Monetary Policy Communication of the Bank ofJapan: Computational Text Analysis

Yusuke Oshima
Yoichi Matsubayashi

April 2018
Discussion Paper No.1816

GRADUATE SCHOOL OF ECONOMICS
KOBE UNIVERSITYROKKO, KOBE, JAPANMonetary Policy Communication of the
Bank of Japan: Computational Text
Analysis
Yusuke Oshima
Yoichi Matsubayashi

GRADUATE SCHOOL OF ECONOMICS
KOBE UNIVERSITYROKKO,KOBE,JAPANMonetary Policy Communication of the Bank ofJapan: Computational Text Analysis
Yusuke Oshima and Yoichi Matsubayashi

Abstract
In this study, we empirically examine the eﬀects of the Bank of Japan(BOJ)’s communications through its meeting minutes on the financial markets,
especially during Mr. Kuroda’s administration from April 2013 to September
2017. Using computational linguistic models and the Latent Dirichlet Allocation,
we quantify the contents of the BOJ minutes and extract topics form theseminutes, including the bank’s historical monetary policy and policymakers’ views
on current economic conditions. The empirical results suggest that a relationshipexists between the estimated topics and the market reactions on the days on
which the minutes are released. Although the market paid attention to themonetary policy description in the minutes in the early period of the introduction ofquantitative and qualitative monetary easing (QQE), the significance of monetary
policy information under the October 2014 expansion of the QQE on financial
markets faded. In contrast, information on fund-provisioning measures to support
Japanese companies’ activities, including a negative interest rate policy, induced adecline in the stock market. We found that the market pays attention to meetingmembers’ opinions on current economic conditions.

1Introduction

Today, central bank communication has become a key tool used by these banks togain support for their monetary policies. Blinder et al. (2008) defined central bankcommunication as information that the central bank makes known to the public regarding
its current and future monetary policy objectives, monetary policy strategy, economic
outlook and outlook regarding the path of future policy decisions. Two main reasons exist
for why an increasing number of central banks have activated such communication. First,
central banks as independent institutions have a duty to explain both their actions andthe thinking that underlines their monetary policies. Second, central banks communicate
to manage market expectations and to influence asset prices. Moreover, Blinder et al.
(2008) explained that the latter using the two aspects of ‘creating news’ and ‘reducing
noise’. ‘Creating news’ means that a central bank’s announcement promotes expectations
and moves asset prices. ‘Reducing noise’ means that a central bank’s talk contributes tothe predictability of its actions, which reduces financial market volatility.
Recently, the Bank of Japan (BOJ) regarded central bank communication also as animportant toolkit to ensure the eﬃciency of its monetary policy. Shirai (2014), as a policy
board member of the BOJ, presented three reasons why the BOJ accepted central bankcommunication. First, in January 2013, the BOJ adopted a 2% price stability target
in terms of the year-over-year rate of change on the basis of the consumer price index(CPI). Second, also in January 2013, the BOJ and the Japanese government released ajoint statement on their cooperation to overcome deflation and to achieve sustainableeconomic growth. Finally, the BOJ is actively using its communication strategy toachieve a 2% price stability target on monetary accommodations under quantitative andqualitative monetary easing (QQE) that started in February 2013. In particular, theBOJ declared that from April 2013, ‘The Bank will continue with the quantitative andqualitative monetary easing, aiming to achieve the price stability target of 2%, as long as
it is necessary for maintaining that target in a stable manner’. The strategy was called
the open-ended forward guidance and was an attempt to enhance the eﬀect of the QQE.
However, some market participants pointed out that the monetary policy under
Mr. Kuroda’s BOJ administration, including the introduction of the QQE in April
2013, Expansion of the QQE’ in October 2014 and the introduction of the QQEwith a Negative Interest Rate’ in January 2016, provided no signals before they were
implemented. Although such a monetary policy, which cannot be expected by market
participants, influences asset prices given the sudden change, the eﬀect of monetary policy
transparency through central bank communication is weakened. As a result, asset pricevolatility can be higher because of the uncertainty that monetary policy induces. In
that case, we speculate that market participants seek to obtain additional clues on futuremonetary policy in the information that the BOJ publishes, such as statements, speeches
and minutes, after every monetary policy meeting (MPM).
Typically, the BOJ minutes of a meeting are released three business days after the next
MPM. Beforehand, the BOJ provides a lot of information on its monetary policy stancethrough statements and speeches immediately after the meeting and outlook reports.
Thus, market participants may have already expected the BOJ’s future actions before thepublication of the minutes. However, market participants who are concerned about sudden

1changes in monetary policy focus on the contents of the deliberations over monetary
policy in the minutes and volatility moves on release days. Then, we hypothesise that thechanges in the substance of the minutes can influence the market’s mind. To examine thishypothesis, we use tools from computational linguistics and measure topics in the BOJ
minutes, allowing us to analyse whether each topic aﬀects asset prices.
Our study proceeds as follows. Section 2 reviews previous studies on the impact of
central bank communication on asset prices, and Section 3 describes our sample anddata sources. Section 4 introduces our computational linguistic approach and reports
the estimations. Section 5 verifies the asset price movements on the release day of the
BOJ minutes and reports the results of our empirical tests on the relationship between
volatility and the topics extracted in Section 4. Section 6 concludes.

2

Previous Studies

Numerous studies exist on central bank communication on both the theoretical andempirical fronts. Geraats (2006) and Eusepi and Preston (2010) showed a model-based
evaluation of central bank communication strategies. In terms of the empirical literature,
Kohn and Sack (2003) and Gürkaynak et al. (2005) measured the eﬀect of FOMC
monetary policy surprises in financial markets using multiple factors. The latter study
uses a high-frequency event-study analysis and measures the movements of bond yields
and stock prices after central bank announcements. They decomposed the eﬀect of theannouncements into two factors, as explained by a monetary policy action factor anda statements factor. They concluded that a statements factor has an important eﬀect
on longer-term Treasury yields, and the statements have a significant eﬀect on investor
expectations.
Previously, ample empirical studies demonstrated that monetary policy information
released by the BOJ aﬀects market expectations. For example, Honda and Kuroki (2006)
showed that changes in the monetary policy target significantly impact both intermediateand long-term interest rates. Nakajima and Hattori (2009) proposed also that the releaseof economic outlook reports or the MPM minutes decreases volatility, whereas changes
in monetary policy and an increase in the MPM members who vote against the proposal
increase volatility.
Simultaneously, certain empirical studies approached the content of central bankcommunications and focused on the wording. As an initial study, Romer and Romer(1989) read minutes of the FOMC and identified occasions when policymakers seemed totake a more anti-inflationary stance by picking up words in the minutes. Their approach
attempted to find exogenous monetary policy shocks but had the problem of subjectivity
because of the manual selection of target words. To remove this obstacle, alternative
studies assessed the context of monetary policy using computational linguistics tools.
Fligstein et al. (2014) applied Latent Dirichlet Allocation (LDA), which was developed
by Blei et al. (2003), to FOMC transcripts in order to analyse policymakers’ recognitionof financial crises. Using LDA, Hansen et al. (2014) examined transparency in FOMC
monetary policymakers’ statements from FOMC minutes.
Hendry and Madeley (2010) and Hendry (2012) measured the impact of central bankcommunication in Canada on financial markets using other text-mining tools. Jegadeesh
2and Wu (2015) extracted contents also from FOMC meeting minutes and applied theLDA. They reported topics on economic outlook and monetary policy stance, particularly
as related to return volatility. Hansen and McMahon (2016) decomposed monetary policy
information from the FOMC into multi-dimension aspects and measured the dimensions
that most aﬀected both market and real economic variables. To distinguish the state of
the economic condition from the information in the FOMC transcript, they use the LDA
and found that shocks from the current economic condition factor is less important than
the forward guidance factor on financial markets in FOMC communications.
To the best of our knowledge, several studies exist on BOJ communication using
textual analysis. Shibamoto (2016) applied a text-mining approach to words in press
conferences after the MPMs and found that asset prices react through BOJ communication
factors, which are especially the central bank’s policy intentions and preferences. In termsof the LDA, which our study uses, Shirota et al. (2014) and Shirota et al. (2015) extracted
topics from BOJ minutes and analysed the transitions. However, these studies do not
point out the relationship between each topic and financial markets. In this study, we
confirm the relationship.

3

Data

3.1

Introduction of BOJ minutes

In this subsection, we first provide how and when the BOJ releases decisions in
the MPMs. Approximately three stages exist for informing monetary policy. First,
monetary policy releases and outlook report outlines are announced rapidly after the
MPMs. Second, entire outlook reports are published the following day. Finally, theminutes are released after approximately one month after the completion of the MPMs
(the details of the timing of each piece of information are shown in Table 1). Therefore, theimpact of the minutes on financial markets seems very restrictive. However, the minutes
include a lot of information that indicates the likely future path of monetary policy. Thus,
we consider that the minutes can influence market expectations about future monetary
policy.
Before our analysis, we briefly reviewed the BOJ’s monetary policy since Haruhiko
Kuroda was inaugurated as the 31st governor because we believe that such information
can be meaningful for the following sections. The BOJ implemented the QQE under
Kuroda’s BOJ administration. Table 2 summarises the deliberation results of monetary
policies noted in the minutes. Table 2 shows that the BOJ monetary policy changed six
times in the relevant terms, as follows: 1) introduction in April 2013 of the QQE; 2)
expansion in October 2014 of the QQE; 3) introduction of supplementary measures in
December 2015 for the QQE; 4) introduction of the QQE in January 2016 with a negativeinterest rate; 5) enhancement in July 2016 of monetary easing and 6) introduction of the
QQE in September 2016 with yield curve control.
Given the introduction of the QQE, the BOJ shifts the monetary policy target from theuncollateralised overnight call rate to the monetary base. Accordingly, the BOJ decided
to increase asset purchases of Japanese government bonds (JGBs), exchange traded funds(ETFs) and Japan real estate investment trusts (J-REITs). During the period of the3

QQE expansion, the BOJ announced that it accelerated the pace of the increases in
the monetary base and expanded asset purchases. However, these increases in asset
purchases could lead to decreases in financial institutions’ holdings of eligible collateral,
increases in the average remaining maturity of the JGBs and shortages of the J-REITs
eligible for the BOJ to purchases. Therefore, in December 2015, the BOJ introduced
supplementary measures for the QQE. In the next MPM, the BOJ announced that it
applied a negative interest rate of 0.1% to its current accounts of financial institutions.
From this period, the BOJ adopted measures in terms of three dimensions: quantity,
quality and interest rate. In 2016, the Japanese economy was exposed to uncertainties
from the global financial market because of the United Kingdom’s withdrawal from theEuropean Union and a slowdown in emerging economies. To reduce the impact of these
uncertainties on the domestic economy, in July 2016, the BOJ enhanced monetary policyby increasing purchases of ETFs and establishing measures to ensure smooth funding
in foreign currencies by Japanese firms and financial institutions. In September 2016,
the BOJ reviewed the outcome of the QQE that started in April 2016 and decided to
introduce the QQE with yield curve control to enhance the monetary easing eﬀect. This
new framework consisted mainly of two components: 1) ‘yield curve control’ throughwhich the BOJ controls short-term and long-term interest rates; 2) ‘inflation-overshooting
commitment’ through which the BOJ promises to continue to expand the monetary base
until the price stability target is achieved. From the minutes, we are able to understand
not only these monetary policies decisions above our explanations but also the backgroundand the path to them.
In our study, we focus on the minutes from April 2013 to September 2017 anddownloaded them from the BOJ’s web site.1 Our sample consists of 52 meeting minutes.
We adopted the minutes in Japanese because our main target in the following analysis
is the domestic financial market, and we supposed that the original version in Japanese
can convey more accurately the discussion contents. To apply Japanese minutes to our
textural analysis method, we use morphological analysis with MeCab.2 The BOJ minutes
include technical terms on finance and economics. We employed mecab-ipdic-NEologd3
as the morphological analysis dictionary in MeCab. Using SlothLib,4 we picked up only
nouns in the minutes after removing terms in the stop word list. After these processes,
the size of the source text used is 94,235 words.

3.2

Market reaction data

In this study, we used daily business data from financial markets to measure market
reactions on the days on which the BOJ minutes are released. For the bond market, weused two-year, five-year, ten-year and 40-year JGB yields. We downloaded these datafrom the Ministry of Economy, Trade and Industry in Japan. We employed also TOPIX,
1

Minutes downloaded in PDF from https://www.boj.or.jp/mopo/mpmsche_minu/minu_all/index.
htm/
2
MeCab is a morphological analyser for Japanese language developed by the Nara Institute of Scienceand Technology and is currently maintained by Taku Kudou.
3
See https://github.com/neologd/mecab-ipadic-neologd
4
See http://svn.sourceforge.jp/svnroot/slothlib/CSharp/Version1/SlothLib/NLP/Filter/
StopWord/word/Japanese.txt

4Nikkei225 and the yen/dollar exchange rate. To observe changes in the J-REITs, which
are target assets for the BOJ’s purchases, we used the TSEREIT also. Except for bonddata, these data resources are all from Datastream. The observation term is from April
2013 through September 2017, which includes 1,175 business days. The BOJ meeting
minutes are published at 8:50 a.m. on the release day. If the financial market reacts tothe minutes’ release, asset value changes are observed on that day or after the next day.
Therefore, we constructed our event window as one day or two days.
Defining τ = 0 as the event date, τ = T1 + 1 to τ = T2 − l indicates the event window,
where l is the event window length of one or two days. We calculate the event-window
return volatility for each equity LBi using the following equation. Specifically, for eachminutes t in our sample:
LBi
LBi
VtLBi = (Yt,T− Yt,T) × 100(1)
2
1
For other assets OAi , we computed the event-window return volatility using the following
equation:
OAi
OAi
VtOAi = (log Pt,T− log Pt,T
) × 100(2)
2
1
To simplify the following explanation, these event-window return volatilities in Eq. 1 andEq. 2 are collectively referred to as Vt .

4

Measuring BOJ minutes

In this section, we explain the LDA developed by Blei et al. (2003), which we use
for the topic extraction from the BOJ minutes and consider the output from the BOJ
minutes using the model. The LDA assumes that each minute is a mix of a large range of‘topics’. These topics appear as a group of words, and each word has an internal latent
meaning.
Two primary motivations exist to use the LDA for the extraction topics from theminutes. First, this topic model can estimate consistently topics that appear natural
without a pre-assigned label (Hansen et al. 2014). Therefore, this approach can exclude
a researcher’s subjectivity and can classify using common intuition despite time-varying
topics. Second, although standard topic models allocate the same words to just one topic,
this model allows the same word to appear in multiple topics (Hansen et al. 2014). This
flexibility enables more accurate descriptions of the content in the minutes.
The remainder of this section describes the frame of the LDA. Subsequently, we discuss
the result of the estimated topics from each BOJ minute.

4.1

Latent Dirichlet Allocation (LDA)

The LDA is a very popular algorithm based on the multi-hierarchical Bayesianmodel. This model supposes that each topic has group words on the basis of repeatedco-occurrence across paragraphs, and that one document (or one minute) has several
topics. Each topic is characterised by diﬀerent probability distribution over the words.
The document is modelled as a distribution over the topics.
For a further description of LDA, the following symbols are used:5wt = (wt,1 , wt,2 , · · · , wt,j , · · · , wt,It ) are the words that appear in minutes t, which
represent the minutes released on day t; It is the total number of words in eachminute tzt = (zt,1 , zt,2 , · · · , zt,j , · · · , zt,It ) are the topics for wt
D is the total number of the sample minutes
K is the total number of topics
V is the total number of vocabulary words that appear in all minutes for the sample
θk,t is the probability that topic k appears in minutes t: the proportion of topic k inminutes t
θt = (θ1,t , θ2,t , · · · , θK,t ) is the topic distribution for minutes t
ϕk,v is the probability that word v appears in topic k
ϕk is the word distribution for topic k
α = (α1 , α2 , · · · , αK ) are the hyper-parameters of the Dirichlet prior on the per-minutetopic distributions, which are K-dimensional vectors
β = (β1 , β2 , · · · , βV ) are the hyper-parameters of the Dirichlet prior on the per-minutetopic distributions, which are V -dimensional vectors
We consider the statistical process of topic distribution θt . θt is the probability
K-dimensional vector. For each minute t, we assume that these vectors follow an order-K
Dirichlet distribution over the K topics:θt ∼ Dir(α)(t = 1, · · · , M ).

(3)

Given minutes t’s topic mixture θt , each word wt,i is assigned to topics zt,i . We assume
that this allocation follows the multinomial distribution governed by topic vector θt :zt,i ∼ M ulti(θt )(i = 1, · · · , nt ).

(4)

The K topic distributions ϕk are collections of dimensional vectors that follow an order-V
Dirichlet distribution over the V vocabularies, governed by hyper-parameter β:ϕk ∼ Dir(β)(k = 1, · · · , K).

(5)

The word wt,i in minute t is selected from V unique words from our BOJ minutes sample.
We assume that the choice of word wt,i follows a multinomial distribution governed by
the result of ϕzt,i :
wt,i ∼ M ulti(ϕzt,i )(i = 1, · · · , nt ).
(6)
Although wt is the only observable variable, the other variables are latent. We describe
this generating process as the joint distribution of latent variables, ϕk , θt and zt and theobservable variable wt , as follows:
[ I
]
K
D
t
∏
∏
∏
P (ϕk , θt , zt , wt ) =P (ϕk )
P (θt )
P (zt,i |θt )P (wt,i |ϕk , zt,i )
(7)
k=1

t=1

i=1

6

If we observe wt from our BOJ minutes sample, we can compute the posterior distributionof the document-topic structure given the observed minutes using Bayes’ Rule:P (ϕk , θt , zt |wt ) =P (ϕk , θt , zt , wt ).
P (wt )

(8)

Although we can compute the numerator in Eq. 8 with other Bayesian inference
methods, the denominator is by construction a double integral, which cannot be computed.
Then, we estimate the parameters in the LDA using a collapsed Gibbs samplingalgorithm introduced by Griﬃths and Steyvers (2004). Their approach directory estimates
the posterior distribution over topic assignments zt,i by integrating out ϕk and θt .
The algorithm first randomly assigns topics to words and updates topic assignmentsby repeatedly sampling from the appropriate posterior distribution. For algorithm
implementation, we use models.ldamallet5 in Gensim, which is in the Python package.
To estimate the parameters in the LDA, we must set the number of topics K. In termsof deciding on the number, we adopt an evaluation index for a topic model introduced
by Newman et al. (2010), which is called ‘coherence’. The score measures word-pairco-occurrence between the set of the N highest probability words of a topic. Thisevaluation defines that the LDA model with the highest score is the best model. We
compare the models with a diﬀerent number of topics K, and decide on the number of
the topic whose model has the largest coherence score. As a result, we set the number of
topics K to eight.

4.2

Estimated topics

In this subsection, we discuss the outputs from the LDA estimation. As mentioneddc
in a previous subsection, LDA estimates latent variables: ϕcNow,k,v , θk,t and z
t,i .
d
c
we mainly focus on ϕk,v and θk,t , and use them to examine the contents of the BOJ
minutes. The LDA is an unsupervised learning algorithm. Accordingly, it does not havea meaningful label before classification, making the implications of each topic depend on
a researcher’s subjective judgement (Hansen et al. 2014). To avoid the misinterpretationof each estimated topic, we revalidate these results by reading the raw text of the minutes.
d
The rank of topic probability ϕk,v of each word v can describe the meaning of topic k.
Table 3 and Table 4 report the top 40 words for each topic. They should be noted thatthe same words can appear in multiple topics because of the property of the LDA. For
example, ‘物価 (prices)’ appears in almost all topics, as shown in the table. In the tables,d‘weight’ indicates the score of ϕk,v , which the LDA estimates. A higher weight score fora word indicates that the word is more characteristic in the topic. For example, Topic
0 in Table 3 is characterised by the words that have a high weight score, such as ‘物価(prices)’, ‘経済 (economy)’, ‘目標 (target)’, ‘買入れ (purchases)’ and others.
In contrast, the topic proportion θk,t over time can grasp the trend of the contents inthe minutes. The fluctuations in the proportions of the entire estimated topic in the BOJ
minutes for the MPMs between April 2013 and September 2017 are shown in Figure 1.
At each point in time, the trend of the contents in the minutes can be explained by the5

See https://radimrehurek.com/gensim/models/ldamallet.html

7high score of the ratios of the topics: θck,t . For instance, Topic 0 accounts for a large partof the minutes released on 2 May 2013, indicating that these minutes are devoted mainly
to Topic 0. For further consideration, the MPM members discussed mainly Topic 0 at
the MPM for these recoded minutes, and market participants can understand the BOJ’s
stance at that time by reading the minutes.
Based on the frequency appearance words in each topic, θck,t , and each topic proportion
over time, we interpret the topics as follows.
Topic 0: BOJ’s Monetary Policy Decision under Introduction of the QQE
Topic 0 includes the words related to the BOJ’s monetary policy decision on the top
word distributions, as shown in Table 3, such as ‘買入れ (purchases)’, ‘国債 (JGB)’, ‘量的・質的金融緩和 (quantitative and qualitative easing)’ and ‘マネタリーベース (monetarybase)’, among others. Figure 2 shows time series changes of the topic proportion regarding
Topic 0: θc
0,t . The score reaches its peak after the introduction in April 2013 of the QQE,
and decreases towards the October 2014 expansion of the QQE.
To validate our interpretation, we read the minutes for which Topic 0 accounts
for a large part. In general, the BOJ’s minutes were summarised in approximately
20 pages and consisted mainly of six components: 1) Summary of Staﬀ Reports on
Economic and Financial Development; 2) Summary of Discussions by the Policy Board on
Economic and Financial Developments; 3) Summary of Discussions on Monetary Policy
for the Immediate Future; 4) Remarks by Government Representatives; 5) Votes; and 6)
Discussion on the Statement on Monetary Policy.
Our investigation objects are the minutes released on 2 May 2013, 14 June 2013 and
17 July 2013, and have high topic proportion regarding Topic 0. The common features ofthese minutes describe the explanation and eﬀect of the QQE on the part of Summaryof Discussions on Monetary Policy for the Immediate Future’ and comprise a significant
number of pages. Meanwhile, we confirmed the content of the minutes for which Topic 0
comprises a low proportion. We searched the minutes released on 6 November 2014, andfound that the chapter on monetary policy accounts for fewer pages than the pages forthe previously described minutes. For these reasons, we interpreted the implications ofTopic 0 as the monetary policy decision during the early period of the introduction of the
QQE. Then, we labelled this topic Monetary Policy 1.
Topic1: BOJ’s Monetary Policy Decision under the QQE Expansion
Similar to Topic 0, Topic 1 as reported in Table 3 includes also words related tomonetary policy, such as ‘量的・質的金融緩和 (quantitative and qualitative easing)’, ‘金利 (interest rate)’, ‘金融政策 (monetary policy)’, ‘マネタリーベース (monetary base)’and others. Compared with the word list for Topic 0, Topic 1 is described by words on
asset purchases, such as ‘買入れ (purchases)’, ‘資産 (asset)’, ‘ETF’ and others. From
Figure 2, the proportion changes of Topic 1, θc
1,t , peaks from November 2014 to November
2015. This period corresponds to the term under the QQE expansion that begins from
October 2014. We confirmed the minutes with a high proportion of Topic 1. In theminutes released on 25 December 2014, for which the proportion is elevated to the peak,
we discovered that these minutes emphasised that the QQE expansion is beneficial to an
8increase in inflation expectations. Furthermore, we found that the minutes released on
20 March 2015, whose proportion of Topic 1 has peaks, mentioned also the relationshipbetween the QQE expansion and inflation expectations. From this discussion, we interpretthat Topic 1 concerns monetary policy under the QQE expansion after October 2014. Welabelled this topic Monetary Policy 2.
Topic 2: BOJ’s Monetary Policy Decision after the Introduction of the QQEwith Yield Curve Control
Topic 2 in Table 3 is also characterised by the words related to monetary policy.
Compared with Topic 0 and Topic 1, certain characteristic words appear only in Topic2, such as ‘操作 (control)’, ‘イールドカーブ (yield curve)’, ‘長期金利 (long-term interest
rates)’ and others. In turn, the proportion of Topic 2, θc
2,t , in Figure 2 peaks on 7
November 2016. Concerned minutes describe the introduction of the QQE with yield
curve control from September 2016. After the proportion peaks, this topic maintains highlevels until September 2017. Confirming the contents of the minutes in these terms, yield
curve control through asset purchases is mentioned. From this discussion, Topic 2 seems
to be about monetary policy after the introduction of the QQE with yield curve control
after September 2016. Therefore, we defined Topic 2 as Monetary Policy 3.
Topic 3: Fund-provisioning Measures
Topic 3 in Table 3 includes also words that appear in the above topics, such as ‘買入
れ (purchases)’, ‘量的・質的金融緩和 (quantitative and qualitative easing)’ and others.
Meanwhile, this topic is characterised by specific words, such as ‘支援 (support)’, ‘金融機
関 (financial institutions)’, ‘貸出 (lending)’, ‘資金供給 (fund-provisioning)’, ‘マイナス金利 (negative interest rate)’ and others. Figure 3 reports time series changes of the Topic
3 proportion, θc
3,t . From this figure, the topic increases in certain minutes, including thosereleased on 2 May 2013, 14 March 2014, 3 February 2016 and 18 March 2016. We checked
these minutes using the words in Table 3 and found that they describe fund-provision
measures to stimulate domestic corporate activities. In the minutes released on 14
March 2013, policymakers discussed the Stimulating Bank Lending Facility and othermeasures to strengthen the growth of Japan’s economy. They concluded that these
operations can enhance the eﬀect of the QQE. Additionally, the minutes released on
3 February 2016, which had an extremely high Topic 3 ratio, described the introductionof supplementary measures for the QQE. Through this operation, policymakers decided
to introduce measures to support companies that invest in physical and human capital tostimulate the domestic economy. The next set of minutes released on 18 March 2016 wasalso occupied by this topic, corresponding to the MPMs that discuss the introduction of
the QQE with a negative interest rate. The purpose of this operation stimulates banklending. Therefore, this measure intends also to enhance the supply of money to domestic
firms, strengthening economic growth. From these reasons, we interpreted Topic 3 as afund provisioning measure to stimulate Japanese companies’ activities. Thus, we labelled
this topic Fund-provisioning Measures.

9Topic 4: Outlook for Economic Activity and Prices
The BOJ issues economic outlook reports four times a year after the MPMs6 , inJanuary, April, July and October. The contents of the reports are discussed at theconcerned MPMs. Figure 4 indicates the changes in the proportion of Topic 4: θc
4,t .
The ratio of the topic has regularity; that is, the minutes released at the end of May
and November until 2015, and March, June, September and November after 2016, havea high ratio of Topic 4. We confirmed the content of these minutes using the words
list for Topic 4 in Table 4, which includes words related to economic outlook, such as‘物価 (prices)’, ‘見通し (outlook)’, ‘物価上昇率 (inflation rate)’, ‘経済 (economy)’, ‘情勢(condition)’ and others. Then, we found that these minutes correspond to the MPMs that
discussed economic outlook reports. Hence, we viewed Topic 4 as concerning discussions
on economic outlook reports and labelled this topic Outlook Report.
Topic 5: Economic and Financial Development
From Table 4, Topic 5 is characterised by words related to economic trends, suchas ‘先行き (future)’, ‘環境 (circumstance)’, ‘個人消費 (consumer spending)’, ‘設備投資(capital investment)’, ‘情勢 (condition)’, ‘回復 (recovery)’ and others. Figure 4 reports
also the time series changes of Topic 5’s proportion: θc5,t . As shown in the figure, Topic
5’s ratio seems inversely correlated with Topic 4’s ratio; that is, the ratio of Topic 5
increases when the ratio of Topic 4 decreases. We checked the contents of the minutes
and found that these topics are allocated in same chapter: Summary of Staﬀ Reports on
Economic and Financial Development. In the MPMs without an economic outlook report,
in this chapter, policymakers only shared their opinions on the economic and financial
situations. In contrast, the MPMs that discussed economic outlook reports simultaneously
addressed sharing opinions and summarising drafts of the reports. Thus, the ratio of Topic
5 decreased and the ratio of Topic 4 increased. From these considerations, we interpreted
that Topic 5 refers to policymakers’ opinions of economic and financial circumstances andlabelled it Economic and Financial Development.
Topic 6: Emerging Economies
Topic 6 in Table 4 seems to consist of keywords related to emerging economies, such as‘経済 (economy)’, ‘新興国 (emerging country)’, ‘輸出 (exports)’, ‘エネルギー (energy)’
and others. Figure 5 plots the time series of the proportion of Topic 6: θc
6,t . According
to the transition, the proportion peaks in the minutes released on 13 October 2015,24 December 2015 and 3 August 2016. In these minutes, we found that policymakers
discussed the eﬀect of the slowdown of emerging economies on the domestic economy interms of imports and productions. In contrast, we observed that the minutes released on
22 March 2017, whose ratio of Topic 6 is relatively low, does not indicate as such. Hence,
we defined this topic, which explains the impact of the emerging economy on Japan’s
economic activities and labelled it Emerging Economies.
For further discussion, Figure 1, which displays changes in entire topics’ proportions
over the time, indicates that the ratio of Topic 6 increases from mid-2015 to mid-2016
6

Until 2015, the outlook report was released twice a year: at end of April and end of October.

10

relative to other topics. This finding suggests that policymakers discussed this topic ingreater detailed and, above all, worried about economic and financial developments inemerging countries.
Topic 7: Impact of Consumption Tax Hike
Topic 7 in Table 4 captures the words related to consumption tax hikes, such as‘引き上げ (hike)’, ‘消費税 (consumption tax)’, ‘駆け込み需要 (rush demand)’, ‘消費者
(consumer)’ and others. In Figure 6, the time series proportion of the topic, θc
7,t , increases
from when the Japanese government passed the consumption tax hike bill in October
2013, and maintains its peak after the implementation of the tax hike in the subsequent
half a year. We confirmed the contents of these minutes and found that policymakers pay
attention to the eﬀects of the tax hike on domestic economic activities, such as economic
outlook, consumer spending, price development and others. Accordingly, we interpreted
that this topic captures the content of meeting members’ consideration of the impact ofconsumption tax hikes on the domestic economy, and we labelled this topic Consumption
Tax Hike.

5

Empirical test and result

5.1

Measuring the informativeness of the BOJ minutes

In this subsection, we examine whether the BOJ minutes influence asset prices andyields. As mentioned in section 3.1, a long time passes between when the MPM minutes
are recorded and released. Thus, the impact may very well be quite small or non-existent.
To reject this possibility, we test the impact using the high-frequency event-study test
introduced by Swanson (2011). This method uses changes in financial markets within
narrow windows of times, especially one- or two-day changes in each asset price or yields
in this study. We assume that changes around the BOJ’s minutes’ release days shouldreflect significant reactions from the releases relative to other days. To investigate thishypothesis, we develop hypothesis tests. The null hypothesis is that releases of the BOJ’s
minutes had no eﬀects on market participants’ expectations; thus, the change in the asset
price or yield was the same: H0 : Vt = 0. Vt is computed in Eq. 1 or Eq. 2. An alternative
hypothesis is that the announcements lead to significant eﬀects on the market’s mind, andthen the changes in asset prices or yields are statistically significant: H1 : Vt ̸= 0.
Table 5 and Table 6 report the results of the event-study analysis explained previously.
The top panel in each table reports the change in each asset across every event window
for each release day. The bottom panel reports the unconditional standard deviation ofeach change in assets for one- and two-day windows during our observation terms. The
statistical significance of each asset response is assessed by dividing each change by theunconditional standard deviation for the same asset and window size in the bottom panel.
Next to each change in asset, the statistical significance for a two-sided t-test is reported
using asterisks: * 10 %, ** 5 % and *** 1 % level.
From Table 5, the changes within the one- and two-day windows in two-year andfive-year Treaty yields were statistically significant on 3 February 2016 when the minutes
11

on the introduction of supplementary measures for the QQE were released. On 18 March
2016, the minutes indicated that the introduction of the QQE with a negative interest
rate had a remarkable eﬀect on the changes within a one-day window in all Treaty
yields for all maturities. Subsequently, the release of minutes that recorded the MPMs
on the enhancement of monetary easing in July 2016 (released on 27 September 2016)
caused changes within one- and two-day windows in two- and five-year Treaty yields withstatistical significance. These results show that the bond market changed around therelease days of the minutes that described the BOJ’s monetary policy changes, especiallyduring the implementation period of the QQE with a negative interest rate.
In contrast, other asset prices did not seem to change on specific days, such as the bondmarket, as shown in Table 6. The change in the TOPIX and Nikkei225 stock markets
are statistically significant on the release days between May 2013 and May 2014. Thechange in the J-REITs (TSEREIT) often seemed to occur on release days in 2013 and,
subsequently, such changes are not statistically significant. The change in the yen/dollar
exchange rate seems to have no trend relative to other asset prices or yields.
The reaction of the assets reported previously seems to have been caused by not only
the release of the minutes but also by other factors. However, we show the possibility
that this factor influences changes in asset values from the result of the aforementioned
event-study analysis.

5.2

Relationship between individual BOJ’s minutes’ topics andchanges in asset values

In this subsection, we analyse the informativeness of the individual topics estimated by
the LDA, particularly using time series changes to each topic’s proportion. To investigate
this phenomenon, we are motivated by the approach in Jegadeesh and Wu (2015). They
examined the relationship between unexpected volatility and the proportion of estimatedtopics’ proportions. We calculate also the unexpected volatility on release day t as theraw volatility and the average event-window volatility as follows:
U Vt,n = Vt −

n
∑
Vt−j
j=1

n

(9)

Because we follow Jegadeesh’s approach, we use n = 20 days. Regarding event-window
return volatility Vt as computed in Eq. 1 or Eq. 2, we set the event-window length as one
day: l = 1 day. Then, we assess the relationship between the unexpected volatility andthe proportion of each topic, as in the following equation:
U Vt = α + β θc
k,t +

M
∑

γm Xm,t + ϵt

(10)

m=1

where U Vt is the unexpected volatility of each asset around the event window on release
date t computed per Eq. 9, θck,t is the proportion of topic k estimated by LDA and Xt
represents the control variables, including:
SP Xt : Standard and Poor’s 500 Index, which is calculated as 100 times the first log
change over the time window under consideration on release day t (basis point);
12

DJIAt : Dow Jones Industrial Average, which is calculated as 100 times the first log
change over the time window under consideration on release day t (basis point);
W T It : West Texas Intermediate, which is calculated as 100 times the first log changeover the time window under consideration on release day t (basis point);
SHCOM Pt : SSE Composite Index, which is calculated as 100 times the first log changeover the time window under consideration on release day t (basis point); andLU Vt : the unexpected volatility of each asset on the previous business day of release dayt, calculated per Eq. 9.
Each regression uses 52 daily observations that capture all minutes’ release days in our
sample from April 2013 to September 2017.
Table 7 reports the coeﬃcient estimates for each topic proportion θck,t from regression
10. First, the coeﬃcient estimates for the Monetary Policy 1 topic proportion, which
captures the content for the period of the introduction of the QQE, are statisticallysignificant and negative and use the unexpected volatility of the five- and 10-year Treaty
yields as explained variables. In addition, the coeﬃcient estimate for this topic proportionis statistically significant and positive with the unexpected volatility in J-REITs. This
result corresponds to the outcome in Table 6 and gives us a further topic for discussion.
That is, information on the Monetary Policy 1 topic in the minutes aﬀected the volatilityof J-REITs. The slope coeﬃcient for the yen/dollar exchange rate is also significantly
positive for this topic. We interpret that information on monetary policy during the
introduction of the QQE caused the yen to fall against the dollar.
In contrast, the coeﬃcient estimate for the proportion of the Monetary Policy 2 topic,
which describes monetary policy under the October 2014 expansion of the QQE, is only
statistically significant and negative with the yen/dollar exchange rate. Furthermore, thecoeﬃcient estimates for the Monetary Policy 3 topic concerned monetary policy after
the introduction in September 2016 of the QQE with yield curve control, and are notstatistically significant with unexpected volatility in any assets. These findings suggestthat information in the minutes on monetary policy, especially the expansion of the QQE
and the QQE with yield curve control, did not influence market expectations.
The Fund-provisioning Measures topic significantly aﬀects both bond and stock
markets. Specifically, the slope coeﬃcient for government bond yields, except for the
40-year Treaty yield, is significantly negative for this topic. Regarding the stock market,
the proportion of the Fund-provisioning Measures topic is significantly related to negativechanges in stock price indices. According to the interpretation of the extraction fromthe minutes in subsection 4.2, the Fund-provisioning Measures topic is strongly related
to the description of monetary policies that introduced in December 2015 supplementarymeasures for the QQE, and that introduced in January 2016 the QQE with a negativeinterest rate because these policies stimulated the supply of money to domestic companies.
The findings from these results identify that the market paid attention to this informationin the minutes, and that the descriptions on the measures forced the stock market to
decline.
The coeﬃcient estimates for the other topics - ‘Outlook Report’, ‘Economic andFinancial Development’ and ‘Consumption Tax Hike’ - are also statistically significant
13with the unexpected volatility in some assets in Table 7. The findings from this result
suggests that market participants pay attention to the monetary policy description andto information such as policymakers’ views on current economic conditions.

6

Conclusion

In this study, we empirically examined the eﬀect of BOJ communication through BOJ
meeting minutes on financial markets, especially under Mr. Kuroda’s BOJ administrationfrom April 2013 to September 2017. Using a computational linguistic model, we quantify
the contents of and extract eight topics from the minutes, including their historicalmonetary policy and policymakers’ views on current economic conditions. The empiricalresults suggest that a relationship exists between the estimated topics and market
reactions on the minutes’ release days. During the early term of the introduction of
the QQE, the market paid attention to the monetary policy description in the minutes,
for which a long period had passed from being the subject of the MPMs. However,information in the minutes on monetary policy under the October 2014 expansion of the
QQE and under the September 2016 QQE with yield curve control resulted in no changes
to the bond and stock markets. From this point, the eﬀect of communicating throughthe minutes during the four and a half years from April 2013 faded. Far from that,
information on fund-provisioning measures to support Japanese companies’ activities,
including a negative interest rate policy, induces the stock market to decline. In contrast,
we found that the market pays attention to meeting members’ opinions about current
economic conditions.
Significant improvements can be made to this study in future research. The first
improvement is to exclude other factors that aﬀect the changes in asset prices or yields.
One approach is to use tick-by-tick trading data and to construct a narrower event window.
The second approach is to develop a tool that measures market sentiment in financial
markets from words appearing in the text, such as in Loughran and McDonald (2014).
They used directional word lists to measure the tone of the financial text in English, but
no Japanese word list exists that is specialised for the financial field. The third approachis to apply this method to other BOJ communications that were announced faster thanthe minutes were released, such as speeches and summaries of policymakers’ opinions. We
leave these extensions for future work.

14

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the FOMC: a Computational Linguistics Approach,” Discussion Papers, Centre for
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[14] Jegadeesh, N., & Wu, D. A. (2015), “Deciphering Fedspeak: The Information
Content of FOMC Meetings,” Working Papers, Emory University.
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16

Table 1: The BOJ Releases Decisions in the MPMs
Event
Statement on MPMs
Outlook
ReportBank’s View)(The

Speeches
Outlook Report (Full Text)

Summary of Opinions
MPM Minutes
The Full Text of MPM
Minutes

The time of release
Immediately
after
relevant MPM
Immediately
after
relevant MPM

3:30 p.m. at the last
day of relevant MPM
2:00 p.m. at the next
day of relevant MPM

Six business days after
relevant MPM
Three business days
after the next MPM
10 years after relevant
MPM

17

Notes

Before 2015: End of
April and October/
After 2016: January,
April,Julyand
October

Before 2015: End of
April and October/
After 2016: January,
April,Julyand
October
It started from 2016

Table 2:
The Deliberation Results of Monetary
Policies Noted in the Minutes under Kuroda’s BOJ
Administration
Date of MPM
03, 04/04/2013

26/04/2013

21, 22/05/2013
10, 11/06/2013
10, 11/07/2013
07, 08/08/2013
04, 05/09/2013
03, 04/10/2013
31/10/2013

20, 21/11/2013
19, 20/12/2013
21, 22/01/2014
17, 18/02/2014

MPM Minutes Votes
02/05/2013
1. The Adoption of the ‘Monetary BaseControl’
2. An Increase in JGB Purchases andTheir Maturity Extension
3. An Increase in ETF and J-REIT
Purchases
4. The Continuation of the QQE
5. The Extension of the Funds-Supplying
Operation to Support Financial Institutions
in Disaster Areas Aﬀected by the Great East
Japan Earthquake
27/05/2013
1. Maintenance of the Current Guideline forMoney Market Operation2.
Decision regarding the Outlook for
Economic Activity and Prices
14/06/2013
Maintenance of the Current Guideline forMoney Market Operation
17/07/2013
Maintenance of the Current Guideline forMoney Market Operation
13/08/2013
Maintenance of the Current Guideline forMoney Market Operation
10/09/2013
Maintenance of the Current Guideline forMoney Market Operation
09/10/2013
Maintenance of the Current Guideline forMoney Market Operation
06/11/2013
Maintenance of the Current Guideline forMoney Market Operation
26/11/2013
1. Maintenance of the Current Guideline forMoney Market Operation2.
Decision regarding the Outlook for
Economic Activity and Prices
26/12/2013
Maintenance of the Current Guideline forMoney Market Operation
27/01/2014
Maintenance of the Current Guideline forMoney Market Operation
21/02/2014
Maintenance of the Current Guideline forMoney Market Operation
14/03/2014
1. Maintenance of the Current Guideline forMoney Market Operation
Continue to the next page18

Continued from the previous page

Date of MPM

10, 11/03/2014
07, 08/04/2014
30/04/2014

20, 21/05/2014
12, 13/06/2014
14, 15/07/2014
07, 08/08/2014
03, 04/09/2014
06, 07/10/2014
31/10/2014

18, 19/11/2014

18, 19/12/2014

MPM Minutes Votes
2.
Release of ‘Outline of the Enhanced
Framework for the Stimulating Bank Lending
Facility and the Growth-Supporting Funding
Facility’3.
Amendment to ‘Principal Terms andConditions for the Funds-Supplying Operation
to Support Financial Institutions in Disaster
Areas’ and ‘Temporary Rules regarding the
Eligibility Standards for Debt of Companies
in Disaster Areas’
11/04/2014
Maintenance of the Current Guideline forMoney Market Operation
07/05/2014
Maintenance of the Current Guideline forMoney Market Operation
26/05/2014
1. Maintenance of the Current Guideline forMoney Market Operation2.
Decision regarding the Outlook for
Economic Activity and Prices
18/06/2014
Maintenance of the Current Guideline forMoney Market Operation
18/07/2014
Maintenance of the Current Guideline forMoney Market Operation
13/08/2014
Maintenance of the Current Guideline forMoney Market Operation
09/09/2014
Maintenance of the Current Guideline forMoney Market Operation
10/10/2014
Maintenance of the Current Guideline forMoney Market Operation
06/11/2014
Maintenance of the Current Guideline forMoney Market Operation
25/11/2014
1. Accelerating the Pace of Increase in
the Monetary Base2.
Increasing Asset Purchases andExtending the Average Remaining
Maturity of JGB Purchases
3.
Decision regarding the Outlook for
Economic Activity and Prices
25/12/2014
1. Maintenance of the Current Guideline forMoney Market Operation
2. Maintenance of the Current Guideline for
Asset Purchases
16/01/2015
1. Maintenance of the Current Guideline forMoney Market Operation
Continue to the next page19

Continued from the previous page

Date of MPM

20, 21/01/2015

17, 18/02/2015

16, 17/03/2015

07, 08/04/2015

30/04/2015

21, 22/05/2015

18, 19/06/2015

14, 15/07/2015

06, 07/08/2015

MPM Minutes Votes
2. Maintenance of the Current Guideline for
Asset Purchases
23/02/2015
1. Maintenance of the Current Guideline forMoney Market Operation
2. Maintenance of the Current Guideline for
Asset Purchases
3. Amendments to the Loan Support Programand other measures
20/03/2015
1. Maintenance of the Current Guideline forMoney Market Operation
2. Maintenance of the Current Guideline for
Asset Purchases
13/04/2015
1. Maintenance of the Current Guideline forMoney Market Operation
2. Maintenance of the Current Guideline for
Asset Purchases
08/05/2015
1. Maintenance of the Current Guideline forMoney Market Operation
2. Maintenance of the Current Guideline for
Asset Purchases
27/05/2015
1. Maintenance of the Current Guideline forMoney Market Operation
2. Maintenance of the Current Guideline for
Asset Purchases
3.
Decision regarding the Outlook for
Economic Activity and Prices
24/06/2015
1. Maintenance of the Current Guideline forMoney Market Operation
2. Maintenance of the Current Guideline for
Asset Purchases
21/07/2015
1. New Framework for MPM
2. Maintenance of the Current Guideline forMoney Market Operation
3. Maintenance of the Current Guideline for
Asset Purchases
12/08/2015
1. Maintenance of the Current Guideline forMoney Market Operation
2. Maintenance of the Current Guideline for
Asset Purchases
18/09/2015
1. Maintenance of the Current Guideline forMoney Market Operation
2. Maintenance of the Current Guideline for
Asset Purchases
Continue to the next page20

Continued from the previous page

Date of MPM
14, 15/09/2015

06, 07/10/2015

30/10/2015

18, 19/11/2015

17, 18/12/2015

28, 29/01/2016

MPM Minutes Votes
13/10/2015
1. Maintenance of the Current Guideline forMoney Market Operation
2. Maintenance of the Current Guideline for
Asset Purchases
05/11/2015
1. Maintenance of the Current Guideline forMoney Market Operation
2. Maintenance of the Current Guideline for
Asset Purchases
25/11/2015
1. Maintenance of the Current Guideline forMoney Market Operation
2. Maintenance of the Current Guideline for
Asset Purchases
3.
Decision regarding the Outlook for
Economic Activity and Prices
24/12/2015
1. Maintenance of the Current Guideline forMoney Market Operation
2. Maintenance of the Current Guideline for
Asset Purchases
03/02/2016
1. The Introduction of Supplementary
Measures for QQE- Extending the Application Periods for
the Loan Support Program and Other
Measures- Extending Eligible Collateral for the
Bank’s Provision of Credit- Extending the Average Remaining
Maturity of JGB Purchases- Increasing the Maximum Amount ofEach Issue of J-REIT to Be Purchasesd- Establishing a New Program for
Purchases of ETFs
- Enhancing the Fund-Provisioning
Measure to Support Strengthening theFoundations for Economic Growth
2. Maintenance of the Current Guideline forMoney Market Operation
3. Maintenance of the Current Guideline for
Asset Purchases
18/03/2016
1. The Amendment to Principal Terms
and Conditions of Complementary
Deposit Facility as a Temporary
Measure to Facilitate Supplying ofFunds
Continue to the next page

21

Continued from the previous page

Date of MPM

14, 15/03/2016

27, 28/04/2016

15, 16/06/2016

28, 29/07/2016

MPM Minutes Votes
2. Maintenance of the Current Guideline forMoney Market Operation
3. Maintenance of the Current Guideline for
Asset Purchases
4.
Decision regarding the Outlook for
Economic Activity and Prices
09/05/2016
1. Maintenance of the Current Guideline forMoney Market Operation
2. Maintenance of the Current Guideline for
Asset Purchases
3. Applying a Negative Interest Rate of
Minus 0.1 Percent to the Policy-Rate Balancesin Current Accounts Held by Financial
Institutions at the Bank
21/06/2016
1. Maintenance of the Current Guideline forMoney Market Operation
2. Maintenance of the Current Guideline for
Asset Purchases
3. Maintenance of the Current Policy Rate
4.
Decision regarding the Outlook for
Economic Activity and Prices
03/08/2016
1. Maintenance of the Current Guideline forMoney Market Operation
2. Maintenance of the Current Guideline for
Asset Purchases
3. Maintenance of the Current Policy Rate
27/09/2016
1. An Increase in Purchases of ETFs
2. Measures to Ensure Smooth Fundingin Foreign Currencies by Japanese Firms
and Financial Institutions- Increasing the Size of the Bank’s
Lending Program to Support Growth in
U.S. Dollars- Establishing a New Facility for Lending
Securities to Be Pledged as Collateral
for the U.S. Dollar Funds-Supplying
Operations
3. Maintenance of the Current Guideline forMoney Market Operation
4. Maintenance of the Current Guideline for
Asset Purchases except for ETF Purchases
5. Maintenance of the Current Policy Rate
Continue to the next page

22

Continued from the previous page

Date of MPM

MPM Minutes Votes
6.
Decision regarding the Outlook for
Economic Activity and Prices
20, 21/09/2016
07/11/2016
1.
‘Comprehensive Assessment:
Developments in Economic Activity
and Prices as well as Policy Eﬀects
since the Introduction of QQE
2. Current Situation of and Outlook for
Economic Activity and Prices in Japan
3. The Guideline for Market Operations- Applying a Negative Interest Rate of
Minus 0.1 Percent to the Policy-Rate
Balances in Current Accounts Held byFinancial Institutions at the Bank
- Purchases of JGBs so that 10-year
JGB Yields Remain more or less at theCurrent Level of around 0 Percent
4. The New Tools of Market Operations
for Facilitating Yield Curve Control
5. Maintenance of the Current Guideline for
Asset Purchases
31/10/2016, 01/11/2016 26/12/2016
1. Maintenance of the Current Guideline forMoney Market Operation
2. Maintenance of the Current Guideline for
Asset Purchases
3.
Decision regarding the Outlook for
Economic Activity and Prices
19, 20/12/2016
03/02/2017
1. Maintenance of the Current Guideline forMoney Market Operation
2. Maintenance of the Current Guideline for
Asset Purchases
30, 31/01/2017
22/03/2017
1. Maintenance of the Current Guideline forMoney Market Operation
2. Maintenance of the Current Guideline for
Asset Purchases
3.
Decision regarding the Outlook for
Economic Activity and Prices
15, 16/03/2017
02/05/2017
1. Maintenance of the Current Guideline forMoney Market Operation
2. Maintenance of the Current Guideline for
Asset Purchases
26, 27/04/2017
21/06/2017
1. Maintenance of the Current Guideline forMoney Market Operation
Continue to the next page23

Continued from the previous page

Date of MPM

15, 16/06/2017

19, 20/07/2017

MPM Minutes Votes
2. Maintenance of the Current Guideline for
Asset Purchases
3.
Decision regarding the Outlook for
Economic Activity and Prices
25/07/2017
1. Maintenance of the Current Guideline forMoney Market Operation
2. Maintenance of the Current Guideline for
Asset Purchases
26/09/2017
1. Maintenance of the Current Guideline forMoney Market Operation
2. Maintenance of the Current Guideline for
Asset Purchases

Sources: Bank of Japan; author’s compilation

24

25

Weight
0.034
0.022
0.017
0.017
0.016
0.015
0.015
0.014
0.014
0.012
0.012
0.01
0.01
0.009
0.009
0.009
0.009
0.008
0.008
0.008
0.008
0.008
0.007
0.007
0.007
0.007
0.007
0.007
0.006
0.006
0.006
0.006
0.006
0.006
0.006
0.006
0.005
0.005
0.005
0.005

Topic 0Word
物価 (Prices)
経済 (Economy)
目標 (Target)
買入れ (Purchases)
市場 (Market)
国債 (JGB)
安定 (Stability)
予想 (Forecast)
期待 (Expectation)
財政 (Finance)
政府 (Government)
量的・質的金融緩和 (QQE)
マネタリーベース (Monetary Base)
日本銀行 (BOJ)
実現 (Realization)
米国 (U.S.)
金融政策 (Monetary Policy)
効果 (Eﬀect)
資産 (Asset)
企業 (Company)
持ち直し (Recovery)
日本経済 (Japanese Economy)
デフレ (Deflation)
欧州 (Europe)
圧力 (Pressure)
金利 (Interest Rate)
リスク (Risk)
継続 (Continuation)
輸出 (Export)
マインド (Mind)
住宅 (House)
達成 (Accomplishment)
景気 (Business)
物価上昇率 (Inflation Rate)
状況 (Situation)
社債 (Bond)
見解 (Opinion)
注意 (Caution)
消費者 (Consumer)
金融緩和 (Monetary Easing)
Weight
0.038
0.027
0.025
0.019
0.019
0.017
0.016
0.016
0.015
0.015
0.014
0.014
0.013
0.013
0.012
0.012
0.012
0.011
0.011
0.011
0.011
0.011
0.01
0.01
0.009
0.009
0.009
0.009
0.009
0.008
0.008
0.008
0.008
0.008
0.007
0.007
0.006
0.006
0.006
0.006

Topic 1
Word
買入れ (Purchases)
物価 (Prices)
回復 (Recovery)
調整 (Adjustment)
量的・質的金融緩和 (QQE)
目標 (Target)
資産 (Asset)
効果 (Eﬀect)
予想 (Forecast)
原油価格 (Oil Price)
価格 (Price)
金利 (Interest Rate)
継続 (Continuation)
先進国 (Developed Country)
金融政策 (Monetary Policy)
ペース (Pace)
在庫 (Stock)
国際 (International)
長期 (Long Term)
先行き (Future)
インフレ率 (Inflation Rate)
マネタリーベース (Monetary Base)
物価上昇率 (Inflation Rate)
金融市場 (Financial Market)
ユーロ (Euro)
期待 (Expectation)
達成 (Accomplishment)
残存 (Persistence)
欧州 (Europe)
情勢 (Condition)
指標 (Index)
個人消費 (Consumer Spending)
モメンタム (Momentum)
国債 (JGB)
商品 (Product)
イールドカーブ (Yield Curve)
日本銀行 (BOJ)
進捗 (Progress)
ETF
景気 (Business)
Weight
0.043
0.037
0.026
0.026
0.025
0.021
0.018
0.018
0.015
0.015
0.015
0.014
0.013
0.013
0.013
0.012
0.012
0.012
0.011
0.011
0.011
0.011
0.01
0.009
0.009
0.009
0.009
0.009
0.008
0.008
0.008
0.007
0.007
0.007
0.007
0.007
0.007
0.006
0.006
0.006

Topic 2
Word
買入れ (Purchases)
経済 (Economy)
金利 (Interest Rate)
目標 (Target)
物価 (Prices)
国債 (JGB)
効果 (Eﬀect)
金融 (Finance)
安定 (Stability)
物価上昇率 (Inflation Rate)
実現 (Realization)
政策 (Policy)
期待 (Expectation)
予想 (Forecast)
先行き (Future)
操作 (Operation)
イールドカーブ (Yield Curve)
長期金利 (Long-term Interest Rate)
資産 (Asset)
形成 (Formation)
海外 (Overseas)
残高 (Stock)
所得 (Income)
金融政策 (Monetary Policy)
政策金利 (Policy Interest Rate)
緩和 (Easing)
長期 (Long Term)
ETF
金融緩和 (Monetary Easing)
ゼロ (Zero)
対策 (Measure)
環境 (Circumstance)
持続 (Continuation)
現状 (Current Situation)
新興国 (Emerging Country)
欧州 (Europe)
波及 (Spread)
株価 (Stock Price)
社債 (Bond)
枠組み (Framework)

Table 3: Distribution of Top LDA Topic Keywords
Weight
0.034
0.033
0.025
0.023
0.02
0.019
0.018
0.018
0.017
0.016
0.015
0.014
0.014
0.014
0.014
0.013
0.013
0.012
0.01
0.01
0.01
0.01
0.01
0.01
0.009
0.009
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.007
0.007
0.007
0.007
0.007
0.007
0.007

Topic 3
Word
支援 (Support)
金融機関 (Financial Institutions)
量的・質的金融緩和 (QQE)
買入れ (Purchases)
貸出 (Lending)
資金供給 (Fund-Provisioning)
導入 (Introduction)
日本銀行 (BOJ)
金利 (Interest Rate)
措置 (Measure)執行部 (Staﬀ)
成長 (Growth)
マイナス金利 (Negative Interest Rate)
国債 (JGB)
長期 (Long Term)
残高 (Stock)
強化 (Strengthening)
金融市場 (Financial Market)
先行き (Future)
基盤 (Base)
緩和 (Easing)ETF
制度 (System)
担保 (Collateral)
対応 (Correspondence)
市場 (Market)
調節 (Adjustment)
情勢 (Condition)
当座預金 (Current Deposit)
対象 (Target)
追加 (Supplement)
延長 (Extension)
改正 (Amendment)
要領 (Point)
観点 (Point)
JREIT
マネタリーベース (Monetary Base)
被災地 (Disaster Stricken Area)
買入れ (Purchases)
基金 (Fund)26

Weight
0.059
0.047
0.03
0.028
0.025
0.024
0.022
0.021
0.021
0.018
0.018
0.017
0.016
0.016
0.014
0.014
0.014
0.013
0.013
0.013
0.011
0.011
0.01
0.009
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.007
0.007
0.007
0.007
0.007

Topic 4Word
物価 (Prices)
見通し (Future)
企業 (Company)
物価上昇率 (Inflation Rate)
成長 (Growth)
予想 (Forecast)
動向 (Trend)
経済 (Economy)
情勢 (Condition)
金融市場 (Financial Market)
賃金 (Wage)
安定 (Stability)
需給 (Supply and Demand)
海外 (Overseas)
家計 (Household Budget)
提出 (Submission)
実現 (Realization)
調節 (Adjustment)
成長率 (Growth Rate)
需給ギャップ (Supply and Demand Gap)
ペース (Pace)
労働 (Labor)
不確実性 (Uncertainty)
黒田 (Kuroda)
展望レポート (Outlook Report)
循環 (Circulation)
リスク (Risk)
期待 (Expectation)
変更 (Change)
見解 (View)
説明 (Description)
時期 (Period)
設備投資 (Capital Investment)
物価上昇 (Inflation)
輸出 (Export)
マクロ (Macro)
環境 (Circumstance)
柱 (Pillar)
為替相場 (Exchange Rate)
価格 (Price)
Weight
0.039
0.025
0.024
0.023
0.023
0.022
0.022
0.018
0.018
0.017
0.017
0.017
0.015
0.015
0.014
0.014
0.013
0.012
0.011
0.011
0.011
0.01
0.01
0.01
0.01
0.009
0.009
0.009
0.009
0.009
0.009
0.009
0.009
0.008
0.008
0.008
0.008
0.007
0.007
0.007

Topic 5Word
先行き (Future)
環境 (Circumstance)
個人消費 (Consumer Spending)
設備投資 (Capital Investment)
調節 (Adjustment)
回復 (Recovery)
情勢 (Condition)
金融市場 (Financial Market)
投資 (Investment)
海外 (Overseas)
金融 (Finance)
生産 (Production)
残高 (Balance)
市場 (Market)
需要 (Demand)
金融政策 (Financial Market)
反映 (Reflection)
景気 (Business)
持ち直し (Recovery)
金融経済 (Monetary Economy)
ベース (Base)
継続 (Continuation)
米国経済 (US Economy)
内需 (Domestic Demand)
成長 (Growth)
輸出 (Export)
米国 (U.S.)対外 (Foreign)
所得 (Income)緩和 (Easing)CP
雇用 (Employment)
調整 (Adjustment)
前向き (Forward-looking)
株価 (Stock Price)
貸出 (Lending)
発言 (Speech)
実質 (Real)
金融政策決定会合 (MPM)
内外 (Inside and Outside)
Weight
0.065
0.042
0.039
0.039
0.023
0.022
0.022
0.02
0.019
0.018
0.017
0.016
0.016
0.015
0.014
0.013
0.013
0.013
0.013
0.012
0.011
0.011
0.01
0.01
0.01
0.01
0.01
0.009
0.009
0.008
0.008
0.008
0.006
0.006
0.006
0.006
0.006
0.006
0.006
0.006

Topic 6Word
経済 (Economy)
物価 (Prices)
企業 (Company)
新興国 (Emerging Country)
安定 (Stability)
輸出 (Export)
ペース (Pace)
エネルギー (Energy)
所得 (Income)環境 (Circumstance)
残高 (Balance)
動向 (Trend)
生産 (Production)
雇用 (Employment)
日本銀行 (BOJ)
部門 (Department)
消費者 (Consumer)
支出 (Spending)
政策 (Policy)
状況 (Situation)
リスク (Risk)
収益 (Revenue)
生鮮食品 (Fresh Food)
家計 (Household Budget)
価格 (Price)
保有 (Possession)
社債 (Bond)
実現 (Realization)
要因 (Factor)
金融政策決定会合 (MPM)
意見 (Opinion)
中国 (China)
黒田 (Kuroda)
消費 (Consumption)
先行き (Future)
点検 (Inspection)
住宅 (House)
買入れ (Purchases)
資金調達 (Funding)
委員会 (Committee)

Table 4: Distribution of Top LDA Topic Keywords
Weight
0.035
0.032
0.031
0.029
0.029
0.026
0.024
0.023
0.023
0.021
0.019
0.018
0.017
0.014
0.014
0.013
0.011
0.011
0.011
0.01
0.009
0.008
0.008
0.008
0.008
0.007
0.007
0.007
0.007
0.007
0.007
0.007
0.007
0.006
0.006
0.006
0.005
0.005
0.005
0.005

Topic 7
Word
引き上げ (Hike)
消費税率 (Consumption Tax)
物価 (Prices)
反動 (Reaction)
経済 (Economy)
駆け込み需要 (Rush Demand)
企業 (Company)
所得 (Income)安定 (Stability)
雇用 (Employment)
環境 (Circumstance)
回復 (Recovery)
消費者 (Consumer)
輸出 (Export)
ペース (Pace)
要因 (Factor)
リスク (Risk)
先行き (Future)
成長 (Growth)
動向 (Trend)
量的・質的金融緩和 (QQE)
持続 (Continuation)
日本銀行 (BOJ)
先進国 (Developed Country)
ASEAN
NIEs
構造 (Structure)
緩和 (Easing)
実現 (Realization)
点検 (Inspection)
賃金 (Wage)
ベース (Base)
銀行 (Bank)
貸出 (Lending)
マネタリーベース (Monetary Base)
住宅 (House)
コスト (Cost)
考え方 (Approach)
景気 (Business)
需給 (Supply and Demand)

Table 5: Treaty Yields and Estimated Impacts on Yields
around BOJ’s Minutes’ Release Days

Release date
02/05/2013
27/05/2013
14/06/2013
17/07/2013
13/08/2013
10/09/2013
09/10/2013
06/11/2013
26/11/2013
26/12/2013
27/01/2014
21/02/2014
14/03/2014
11/04/2014
07/05/2014
26/05/2014
18/06/2014
18/07/2014
13/08/2014
09/09/2014
10/10/2014
06/11/2014
25/11/2014
25/12/2014
16/01/2015
23/02/2015
20/03/2015
13/04/2015
08/05/2015
27/05/2015
24/06/2015
21/07/2015
12/08/2015
18/09/2015
13/10/2015
05/11/2015
25/11/2015
24/12/2015
03/02/2016
18/03/2016

1-day changes
2-year 5-year 10-year 40-year
−0.4
−1.8
−2.8
0
0
−1
−0.2
−2.5
0
−2.8** −4.4** −0.8
0
−1
−0.6
−1.6
0
−1.5
−1.4
−1.7
0
−1.3
−1.9
−1.6
0
0.6
0
−1.2
0
0.5
0.5
−0.5
0
−0.8
−2
−2.5
0
1
1.8
0.8
0
0
0.1
1.1
0
0.4
1
1.6
−0.1
−1.1
−1.8
−0.9
0
0
−0.4
−0.1
0
0
−0.8
−0.8
0
0.2
0.2
0.1
0
0
0.5
−0.4
0
0
0.6
−0.4
−0.1
0
0
−0.4
−0.1
0
0.1
1.2
0
1
1.2
2
1
0
0.1
1.6
0
0.2
−1
−0.8
1
0
−2
−3.2
0
0
−0.9
−0.5
−0.1
−0.5
−0.4
−1.2
0.6
−0.6
0
4.1
−0.1
−0.4
0.1
1.7
−1
−1.8
−1.9
0
0
−1.4
−3.1*
−1.2
−0.1
−1
−1
0.1
0
−0.5
−0.3
−1.2
0
−0.7
−4**
−2.7
−0.1
−2
−2.9
−3.5
0
0
−0.4
−0.4
−0.1
0
−0.1
0
−0.5
−0.7
−1.6
−0.8
0.2
0
0.5
0
−3*** −3.4** −1.8
−0.4
−2.1** −3.6*** −4.7** −13.7***

2-day changes
2-year 5-year 10-year
−0.3
−0.2
0.7
0.6
3.7*
6.3**
0
−3.1
−2.4
0
−1.6
−1.9
0
−0.4
0.7
0.1
−0.7
−1.4
−0.5
0.6
0
−0.5
0.1
−1.5
0.1
−1.5
−3.5
0
1
1.9
0
−0.4
−0.5
0
0.4
0.5
−0.1
−1
−1.8
0.9
0.6
−0.4
0
0.1
−0.3
0
0.1
0.6
0
−0.6
0
0.5
0.1
0.7
−0.1
−0.6
−0.4
−0.1
0.3
1.6
−0.4
1
0.6
1
0.6
0.7
−0.1
−0.7
−2.4
0.8
0.6
−0.5
−0.1
−0.7
−4.4
−0.5
−1
−1.2
1.5
0
−1.5
−0.1
−2
−1.4
−1.5
−2.9
−3.8
−0.7
−1.9
−2
−0.2
−1
0.5
−0.1
−0.9
−1
0
−0.5
−1.9
−0.2
−2
−3.2
0
−1
−1.3
−0.2
0
0.5
−0.5
−0.7
−2
0.3
0.6
0.6
−2.6* −4.4** −2.1
−1.6
−3.6*
−4.6*

40-year
2.9
−0.9
−0.5
−1.6
0.4
−1
−2
−1.6
−5
1.6
3.9
1.2
−0.9
−0.4
−0.8
−0.9
4.3
0.4
0.3
1.9
2.7
1.7
−2
−1.6
−1.3
−3.7
5.5
0
−0.4
1.6
1.3
−3.6
−0.8
−4.6
0
0.8
−1.9
0
−0.4
−19.2***

Continue to the next page27

Continued from the previous page

Release date
09/05/2016
21/06/2016
03/08/2016
27/09/2016
07/11/2016
26/12/2016
03/02/2017
22/03/2017
02/05/2017
21/06/2017
25/07/2017
26/09/2017

1-day changes
2-year 5-year 10-year 40-year
−0.1
0.1
1
0.5
0.4
0.6
0.5
0.6
−1.2
−2.7*
−2.5
4.2
−3.9*** −4*** −1.6
0.8
0.5
0.8
1.1
0.7
0.3
0.6
0.5
1.1
−0.5
0
−0.8
0
−0.5
−1
−0.5
−1.5
0.5
0.7
0.6
0.2
1
0.6
0.4
−0.9
0.6
−0.1
0
−1.3
0
0.6
0.5
−0.2

Unconditional standard deviation of yield changes.
0.96
1.38
1.87
2.62
Note

2-day changes
2-year 5-year 10-year
−0.1
0.2
2.1
0.9
0.6
0.1
−1.3
−2.1
−1.5
−6.4*** −4.6** −3.1
0.1
0.6
−0.4
1.2
0.6
1
0.5
1.7
−0.4
−1
−2
−1
0.9
1.7
1.6
1
0.6
0
1.1
0.9
1.1
0.9
2.6
2.6

1.44

1.96

2.59

40-year
3.7
−1.4
10***
−2.9
0.7
0.8
3.7
−1.5
1.2
−1.6
−0.5
2

3.89

Asterisks indicate statistical significance at the *10 percent, **5 percent, and ***1 percent level.

28

29

02/05/2013
27/05/2013
14/06/2013
17/07/2013
13/08/2013
10/09/2013
09/10/2013
06/11/2013
26/11/2013
26/12/2013
27/01/2014
21/02/2014
14/03/2014
11/04/2014
07/05/2014
26/05/2014
18/06/2014
18/07/2014
13/08/2014
09/09/2014
10/10/2014
06/11/2014
25/11/2014
25/12/2014
16/01/2015

Release dateContinue to the next page

1-day changes
2-day changes
TOPIX Nikkei225 TSEREIT Yen/Dollar
TOPIX Nikkei225 TSEREIT Yen/Dollar−0.191−0.333−0.5410.300−0.191−0.333−0.5410.706*−1.480*** −1.419**
1.284*** −0.047−0.949−0.902
1.447**
0.497
0.508
0.833
2.348***
0.166
1.655**
2.004**
1.810***
0.264
0.097
0.047
−0.398
0.205
0.410
0.618
−0.2470.582
0.854
1.102*
0.112
0.727***
1.383*
1.672**
0.485
0.665*
0.633
0.662
1.140**
0.369
0.598
0.667
1.815***
0.178
0.629
0.445
0.964**
0.110
1.038
0.928
0.935
0.508
0.350
0.340
−0.506
0.046
0.079
0.009
−1.0510.220−0.228−0.2900.082−0.128−0.434−0.474
0.260
0.173
0.724
0.444
0.811*
0.172
1.087
0.456
1.043
0.286
−1.232** −1.103*−0.3790.034−1.406*−1.177−0.2470.184
0.997*
1.234**
0.089
0.153
0.882
1.152
−0.0290.057−1.422** −1.456** −0.420−0.284−1.788** −1.607** −0.367−0.213−0.586−1.045*−0.2930.051−0.637−1.2010.063
0.141−1.134** −1.293** −0.009
0.068−0.833−0.891−0.105
0.021
0.521
0.419
−0.127
0.021
0.536
0.520
0.391
0.104
0.382
0.404
0.303
−0.015
1.068
1.103
0.437
−0.153−0.345−0.4390.226−0.066−0.345−0.4390.226−0.096
0.153
0.150
0.031
0.079
0.440
0.437
0.506
0.106
0.033
0.122
−0.231
0.345
0.272
0.231
0.342
0.530
−0.614−0.5030.290
0.002−0.614−0.5030.290−0.224−0.491−0.373−1.050**0.081−0.257−0.146−0.656
0.178
0.277
0.125
0.366
−0.199
0.192
0.065
0.298
−0.309−0.145−0.111−0.1830.000
0.045−0.0860.131−0.014−0.408−0.6250.017
0.283−0.132−0.240−0.3230.254

Prices around BOJ’s Minutes’ Release Days

Table 6: Other Assets’ Prices and Estimated Impacts on the30

23/02/2015
20/03/2015
13/04/2015
08/05/2015
27/05/2015
24/06/2015
21/07/2015
12/08/2015
18/09/2015
13/10/2015
05/11/2015
25/11/2015
24/12/2015
03/02/2016
18/03/2016
09/05/2016
21/06/2016
03/08/2016
27/09/2016
07/11/2016
26/12/2016
03/02/2017
22/03/2017
02/05/2017
21/06/2017
25/07/2017
26/09/2017

Release dateContinue to the next page

1-day change
2-day change
TOPIX Nikkei225 TSEREIT Yen/Dollar
TOPIX Nikkei225 TSEREIT Yen/Dollar
0.072
0.318
0.252
0.049
0.230
0.638
0.565
0.166
0.129
0.186
0.179
−0.243
0.451
0.615
0.240
−0.422−0.090−0.005−0.489
0.058
0.035
0.002
−0.347−0.385
0.360
0.196
0.208
0.102
0.649
0.734
0.764
0.163
0.046
0.075
−0.241
0.246
0.344
0.242
−0.188
0.407
0.090
0.122
−0.0240.159−0.142−0.079−0.117−0.0670.285
0.400−0.258−0.149−0.198−0.1210.221−0.073−0.566−0.693−0.275−0.339−0.509−0.263−0.240−0.139−0.868−0.8620.155−0.343−0.868−0.8620.155−0.137−0.345−0.483−0.423−0.018−1.289−1.309−0.278−0.240
0.412
0.433
0.263
−0.005
0.648
0.770
0.217
0.564
−0.306−0.1690.139
0.149−0.098
0.043
0.296
0.035
−0.284−0.224−0.074−0.256−0.496−0.271−0.047−0.256−1.391** −1.391**
0.453−0.828*** −1.934** −1.762**
0.323−1.142***−0.447−0.5460.067
0.031−0.447−0.546
0.067
0.117
0.278
0.294
0.649
0.687**
1.207
1.219
1.092*
0.960**
0.497
0.551
0.269
0.052
0.184
0.272
−0.4230.127−0.953*−0.825−0.2670.137−0.579−0.363
0.086
0.052
0.433
0.364
0.160
−0.037−0.165−0.208
0.086
0.130
0.505
0.693
0.179
0.640**
0.527
0.678
0.108
0.740*−0.160−0.0690.340
0.000−0.214−0.055
0.474
0.135
0.131
0.008
0.018
−0.015
0.287
0.142
0.042
−0.027−0.933*−0.9350.043−0.308−0.927−0.835−0.079−0.288
0.296
0.303
0.465
0.198
0.296
0.303
0.465
0.277
−0.153−0.197−0.042−0.045−0.185−0.258−0.105−0.132−0.121−0.0450.340
0.197−0.018
0.162
0.191
0.345
−0.002−0.144−0.0420.184−0.218−0.279−0.2090.331

Continued from the previous page

31

0.786

Unconditional standard deviation of the prices’ changes.
0.561
0.597
0.449
0.279
Note
0.809

0.665

0.394

2-day change
Nikkei225 TSEREIT Yen/Dollar

Asterisks indicate statistical significance at the *10 percent, **5 percent, and ***1 percent level.

TOPIX

1-day change
TOPIX Nikkei225 TSEREIT Yen/Dollar

Release dateContinued from the previous page32

2.6680(1.08)

3.7337(1.09)

6.3567(1.31)

0.8432(1.32)

2.6552** 3.8304** 3.5865(2.07)(2.12)(1.35)

0.1904(0.26)

0.3163(0.40)−0.3161(−0.28)−0.4361(−1.11)−0.1472(−0.54)−0.6458(−0.84)

1.1961**(2.59)−0.3131(−0.27)3.7317*** 4.0481*** 1.0596(3.11)(3.17)(0.75)−0.7100 −0.3945 −1.1022 −0.0474 −0.2505(−0.74)(−0.20)(−0.40)(−0.01)(−0.23)

1.1832(0.95)

Asterisks indicate statistical significance at the *10 percent, **5 percent, and ***1 percent level.

Note

Tax Hike

Emerging Economies

Economic and Financial Development

0.9594(0.77)−0.7109(−1.69)−1.0495(−0.85)−0.3555 −1.4105 −3.9405 −9.0113** −0.9471(−0.34)(−0.66)(−1.32)(−2.19)(−0.82)

Outlook Report

2.0989(1.05)−0.2752(−0.72)−0.8418**(−2.49)−1.7781* −4.9826** −4.5836* −5.3252 −2.1263** −2.4346** −0.6572(−1.74)(−2.66)(−1.77)(−1.41)(−2.16)(−2.34)(−0.58)−0.7869(−0.96)0.7641 −0.7572(0.27)(−0.99)−1.5085(−1.50)Fund-provisioning Measures−0.2421(−0.23)4.6150 −0.1569(1.31)(−0.16)

Nikkei225 TSEREIT Yen/Dollar
1.37382.0668**1.2322***(1.60)(2.45)(4.92)−0.0588(−0.20)1.7594(1.27)

0.2134(0.31)

Policy 3

0.4749(0.19)

TOPIX
1.2689(1.58)−0.3105(−0.37)0.6589(0.37)

0.0697(0.08)

Policy 2

Policy 1Treaty yields
2-year5-year10-year40-year−0.3291 −3.1108** −3.5439* −3.3077(−0.45)(−2.15)(−1.70)(−1.09)

Table 7: Topic Proportion and Market Reaction

02/05/2013

0.6

0.5

0.2

27/05/2013
14/06/2013
17/07/2013
13/08/2013
10/09/2013
09/10/2013
06/11/2013
26/11/2013
26/12/2013
27/01/2014
21/02/2014
14/03/2014
11/04/2014
07/05/2014
26/05/2014
18/06/2014
18/07/2014
13/08/2014
09/09/2014
10/10/2014
06/11/2014
25/11/2014
25/12/2014
26/01/2015
23/02/2015
20/03/2015
13/04/2015
08/05/2015
27/05/2015
24/06/2015
21/07/2015
12/08/2015
18/09/2015
13/10/2015
05/11/2015
25/11/2015
24/12/2015
03/02/2016
18/03/2016
09/05/2016
21/06/2016
03/08/2016
27/09/2016
07/11/2016
26/12/2016
03/02/2017
22/03/2017
02/05/2017
21/06/2017
25/07/2017
26/09/2017

Figure 1: BOJ Topic Proportions Over Time

Introduction in April 2013of the QQE
Expansion in October 2014of the QQE

Policy 1

33

Introduction of the QQE in January 2016
with a negative interest rate

0.8

0.3
Introduction of the QQE in
Septempber 2016 with yield curve
control1

0.9
Tax Hike

Emerging
Economies

0.7

Economic and Financial
Development

Outlook
Report0.4

Fund-provisioning
Measures

Policy 3

Policy 2

0.1

002/05/2013
27/05/2013
14/06/2013
17/07/2013
13/08/2013
10/09/2013
09/10/2013
06/11/2013
26/11/2013
26/12/2013
27/01/2014
21/02/2014
14/03/2014
11/04/2014
07/05/2014
26/05/2014
18/06/2014
18/07/2014
13/08/2014
09/09/2014
10/10/2014
06/11/2014
25/11/2014
25/12/2014
26/01/2015
23/02/2015
20/03/2015
13/04/2015
08/05/2015
27/05/2015
24/06/2015
21/07/2015
12/08/2015
18/09/2015
13/10/2015
05/11/2015
25/11/2015
24/12/2015
03/02/2016
18/03/2016
09/05/2016
21/06/2016
03/08/2016
27/09/2016
07/11/2016
26/12/2016
03/02/2017
22/03/2017
02/05/2017
21/06/2017
25/07/2017
26/09/2017

Figure 2: Topic 0, 1 and 2 Proportions Over Time

Introduction in April 2013 of
the QQE
Expansion in October 2014 of
the QQE

34

Introdution of the QQE in January
2016 with negative interesst rate

0.4
Introduction of the QQE in
September 2016 with yield curve
control

0.45

Policy 3

0.35

Policy 1

0.3

Policy 2

0.25

0.2

0.15

0.1

0.05

0

02/05/2013

0.45

27/05/2013
14/06/2013
17/07/2013
13/08/2013
10/09/2013
09/10/2013
06/11/2013
26/11/2013
26/12/2013
27/01/2014
21/02/2014
14/03/2014
11/04/2014
07/05/2014
26/05/2014
18/06/2014
18/07/2014
13/08/2014
09/09/2014
10/10/2014
06/11/2014
25/11/2014
25/12/2014
26/01/2015
23/02/2015
20/03/2015
13/04/2015
08/05/2015
27/05/2015
24/06/2015
21/07/2015
12/08/2015
18/09/2015
13/10/2015
05/11/2015
25/11/2015
24/12/2015
03/02/2016
18/03/2016
09/05/2016
21/06/2016
03/08/2016
27/09/2016
07/11/2016
26/12/2016
03/02/2017
22/03/2017
02/05/2017
21/06/2017
25/07/2017
26/09/2017

Figure 3: Topic 3 Proportions Over Time
Introduction of the QQE in January 2016 with anegative interest rate

35

Enhancement in July
2016 of monetary easing

Introduction of Supplementarymeasures in December 2015 for the
QQE

0.4

0.35

0.3

0.25

0.2

0.15

0.1

0.05

0

02/05/2013

0.35

27/05/2013
14/06/2013
17/07/2013
13/08/2013
10/09/2013
09/10/2013
06/11/2013
26/11/2013
26/12/2013
27/01/2014
21/02/2014
14/03/2014
11/04/2014
07/05/2014
26/05/2014
18/06/2014
18/07/2014
13/08/2014
09/09/2014
10/10/2014
06/11/2014
25/11/2014
25/12/2014
26/01/2015
23/02/2015
20/03/2015
13/04/2015
08/05/2015
27/05/2015
24/06/2015
21/07/2015
12/08/2015
18/09/2015
13/10/2015
05/11/2015
25/11/2015
24/12/2015
03/02/2016
18/03/2016
09/05/2016
21/06/2016
03/08/2016
27/09/2016
07/11/2016
26/12/2016
03/02/2017
22/03/2017
02/05/2017
21/06/2017
25/07/2017
26/09/2017

Figure 4: Topic 4 and 5 Proportions Over Time

0.4

Economic andFinancial
Development

0.3

0.25

0.2

0.15
Outlook
Report

0.1

0.05

0

36

02/05/2013
27/05/2013
14/06/2013
17/07/2013
13/08/2013
10/09/2013
09/10/2013
06/11/2013
26/11/2013
26/12/2013
27/01/2014
21/02/2014
14/03/2014
11/04/2014
07/05/2014
26/05/2014
18/06/2014
18/07/2014
13/08/2014
09/09/2014
10/10/2014
06/11/2014
25/11/2014
25/12/2014
26/01/2015
23/02/2015
20/03/2015
13/04/2015
08/05/2015
27/05/2015
24/06/2015
21/07/2015
12/08/2015
18/09/2015
13/10/2015
05/11/2015
25/11/2015
24/12/2015
03/02/2016
18/03/2016
09/05/2016
21/06/2016
03/08/2016
27/09/2016
07/11/2016
26/12/2016
03/02/2017
22/03/2017
02/05/2017
21/06/2017
25/07/2017
26/09/2017

Figure 5: Topic 6 Proportions Over Time

0.35

0.3

0.25

0.2

0.15

0.1

0.05

0

37

02/05/2013
27/05/2013
14/06/2013
17/07/2013
13/08/2013
10/09/2013
09/10/2013
06/11/2013
26/11/2013
26/12/2013
27/01/2014
21/02/2014
14/03/2014
11/04/2014
07/05/2014
26/05/2014
18/06/2014
18/07/2014
13/08/2014
09/09/2014
10/10/2014
06/11/2014
25/11/2014
25/12/2014
26/01/2015
23/02/2015
20/03/2015
13/04/2015
08/05/2015
27/05/2015
24/06/2015
21/07/2015
12/08/2015
18/09/2015
13/10/2015
05/11/2015
25/11/2015
24/12/2015
03/02/2016
18/03/2016
09/05/2016
21/06/2016
03/08/2016
27/09/2016
07/11/2016
26/12/2016
03/02/2017
22/03/2017
02/05/2017
21/06/2017
25/07/2017
26/09/2017

Figure 6: Topic 7 Proportions Over Time

0.4

0.35

0.3

0.25

0.2

0.15

0.1

0.05

0

38