Testing the Validity of Capital Asset Pricing Model: Case Study on Indonesian Stock Market Roberta Octami Sorongan 10436081 Bachelor Thesis in Economics and Finance Supervisor: dhr. dr. K.B.T. Boe Thio Faculty of Economics and Business University of Amsterdam 2014
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Testing the Validity of Capital Asset Pricing Model:
where π π ππ,π‘π‘ is the return of stock i at time t, πππ‘π‘ is stock price at time t, πππ‘π‘β1 is the stock price
at time t β 1, and π·π·π‘π‘ is the amount of dividends paid on stock i at time t. The data on these
returns was retrieved from finance.yahoo.com and was already adjusted for dividends and
splits.
The value of risk-free rate will be according to the BI Rate, which is the policy rate
that reflects the monetary policy stance adopted by Bank Indonesia (i.e. Indonesiaβs
central bank) and announced to the public2. This rate is announced by the Board of
Governors of Bank Indonesia in each of monthly Board of Governors Meeting.
3.2 Sub Periods and Portfolios Formation
The testing will employ the method used by Black, Jensen, and Scholes (1972). In
general, the test will be done within the entire period of January 2010 β December 2013,
as well as four equally divided sub periods, each containing 24 months, summarized in the
1 Sample companies are listed in Appendix 1. These are the companies which data on returns are available for the whole sets of estimation and testing period, which is from January 1, 2008 to December 31, 2013. 2 Complete risk-free rates are shown in Appendix 2. The monthly data is obtained from Bank Indonesiaβs website (www.bi.go.id) and it is actually yearly rate. Therefore, in order to adjust it to monthly rate the following formula is used:
This equation is basically obtained by assuming that the stocks are priced in the market
such that equation (1) holds over each short time interval (in this case a month), then we
can do the test by rearranging the traditional form of the model and adding an intercept πΌπΌππ.
ππππ,π‘π‘ simply represents expected excess returns on stock i at time t, πΈπΈοΏ½π π ππ,π‘π‘οΏ½ β π π ππ, while ππππ,π‘π‘
represents expected excess market returns at time t, πΈπΈοΏ½π π ππ,π‘π‘οΏ½ β π π ππ.
These securities were then ranked from the on the basis of estimates οΏ½ΜοΏ½π½ππ from
highest to the lowest, which then were assigned to six equally-weighted portfolios, with
each containing 6 to 7 stocks. Combining stocks into portfolio will diversify away most of
the firm-specific part of returns, and therefore will enhance the precision of the beta
estimates and the expected rate of return on the portfolios (Michailidis et. al., 2006). The
return in each of the next 12 months (year 2010) for each of the six portfolios was
calculated. This process was then repeated for the next sub periods.
The following step is to estimate the portfolio beta, οΏ½ΜοΏ½π½ππ according to the equation
The estimated risk coefficients, οΏ½ΜοΏ½π½ππ, range from 1.393 for portfolio 1 to 0.754 for
portfolio 6. In general these coefficients are getting lower as we move from the first
through the sixth portfolio, except for portfolio 5 in which beta is relatively higher. The
significance tests of πΌπΌοΏ½ππ, given by the t-values π‘π‘οΏ½πΌπΌοΏ½πποΏ½, show that 5 out of 6 coefficients have
t-values greater than 1.96, which is the critical value for 5% significance level. The
correlation coefficient between portfolio return and market return, ππ(π π οΏ½,π π οΏ½ππ), is also given
in the table. The numbers appear to be lower than expected, with portfolio 2 being the
highest at 0.859.
3 For complete average monthly returns on the six portfolios, see Appendix 3. These portfolios indeed have different composition of company stocks for each sub period.
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However, it may be too early to derive a conclusion from this entire period result,
due to a possibility of the existence of some non-stationarity in the relations, as well as the
lack of more complete aggregation (Black et al., 1972). Therefore, we need to do the
testing for each of the sub periods.
4.2 Sub Periods
After dividing into four equal sub periods each containing 24 months, we repeat
the estimation process for each of the sub periods. The table below presents a summary of
regression on equation (4) calculated using the data for each of these sub periods, as well
Hypothesis Rejected Rejected Not rejected Not rejected Not rejected
The result shows that πΎπΎοΏ½ππ is insignificant in sub period 3 and 4, as well as the entire
period. More or less similar results are also obtained for the intercept and other slopes.
When the explanatory variable unsystematic/idiosyncratic risk is introduced, the result
suggests no significant relationship between these measures of risk and average portfolio
returns.
The study by Johnson and Soenen (1996) also suggests a similar result in which
only systematic risks have a considerable effect on Indonesian stock movements. This is in
accordance with the theory, as the investor is only rewarded for taking systematic risk
because non-systematic risk can be diversified away.
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5. Conclusion
This study provides the investigation on the validity of CAPM when applied to the
Indonesian stock market using the testing method by Black, Jensen, and Scholes (1972).
Using monthly returns data of 38 companies registered in the LQ45 index for the estimation
period of 2008-2012, there are four hypotheses associated with CAPM to be tested: intercept
equals zero, average risk premium exists, the relation between risk and return is linear, and
beta is the only risk variable.
The results provide no significant evidence to reject and rather supportive of these
CAPMβs prediction, apart from the sub period 1 and most of the sub period 2 results. These
are contrary to many other tests conducted in the emerging market, and suggest that CAPM
actually holds in the Indonesian stock market.
5.1 Remarks on the Effect of 2008 Crisis
In general, each of the tests has shown insignificant results for the hypotheses
proposed. However, it is obvious that all of these tests are in fact rejected in sub period 1,
also for the Security Market Line and Non-Systematic Risk tests in sub period 2. As
mentioned previously in the methodology section, the sub period 1 is using beta estimation
from 2008-2009 and the sub period 2 from 2009-2010.
Just as we acknowledge, the crisis in 2008 that hit the global financial market may
also affect the Indonesian stock market down to the following years after. While no
separated tests results on CAPM performance are provided between crisis and non-crisis
periods in this study, there are several previous empirical findings that may support this
argument.
In their study, Black et. al. (1972) obtained first sub period results that mainly
deviate from the latter sub periods. The first sub period of their study was using the excess
returns from 1926-1930 for the beta estimation period and excess returns from 1930 for
the testing period. During the 1930s, a major crisis also occured in the U.S. which may
have derived those contradictory results. Thus, there may as well be an effect of the 2008
financial crisis to these Indonesian stock market results.
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5.2 Limitations to This Study
Several limitations to this paper may exist and should be considered before
drawing a clear-cut conclusion to these results. First of all, the time period of estimation is
rather short, which only covers 5 years returns (2008-2012). Even though longer time span
may help reducing the distortion from random factors that can arise in shorter time span,
there are impediments in collecting the complete data set for the whole longer period.
Some historical prices are not published anywhere, even some of the companies were not
established or have not launched their stock to public before 2008.
Second, the sample stocks used in this test are not randomly selected. They are
taken from an index which includes only the largest and most liquid companies in the
market. The purpose of using this index is that it is likely to represent the whole market.
However, since the number of stocks included here is relatively small, this can lead to
inefficient and/or biased tests results.
Moreover, it may be important to put emphasize on analyzing the effect of crisis to
CAPM performance since the tests conducted during the period of financial crisis have
shown anomalies in the results. There are possibilities that the tests yield in different
conclusion when the impact of crisis is taken into account. Therefore, further investigation
on this matter may be essential to conduct in another extensive study.
Despite these limitations, we can still conclude from the study that so far the results
from the Indonesian market in general are consistent with the hypotheses proposed in order to
test the validity of CAPM. In other words, the returns on the Indonesian stock market are
relatively predictable by using the Capital Asset Pricing Model. These empirical findings,
especially the distinctive results compared to other emerging markets, may be interesting for
further studies and useful to the financial analysts or investors in their consideration
regarding the Indonesian stock market.
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Company Names Ticker Symbol Sector Astra Agro Lestari, Tbk. AALI Agriculture Adhi Karya, Tbk. ADHI Infrastructure and Transportations Adaro Energy, Tbk. ADRO Industrials AKR Corporindo, Tbk. AKRA Trade, Service & Investment Astra International, Tbk. ASII Industrials Alam Sutera Realty, Tbk. ASRI Property and Real Estate Bank Central Asia, Tbk. BBCA Finance Bank Negara Indonesia, Tbk. BBNI Finance Bank Rakyat Indonesia, Tbk. BBRI Finance Bank Danamon Indonesia, Tbk. BDMN Finance Sentul City, Tbk. BKSL Property and Real Estate Bank Mandiri, Tbk. BMRI Finance Global Mediacom, Tbk. BMTR Infrastructure and Transportations Bumi Serpong Damai, Tbk. BSDE Property and Real Estate Charoen Pokphand Indonesia, Tbk. CPIN Basic Industry and Chemicals Ciputra Development, Tbk. CTRA Property and Real Estate XL Axiata, Tbk. EXCL Infrastructure and Transportation Gudang Garam, Tbk. GGRM Consumer Goods Indofood Sukses Makmur, Tbk. INDF Consumer Goods Indocement Tunggal Prakasa, Tbk. INTP Basic Industry and Chemicals Indo Tambangraya Megah, Tbk. ITMG Mining Jasa Marga Persero, Tbk. JSMR Infrastructure and Transportation Kalbe Farma, Tbk. KLBF Consumer Goods Lippo Karawaci, Tbk. LPKR Property and Real Estate PP London Sumatra Indonesia, Tbk LSIP Agriculture Malindo Feedmill, Tbk. MAIN Basic Industry and Chemicals Multipolar, Tbk. MLPL Trade, Services & Investment Media Nusantara Citra, Tbk. MNCN Trade, Services & Investment Perusahaan Gas Negara, Tbk. PGAS Infrastructure and Transportation Tambang Baturbara Bukit Asam, Tbk. PTBA Mining Pakuwon Jati, Tbk. PWON Property and Real Estate Semen Gresik, Tbk. SMGR Basic Industry and Chemicals Summarecon Agung, Tbk. SMRA Property and Real Estate Surya Semestra Internusa, Tbk. SSIA Property and Real Estate Telekomunikasi Indonesia, Tbk. TLKM Infrastructure and Transportation United Tractors, Tbk. UNTR Trade, Services & Investment Unilever Indonesia, Tbk. UNVR Consumer Goods Wijaya Karya Persero, Tbk. WIKA Infrastructure and Transportation
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Appendix 2: Bank Indonesiaβs Risk-Free Rate
Date Yearly Rate Adjusted for Monthly Dec 01, 2013 7,50% 0,6045% Nov 01, 2013 7,50% 0,6045% Oct 01, 2013 7,25% 0,5850% Sep 01, 2013 7,25% 0,5850% Aug 01, 2013 6,50% 0,5262% Jul 01, 2013 6,50% 0,5262% Jun 01, 2013 6,00% 0,4868% May 01, 2013 5,75% 0,4670% Apr 01, 2013 5,75% 0,4670% Mar 01, 2013 5,75% 0,4670% Feb 01, 2013 5,75% 0,4670% Jan 01, 2013 5,75% 0,4670% Dec 01, 2012 5,75% 0,4670% Nov 01, 2012 5,75% 0,4670% Oct 01, 2012 5,75% 0,4670% Sep 01, 2012 5,75% 0,4670% Aug 01, 2012 5,75% 0,4670% Jul 01, 2012 5,75% 0,4670% Jun 01, 2012 5,75% 0,4670% May 01, 2012 5,75% 0,4670% Apr 01, 2012 5,75% 0,4670% Mar 01, 2012 5,75% 0,4670% Feb 01, 2012 5,75% 0,4670% Jan 01, 2012 6,00% 0,4868% Dec 01, 2011 6,00% 0,4868% Nov 01, 2011 6,00% 0,4868% Oct 01, 2011 6,50% 0,5262% Sep 01, 2011 6,75% 0,5458% Aug 01, 2011 6,75% 0,5458% Jul 01, 2011 6,75% 0,5458% Jun 01, 2011 6,75% 0,5458% May 01, 2011 6,75% 0,5458% Apr 01, 2011 6,75% 0,5458% Mar 01, 2011 6,75% 0,5458% Feb 01, 2011 6,75% 0,5458% Jan 01, 2011 6,50% 0,5262% Dec 01, 2010 6,50% 0,5262% Nov 01, 2010 6,50% 0,5262% Oct 01, 2010 6,50% 0,5262% Sep 01, 2010 6,50% 0,5262% Aug 01, 2010 6,50% 0,5262% Jul 01, 2010 6,50% 0,5262% Jun 01, 2010 6,50% 0,5262% May 01, 2010 6,50% 0,5262% Apr 01, 2010 6,50% 0,5262% Mar 01, 2010 6,50% 0,5262% Feb 01, 2010 6,50% 0,5262% Jan 01, 2010 6,50% 0,5262% Dec 01, 2009 6,50% 0,5262% Nov 01, 2009 6,50% 0,5262% Oct 01, 2009 6,50% 0,5262% Sep 01, 2009 6,50% 0,5262% Aug 01, 2009 6,50% 0,5262% Jul 01, 2009 6,75% 0,5458% Jun 01, 2009 7,00% 0,5654% May 01, 2009 7,25% 0,5850%
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Apr 01, 2009 7,50% 0,6045% Mar 01, 2009 7,75% 0,6240% Feb 01, 2009 8,25% 0,6628% Jan 01, 2009 8,75% 0,7015% Dec 01, 2008 9,25% 0,7400% Nov 01, 2008 9,50% 0,7592% Oct 01, 2008 9,50% 0,7592% Sep 01, 2008 9,25% 0,7400% Aug 01, 2008 9,00% 0,7207% Jul 01, 2008 8,75% 0,7015% Jun 01, 2008 8,50% 0,6821% May 01, 2008 8,25% 0,6628% Apr 01, 2008 8,00% 0,6434% Mar 01, 2008 8,00% 0,6434% Feb 01, 2008 8,00% 0,6434% Jan 01, 2008 8,00% 0,6434%
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Appendix 3: Portfolio Average Returns for the Entire Period