates lead to similar results, so we choose

the earlier date of August 2007. However the impact of the Lehman Brothers collapse acts so much as a

shock that the ensuing month needs to be treated as a special event, with an extra effect over and above

that of the rest of the crisis. What is particularly interesting is that it is not the zero bound period which

distinguishes behavior in the case of the UK and the euro area but the whole of the crisis period, even

when interest rates were positive and the full extent of the problems not anticipated.

The collapse of Lehmans is not the only special event in the data period as the collapse of the

dotcom bubble in 2002 also led to a short run disturbance in stock markets. We therefore account for

these special events by including two further dummy variables, D2002 and DLehman, to account for

the effects of the dot-com bubble burst and the collapse of Lehman Brothers respectively. DLehman

is equal to 1 between 15 September and 3 December 2008 and 0 otherwise,17 and D2002 is equal to 1

in August 2002 and 0 otherwise.18

1.4 Robustness Checks

17 The 3 December date is that used by Gregoriou et al. (2009), which we maintain for comparative purposes. One might wish to alter the length of period as it is difficult to ascribe any specific event as terminating the episode. Fortunately the estimates are not very sensitive to variation over a two month period round this date. An alternative would be to include a measure of abnormal spreads in the estimation itself in an attempt to get a data driven view of the extent of the abnormal period. 18 For Australia, there is no observation for August 2002, so the D2002 variable is not required.

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We also need to filter out any consistent or identifiable events that might have affected behaviour in

order to get better determined estimates. There is one obvious example in the case of New Zealand. On

many occasions the interest rate announcement is released at the same time as a Monetary Policy

Statement which normally contains a statement about the direction of probable future changes in the

policy rate (see Section 3.2.1 for a more detailed explanation of New Zealand s monetary policy).

While such statements are only a description of what is likely to be needed should events actually

follow the lines suggested in the forecast and analysis, which is published along with the policy

announcement, they will still have an influence on financial markets view of the future. These

influences are likely to be systematic according to sign of the projected changes. We therefore add

three dummy variables to the regression which hold the value unity in the event that there is a

contemporaneous Statement indicating positive, negative or zero interest rate changes in the future. As

in other examples these variables are interacted with PRu t.

These variables will only be approximate as there is a prospective path for interest rates and not

simply an indication of what the next change will be. The ECB goes to a great deal of trouble to

prepare markets for the next interest change through a number of code words, in the main related to the

term vigilant . If the word is not mentioned then a change in interest rates is not likely at the next

meeting. There are other indications released through the press conference that the President of the

ECB holds on the same day as the interest rate announcement.19

Another factor which may affect the outcome of the regressions is inflation targeting. The

practice involves a central bank steering the current inflation rate towards a preset long-term target rate.

Since monetary policy is a major channel for achieving the inflation target, the presence of an inflation

target is likely to alter the financial markets perceptions of monetary policy. Of the four countries in

this study, New Zealand, the UK and Australia have all adopted inflation targets, while the ECB has

been less specific in its approach to inflation, seeking to keep inflation below but close to 2% a year

over the medium term. Our Australian data allow us to test for the impact of the introduction of an

explicit inflation target in 1994 as the Reserve Bank of Australia was announcing its interest rate

decisions before then. The test takes the same form as our other tests for different responses under

different conditions through a dummy variable PRE-IT, which equals to 1 for observations before

19 Rosa and Verga (2007) offer a coherent attempt to identify the various code words and their implication for the euro area policy stance.

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August 1994 and 0 otherwise, in the regression equations for Australia. PRE-IT is interacted with both

PRe t and PRu

t to form two additional variables in the revised regressions.20

2. Data and Sample

Our period of investigation is limited by when central banks have published monetary policy decisions.

It is only relatively recently that central banks have had an announced schedule of meeting dates for

decision making accompanied by a clearly announced decision at a specific time. It is still the case that

only some explain that decision on the announcement day. The end date simply reflects the timing of

the analysis and is hence arbitrary.

2.1 Policy Rate Announcements

Information on policy rates is on the websites of the Reserve Bank of New Zealand, the Reserve Bank

of Australia, the Bank of England and the European Central Bank. The respective times at which the

rate announcements are made are: 9:00am for New Zealand s OCR, 2:30 pm (Eastern time) for

Australia s CR, 12:00 noon for the UK s Repo Rate or Official Bank Rate, and 1:45 pm (CET) for the

euro area s Main Refinancing Rate. The sample periods for the announcements are listed in the

appendix.

As mentioned above, we use the market-based daily 90-Day Bank Bill, 3-month LIBOR and 3-

month EURIBOR rates instead of the actual policy rates in the analysis in order to match with the

futures contracts. The 90-Day Bank Bill rates for NZ and AU are found on the respective reserve

banks

websites. The data source for the EURIBOR is Datastream, while the daily LIBOR rates come

from the British Bankers Association.21 The daily LIBOR is announced at around the same time as the

UK policy rate announcements, while the EURIBOR rates are announced at 11 am (CET), before the

ECB s policy rate announcements.

Observations are generated by every policy announcement, even though the most common

outcome is no change. A no change decision can represent a surprise just as much as a change and

hence there will be unexpected and expected changes on each occasion.

20 There is some debate over what is the appropriate date for the introduction of inflation targeting in Australia. We follow Bernanke et al. (1999) although it could be argued that it is the exchange of letters Governor Ian Macfarlane and Treasurer Peter Costello in August 1996 that constitutes the formal introduction. The earliest reference is in a speech by the then Governor, Bernir Fraser, in March 1993 (Fraser, 1993). 21 We are grateful to Geoffrey Wood for providing these data

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2.2 Stock Prices

The daily closing prices of all the stock indices included in this study are obtained from Datastream.

Although we aimed to have two market indices for each country, the NZXALL is the only usable index

for New Zealand since the only other alternative, the NZX50, has too few observations. For Australia,

we include the ASX/S&P200 index, whose start date of June 1992 is slightly later than that of the Cash

Rate announcements. The prices for the other market indices, FTSEAU of Australia, FTSE100 and

FTSEUK of the UK, and EUROSTOXX50 and EUROSTOXX of the euro area, are all available for the

entire date range of the respective policy rate announcements. Clearly, our sample period for each

country is determined by the length of the shortest series.

2.3 Futures Contracts

For calculating the rate surprises, we chose four futures contracts based on the following criteria: first,

the futures contract must be directly based on either the policy rate or a close substitute; and second,

the futures price data must be available since the first policy rate announcement. There are two

potential futures contracts that satisfy the first criterion but not the second

the New Zealand 30 Day

Official Cash Rate Futures, first traded in 2006, and the Australian 30 Day Interbank Cash Rate Futures,

first traded in 2003. Instead of these futures contracts, we use the NZ and AU 90-day Bank Bill futures,

since the 90-day bank bill rates closely follow the policy rates. For the UK and the euro area, we use

the readily available 3-month LIBOR and 3-month EURIBOR futures. All futures prices are obtained

from Datastream.

2.4 Business Cycles

We use the business cycle turning points data provided in the statistics section of the OECD s website

in determining the contraction periods. The data are found under the title OECD Composite Leading

Indicators: Reference Turning Points and Component Series , and are available for all the OECD

countries and major areas. We use the US National Bureau of Economic Research s method to

determine the business cycle phases

the contraction phase is from a peak to a trough, and the

expansion phase is from the trough to the next peak. A cycle is from a peak (trough) to the next peak

(trough). The date of each trough is included in a contraction phase, while the date of each peak is

included in an expansion phase. In our dataset, there are approximately 2.5 cycles for NZ, 3 cycles for

both AU and UK, and 2 cycles for the euro area.

14

2.5 Sample Period

We include as many rate announcement observations as possible for each stock index, while taking into

account the restrictions imposed by the start dates of the individual indices. The main sample period for

each country is: 21/04/1999

26/02/2010 for NZ, 23/01/1990

26/02/2010 for AU, 10/06/1999

26/02/2010 for UK22 and 4/03/1999

26/02/2010 for the euro area. The only index with a sample

period variation is the ASX/S&P200 of Australia, which has a sample period of 08/07/1992

26/02/2010.

2.6 Descriptive Statistics

It is immediately clear from Table 1 that there is large variation in the number of rate announcements

made by each country, reflecting both the start date and the frequency of monetary policy meetings.

Although the Australian sample has the earliest start date among the four countries, it contains the

fewest announcements, due to the fact that the RBA did not announce zero rate changes until 2007. The

ECB has made the most announcements due to its high frequency of meetings. The standard deviations

of the rate surprises show that the AU surprises are the most volatile, and both the UK and euro area

surprises have low volatility. A possible explanation of this is that, as small open economies, Australia

and New Zealand are more open to external shocks. Two other possibilities are that the UK and euro

area markets are either better at predicting policy rate changes, or are consistently biased in their

predictions.

<Insert Table 1 about here>

A comparison of the stock returns standard deviations (last two rows of Table 1) shows that, as is

expected, the volatility in returns on event days is consistently higher than that on the days preceding

the event in each of the four countries. We follow Kholodilin et al. (2009), in considering this single

adjacent period as the comparator. The euro area indices have the highest return volatility on both event

and pre-event days, while the NZXALL index has the lowest. This could be a reflection of the large

geographical and economic coverage of the euro area indices. The AU and UK indices have very

similar standard deviations on both event and pre-event days.

2.7 Outliers

22 The first two years of Repo Rate announcements are excluded due to insignificant reactions. See Section 3.2.3 for a detailed discussion.

15

The crisis period is inevitably a minority of the period under examination but it represents between

11% and 38% of the interest rate decisions taken by each authority. The zero bound period is shorter

and represents 9% of the decision for the UK and 6% for the euro area. Interest rate increases and

decreases have roughly the same frequency over the period for Australia, the euro area and NZ and the

business cycle phases are also well matched for the UK and NZ. The degree of discrepancy in the other

cases is by no means large enough to suggest that the results are due to just a few observations. There

are therefore sufficient observations to get reasonably determined coefficients on the interaction terms

in the equations. Nevertheless to ensure that it is not extreme or unusual observations that are

generating the results, estimates have also been made with such outliers removed.

3. Results and Discussions

3.1 Main Results

If we apply only the most basic regression, where the effects of asymmetry and the crisis are ignored,

only the New Zealand and Australian stock markets display significant reactions to policy rate changes

(Table 2). The NZXALL index and the FTSEAU index both react negatively to surprises, although an

insignificant reaction is observed for ASX200 which has a slightly shorter sample period than FTSEAU.

The size of the NZXALL and FTSEAU surprise coefficients imply an average reaction of about 0.9%

and 0.28% respectively to an unanticipated 25-basis-point rate increase. These reactions are smaller

than that for the US which, according to Bernanke and Kuttner, is about 1%. Surprisingly, we also find

significant negative coefficients for the expected change component.23 This is a departure from theory,

and could be due to the expected rate changes not being fully acted upon prior to the announcement day.

In contrast, the overall responses of UK and euro area market indices to both components are

insignificant. This is largely because, in these regions, behaviour is clearly different in the crisis period

from normal times (Table 3, Panel A). Separating out normal times gives more conventional responses.

<Insert Table 2 about here>

Nevertheless it is worth pursuing this issue of why expected measures may not work as well as

theory predicts. Rosa and Verga (2008) show that the press conference held by the ECB President after

the announcement of the monetary policy decision modifies the market s reaction to the announcement.

23 We had expected that negative coefficient on the expected change would disappear or at least be insignificant when fuller specifications of the model were estimated. However, while significance levels do fall, the expected change term continues to play a role in many of the regressions. The simplest explanation would be that the particular choice of expectations is poorly specified or that people do not fully act on their expectations.

16

Further information, mainly in the form of key phrases or code words, helps the market get a better

understanding of which way interest rates may move in future, which has an immediate impact on the

current rate. Thus since we are measuring surprises on a daily basis and not a tick by tick basis as Rosa

and Verga do, perhaps we are not getting such a clean measure of the surprise from the interest rate

announcement itself. The central banks vary in the amount of information they produce at the time of

the interest rate announcement. The Reserve Bank of New Zealand produces an extensive statement at

the time and the Governor holds a press conference. The Bank of England only reveals the detailed

reasoning with a lag. The euro area as just noted holds an immediate press conference. We would

therefore expect differences between the countries.

As Rosa and Verga (2007) point out, there is some evidence (Paizzesi and Swanson, 2008) that

excess returns on interest rate futures, in the US at any rate, do fluctuate with the economic cycle. In

this case, this effect would need to be removed before the impact of monetary policy could be

evaluated properly. However, the US does not form part of our sample and we are not aware of

evidence that this result is found in the countries that we do study.

While the NZ and AU stock market responses are not significantly affected by the financial crisis,

the crisis effect found by Gregoriou et al. (2009) is present in the euro area as well as in the UK. Prior

to the crisis, all of the market indices of the four countries/regions (including the ASX200 of AU) react

significantly negatively to monetary policy surprises. However, the reactions of the UK and euro area

indices to both expected and surprise components become positive during the crisis period

rather than

serving its original purpose of stimulating the market, a surprise rate cut causes even more pessimism

about economic conditions. The NZ and AU results are in line with expectations since the central banks

of these two countries did not find it necessary to reduce their policy rates to the zero bound, and the

Australian economy was never in recession. Also as expected, the extreme effect of the collapse of

Lehman Brothers in the crisis and the abnormal impact of the collapse of the dotcom boom are

reflected by highly significant negative coefficients of the DLehman and D2002 variables, evident for

all countries except Australia.

<Insert Table 3 about here>

The crisis effect in the UK and the euro area intensifies as the policy rates approach the zero

bound (Table 4). During the zero bound period, the reactions of UK and euro area market indices to

both components are positive and extremely large, especially for the euro area. The sizes of these

coefficients no longer allow any practical interpretation other than that the markets tumbled even faster

after a negative shock. Compared to the zero-bound period, the pre-zero-bound crisis period has a

17

much smaller, although still significant, effect on the responses. Nevertheless it is clear that the change

from normal behaviour occurs around the time of the onset of the crisis in August 2007 rather than

simply later when the zero bound was approached.

<Insert Table 4 about here>

Although the Australian stock price responses are not significantly affected by the financial crisis,

they are significantly procyclical under the business cycle model. The AU market responses to both

expected and surprise rate changes are insignificant during expansions, but significantly negative

during contractions (Table 3, Panel B). (When the pre-inflation-targeting period is separated out, the

response in expansions becomes positive, as discussed in section 3.2.2.) This is similar to the US

results of Basistha and Kurov (2008) which show a stronger response to the surprise rate changes

during recessions. Basistha and Kurov argue that the presence of cyclicality is a reflection of the credit

channel of monetary policy, and that the underlying cause of the difference in response between

expansions and contractions is procyclical fluctuations in both the availability of banks loans and the

credit worthiness of firms. However, there is no evidence for such cyclicality in the stock responses of

the NZ, UK and euro area.

There is also some evidence from our sample that stock responses can differ depending on the

sign of the surprise. Unlike the experience of Bernanke and Kuttner (2005) in finding no evidence of

asymmetry in the response to positive as opposed to negative surprises in the US, we find a stronger

reaction to positive surprises in the case of the NZ stock market. Table 5 shows that the response of the

NZXALL index to positive rate surprises is larger in magnitude than the response to negative surprises

under all regression models. The difference becomes more significant and clearer if we take account of

the confounding from announcements of probable future rate changes (Table 6). This suggests that NZ

investors are generally conservative and are more willing to adjust to bad news than they are to good

news. However, the conservatism hypothesis is not supported by the results of the other countries,

which do not indicate any clear asymmetry due to the sign of the surprise.

<Insert Table 5 about here>

Thus for all countries in our sample we see changes in stock price responses according to

different conditions: for the UK and the euro area it is in the financial crisis, in Australia it is across the

business cycle and in New Zealand it is according to the sign of the policy surprise.

3.2 Explanation of Some of the Anomalies

3.2.1 Projections of future rate changes

18

New Zealand is unique among our sample of countries in that the Reserve Bank of New Zealand s

announcements frequently contain information about the likely direction and approximate timing of

future rate changes.24 For example, the 18 August 1999 news release states: The Reserve Bank today

left the Official Cash Rate (OCR) unchanged. However, it indicated that an increase before the end of

the year is increasingly likely. We therefore augment our analysis by including the nature of the

projected possible rate changes in our explanatory equation. While the path described can be more

complex we focus on simply whether the initial indication for future decisions is for an increase, a

decrease or maintenance of the present setting. This acts as a complement to the work of Rosa and

Verga (2007, 2008) and Rosa (2008) where they show that there is some predictive power in the use of

code words by the ECB as it tries to make sure that markets are not surprised by policy decisions. Put

differently, the announcement effect, and hence the surprise, are effectively moved forward by one

month to the time of the release of the code words. This complicates the analysis. We have not here

attempted to extend Rosa and Verga s dataset on the ECB, which assigns values of +1, 0 and -1

according to the preponderance of coded phrases, to our data period, however, ECB pronouncements

have been used to construct indicator variables in a different context Montagnoli and Mayes, 2011).

Our tests show that an indication of a probable future change has a significant effect on stock

prices. The NZ market responds to a future positive change or a future negative change in the same

direction as the change, while there is very little reaction to an indication of future zero rate change

(Table 6). These responses contrast with the clear negative reaction to a contemporaneous surprise. In

the case of a contemporaneous positive surprise, the impacts of the surprise and a future increase are

similar in size but opposite in sign. Hence if they occur together there would be little net impact on

stock prices. In comparison, the effect of future negative changes on the contemporaneous response is

larger in magnitude; however, it is only significant during the crisis and business cycle contractions,

unlike the impact of future positive changes, which is unaffected by economic conditions.

<Insert Table 6 about here>

The positive reaction to a probable future rate increase could be explained if such a change

signals both projected growth in the economy and strong credibility in the Reserve Bank of New

Zealand s inflation fighting credentials. The signal may be even stronger if it were to occur during the

crisis period (which is not the case in our dataset). Similarly, a probable future rate cut is perceived as

an indicator of weakening economic conditions, especially during the crisis and contractions, when

24 Other countries publish a similar description of likely future interest changes if expected circumstances do not change. Norway and Sweden are perhaps the best known examples.

19

markets are generally pessimistic. When economic conditions are favourable, a future rate cut is given

a more neutral interpretation and treated similarly to a zero future rate change.

3.2.2 The introduction of full inflation targeting in Australia

We find in the ASX200 index a significant change in stock price response to monetary policy after the

adoption of an explicit inflation target (Table 7). While the index s pre-inflation-targeting reaction to

the surprise component is significantly negative, this becomes insignificant after the adoption of the

target, except when the business cycle effect is taken account of. After the separation of the expansions

and contractions in the inflation targeting period, we observe that the ASX200 reacts positively to both

components in expansions and negatively in contractions. These responses suggest that, when inflation

targeting is taking place, the possible effects of rate surprises on inflation become an important driver

of market reactions.

<Insert Table 7 about here>

During expansions, a positive surprise may be welcomed as an extra effort to combat inflation;

while a negative surprise is seen as unfavourable in an already booming economy, when inflation-

reducing measures are much anticipated. As a result we observe a positive response. During

contractions, however, investors become more risk averse. With the slowed economic growth, inflation

is no longer a primary concern; the detrimental affects of positive surprises now exceed the benefits,

and the theoretical negative reactions expected by theory are restored.

The inflation targeting effect is not evident in the FTSEAU index which has an earlier sample

start date, although the two indices are very similar in terms of the asymmetry and crisis effects.

3.2.3 The impact of the choice of sample period on the results for the UK

For our UK sample, we have chosen the start date as June 1999, the same as Gregoriou et al. (2009),25

even though the Repo Rate announcements began in June 1997. We obtained similar results as

Gregoriou et al. under the crisis model, as their reported coefficients for expected and surprise changes

are -8.17 and -6.52 respectively. When the first two years of data are included, however, we observe

insignificant stock responses to both expected and surprise components (Table 8). This shows that our

UK results, and those reported in previous papers, are somewhat sensitive to the choice of sample

period. In particular, the results cannot be extended to the first two years of Repo Rate announcements.

25 We thank Alberto Montagnoli for helpful comments and suggestions about the data.

20

<Insert Table 8 about here>

There are various possible explanations for the insignificant UK stock reactions during the first

two years. The newly established Monetary Policy Committee might have been less consistent in

setting the interest rates, or participants in the stock market may have been less able to derive correct

expectations of the policy rate changes. There is some evidence for the second explanation from our

data. If the market is less able to anticipate policy rate changes, then the volatility of the surprise

component during the first two years should be higher. This is indeed the case -- the volatility during

the first two years, as measured by the standard deviation, is a little over 9 basis points, as compared to

an average of 7 basis points during the years that followed.26

4. Conclusion

This study explores the responses of aggregate stock price indices of New Zealand, Australia, the UK

and the euro area to monetary policy rate announcements. Similar to previous studies, we find

significant negative stock price reactions to monetary policy surprises. We contribute several new

findings to the literature. First, the financial crisis effect identified by Gregoriou et al.(2009) for the

UK is also present in the euro area stock market. Whereas the pre-crisis reactions are significantly

negative, the UK and euro area responses to both expected and surprise rate change components

become positive during the crisis. This effect is amplified during the zero bound period. In contrast, the

New Zealand and Australian stock responses remain negative during the crisis. This is consistent with

the fact that the NZ and AU policy rates did not reach the zero bound.

Second, the Australian stock market response is significantly procyclical. The responses of both

ASX200 and FTSEAU to the rate change components are stronger (more negative) in business cycle

contractions than in expansions. According to Basistha and Kurov (2008), the cyclicality in response is

attributable to the credit channel of monetary policy. Furthermore, we find clear evidence of a change

in response after the onset of full inflation targeting (August 1994) in the ASX200 index. While the

index reacts negatively to surprise rate changes in the pre-inflation-targeting period, the overall

response from August 1994 onwards is insignificant

in expansions, the response is positive,

consistent with the extra inflation reducing effort of a surprise rate increase or the inflation increasing

effect of a surprise rate cut. In contractions, inflation is presumably no longer a primary concern, and

the theoretical negative reactions are restored.

26 Results for other countries are not so sensitive to the choice of the specific data period.

21

Third, we show that the NZ stock market responds more strongly to positive surprises than

negative ones, which lends support to the investor conservatism hypothesis. However, no evidence of a

similar asymmetry is found for the other countries. NZ is unique in our sample in announcing

conditional probable future interest rates changes at the same time as the current policy decision.

Indications of these probable future rate changes are also found to have a significant effect on the NZ

market. A probable future rate increase has a positive effect on the contemporaneous response of the

NZXALL index, while a probable future rate cut has a negative effect. In the case of a future zero

change there is little reaction. Interestingly, the reaction to future rate cuts is only significant during the

crisis and contractions, indicating that a further cut is only regarded as bad news when markets are

generally pessimistic. In contrast, a future rate increase is viewed as a favourable signal regardless of

economic conditions.

Last, our test of an extended sample period for the UK shows that the market response to

monetary policy is insignificant during the first two years of Repo Rate announcements. Hence the

conclusions drawn from the UK sample in our study and those in the existing literature cannot be

applied to this period.

Taken together therefore our results show that while there are some similarities between the US

and Australia, the euro area, New Zealand and the UK in the response of stock prices to monetary

policy surprises, there are also important differences. There are some signs of asymmetry both across

the economic cycle and depending on the sign of the surprise but Australia and New Zealand, which

did not hit the zero nominal interest rate bound in the global financial crisis, do not show a change in

behaviour unlike the euro area and the UK. However, the global financial crisis is not over and the

addition of further data points could lead to different conclusions.

22

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25

Appendix: Sample Periods for Policy Rate Announcements

Country Start Date Description of Start Date End Date

NZ 21/04/1999

first published OCR policy decision

26/02/2010 AU 23/01/1990

first published monetary decision

UK 06/06/1997

first announcement after intro. of Repo Rate

euro area 4/03/1999 first published monetary decision

26

Table 1 Descriptive Statistics

This table reports selected descriptive statistics for policy rate surprises and returns of equity market indices of New Zealand, Australia, the United Kingdom and the euro area. Sample period is: 21Apr99

26Feb10 for NZ, 08Jul92

26Feb10 for ASX200, 23Jan90

26Feb10 for FTSEAU, 10Jun99

26Feb10 for UK, and 4Mar99

26Feb10 for euro area. Same as Kholodilin et al. (2009), we define non-event days as the days preceding the event

days. NZ Index

AU Indices

UK Indices

euro area Indices

NZXALL ASX200

FTSEAU

FTSE100

FTSEUK

EUROSTOXX50

EUROSTOXX

Number of events in sample: policy rate announcements 88 57 69 130 130 167 167 Standard deviation of rate surprise, basis points 10 15 19 7 7 6 6 Standard deviation of equity return on event days, % 0.80 1.33 1.29 1.29 1.27 1.78 1.60 Standard deviation of equity return on nonevent days, % 0.74 1.07 1.08 1.10 1.08 1.44 1.33

Table 2 Baseline Regression Results

This table reports the results of the baseline regression, where the indices' returns are regressed against the expected and surprise rate change components. Sample size is: 88 for NZXALL, 57 for ASX200, 69 for FTSEAU, 130 for FTSE100 and FTSEUK, and 167 for EUROSTOXX50 and EUROSTOXX. Parentheses contain t-statistics, calculated using Newey-West heteroskedasticity-consistent estimates of the standard errors. ***, **, * indicate statistical significance at the 1, 5, 10 % level, respectively.

NZ Index

AU Indices

UK Indices

euro area Indices

Regressor NZXALL ASX200 FTSEAU FTSE100 FTSEUK EUROSTOXX50 EUROSTOXX Intercept 0.000 0.000 0.000 -0.002 -0.002 -0.001 -0.001

(0.230) (0.093) (0.121) (1.492) (1.544) (1.023) (1.111) Expected rate change -4.787** -2.417** -3.577*** -3.073 -3.177 -8.057 -5.685

(2.475) (2.065) (3.791) (1.107) (1.133) (1.631) (1.369) Surprise rate change -3.694*** -0.601 -1.127** 2.188 2.137 -0.225 1.156

(5.076) (0.575) (2.580) (0.519) (0.511) (0.064) (0.382)

R 2 0.193 0.020 0.079 0.076 0.080 0.046 0.041 Adjusted R2 0.174 -0.017 0.051 0.061 0.065 0.034 0.030

27

Table 3

The Crisis and Business Cycle Effects

This table reports the results of the crisis effect and business cycle effect regressions for each market index. Sample size is: 88 for NZXALL, 57 for ASX200, 69 for FTSEAU, 130 for FTSE100 and FTSEUK, and 167 for EUROSTOXX50 and EUROSTOXX. Crisis is defined as August 2007 onwards for NZ, AU and UK, and end of September 2008 onwards for EA. Contraction is determined using OECD business cycle turning points. Parentheses contain t-statistics, calculated using Newey-West heteroskedasticity-consistent estimates of the standard errors. ***, **, * indicate statistical significance at the 1, 5, 10 % level, respectively.

Panel A: The crisis effect

NZ Index

AU Indices

UK Indices

euro area Indices

Regressor NZXALL ASX200 FTSEAU FTSE100 FTSEUK EUROSTOXX50 EUROSTOXX Intercept 0.000 0.000 0.000 -0.001 -0.001 0.000 0.000

(0.668) (0.045) (0.054) (0.588) (0.646) (0.068) (0.062) Expected rate change -6.015** -2.417 -3.690*** -6.884*** -7.059*** -12.117*** -9.337***

(2.374) (1.510) (3.847) (3.968) (4.035) (3.971) (3.797) Surprise rate change -3.424*** -1.265* -1.415*** -5.130** -5.112** -3.901** -2.188

(3.123) (1.862) (3.793) (2.180) (2.196) (2.347) (1.620) Expected rate change * CRISIS 2.753 4.699 6.280 13.993*** 14.321*** 35.324*** 31.618***

(0.814) (0.784) (1.105) (3.638) (3.696) (3.278) (3.393) Surprise rate change * CRISIS 0.144 5.697 6.403 10.268*** 10.479*** 37.933** 33.874**

(0.086) (0.827) (0.941) (2.914) (2.991) (2.057) (2.095) dLehman -0.029*** -0.008 -0.008 -0.056*** -0.055*** -0.034*** -0.033***

(17.922) (0.542) (0.542) (14.582) (14.241) (2.799) (2.961) d2002 -0.004*** - - -0.050*** -0.048*** -0.048*** -0.038***

(4.258) - - (42.170) (42.801) (39.170) (35.592)

R2 0.353 0.070 0.133 0.436 0.438 0.267 0.263

Adjusted R 2 0.305 -0.021 0.064 0.408 0.411 0.240 0.236

28

Table 3, continued

Panel B: The business cycle effect

NZ Index

AU Indices

UK Indices

euro area Indices

Regressor NZXALL ASX200 FTSEAU FTSE100 FTSEUK EUROSTOXX50 EUROSTOXX Intercept 0.001 0.000 0.000 -0.001 -0.001 0.000 0.000

(0.948) (0.123) (0.174) (0.984) (1.056) (0.276) (0.418)

Expected rate change -4.114** 1.682 1.442 -3.341 -3.519 -9.243** -8.557** (2.289) (0.869) (0.976) (0.961) (1.027) (2.569) (2.430)

Surprise rate change -3.451*** 2.008 1.805 -5.768 -5.649 -0.553 -0.480 (3.677) (1.234) (1.637) (1.575) (1.592) (0.249) (0.237)

Expected rate change * CONTRACT -0.597 -5.023** -5.430*** -0.146 -0.025 1.474 3.635 (0.188) (2.002) (2.924) (0.032) (0.005) (0.246) (0.681)

Surprise rate change * CONTRACT 0.296 -3.519* -3.258** 5.263 5.106 -2.908 -0.741 (0.209) (1.775) (2.498) (1.318) (1.302) (0.779) (0.232)

dLehman -0.030*** -0.011 -0.012 -0.049*** -0.048*** -0.050*** -0.046*** (22.223) (0.763) (0.777) (9.968) (9.935) (5.403) (5.325)

d2002 -0.005*** - - -0.048*** -0.046*** -0.048*** -0.038*** (6.173) - - (39.688) (38.473) (36.698) (33.531)

R2 0.347 0.067 0.125 0.410 0.408 0.220 0.216

Adjusted R 2 0.298 -0.025 0.056 0.382 0.379 0.191 0.186

29

Table 4

Effect of Zero Bound Period on UK and EA Responses

This table reports the effect of the zero bound period on the response of UK and euro area stock markets to expected and surprise rate changes. Only one index per country is shown as the alternative index has very similar results. Zero bound period is defined as March 2009 onwards for the UK and May 2009 onwards for the euro area. Pre-ZB crisis period is defined as Aug 2007

Mar 2009 for the UK and Sep

2008

May 2009 for the euro area. Sample size is 130 for FTSE100 and 167 for EUROSTOXX 50. Parentheses contain t-statistics, calculated using Newey-West heteroskedasticity-consistent estimates of the standard errors. ***, **, * indicate statistical significance at the 1, 5, 10 % level, respectively. Regressor FTSE100

EUROSTOXX50

Intercept -0.001 -0.001 0.000 0.000

(1.032) (0.780) (0.000) (0.224) Expected rate change -4.472** -6.901*** -7.689* -12.089***

(2.143) (3.885) (1.803) (3.945) Surprise rate change -3.415* -5.171** -2.308 -3.896**

(1.674) (2.166) (1.010) (2.327) Expected rate change * PreZBCRISIS - 10.890*** - 34.348**

- (3.782) - (2.269) Surprise rate change * PreZBCRISIS - 9.113*** - 37.013

- (2.823) - (1.138) Expected rate change * ZB 39.052*** 41.485*** 252.770*** 259.388***

(2.607) (2.655) (3.571) (3.706) Surprise rate change * ZB 25.729* 27.531* 230.906*** 234.590***

(1.677) (1.730) (3.541) (3.644) dLehman -0.055*** -0.053*** -0.049*** -0.035*

(11.931) (17.509) (5.352) (1.740) d2002 -0.049*** -0.049*** -0.048*** -0.049***

(39.008) (41.741) (39.399) (39.159)

R2 0.444 0.467 0.236 0.280

Adjusted R 2 0.417 0.431 0.207 0.244

30

Table 5 Asymmetrical Effect of Positive Surprise

This table reports the results of regressions which isolate the effect of positive surprises. Sample size is: 88 for NZXALL, 69 for FTSEAU, 130 for FTSEUK, and 167 for EUROSTOXX50. Only one index is shown per country as the alternative index has similar results. Parentheses contain t-statistics, calculated using Newey-West heteroskedasticity-consistent estimates of the standard errors. ***, **, * indicate statistical significance at the 1, 5, 10 % level, respectively.

Regressor NZXALL

FTSEAU

FTSEUK

EUROSTOXX50

Intercept 0.002 0.002 -0.001 0.000 -0.001 -0.001 -0.001 -0.001

(1.525) (1.656) (0.523) (0.135) (1.141) (1.056) (0.489) (0.796) Expected rate change -6.116** -4.554** -3.289*** 1.452 -7.378*** -3.667 -11.546*** -7.927*

(2.643) (2.491) (2.979) (0.965) (4.472) (1.068) (3.942) (1.793) Surprise rate change -1.924 -1.941* -1.896*** 1.875 -7.356** -6.382 -5.697** -2.352

(1.231) (1.897) (2.653) (0.897) (2.014) (1.448) (2.165) (0.831) Surprise rate change * POSITSURP -3.283 -2.927 1.862 -0.078 3.434 0.878 3.831 4.328

(1.563) (1.594) (1.219) (0.041) (0.786) (0.242) (0.830) (0.963) Expected rate change * CRISIS 2.748 - 6.994 - 16.328*** - 34.966*** -

(0.821) - (1.245) - (3.673) - (3.249) - Surprise rate change * CRISIS -0.598 - 6.572 - 12.782*** - 37.722** -

(0.364) - (0.973) - (2.852) - (2.073) - Expected rate change * CONTRACT - -0.107 - -5.464*** - 0.231 - 0.538

- (0.034) - (2.742) - (0.049) - (0.088) Surprise rate change * CONTRACT - -0.379 - -3.315* - 5.584 - -3.180

- (0.305) - (1.797) - (1.371) - -(0.820) dLehman -0.027*** -0.028*** -0.008 -0.012 -0.058*** -0.049*** -0.035*** -0.050***

(16.308) (21.229) (0.532) (0.771) (10.764) (7.823) (2.901) (5.739) d2002 -0.004*** -0.005*** - - -0.048*** -0.046*** -0.048*** -0.048***

(4.410) (5.568) - - (39.123) (38.578) (39.780) (35.919)

R2 0.369 0.358 0.140 0.125 0.441 0.408 0.270 0.223

Adjusted R2 0.313 0.302 0.057 0.041 0.409 0.374 0.238 0.189

31

Table 6

Confounding Factors in NZ Regressions

This table reports the revised regression results for the NZXALL index, after taking into account the confounding factors of probable future rate changes. Column (a) is the baseline regression, column (b) identifies the crisis and business cycle effects, and column (c) tests for asymmetry according to the sign of surprise. The sample contains 88 observations. Parentheses contain t-statistics, calculated using Newey-West heteroskedasticity-consistent estimates of the standard errors. ***, **, * indicate statistical significance at the 1, 5, 10 % level, respectively.

NZXALL

Regressor (a) (b) (c) Intercept 0.000 0.000 0.000 0.001 0.001 0.001

(0.223) (0.353) (0.577) (1.624) (1.530) (1.606) Expected rate change -5.507** -5.993** -4.085** -5.545** -6.043** -4.568**

(2.344) (2.289) (2.361) (2.328) (2.533) (2.539) Surprise rate change -3.570*** -3.818*** -4.102*** -1.966 -2.196 -2.438**

(4.168) (3.063) (3.815) (1.636) (1.325) (2.054) Surprise rate change * POSITSURP - - - -4.459** -3.774* -3.432*

- - - (2.037) (1.909) (1.897) Surprise rate change * FUTPOSIT 2.750** 2.767** 3.234*** 3.804*** 3.404*** 3.707***

(2.543) (2.247) (2.942) (3.409) (3.288) (3.828) Surprise rate change * FUTNO -4.703 -4.184 -3.536 -3.683 -3.648 -2.956

(0.666) (0.585) (0.454) (0.514) (0.499) (0.389) Surprise rate change * FUTNEG -11.165* -4.453 -5.215 -11.080* -4.446 -5.274

(1.796) (0.996) (1.410) (1.955) (1.008) (1.430) Expected rate change * CRISIS - 2.202 - - 2.132 -

- (0.546) - - (0.524) - Surprise rate change * CRISIS - 0.816 - - 0.063 -

- (0.437) - - (0.036) - Expected rate change * CONTRACT - - -1.065 - - -0.510

- - (0.301) - - (0.145) Surprise rate change * CONTRACT - - 1.022 - - 0.320

- - (0.671) - - (0.249) dLehman - -0.024*** -0.024*** - -0.022*** -0.022***

- (5.967) (6.043) - (5.062) (5.224) d2002 - -0.004*** -0.005*** - -0.004*** -0.005***

- (3.932) (5.929) - (4.295) (5.625)

R2 0.300 0.375 0.376 0.331 0.395 0.392

Adjusted R2 0.257 0.303 0.304 0.281 0.317 0.313

32

Table 7 The Effect of Inflation Targeting

This table reports the revised regression results for the Australian market indices, showing the effect of the pre-inflation-targeting variable on the response coefficients. Column (a) is the baseline regression, column (b) identifies the crisis and business cycle effects, and column (c) tests for asymmetry according to the sign of surprise. Sample size is 57 for ASX200 and 69 for FTSEAU. Parentheses contain t-statistics, calculated using Newey-West heteroskedasticity-consistent estimates of the standard errors. ***, **, * indicate statistical significance at the 1, 5, 10 % level, respectively.

ASX200 Index

FTSEAU Index

Regressor (a) (b) (c) (a) (b) (c) Intercept 0.000 0.000 0.000 0.000 0.000 0.000 0.000 -0.001

(0.057) (0.079) (0.185) (0.062) (0.171) (0.048) (0.207) (0.377) Expected rate change -2.194 -2.024 4.475** 2.826 -2.519* -2.478 2.082 2.142

(1.570) (0.916) (2.460) (1.207) (1.874) (1.105) (1.500) (1.564) Surprise rate change -0.478 -1.144 3.403** 4.436 -0.558 -1.296** 2.060** 1.008

(0.422) (1.515) (2.529) (0.561) (0.523) (2.019) (2.028) (0.340) Surprise rate change * POSITSURP - - - -1.897 - - - 1.253

- - - (0.237) - - - (0.393) Expected rate change * PRE-IT -1.911 -1.997 -7.126*** -0.797 -1.724 -1.697 -1.606 -2.158

(1.489) (0.969) (3.299) (0.902) (1.265) (0.771) (1.219) (1.054) Surprise rate change * PRE-IT -3.918*** -3.396** -6.509*** -7.553** -0.856 -0.084 -0.156 -0.019

(3.103) (2.523) (5.599) (2.144) (0.688) (0.112) (0.126) (0.014) Expected rate change * CRISIS - 4.301 - - - 5.067 - -

- (0.682) - - - (0.829) - - Surprise rate change * CRISIS - 5.565 - - - 6.283 - -

- (0.790) - - - (0.909) - - Expected rate change * CONTRACT - - -7.605*** -7.446 - - -5.174*** -4.582**

- - (3.521) (1.118) - - (3.030) (2.029) Surprise rate change * CONTRACT - - -4.862*** -5.633 - - -3.348** -2.567

- - (3.101) (0.947) - - (2.210) (1.104) dLehman - -0.008 -0.011 -0.011 - -0.008 -0.012 -0.012

- (0.537) (0.742) (0.766) - (0.534) (0.777) (0.772)

R2 0.023 0.073 0.084 0.076 0.085 0.135 0.129 0.130

Adjusted R 2 -0.052 -0.059 -0.046 -0.078 0.028 0.036 0.029 0.014

33

Table 8 Effect of Extended UK Sample Period

This table reports variations in the results of UK market indices under the crisis model, when an extended sample period of Jun 1997

Feb 2010 is used. The main sample contains 130 observations for both

indices; the extended sample contains 154 observations. Parentheses contain t-statistics, calculated using Newey-West heteroskedasticity-consistent estimates of the standard errors. ***, **, * indicate statistical significance at the 1, 5, 10 % level, respectively.

Main Sample (Jun99 - Feb10)

Jun97 - Feb10

Regressor FTSE100 FTSEUK FTSE100 FTSEUK Intercept -0.001 -0.001 -0.001 -0.001

(0.588) (0.646) (1.116) (1.162) Expected rate change -6.884*** -7.059*** -3.699 -4.010

(3.968) (4.035) (1.350) (1.512) Surprise rate change -5.130** -5.112** -1.713 -1.888

(2.180) (2.196) (0.587) (0.677) Expected rate change * CRISIS 13.993*** 14.321*** 10.457** 10.944**

(3.638) (3.696) (2.303) (2.438) Surprise rate change * CRISIS 10.268*** 10.479*** 6.733* 7.144*

(2.914) (2.991) (1.682) (1.832) dLehman -0.056*** -0.055*** -0.055*** -0.054***

(14.582) (14.241) (13.954) (13.731) d2002 -0.050*** -0.048*** -0.048*** -0.047***

(42.170) (42.801) (29.232) (29.963)

R 2 0.436 0.438 0.344 0.352 Adjusted R 2 0.408 0.411 0.317 0.325