Financial market reactions to monetary policy signals
Mapping central bank communication onto yield curve movements is challenging as it is difficult to isolate the component of market participants’ expectations that is exclusively driven by policy actions. The European Central Bank (ECB) has a unique way of communicating its monetary policy decisions – first announcing the policy decision in a press release and then explaining the policy decision further in a press conference. This offers a natural way of separating the financial market effects of the change in policy rates from the effects associated with other policy actions and communications, by employing intraday data. Past research, going back to Kuttner (2001) and Gürkaynak et al. (2005) for the US and Brand et al. (2010) for the euro area, has focused on identifying the effect of monetary policy surprises on asset prices. In a nutshell, these studies collect data at different times on the same day, i.e. before and after a monetary policy decision, to isolate the effect of monetary policy.
The implicit assumption in many of the existing papers is that a policy meeting is perceived to convey a single policy message, for example about immediate policy rate changes, and that this is a constant feature of policy meetings throughout time. There has been little emphasis so far on the presence of multiple policy messages and their effects on the various maturities of the yield curve. Similarly, the combination of policy instruments, and the fact that the number and type of messages may change over time due to the introduction of new policy instruments have received little attention.
In a recent paper (Altavilla et al. 2019), we make use of the newly constructed Euro Area Monetary Policy Event-Study Database (EA-MPD) to study how many dimensions of policy action and communications market participants actually perceive in press releases and press conferences following Governing Council policy meetings. We show how to interpret policy surprises through the lens of the footprint they leave on the yield curve. Our results dovetail with the general understanding of how the ECB policy communication is designed to operate.
Findings from the new Euro Area Monetary Policy Event-Study Database
High-frequency data, i.e. data collected at different times on the same day, are an essential input for studying the effects of monetary policy communication. Recent studies for the euro area analysing the effect of policy surprises on a limited number of asset prices include Andrade and Ferroni (2018), Cieslak and Schrimpf (2018), and Jarociński and Karadi (2020). These studies all required an enormous investment in data collection in order to identify the effect of policy surprises.
The Euro Area Monetary Policy Event-Study Database (EA-MPD) records intraday asset price changes around ECB policy announcements for a wide range of assets. The database covers the period starting in January 2002 and is updated regularly. At the time of writing point, it includes data up to June 2020.
Monetary policy announcements work differently in the euro area than in the US. While the monetary policy decisions and the statement explaining the decisions are made public at the same time in the US, the ECB announces the policy decision and the explanatory statement at different times. The press release containing the policy decisions (including, since March 2016, the policy decisions concerning non-standard measures) is released at 13:45 CET. It is then followed by a press conference that begins at 14:30 CET, when the ECB President reads a statement and holds a Q&A session. The ECB press conference statement is similar to the US Federal Open Market committee (FOMC) statement as it provides a rationale for the policy decision, and presents an outlook on the future course of monetary policy which market participants often find informative.
Using high-frequency intraday data, we measure changes in asset prices over three time windows: the press release window, the press conference window, and the window of both together, called the monetary event window.1 The EA-MPD reports the asset price/yield changes we measure for the three event windows in separate worksheets.2
For an illustration of the intraday data, Figure 1 shows the two-year Overnight Index Swap (OIS) rate on four different monetary policy meeting dates – 4 July 2013, 4 September 2014, 3 December 2015 and 7 September 2017. We select the two-year rate as this maturity is sufficient for the rate to display movements in response to announcements of non-standard as well as standard monetary policy measures. The EA-MPD reports changes around the two vertical lines, denoting the times of the press release and the press conference. Figure 1 makes it clear why these two windows should be separated.
Figure 1 Examples of market reactions across different policy events
Note: The figure shows the intraday movement (percentage points on the y-axis, trading hours on the x-axis) in the two-year OIS rate during four selected monetary policy decision dates. The solid vertical line marks the publication of the press release; the dashed vertical line marks the beginning of the press conference.
The four panels in the figure all depict different situations of how monetary policy surprises may arise at different times during the policy meeting day.
In panel (a) there is no reaction of the two-year OIS rate during the press release window but a reaction in the conference window. This episode corresponds to the first time ever that the ECB announced at its press conference formal forward guidance on the future path of its policy rates. The press conference stated that policy rates were expected to remain at present or lower levels for an extended period of time.
Panel (b) shows an episode with a reaction in the press release window, but no further adjustments of the OIS rate during the press conference window. This episode corresponds to the announcement of a cut in the ECB deposit rate.
Panel (c) depicts a policy date with sizeable movements in both time windows. This episode captures the financial markets’ disappointment following the ECB decision to increase the size of its quantitative easing (QE) programme and decrease the interest rate on the deposit facility. This policy action had not been expected by financial analysists according to survey data collected prior to the policy meeting. Markets had instead been expecting a larger cut in the policy rate (accordingly the yields moved up during the press release window) as well as a larger increase in QE (the related disappointment reinforced the upward movement in yields during the press conference window).
Lastly, panel (d) shows a day without any surprises, neither in the press release nor the conference windows. Policy dates like these are surprisingly rare – there is usually some new information for the financial markets, especially during the press conference window.
The transmission of monetary policy surprises across the interest rate term structure
In order to characterise the yield curve reaction to different policy announcements we use data from January 2002 up to September 2018 and employ a factor analysis. A factor analysis is a statistical technique that aims to reduce the information contained in a large number of variables into a limited set of underlying variables called factors. These factors are extracted so as to maximise the common variance of all variables. In our case, for example, we first collect the reaction of yields on the risk-free curve at various maturities for each official policy communication and then extract a few factors to characterise the typical response of these yields to policy events that share similarities.
We then propose a structural identification of these factors and find surprises that resemble policy rate changes, forward guidance and QE policies. We find that in the period between January 2002 to September 2018 market participants perceived the press release to contain a single piece of information (mainly related to policy rate changes). However, the press conference was not unidimensional and market participants always extracted two dimensions of information from the press conference with a third added after the advent of QE. To better understand these factors, and ultimately give an economic interpretation, we use the methods developed by Gürkaynak et al. (2005) and Swanson (2017).
Figure 2 shows that the estimated footprint that monetary policy measures leave on the yield curve varies across the two event windows. The press release window features a factor related to the surprise in the immediate setting of the policy rate, affecting short rates heavily and having little effect on long-term interest rates. We label it ‘target’, as this factor is similar to the behaviour of the target factor identified by Gürkaynak et al. (2005) for the US. In the press conference window, we find two statistically significant factors that have always been present, and the QE factor which became statistically significant after the announcement of the QE policy in January 2015.
The two factors that have always been present, even before forward guidance became an explicit ECB monetary policy tool, can both be understood as forward guidance surprises, but with different flavours. It turns out that financial markets have always perceived a short-term and a longer-term forward guidance factor. We call the first factor, which has its peak effect around the six-month maturity with little effect on long-term interest rates, ‘timing’. This is to differentiate it from the second factor, now commonly called ‘forward guidance’, which has a peak effect at two years and significantly affects long-term interest rates. For the QE factor, by contrast, the longer the maturity, the larger the effect. This is consistent with the QE implementation in the euro area, where the average maturity of the securities bought has been about eight years.
We therefore find that there have always been multiple ‘communications’, even before explicit forward guidance and QE became part of the ECB toolkit. This raises the question of whether the way asset prices respond has changed after forward guidance became an explicit policy tool. Our work suggests that market responses to a given communication surprise have been fairly stable. That is, a forward guidance surprise has over time elicited more or less the same financial market response in different sub-samples – in terms of risk-free rates, sovereign yields, exchange rates – but there have been relatively more forward guidance surprises since the onset of the Global Crisis.
Figure 2 The footprint of monetary policy actions on the yield curve
Note: The figure shows the typical reaction of yields at different maturities during the press release window (first row) and the press conference window (second row), in basis points. The ‘target’ and ‘timing’ factors are normalised to have a unit effect on the one-month and six-month OIS rates, respectively. The forward guidance and QE factors are normalised to have a unit effect on the two-year and on the ten-year yields, respectively. The shaded areas indicate the 90% confidence intervals.
The effects of unofficial central bank communications
Since our methodology is easily generalizable we proceed by analysing any policy communication, including policy speeches and market news. Financial markets react to many kinds of news about monetary policy and we can parse them according to the same dimensions we have identified for the Governing Council’s communications.
Two events illustrate the point. The first is a speech given by Mario Draghi on 27 June 2017, at the ECB Forum on Central Banking in Sintra, entitled “Accompanying the economic recovery”. The second is a Bloomberg news article by Jana Randow, Alessandro Speciale and Jeff Black that was released on 4 October 2016 and hinted at a decision on tapering by the ECB.
Given that we estimated the effect of each factor for the different surprises in our analysis above, we can ask which combination of factors best explains the observed market reactions. Figure 3 shows the magnitudes of the effects as fractions of the average absolute value of each type of surprise. This makes each factor reading comparable to other readings of the same factor (but magnitudes cannot be made comparable across factors).
This proof-of-concept exercise shows that all policy-relevant news can be broken down into policy surprise factors once the initial factor extraction exercise is carried out. For example, we can now say that the Draghi speech was seen as a very large QE event – its size is twice the in-sample average for such surprises.
Figure 3 Surprise breakdown over non-governing council events
Note: The figures show the estimated factor decomposition into the timing, forward guidance and QE factors of the two monetary policy events not included in our sample. In each subplot, the first bar is for the June 2017 Draghi speech and the second one is for the October 2016 Bloomberg news article.
Conclusions and policy implications
The two-stage nature of ECB policy news dissemination turns out to be helpful in identifying the market response to monetary policy announcements. Rather than assuming the presence of predefined surprises in different windows, we estimated and identified these surprises, finding a multi-faceted information structure in the press conference window.
We find that in our sample (from January 2002 to September 2018) the target surprises are dominant in the announcement window, while they do not even exist in the press conference window. In fact, in the press conference window news about the future path of policy was the main driver of yield changes until QE was introduced, with QE then adding a new factor thereafter.
Importantly, we estimate and identify the footprint that different monetary policy announcements leave on the yield curve. While changes in the policy interest rate mostly influence the short maturities of the curve, the impact of forward guidance policies reaches its peak at intermediate maturities. Quantitative easing measures, by contrast, exert their maximum impact at long maturities.
We also demonstrate how to use the policy surprise factors we identified to analyse any policy communication, such as speeches or market news, and show that the EA-MPD is a useful resource for studying future rounds of monetary policy measures and assessing the relative effectiveness of the policies announced.3
Authors’ note: This column is based on an ECB working paper written by Carlo Altavilla, Luca Brugnolini, Refet S. Gürkaynak, Roberto Motto and Giuseppe Ragusa. The authors gratefully acknowledge the comments of Marek Jarocinski, Alberto Martin and Louise Sagar. The views expressed here are those of the authors and do not necessarily represent the views of the European Central Bank or the Eurosystem.
Altavilla, C, L Brugnolini, R Gürkaynak, R Motto, G and Ragusa (2019), “Measuring euro area monetary policy”, Journal of Monetary Economics 108:162-179.
Andrade, P and F Ferroni (2018), “Delphic and Odyssean Monetary Policy Shocks: Evidence from the Euro Area”, Federal Reserve Board of Chicago Working Papers, No WP-2018-12.
Brand, C, D Buncic and J Turunen (2010), “The impact of the ECB monetary policy decisions and communication on the yield curve”, Journal of the European Economic Association 8: 1266-98.
Cieslak, A and A Schrimpf (2018), “Non-Monetary News in Central Bank Communication”, NBER Working Papers No 25032.
Gürkaynak, R, B Sack and E Swanson (2005), “Do actions speak louder than words? The response of asset prices to monetary policy actions and statements”, International Journal of Central Banking 1: 55-93.
Jarociński, M and P Karadi (2020), “Deconstructing Monetary Policy Surprises—The Role of Information Shocks”, American Economic Journal: Macroeconomics 12: 1-43.
Kuttner, K (2001), “Monetary policy surprises and interest rates: Evidence from the fed funds futures market”, Journal of Monetary Economics 47: 523-44.
Swanson, E (2017), “Measuring the effects of Federal Reserve Forward Guidance and Asset Purchases on Financial Markets”, NBER Working Papers No 23311.
1 In constructing the database, we first cleanse the data of misquotes – which were prevalent especially in the first years of the ECB operations – then report the changes from the pre-event quote to the post-event quote for each communication window. The quotes are the median prices/yields in each event interval, where we discretise the data by taking the last quote for each minute in the interval.
2 The market indicators covered are the rates on Overnight Index Swaps (OIS) with maturities of one, three, and six months and one to ten years, 15 and 20 years, German Bunds with maturities of three and six months and one to ten years, 15, 20 and 30 years, French, Italian, and Spanish sovereign bonds with maturities of two, five, and ten years, the stock market price index and the stock price index comprising only banks, as well as the exchange rate of the euro.
3 We hope that the dataset, which we will update regularly, will encourage more research on monetary policy and its effects in the euro area. For example, the dataset could be useful in the study of the following questions, which continue to be important for academics and policymakers alike: the effects of monetary policy on markets in different euro area countries; how these differ according to the fundamentals of those countries; the central bank information effects, i.e. how central banks affect market beliefs about economic fundamentals; identifying VAR-based real effects; and the transmission of ECB policies to non-euro area countries.