１【論文】

Asymmetric Effects of Monetary Policy
Shocks on Stock Markets:
An Empirical Test for China
LV XinKeywords: Stock returns, Markov‑Switching model, Official Interest Rate
JEL Classification: G12, E52

Kurov (2010) reveal further results that prove

１ Introduction

the asymmetric effects of monetary policy

It is well known that monetary policy shocks

shocks on stock markets in both the U.K. andhave negative impacts on stock markets. Most

the U.S. This new evidence is opposed withworld scholars (Thorbecke (1997), Rigobon andclassical financial economics such as Fama

Sack (2003), Basistha and Kurov (2008)) follow(1965) who promulgates that the monetary

the wisdom of Bernanke and Blinder (1992) andpolicy produces asymmetric effects on thehave adopted interest rate (federal funds rate

stock market.

in the U.S.) changes as the primary monetary

Unfortunately, no systematic empirical ana-

policy tool when conducting assessments oflysis addressing China s stock market current-

how monetary policy shocks impact the stockly exists. In addition, much literature indicatesmarket. Bernanke and Kuttner (2005) foundthat developed countries experiences are notthat a hypothetical, unanticipated 100‑basis‑always applicable to the case of China１, andpoint cut in the federal funds rate target would

thus, the effects of monetary policy on stockcause a 4% increase in the U.S. stock market.

returns in China may differ greatly from the

Honda and Kuroki (2006) conducted an analysis

traditional responses observed in developedin a Japanese context that also suggested a

countries. Therefore, two questions arise

significant

betweenregarding the relationship between monetary

marketpolicy and stock market returns in China. One

interest

negative
rate

shocksrelationship
and

stock

performance.

of these questions is whether monetary policy

However, Chen (2007) innovatively demonst-

could negatively affect the Chinese stock

rates that monetary policy shocks do notmarket, and the other is whether monetary

always produce linear impacts on the U.S.

policy has similar asymmetric impacts on thestock market. Instead, shocks cause asymmetric effects on the stock market, with larger
effects on stock returns in a bear market thanin a bull market. In addition, Henry (2009) and───────────
１ In section 2, we will introduce the differences
between China and developed countries indetail.

２

中国経済研究第９巻第２号

stock market in China as it does in otherasymmetric reactions of China s stock market

nations. Addressing these questions is very

to other economic indicators.

important for both the Chinese government

After dividing China s stock market into
regimes, we move to the second stage of thisand investors.
We employ a two‑step process to answer

study, which explains the specialized asymmet-these questions. The first of these steps is to

ric effects of monetary policy shocks observed

identify China s stock market regimes. We

in the Chinese stock market. In this investiga-

adopt a Markov Regime Switching model totive phase, event study methodology (Bernanke

distinguish between market regimes, as theand Kuttner (2005)) is applied. We find that

Markov model is the most famous and widely

monetary policy shocks do not have significant-used method for determining distinct categories

ly negative impacts on the stock return either

that encompass various market scenariosin the Bull Market regime or No‑Market‑(Hamilton (1989)). In accordance with traditio-

Regime‑Division data as a whole. However, a

nal classifications, stock market performance

significant negative relation between monetaryin developed countries can generally bepolicy shocks and stock return does exist in

divided into Bull Market (higher mean, lower

both the Bear and Volatility Market regimes.

variance２) and Bear Market (lower mean,

Overall, this paper s main contribution canhigher variance) conditions (Chen (2007) andbe divided into two aspects, the first of which

Henry (2009)). However, China s market doesis the aforementioned division of China s stock

not display this type of structure. In China,

market regimes. We explain that China s stock

higher average variance of the market ismarket should be divided into three regimes

typically correlated with the highest andrather than two regimes. We also analyze thelowestByreasons underlying these regime divisions andcontrast, a lower market variance corresponds

demonstrate the differences between theto intermediate values of the mean return.

Chinese and U.S. markets. This paper s

Thus, we capture the specialized character offindings regarding regime division provide

China s stock market by dividing this market

indications that it would be incorrect tointo three regimes: Bull Market (highest mean,

directly apply developed countries

intermediatemarket experiences to analyses of China s

mean

stock

marketvariance),

returns.

Volatility

Market(intermediate mean, lowest variance) and Bearvariance)３.

stock

stock market.

We

Secondly, this paper finds that China s

then classify time periods from 1997 to 2011

official interest rate shocks also produce

into these three regimes, a categorization thatasymmetric impacts on stock market return.

not only is useful for us but may also prove

However, these types of asymmetric effects

valuable to researchers investigating theare different from those observed in the U.S. or───────────
２ The mean of the stock market is the average
return of the stock market, and the variance ofthe stock market is always a measure ofmarket risk.
３ The paper will explain this regime division
for China in details in section 3.

other developed countries. In the U.S., theMarket (lowest mean, highest

asymmetric effects cause interest rate shocks
to always negatively affect the market, butthese effects are larger in the Bear Market
than in the Bull Market. By contrast, in China,
interest rate shocks do not always negatively

Asymmetric Effects of Monetary Policy Shocks on Stock Markets:
An Empirical Test for China３

affect the stock market; in particular, ahave reached 16.9 trillion and 8.4 trillion RMB,

negative relationship can only be confirmed in

respectively.

Bear Market and Volatility Market, whereas a

As China represents the world s largest

nonnegative reaction occurs in the Bullemerging market, Chinese stock markets

Market. Therefore, the impact of interest rate

possess many specific characteristics andshocks demonstrates more obvious asymmet-

drawbacks. First, Laurence, Cai and Qiang

ries between Bull Markets and Bear or(1997), Lee and Rui (2000) and Lee Chen, andVolatility markets in China than in the U.S.

Rui (2001) indicated that Chinese stock

The remainder of the paper is structured as

markets are weak‑form efficient４. This weak‑follows. Section 2 presents several characteris-form efficiency likely results from information

tics of China s stock market, monetary policy

asymmetry (Long, Payne and Feng (1999)). In

and the data used in this study. Section 3

addition, Chen et al. (2010) argued that China s

specifies the basic models of Markov Regime

markets are difficult to predict and that only

Switching and the identification of China s

five firm‑specific variables have been shownstock market regimes (Bull, Volatility, andto be significant in Chinese markets. Lee andBear). Section 4 demonstrates asymmetricRui (2001), Lee, Chen and Rui (2001) demonstra-effects from China s monetary policy shocks

ted that China s markets feature no relation-

on its stock market performance. Section 5

ship between risk and return. Overall, China s

tests subsample data to establish the robust-

stock markets are large, inefficient, and almost

ness of the study s conclusions. Section 6

unpredictable, differing in many ways fromextends this robustness check by controllingmarkets in the U.S. and other developed

for firm‑ and industry‑specific effects. Finally,

countries.

the conclusions and policy implications are
summarized in Section 7.

Although China has two stock exchange
markets, investors and financial institutions

２ China s Stock Markets, Monetary Policy
and Data
２．
１ China s Stock Markets

generally devote greater attention to the
Shanghai Stock Exchange Market index,
largely because China s larger and moremature companies are almost exclusively

China has two stock exchange markets, thelisted on the Shanghai Stock Exchange Market,

Shanghai Stock Exchange Market and thewhereas small and medium‑sized enterprises

Shenzhen Stock Exchange Market. The Shang-

are listed on the Shenzhen Stock Exchange

hai Stock Exchange Market was established on

Market. As a result, the market value ofNovember 26th, 1990, and opened on December

Shanghai s market is also much larger than

19ththat of Shenzhen s market, with a ratioof the same year. The Shenzhen Stock
3rdof

between the two values of nearly 2:1.

the following year. As a result of the past

Therefore, this paper primarily addresses thetwenty years of development, 949 companies

behavior of the Shanghai Stock Exchange

Exchange Market was opened on July

are

now

listedonthe

ShanghaiStock

Exchange Market, and 1378 companies arelisted on the Shenzhen market. The market
values of the Shanghai and Shenzen markets───────────
４ A weak‑form efficient market generally
implies that the stock market cannot reflect
macroeconomic conditions.

４

中国経済研究第９巻第２号

Market. Fig. 1 describes the Shanghai Stockcredit plan for bank lending as the primary

Exchange Composite Index. This figure makes

monetary policy instrument. This situation

it clear that China s stock market index does

continued until the PBC replaced the credit

not show long‑run growth character, however,plan with the creation of a deposit reserve

it frequently demonstrates volatility levels thatsystem that featured a required ratio for the

do not correlate with China s sustainablerefinancing of banks. Subsequently, the PBC

economic growth.

began utilizing market methods to implement

Fig. 1: China s Stock Exchange Composite
Index

monetary policy, and open market operations
have become one of the main monetary policy
levers in China.
The PBC has long claimed that

The

monetary policy instruments applied by the
PBC include reserve requirement ratio, central
bank base interest rate, rediscounting, central
bank lending, open market operation and otherpolicy instruments specified by the StateCouncil .

This

paper

follows

traditional

methods in considering interest rates to be theprimary lever of monetary policy５. Among thevarious interest rates available, we choose
China s official deposit and loan rates as
２．
２ China s Monetary Policy
Under its highly planned economic system,
China initially had no true central bank.
However, this situation changed in 1984, when
the People s Bank of China (PBC) became thecentral bank and started to play an importantrole in fine‑tuning economic activities. Between
1984 and 1994, the main objectives of the PBC
were to stimulate economic growth and tomaintainstabilityincommodity

prices.

However, after the outbreak of three serious
inflation events during this period, the PBC
revised its policy goals in 1995 to make thecontrol of inflation its major priority. This shiftof the PBC s main objectives coincided withchanges in China s main monetary policy
instruments. Variations in interest rates havealways been the monetary policy instruments
in China. When beginning to implement
economic reforms, China initially adopted a

Fig. 2: Official Deposit Rate and Loan Rate
ChangesAsymmetric Effects of Monetary Policy Shocks on Stock Markets:
An Empirical Test for China

５indicative of monetary policy. Fig. 2 shows the

The firm‑level data indicate the Tobin s q

deposit and loan rates for different maturity

ratio, cash flow to income ratio, price‑earnings

times.

ratio, debt‑to‑total‑capital ratio, and market
value of each individual firm. The industry‑２．
３ Datalevel data differentiate between the industries

The paper utilizes Shanghai Stock Exchangeof agriculture, mining, manufacturing,

Composite Index data, individual firms stock

electricity, building, transport, IT, retail,return data, deposit rate data, loan rate data,

finance, real estate, social service, and culture.

firm‑level data and industry‑level data. The

The classification of industries is based upon

Markov Regime Switching model will use thethe rules of the China Securities Regulatory

Shanghai Stock Exchange Composite Index

Commission (CSRC). Both firm‑ and industry‑data and it is from January 2nd, 1997 to Augustlevel data are collected from the China Center

16th,

for Economic Research (CCER) Database.

2011. In addition, individual firms stock

return data, deposit rate data, loan rate data,
firm‑level data and industry‑level data areused in event study model. The full sample
period of these data contains 1035 days fromJanuary

1st,

31st,

３ The Identification of China s Stock Market
Regimes (Bull, Volatility, and Bear)
３．
１ Methodology of Market Regime Divisions

2010.

The paper adopts the widely used Markov

Although the data used in Markov model has

Regime Switching model to identify market

different length with the data used in event

regimes. Hamilton (1989) presented the Markov

study model, it will not affect the empirical

Regime Switching model to describe theresult. Because the Stock Exchange Compositechanges in regime for time series data. The

Index data is just used to divide the market

Markov Regime Switching model describes

regimes, it is independent with the event study

probabilistic inference in the form of adata.

nonlinear iterative filter, and this filter,1997 to December

Data regarding the Shanghai Stock Exchange

together with its smoothed filter probabilities,

Composite Index, individual firm stock returns,

can be estimated by the maximum likelihood

loan rates, and deposit rates are collected frommethod. The Markov Regime Switching model

the Wind Information Database. During theof China s stock returns can be shown:

period investigated, the deposit rate changed
20 times and the loan rate changed on 22(3.1)６

occasions. The sample incorporates a total of
14486 observations.
───────────
５ Although the China s monetary policy does
not merely indicate official interest rates, thispaper only adopts the official interest rates, inaccordance with Bernanke and Kuttner (2005).
The effect of other monetary policy tools, suchas changes in the monetary supply, will betested using certain other empirical models (butnot event study) in our future research papers.

where

denotes China s stock market

return andidentifies different stock market

regimes. In this paper, we assumed that───────────
６ The stock return in our paper is calculatedusing the equation
value is nearly equalin several other papers.

to, and itsthat given by, which is used

６

中国経済研究第９巻第２号

indicated the Bull Market, Volatility

However, in the next regime, P1 will no longer

Market, and Bear Market regimes, respectively;

be greater, as P1 will have decreased and one

in addition,of the other probabilities will have increased.

dependent

and
mean

represent the state‑andvariance

respectively, whereasof,This equivalence point (where P1 is equal toinnovatively follows

one of the other probabilities) is defined as thethe student s t‑distribution (Hamilton andend of the Bull Market and the start of anotherSusmel (1994)). The model can thus be written

regime. We will follow this rule to divide all

separately:

periods into different regimes.
(3.2)

３．
２ The Choice between Two and Three
Market Regimes(3.3)

Based on the Markov Regime Switchingmodel (Hamilton (1989)), we construct Markov(3.4)

Regime Switching models for Chinese stock

Additionally, China s stock returns have thereturns (equation (3.1) to (3.7)). When applying

following transition probability matrix:

the Markov s models to Chinese data, wefound that we should not divide China s stock

,

(3.5)

market performance into two regimes, as is
typically performed for markets in the U.S. orother developed countries. However, it iswherereasonable to divide China s stock market
performance

into

three

regimes.

Fig. 3

describes the smoothed probabilities if we only
(3.6)

divide Chinese market conditions into two

Based on Hamilton s calculation method, we

regimes. These two smoothed probabilities

can obtain the smoothed probability for eachcannot model China s real market situation

state:

well. For example, during the years between
2006 and 2009, the smoothed probabilities ofregime two in Fig. 3 are much higher than theprobabilities of the other regime, nearly(3.7)

reaching one at times. This high regime

We then divide the market into regimes by

probability would indicate that the stockcomparing P1, P2 and P3. For the initial regime,

market remains in a similar state during thisthe division is simply determined by the value

time interval. However, from Fig. 1, we canof smoothed probability. However, in the next

observe that the stock index first increased

several regimes, the state periods start at thegreatly and then decreased sharply between

equivalencethree2006 and 2009, belying the notion that its state

probabilities and end at the next equivalence

was unchanged during this period. Thus, it ispoint for each probability. For example, if theclear that considering the stock market from afirst stage is considered to be a Bull Market, P1

two‑regime perspective may not adequately

will be greater than P2 and P3 at this period.

model real economic data.

point

of

two

of

the

Asymmetric Effects of Monetary Policy Shocks on Stock Markets:
An Empirical Test for China

７

Fortunately, when we divide China s market

this three‑regime division. From Fig. 4, we caninto three regimes, we find that the three‑observe that the first smoothed probability

regime division matches the real situation well.

(the first picture) is greatest during the periods

Fig. 4 describes the smoothed probabilities ofwhen the stock market sharply increases andFig. 3: Smoothed Probabilities of Two‑Regime‑Division

Fig. 4: Smoothed Probabilities of Three‑Regime‑Division

８

中国経済研究第９巻第２号the third probability (the third picture) isand the lower mean ( =0.0003) corresponds togreatest during the periods when the stock

lower variance ( =0.000088). By contrast, themarketsecondU.S. market evinces completely different

probability (the second picture) accurately

features, with higher mean corresponding to

depicts times when the stock market moves

lower variance and lower mean corresponding

up and down. Therefore, it appears reasonable

to higher variance.

sharply

decreases.

The

to divide China s stock market into three
regimes.

The third column in Table 1 depicts China s
three market regimes. Based on this regime
division

method,China sstock

market３．
３ Why China s Stock Market Does Not

incorporates three risk‑return combinations:Show the U.S. s Two-Regime Character

Bull Market (highest mean, intermediate

When applying the Markov models to China s

variance), Volatility Market (intermediate mean,data, we found that Chinese market structure

lowest variance) and Bear Market (lowest

differs greatly from the market structuremean,found in the U.S. To explain China s regime

combinations display the same characteristics

divisions, we compare China s market regimes

as regimes of the U.S. market.

with the U.S. market regimes. Table 1 depicts
the results of this comparison.

highestvariance).

Two

of

these

The question remains of why the Chinese
market possesses similar characteristics to the

If the Chinese market is divided into two

U.S. markets in a three‑regime division, but

regimes, the higher mean ( =0.0015) is found to

appears to behave totally differently in a two‑correspond with higher variance ( =0.000436),

regime division. The main reason for thisTable 1: Comparison between China s Market Regimes with the U.S. Regimes
China s Market

The U.S. Market

Two Regimes

Three Regimes

Two Regimes

Three Regimes

0.0015＊＊0.0066＊＊＊0.0006＊＊＊（0.0007）（0.0010）（0.0001）

0.0008＊＊＊（0.0003）0.0003（0.0002）−0.0002（0.0003）0.0001（0.0003）0.0005＊＊＊（0.0002）−0.0021＊（0.0013）−0.0011（0.0007）0.000436＊＊＊（0.0000）

0.000143＊＊＊（0.0000）

0.000027＊＊＊（0.0000）

0.000090＊＊＊（0.0000）

0.000088＊＊＊（0.0000）

0.000089＊＊＊（0.0000）

0.000126＊＊＊（0.0000）

0.000024＊＊＊（0.0000）

0.000574＊＊＊（0.0001）

0.000238＊＊＊（0.0000）

0.98

0.94

1.00

0.99

0.99

0.99

1.00

1.00

9867.6666

9900.7528

11557.3616

11614.8593

0.94
LogLik0.98

Notes: the number in parentheses is stand error, ＊,＊＊ and ＊＊＊ indicate 10%, 5% and 1% levels ofsignificance, respectively.

Asymmetric Effects of Monetary Policy Shocks on Stock Markets:
An Empirical Test for China

９

phenomenon is that in the long term, China s

division classifies the basic volatility state as

market shows volatility, whereas the U.S.

themarket demonstrates growth. If we adopt

combination of booming state and slump state

Markov s model to these two markets, theas higher mean and higher variance. However,Markov method will first set volatility as theif we divide China s market into three regimes,

Chinese market s basic status and growth as

the model can separate the booming state andthe basic status for the U.S. market, thenslump

compare the status of other periods with thisintermediate variance category and a lowest

basic status. Thus, the U.S. market s growthmeanstatus is higher return and lower variance, andrespectively.

lower

state
and

variance

intoahighestconditionhigherandmeanvariancetheandcategory,

the other state must necessarily be lower
return and higher variance. However, for

３．
４ The Identification of China s Stock Market
Regimes

China s market, the basic volatility status does
not

show

growth,butratherindicates

After dividing China s market into threefluctuations within an interval. If we divide

regimes, Hamilton s Markov Regime Switching

China s market into only two regimes bymodel offers a very accurate way to present

comparing other periods with this volatility

these three market regimes; namely, it canstate, booming and slump states will becalculate the smoothed probability for eachbracketed together because both booming andday. For example, the probability of a Bull

slump states differ sufficiently from theMarket on January 2nd, 1997 is approximately

volatile state. In addition, the period of the

50%, and, the probabilities for a Volatility

booming state is also longer than that of theMarket or a Bear Market are estimated at 45%

slump state; therefore, on the whole, mean

and 5%, respectively. The stock market regime

returns from the booming state will overwhelm

on January 2nd, 1997 is therefore defined as areturns from the slump state when these

Bull Market. We calculate the daily smoothedstates are grouped. Thus, the two‑regime

probabilities of all three regimes from January

Table 2: Details of Division of Market Regimes
Time

Duration

Change Rate of Return

Bull Market

1997.01.02‑‑‑1997.05.07

4 Months+63.08%（Highest Mean, Media

1999.05.21‑‑‑2000.04.19

11 Months+56.57%

Variance）

2006.04.03‑‑‑2008.01.15

22 Months+312.96%

Mean: 0.0066

2008.11.26‑‑‑2010.01.07

13 Months+67.99%Volatility Market

1997.10.31‑‑‑1999.05.20

19 Months−1.58%（Media Mean, Lowest

2000.04.20‑‑‑2001.07.23

15 Months−15.20%

Variance）

2002.03.21‑‑‑2006.03.31

48 Months−22.59%

Mean: −0.0002

2010.01.08‑‑‑2011.08.16

20 Months−22.18%Bear Market

1997.05.08‑‑‑1997.10.30

6 Months−16.00%（Lowest Mean, Highest

2001.07.24‑‑‑2002.03.20

8 Months−21.36%

Variance）

2008.01.16‑‑‑2008.11.25

10 Months−65.28%

Mean: −0.0021

１０

中国経済研究2nd, 1997 to August 16th, 2011 and present themin Fig. 4. Based on these results, China s stock
market (the Shanghai Stock Exchange Market)
performance can be classified into 4 Bull

第９巻第２号

４ The Asymmetrical Impact of Monetary
Policy Shocks on the Stock Market
４．
１ The Simple Event Study Model

Market periods, 4 Volatility Market periods,

The widely used methodology we employ toand 3 Bear Market periods during 1997 toinvestigate the relationship between monetary

2011. These divisions of market performancepolicy and stock market performance is theare listed in table 2.

event study model initially introduced by

Table 2 represents our definition for

Bernanke and Kuttner (2005). We first define

different regimes. The main characteristics ofthe relevant sample of events as the days on

the Bull Market are the highest mean andwhich the PBC announced adjustments to theintermediate variance. Moreover, the stock

official interest rates between 1997 and 2010.

returns increase dramatically within a short

We then include all individual companies listed

time, such as returns of +312.96% in only 22

on the Shanghai Stock Exchange Market as

months. In contrast, the Bear Market has thepart of the data sample by determining stock

lowest mean and highest variance. The Bear

returns for all of these individual firms afterMarket accompanies sharp declines in returnchanges in China s official interest rates. As

within a short time, such as returns of −65.28%

suggested by Ehrmann and Fratzscher (2004),

in only 10 months. Compared with the twothis method can enlarge the data sample toregimes mentioned above, the Volatility Market

satisfy the demand for large sample statistics.

is characterized as possessing an intermediate

According to this method, our total sample size

mean and the lowest variance. That is, thisreaches nearly 13800, and each regime s

regime is revealed to exhibit low volatility andsubsample size is larger than one thousand.

declines in return of intermediate magnitude.

The simple event study model can be

The results of China s stock market regime

expressed as follows:

divisions in Table 2 contribute to the field of(4.1)

investigating asymmetric effects within China s(4.2)

stock market.７
whereis the stock return of firm i inmarket regime

and the values ofrepresent No‑Market‑Regime‑Division, Bull
Market regime, Volatility Market regime, andBear Market regime, respectively８. In this───────────
７ There are many methods of defining market
regimes. This paper s contribution is to indicatethat we could not effectively use the two‑
regime definition that is typically employed todescribe U.S. markets because the division ofChina s market performance into two regimes
does not correspond well to real economic data.
However, it should be noted that market
regime divisions are not unique.

case,

and

denote official deposit

rate change and official loan rate change,
respectively.
───────────
８ The No‑Market‑Regime‑Division data include the entirety of the data without regimes
divisions; thus, it contains all bull, volatility andbear market data.

Asymmetric Effects of Monetary Policy Shocks on Stock Markets:
An Empirical Test for China

Both

and

１
１

are nominal values,

as complex and continuous processes thatbut not real values. Nominal values are usedcannot be defined as macroeconomic shocks

becauseor monetary policy shocks .

weemploy

the

event

study

methodology (Bernanke and Kuttner (2005))

The empirical results from the simple event

and wish to test how changes in the

study model are illustrated in Table 3 andmacroeconomic indicator immediately (theTable 4. Table 3 represents the effects ofnext day) affect the stock market. Generally,monetary policy shocks on individual stockchanges in real interest rates result from long

returns for No‑Market‑Regime‑Division data,and subtle developments and are thus much

and Table 4 depicts the results from the data

more difficult to track than theshock ofof each of the three market regime divisions

nominal interest rate changes. Therefore, we

identified earlier. From Table 3, the estimatescannot accurately define the time of realofinterest rate changes, which should be viewed

values that are approximately 0.02, implying

andare significant and positive

Table 3: The Results of Simple Event Model (No‑Market‑Regime‑Division)
Deposit Rate (One Year)

Deposit Rate (Three Years)

Deposit Rate (Five Years)C−8.86E-05（−0.0123）−0.0029（−0.4087）−0.0030（−0.4266）

Official Rate Change

0.0417＊＊＊（3.3134）

0.0295＊＊＊（2.7527）

0.0266＊＊＊（2.7511）

Adjust-R2

0.00070.00050.0005

Loan Rate (One Year)

Loan Rate (Three Years)

Loan Rate (Five Years)

C−0.0004（−0.0553）−8.18E-05（−0.0119）0.0006（0.0924）

Official Rate Change

0.0277＊＊（1.9614）0.0242＊（1.9544）0.0281＊＊（2.4767）

Adjust-R2

0.00020.00020.0004

Notes: the number in parentheses is t‑value, ＊,＊＊ and ＊＊＊ indicate 10%, 5% and 1% levels ofsignificance, respectively.
Table 4: The Results of Simple Event Model (Three‑Regime‑Division)
Deposit Rate （One Year）
Bull

Volatility

Bear

Deposit Rate （Three Years）
Bull

Volatility

Bear

Deposit Rate （Five Years）
Bull

Volatility

Bear

C

0.0033（0.2528）−0.0053＊＊＊−0.0305＊＊＊（−12.2464） （−27.4371）

0.0014（0.1050）−0.0033＊＊＊−0.0287＊＊＊（−7.4947） （−26.4639）

0.0020（0.1533）−0.0031＊＊＊−0.0273＊＊＊（−6.8490） （−25.8038）

Official
Rate
Change0.0782＊＊＊（3.4366）−0.0196＊＊＊−0.0193＊＊＊（−20.2611） （−12.4062）

0.0701＊＊＊（3.2195）−0.0110＊＊＊−0.0142＊＊＊（−16.3923） （−10.6725）

0.0643＊＊＊（3.2363）−0.0098＊＊＊−0.0108＊＊＊（−16.0081） （−9.3455）

Adjust‑R2

0.00140.09980.0550Loan Rate （One Year）
Bull

Volatility

Bear0.00120.0676

0.0412

Loan Rate （Three Years）
Bull

Volatility

Bear0.00130.0646

0.0318

Loan Rate （Five Years）
Bull

Volatility

Bear

C

0.0025（0.2095）−0.0059＊＊＊−0.0428＊＊＊（−13.4996） （−34.3805）

0.0038（0.3159）−0.0062＊＊＊−0.0369＊＊＊（−13.9588） （−31.2129）

0.0044（0.3662）−0.0060＊＊＊−0.0353＊＊＊（−13.5608） （−30.9292）

Official
Rate
Change0.0670**（2.4016）−0.0181＊＊＊−0.0436＊＊＊（−20.2768） （−22.1768）

0.0738＊＊＊（2.7172）−0.0120＊＊＊−0.0316＊＊＊（−18.3497） （−17.9906）

0.0805＊＊＊（3.3050）−0.0107＊＊＊−0.0269＊＊＊（−17.6409） （−17.3195）

Adjust-R2

0.0006

0.09990.15740.00080.08320.10940.00120.07750.1022

Notes: the number in parentheses is t‑value, ＊,＊＊ and ＊＊＊ indicate 10%, 5% and 1% levels ofsignificance, respectively.

１２

中国経済研究第９巻第２号

that a 100‑basis‑point increase in the interest

regimes but only ‑0.0181 during Volatility

rate will cause stock returns to increase byMarket regimes.

0.02. However, in the U.S., an unanticipatedThus, it is clear that the impacts of

100‑basis‑point increase in the federal funds

monetary policy shocks on the stock market

rate target is associated with a 0.04 decrease inshow enormous differences between a Bull

broad stock indexes. This result shows that on

Market regime and Volatility or Bear Market

the whole, monetary policy shocks have aregimes. The results from Volatility or Bearnonnegative impact on stock returns in China,

Market regimes are similar to the results

which is markedly different from the results

obtained from markets in developed countries,

noted for the U.S. markets.

whereas the impact of monetary policy shocks

The question of how to explain this curious

during a Bull Market regime is very muchphenomenon poses a thorny problem. To

distinct from the impact noted in the U.S. or

address this issue, we first need to analyze the

U.K. markets. In particular, monetary policy

asymmetric effects of monetary policy shocks

changes negatively affect stock returns during

on stock markets in China. The detailed results

Volatility or Bear Market regimes, but notregardingareduring a Bull Market regime. In addition, half

provided in Table 4. The statistical estimatesthese

asymmetriceffectsof the monetary policy changes in China

based upon Bull Market conditions demonstrateduring the examined time period occurredsignificant and positive responses of market

during a Bull Market period (interest rates

returns to monetary policy shocks, a verychanged 10 times during Bull Market regimes).

similar conclusion to that obtained from theThis situation will cause the results from the

No‑Market‑Regime‑Division data as a whole.

overall No‑Market‑Regime‑Division data to

In particular, both coefficient

be similar to results from a Bull Market, with aandare significant near 0.07. This indicates that

nonnegative relationship between monetary

monetary policy changes do not negatively

policy shocks and stock returns. Therefore, we

affect the stock market during the Bull Market

conclude that China s stock market

regime. However, the estimated coefficientsdemonstrates asymmetric effects of monetaryduring Volatility or Bear Market regimes

policy shocks on stock returns in the threedemonstrate a very different pattern, as all ofdifferent market regimes specified earlier, andthe estimates of, andthese asymmetric effects cause a generally

are negative and significant. This result

nonnegative reaction of China s stock market

suggests that monetary policy shocks can

as a whole to monetary policy changes, which

produce a meaningful negative influence on

differs greatly from stock market reactions

stock market returns in the Volatility and Bearobserved in developed countries.

,,

Market regimes. Furthermore, we find that

However, this simple event study model

monetary policy shocks, particularly loan rate

may be contaminated by serious endogenous

shocks, produce much more negative impacts

problems, as suggested by Bernanke andon the stock returns during Bear Market

Kuttner (2005) and Honda and Kuroki (2006);

regimes than during Volatility Market regimes;

therefore, we adopt the specified event study

for example, the estimated coefficient for themodel and subsample methodology discussed

one‑year loan rate is ‑0.0436 for Bear Market

in the next two sections to correct for potential

Asymmetric Effects of Monetary Policy Shocks on Stock Markets:
An Empirical Test for China

１
３

Event Study model is expressed as follows:

endogenous problems.
４．
２ The Specified Event Study Model(4.3)

We find asymmetric effects of monetary
policy shock on stock market in China and(4.4)

predict that these asymmetric effects may
cause

no

negative

relationshipbetweenwhere

is a dummy variable of CPI ormonetary policy and stock returns for the No‑

IPI in market regime

Market‑Regime‑Division case. However, this

there is a CPI or IPI announcement duringconclusion may not hold true because of

event periods and 0 otherwise; similarly,

endogenous problems within our empiricalrepresents a dummy variable of IP in market

models. In this section, we therefore follow

regimeHonda and Kuroki s (2006) logical setup andannouncement happens during event periods

construct a specified event study model toand is 0 otherwise.

control for endogenous issues.

, which equals 1 when

, which takes the value of 1 if IP

Table 5 reveals that the variables of CPI and

In general, event periods include days on

IP have significant impact on the stock returns

which macroeconomic news beyond interestof No‑Market‑Regime‑Division data. In addi-

rate changes is also announced, a situation thattion, Table 6 shows that these two economic

creates endogenous problems. We therefore

indicators also significantly influence the stock

assessed whether the event periods considered

returns in each of the three regimes. It isin this study were associated with macroecono-

reasonable to control for changes in these two

mic news. Note that we define all economic

macroeconomic variables to avoid estimation

news announcements occurring near an interest

bias, especially as the PBC has prominently

rate change event day asassociated ,mentioned that controlling inflation is its

regardless of whether the announcements

primary task. After controlling for macroecono-

actually fall on, before, or after the day of the

mic news, however, the core empirical results

event in question. China s macroeconomic

shown in Table 5 and Table 6 remain the samenews or indicators are primarily announced byas in the simple event study model. In

the National Bureau of Statistics of China.

particular,

Every year, the National Bureau of Statistics ofcontinue to display no negative correlation to

China summarizes a schedule of economic

the stock market returns for either the No‑

statistical information. We summarize theMarket‑Regime‑Division

economic news that is released during each of

regime samples, but significant and negative

the event periods based on this schedule. The

effects on stock returns from monetary policy

economic news that may create endogenous

shocks are still observed during Volatility andproblems relates to Industrial Production (IP),Bear Market regimes.

official

interest

or

rate

Bull

changesMarketthe Consumer Price Index (CPI), and/or the

The difference between these two types ofIndustrial Price Index (IPI). However, IPI ismodels is that the specified event study models

always announced on the same day as CPI;

improve the adjusted R2 value. The average

thus, we chose the same dummy variable toadjusted R2 value for the whole sample casemeasure CPI and IPI. The resulting Specified

examined in Table 5 is approximately 0.0008,

１４中国経済研究第９巻第２号

Table 5： Test for Endogenity （Specified Event Study Model, No‑Market‑Regime‑Division）
Deposit Rate （One Year） Deposit Rate （Three Years） Deposit Rate （Five Years）
C−0.0016（−0.1885）−0.0032（−0.3721）−0.0033（−0.3834）

Official Rate Change

0.0404＊＊＊（3.1978）0.0291＊＊＊（2.7109）

0.0260＊＊＊（2.6845）CPI

0.0448＊＊（2.3917）0.0448＊＊（2.3928）0.0443＊＊（2.3662）IP−0.0254（−1.5454）−0.0294＊（−1.7942）−0.0292＊（−1.7836）

Adjustt-R2

0.00100.00080.0008

Loan Rate （One Year）

Loan Rate （Three Years）

Loan Rate （Five Years）

C−0.0003（−0.0414）

0.0005（0.0654）0.0009（0.1065）

Official Rate Change

0.0275＊（1.9421）0.0252＊（2.0265）

0.0287＊＊（2.5235）CPI

0.0449＊＊（2.4534）

0.0451＊＊（2.4666）

0.0456＊＊（2.4931）IP−0.0306＊（−1.9181）−0.0324＊（−2.0376）−0.0314＊（−1.9765）

Adjustt-R2

0.00060.00060.0008Notes: the number in parentheses is t-value, ＊,＊＊ and ＊＊＊ indicate 10%, 5% and 1% levels ofsignificance, respectively.
Table 6: Test for Endogenity （Specified Event Study Model, Three-Regime-Division）
Deposit Rate （One Year）
Bull

Volatility

Bear

Deposit Rate （Three Years）
Bull

Volatility

Bear

Deposit Rate （Five Years）
Bull

Volatility

Bear

C

0.0069（0.4539）−0.0110＊＊＊−0.0712＊＊＊（−22.0276） （−60.4505）

0.0053（0.3532）−0.0093＊＊＊−0.0700＊＊＊（−18.3746） （−62.5850）

0.0055（0.3618）−0.0088＊＊＊−0.0693＊＊＊（−17.4030） （−63.9197）

Official
Rate
Change0.0682＊＊＊（2.8546）-0.0266＊＊＊-0.0197＊＊＊（-26.2923） （-13.3626）

0.0605＊＊＊（2.6677）-0.0154＊＊＊-0.0152＊＊＊（-23.0972） （-13.3626）

0.0554＊＊＊（2.6721）-0.0138＊＊＊-0.0124＊＊＊（-22.5240） （-13.3626）

CPI

0.0269（0.6270）0.0202＊＊＊（12.0221）

0.0401＊＊＊（27.6283）

0.0305（0.7131）0.0096＊＊＊（6.0383）

0.0428＊＊＊（32.2390）

0.0317（0.7432）

0.0098＊＊＊（6.1679）

0.04457＊＊＊（35.2961）

IP-0.0424（-1.1588）

0.0026＊（1.8632）

0.0466＊＊＊（34.5855）-0.0458（-1.2565）

0.0128＊＊＊（9.2974）

0.0452＊＊＊（35.0955）-0.0441（-1.2047）

0.0124＊＊＊（8.9378）0.0443＊＊＊（35.3593）

Adjust-R2

0.00140.20440.60200.00130.17470.60200.00130.16950.6020Loan Rate （One Year）
Bull

Volatility

Bear

Loan Rate （Three Years）
Bull

Volatility

Bear

Loan Rate （Five Years）
Bull

Volatility

Bear

C

0.0106（0.7759）-0.0113＊＊＊-0.0750（-22.6227） （-54.2047）

0.0115（0.8353）-0.0123＊＊＊-0.0729（-23.6069） （-57.6148）

0.0099（0.7261）-0.0124＊＊＊-0.0720＊＊＊（-23.6519） （-59.2092）

Official
Rate
Change0.0615＊＊（2.1602）-0.0266＊＊＊-0.0335（-26.8191） （-13.3626）

0.0663＊＊（2.3850）-0.0149＊＊＊-0.0257（-23.1087） （-13.3626）

0.0697＊＊＊（2.7642）-0.0136＊＊＊-0.0223＊＊＊（-22.7830） （-13.3626）

CPI

0.0249（0.6048）0.0274＊＊＊（15.2500）

0.0311（15.8804）

0.0228（0.5529）0.0099＊＊＊（6.2159）

0.0355（20.9183）

0.0234（0.5706）

0.0067＊＊＊（4.2798）

0.03609＊＊＊（21.7266）

IP-0.0708＊＊＊（-2.0972）-0.0043＊＊＊（-2.8692）

0.0466（34.5855）-0.0672＊＊（-1.9879）

0.0105＊＊＊（7.6150）

0.0466（34.5855）-0.0540（-1.5734）

0.0135＊＊＊（9.7770）0.04655＊＊＊（34.5855）

Adjust-R2

0.00100.20940.60200.00110.17480.60200.00130.17180.6020Notes: the number in parentheses is t-value, ＊,＊＊ and ＊＊＊ indicate 10%, 5% and 1% levels ofsignificance, respectively.
whereas this value is only 0.0004 in Table 3 forof these numbers are very small, the increase

the simple event study model. Although bothin adjusted R2 also suggests that specified

Asymmetric Effects of Monetary Policy Shocks on Stock Markets:
An Empirical Test for China

１５event study models have certain advantages

The subsample estimates for the simple

when estimating the relationship between

event study models allow us to obtain verymonetary policy and stock returns. Overall,similar conclusions as those reached in the

however, based on these preferred specified

previous section, which indicates the robustness

event study models, we also reach theof our main argument. In particular, we findconclusion that China s stock returns react tothat the coefficients of monetary policy shockmonetary policy shocks asymmetrically, as

in the subsample become slightly smaller thanmonetary policy negatively affects the stockin the models generated for the whole sample.

market to a much larger degree in Volatility or

For instance, the estimation ofBear Market regimes than in Bull Market

year deposit for the whole sample is 0.0417, but

regimes. These asymmetrical effects result inthis value decreases to 0.034 for the subsample.

no significant negative response for the overall

The average values ofstock returns (the No‑Market‑Regime‑

decreases from approximately 0.03 in the fullDivision data) in China to monetary policy

sample to 0.02 in the subsample. Although theshocks.

values obtained from the subsample do not

５ Endogenous Problems and Subsample
Stabilityof one‑anddiffer greatly from those obtained using theentire sample, the presence of an effect stillsuggests that the holiday news may affect theWe have already mentioned one of thestock market, and the subsample method is

endogenous problems that can arise inthus preferred to the method using the entire

empirical models and the resolution to thissample.

concern, namely, the specified event study

When comparing the specialized event

model. However, another endogenous issue

study model s results from the whole sample

may arise because of the great length of theand the subsample, it should be noted that theevent periods examined in this study. Whenspecialized event study model for the subsample

we examine data for China s monetary policy

does not include the variable of CPI in both thechanges, we find that China s official interest

Bull and Bear Market regimes. The reason for

rates frequently change just before holidays,

this change is that CPI announcements in Bull

and certain macroeconomic or other relevant

and Bear Markets always occurred during

news are announced during holidays, when theholidays, and these data are all excluded fromstock market is not open. Therefore, if wethe subsample. Thus, it suffices to include only

include the interest rate change events that

the IP as a dummy variable in the specialized

happened just before holidays, the empiricalevent study model for the subsample. However,results obtained may be disrupted by othereven though we make these small changes toeconomic or social events that occurred during

the model s form, the subsample model

the holiday in question. Thus, we consider

produces the same fundamental conclusions asconstructing a subsample to exclude the eightthe models detailed in the previous section.

interest rate changes announced just before

The values ofholidays from our sample. Based on thisboth the specified event study model and thesubsample, we estimate both the simple andsimple event study model when considering

specialized event study models.

only subsample data. Moreover, monetaryanddecrease in

１
６

中国経済研究第９巻第２号

policy shocks produce less significant impacts

empirical results after controlling for industry‑on the stock returns in both the Bull Market

specific effects in the specialized event study

Regime and the overall No‑Market‑Regime‑

models. All of these empirical results indicate

Division conditions when using only subsample

that our main conclusion is robust. In particular,

data. However, we still obtain the conclusion

the estimates of the effect of monetary policythat monetary policy negatively affects theshocks on stock returns remain nonnegative atstock market to a much greater extent inapproximately 0.03 when considering No‑

Volatility or Bear Market regimes than in Bull

Market‑Regime‑Division data, and in thisMarket regimes. Based on subsample

case, the coefficients of

estimates, we have succeeded in addressing

remain nonnegative, with values between 0.06

the endogenous problems in a new way andand 0.08. Monetary policy changes do continue

ensuring that the main conclusion is free fromto produce a significant negative effect onthese concerns.

stock returns in the Volatility and Bear

６ Robustness Check−Controlling for Firm‑and Industry‑Specific Effects
We use individual, firm‑level data to conduct

andMarket regimes, with an average estimatedcoefficient of approximately ‑0.01 in theVolatility Market regime and ‑0.02 in the Bear
Market regime.

the estimates in this paper. It would therefore

Note that nearly all of the firm‑ andbehoove us to add certain other control

industry‑specific control variables appear tovariables to eliminate firm‑ and industry‑

be insignificant. This result is consistent withspecific effects. Controlling for these firm‑ andthe findings of Chen et al. (2010), whose

industry‑specific effects can help us solve theconclusion is that China s stock market is too

problem of estimation bias. Following Ehrmanndifficult to predict, as many predictive variables

and Fratzscher s (2004) methodology, we

found in the U.S. market do not significantly

control for 5 firm‑specific variables and 12

affect the Chinese stock market.

industry‑specific variables. The firm specificvariables are the Tobin s q ratio, cash flow to

７ Conclusion and Policy Implications

income ratio, price earnings ratio, debt to total

This paper adopts China s official interest

capital ratio and market value for eachrates as the monetary policy and tests how thecompany.

variablesinterest rate changes affect the stock market.

denote the separate industries of agriculture,

We first adopts Markov Regime Switching

mining, manufacturing, electricity, building,model to divide China s market into Bulltransport, IT, retail, finance, real estate, social

Marketservice, and culture. We incorporate these

Volatility Market (media mean, lowest variance)firm‑ andThe

industry‑specificindustry‑specificvariables(highest

mean,

media

variance),

intoand Bear Market (lowest mean, highest

equation (4.3) and (4.4). After controlling forvariance). This finding implies monetary policy

these variables, we obtain the following

shocks do not have significantly negative

empirical results.

impacts on the stock return either in the Bull

We estimate the empirical results afterMarket regime or No‑Market‑Regime‑Divisioncontrolling for the firm‑specific effects for thedata as a whole However, a significant

specialized event study models and thenegative relation between monetary policy

Asymmetric Effects of Monetary Policy Shocks on Stock Markets:
An Empirical Test for China

shocks and stock return does exist in both the
Bear and Volatility Market regimes.
The conclusions from this study yieldcertain policy implications for both China s
central bank and investors. Firstly, from thispaper, we conclude that official interest ratechanges do not have a negative effect on thestock market during the Bull Market regime.
Thus, central bank interest rate manipulations
may not be able to cool down a bullish stock
market; therefore, if the PBC wishes to prevent
stock market from overheating through interest
rate adjustments, the bank should implement
its monetary policies as early as possible,
before the stock market begins to increase
dramatically. If a market bubble has alreadyformed, the PBC should seek to affect mattersthrough other policy tools instead of official
interest rate changes.
Secondly, this paper s findings are very
important for Chinese stock market investors.
Based on the analyses presented in this study,
we have demonstrated that stock market
returns will drop dramatically in the bear andvolatile market conditions if monetary policy
becomes tight. Therefore, investors should sell
their stock and decrease their share holdings if
the PBC increases the official interest rates inbear or volatile markets, as these actions
would allow investors to reduce their losses.
Overall, this study s conclusions can provide
significant revelations to individual investors
and larger financial institutions alike regarding
the impact of monetary policy shocks on
Chinese stock market performance, permitting
investors to accurately assess their courses ofaction in response to these shocks.
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Acknowledge: The author would like to thank Professor Yan Shanping (Editor) and an anonymousreferee for excellent suggestions. Additionally, we would like to thank Professor Arayama Yuko,
Professor Katsutoshi Shimizu, Professor Liu Deqiang, Associate Professor Go Yano and Associate
Professor Cen Zhiwei and seminar participants at the western seminar of Japanese Research
Associate for Chinese Economy for useful comments. Comments are welcome to lvxin2311@gmail.
com.

Asymmetric Effects of Monetary Policy Shocks on Stock Markets:
An Empirical Test for China

１９Asymmetric Effects of Monetary Policy Shocks on Stock Markets:
An Empirical Test for China
Xin LV (Nagoya University)
Keywords: Stock Returns, Markov‑Switching Model, Official Interest Rate
JEL Classification: G12, E52
Interest rates shock which is a measurement of monetary policy changes has significant effect on
stock return. Most of the evidences are from the U.S., U.K, Japan and other developed countries.
However, there is rare empirical analysis considering China s case. As an important emerging
stock market, China s stock market shows many specific characters comparing with developed andstrong efficient stock market. On the other hand, China s base interest rates are only controlled by
the central bank but not the monetary market which also differ from developed countries. So
China s specificities from both stock markets and interest rates determination mechanism
motivate us to analyze the relationship between China s stock return and interest rates shock. We
first adopts Markov Regime Switching model to divide China s market into Bull Market (highest
mean, media variance), Volatility Market (media mean, lowest variance) and Bear Market (lowest
mean, highest variance). And then we find monetary policy shocks do not have significantly
negative impacts on the stock return either in the Bull Market regime or No‑Market‑Regime‑
Division data as a whole However, a significant negative relation between monetary policy shocks
and stock return does exist in both the Bear and Volatility Market regimes.