Download The Risk-Return Relationship in Asean-5 Stock Markets

Journal of Asia Pacific Business Innovation & Technology Management 003 (2013) 066-070
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Journal of Asia Pacific Business Innovation &
Technology Management
APBITMS Homepage: http://apbitm.org
The Risk-Return Relationship in Asean-5 Stock Markets: An Empirical Study Using Capital
Asset Pricing Model
Maraporn Kiwiriyakun
Thammasat University, 2 Prachan Rd., Bangkok, Thailand, 10200
ABSTRACT
By using all assets, the top 100 assets, and 30 ASEAN Stars assets as the regressors, the negative risk
premium is explicitly shown in 1997 (financial crisis), 2000 to 2002 (NASDAQ and World Trade Center
crises), and 2008 (Hamburger crisis). The average risk premium of the SET is the highest, which is
approximately 4.9% annually. SGX, KLSE, and PSE are 3.2% to 4.7%, 1.2% to 3.4%, and 0.1% to 1.3%
annually, respectively. However, IDX is equal to -0.8% to -7.5% annually. The higher value of the risk
premium attracts risk-loving investors but the high volatility of the market is also a cause for concern. PSE
has a risk premium close to zero, which is suitable for risk-averse investors. For IDX, the risk premium over
the periods indicates a negative value, which is not a feasibly interesting investment. All stock markets are
not correlated with Malaysia because the majority shareholder is government funds.
© 2013 APBITM Society. All rights reserved.
Keywords: Risk-return relationship, ASEAN-5, CAPM, Negative risk premium, Correlation
I. INTRODUCTION
Normally, investors always seek higher returns from any investment. They decide to invest in the stock
market only when they get return higher than bank deposits. But the higher return also carries with higher
risk. So, investing in the stock market, the investors must bear the risk-return tradeoffs.
Changing in global economic conditions provides the significant shocks to the stock markets, making
the price volatility occur. So, investors have to ensure that investing in the risky assets, they will be
compensated with preferable high returns. Anyway, they also face the equal chance of getting loss. In order
to reduce the possibility of getting loss, portfolio management plays an important role in making decision on
various combinations of asset’s risk and return.
By 2015, there will be a complete integration of leading financial market from ASEAN called ASEAN

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M. Kiwiriyakun /Journal of Asia Pacific Business Innovation & Technology Management 003 (2013) 066-070
Exchanges. It is interesting to study the impacts of them on the risk-return relationship in ASEAN-5 stock
markets. The ASEAN-5 consists of Singapore Stock Exchange (SGX), Kuala Lumpur Stock Exchange
(KLSE), Stock Exchange of Thailand (SET), Philippine Stock Exchange (PSE) and Indonesia Stock
Exchange (IDX).
For the investor side, this paper will help investors evaluate choices and establish the investment
decisions of which countries can make their investment greater profits based on the risks they are facing.
From the perspective view of investors, the research problem is stated as follows: In the case of Singapore
Stock Exchange (SGX), Kuala Lumpur Stock Exchange (KLSE), Stock Exchange of Thailand (SET),
Philippine Stock Exchange (PSE) and Indonesia Stock Exchange (IDX), whether the risk premiums of five
stock markets during the period of January 1990 to July 2012 have the same pattern and tend to converge.
II. METHODOLOGY
This paper proposes an evaluation framework which utilizes the CAPM set theory to interpret the
relationship between the returns and risks of individual stocks. Additional factors are excluded as stated in
the framework of the study. The volatility of stock price is determined by the movement of stock price over
the period of interest. Price changes will affect risk level and volatility and the returns of assets. The
expected return of the individual assets can be written as:
E ( Ri )  R f   i [ E ( Rm )  R f ]
(1)
where E ( Ri ) is the expected return of asset I, R f is the return of risk-free asset, E ( Rm ) is the expected
return of stock market and  i is the systematic risk of asset i.
This model assumes that assets with the same risk should have the same expected rate of return, which
implies that the prices of the assets in the capital market are adjusted until the risks are equivalent to the
expected return. The co-variance of the return of asset and the market return measure the risk of the asset.
These scenario benefits investors in evaluating whether an asset is overpriced or underpriced compared with
the initial results of CAPM. Thus, the investors will invest only if the returns on the asset investment are
greater than the risk-free return.
2.1 Methodology
2.1.1 The risk premium of the market (  )
The methodology and procedure are regressed based on Fama-MacBeth (1973) regression, a method
used to estimate the parameters of asset pricing models such as the CAPM. A two-stage approach is
employed to minimize the variance of betas within the portfolio.
The risk premium of the market exposes the relationship of the average excess return of all portfolio j
in year T and the average betas of all portfolio j in year T-1. The cross-sectional regression of the market risk
premium (called “the average weekly portfolio risk premium”) in each year is given as:
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M. Kiwiriyakun /Journal of Asia Pacific Business Innovation & Technology Management 003 (2013) 066-070
Pj
Pj
R T   T   βT 1  T
where
Pj
(2)
RT
is the average excess return of portfolio j, j=1,…,30 in the current year
T
is the constant coefficient term of stock market in the current year
Pj
βT 1 is the average beta of portfolio j, j=1,…,30 in the previous year
T
is the stochastic error term of stock market.
2.1.2 The relationship of excess market index return of ASEAN-5 stock markets
To study in 4 stock markets whether they have the impact or the relationship with the stock market
remaining one country (left hand side) or not. By following Granger Causality Test (1969), the correlated
equation is given as:
d
h
k
p
s
c 1
g 1
i 1
j 1
r 1
sett   t    c sett  c    g sin g t  g    i philt i    j malayt  j    r indot  r
(3)
H 0 :  g  i   j   r  0
H a :  g  i   j   r  0
The equation (3) explains the change in excess index return in which countries can affect and make the
excess index return of SET changes. To examine this relationship, if p-value of each coefficient is less than
0.05 (significant level) that means we cannot accept the null hypothesis ( ) and the independent variables
(SGX, PSE, KLSE and IDX) have the impact to the SET.
III. RESULTS
3.1 Results
By using all assets in each stock exchange, similar pattern of risk-premiums in the five stock markets
emerges; they tend to move in the same direction. According to the results, the statistically significant
positive risk premium occurred in 1993, 1998 to 1999, 2003, and 2009 and the negative risk premium
occurred in 1997 (Asia financial crisis), 2000 (NASDAQ crisis), and 2008 (Hamburger crisis) for all five
stock exchanges. After that two sets were examined; the top 100 stocks in size and the 30 ASEAN Stars
stocks. In particular, both positive and negative risk premiums are found and negative risk-premiums are
found during the market crises.
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M. Kiwiriyakun /Journal of Asia Pacific Business Innovation & Technology Management 003 (2013) 066-070
Figure 1. The Risk Premium of the ASEAN-5 Stock Exchanges using all assets in each stock exchange
Considering the top 100 assets in 2012, only in Thailand and the Philippines are the market risk
premium found to be positive, though not significant, whereas negative risk premiums are found in other
three stock markets. Using the set of 30 ASEAN Stars stocks, the risk premiums are negative in the year
2012 in the all markets excluding the Stock Exchange of Thailand where there is 0.4% per week risk
premium. Consistent with the result using the top 100 stocks, the risk premium of the Malaysian exchange
index is significantly negative. The average risk premium is examined. The results are similar whether the
top 100 assets or 30 Asian Stars assets are used for the regression. They show that the average risk premium
of SET is the highest at approximately 4.9% per year. Singapore and Malaysia have positive average risk
premiums at 3.2-4.7% and 1.2-3.4% per year, respectively, and both have risk premiums that are higher than
the Philippines in excess of 0.1% to 1.3% per year. The average risk premium of the Philippines is close to
zero since negative risk premiums can be found in many sub periods. Distinct from other markets, the
average risk-premium of Indonesian exchange index is negative having valued of -0.8% to -7.5% per year.
For the relationship between these 5 stock markets, a two-way relationship occurs between
Indonesia-Thailand and Philippines-Singapore. Others are one-way relationship such as Malaysia is
correlated with Thailand. Thailand, Malaysia and Indonesia are correlated with Singapore. Thailand and
Malaysia are correlated with Philippines and the last one; Philippines and Malaysia are correlated with
Indonesia.
Figure 2. The Risk Premium of the ASEAN-5 Stock Exchanges using the top 100 highest market
capitalizations
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Figure 3. The Risk Premium of the ASEAN-5 Stock Exchanges using 30 ASEAN Stars assets
IV. CONCLUSIONS
The high-risk portfolios cannot regularly offer the higher return than lower risk portfolios although the
period of the market index return is positive. Investing in the stock market will benefit the investors in the
long-term and not in the short-run speculation. In periods of negative risk premium, especially during crisis
or uncertainty period, investing in the risk-free assets is more secure. Although in the normal situations, the
high-risk (high beta) portfolio does not always produce high return, and vice versa. Hence, an investor who
expects to receive high excess returns in the current period by investing in risky asset in previous year might
possibly miss the expected return. In addition to the market risk premium of each market, the investors
should exploit all available information such as the fundamentals of assets, the current economic condition,
and the forecast of the government’s future policies.
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