Analysis of the effect of inflation rate, interest rate and exchange rate on stock return of consumer goods and property and real estate sector in Indonesia stock exchange (IDX) 2006-2010
“ANALYSIS OF THE EFFECT OF INFLATION RATE,
INTEREST
RATE AND EXCHANGE RATE ON STOCK RETURN OF CONSUMER
GOODS AND PROPERTY AND REAL ESTATE SECTOR IN
INDONESIA STOCK EXCHANGE (IDX) 2006-2010
”
Submitted by:
Ariningtyas Widyasnia Agustina Student ID:107081101584
INTERNATIONAL UNDERGRADUATE PROGRAM MANAGEMENT DEPARTMENT
FACULTY OF ECONOMICS AND BUSINESS UIN SYARIF HIDAYATULLAH JAKARTA
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i ACKNOWLEDGEMENT
My greatest gratitude to Allah SWT, the Grandest and Almighty, the Most Gracious and the Most Merciful, for giving me the chance and ability to complete this thesis,and for all the miracles He has granted to my life. May the talent You have bestowed upon me will not got to waste. My greatest ggratitude to Prophet Muhammad SAW for the teachings and love he has spread to all the creatures in this whole universe. May we all always under his guidance.
First and foremost, I would like to thank to my thesis supervisors; Prof. Dr. Ahmad Rodhoni, MM and Mr. Tirmidzi Taridi,MBA for their help, time, contribution and effort in providing guidance and constructive suggestion to perform this study, and for the understanding and support they had given.
I would also like to thank to the head of International Program, Faculty of Economics and Business, UIN Syarif Hidayatullah Jakarta, Mr. Arief Mufraini, Lc. M.Si, and his deputies Mr. Ahmad Dumiyati. Also, thanks to Kak Sugih, for his patients in accomodating all of my administrative needs. Thank you.
This thesis will never be completed without the continous support and prays from my friends, collagues, and people around me. Thank you for the people in my current internship place, Bank Indonesia, the place where this thesis born. I would also like to thank to my bestfriends in International Program Batch 4; Sukria, Andrea Ardilla, Wike Vidya, Pramayassya, Fitra, Weldan, Muhammad Kharisma and all, whose name can’t be mentioned one by one. Individually, thank you to Aprima Arta for his continous support and understanding during my hardest time in making this thesis.
Last, but not least, I dedicated this thesis to the greatest gift God has given to my life, my family. My father, H. Sumarno, for his support and increadible patient, you are the soul of our life. My mother, Hj. Sri Irawati, for her unlimited guidance that always keeping me on the right track. My brother, Rifki Hidayat Rahkumulyo, and my sister, Arindani Tri Ramadhani, for made my life so blessed and colorful everyday. Thank you.
Ariningtyas W. Agustina
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ii ABSTRAK
Penelitian ini bertujuan untuk menganalisis pengaruh suku bunga, inflasi, dan nilai tukar terhadap tingkat pengembalian saham pada sektor properti dan real estate serta sektor industry barang konsumsi periode 2006-2010. Penelitian ini menggunakan model regresi linear berganda. Berdasarkan hasil penelitian, secara parsial suku bunga berpengaruh signifikan negatif terhadap tingkat pengembalian saham property dan real estate dan tingkat pengembalian saham barang konsumsi .Inflasi tidak berpengaruh terhadap tingkat pengembalian saham property dan real estate serta saham barang konsumsi. Nilai tukar berpengaruh signifikan negatif terhadap tingkat pengembalian saham property dan real estate serta saham barang konsumsi. Hasil penelitian juga menunjukkan bahwa suku bunga, inflasi, dan nilai tukar berpengaruh lebih besar terhadap tingkat pengembalian saham property dan real estate daripada saham barang konsumsi.
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iii ABSTRACT
This research shows the effect of inflation rate, interest rate, and exchange rate on stock return of property and real estate and consumer goods sector in period 2006-2010. A multiple regression model is applied to test the significance of influence between the independent variable and the dependent variable. Based on the result, partially interest rate has a negative effect to stock return of property and real estate sector and consumer goods sector. Inflation has no effect to stock return of property and real estate and consumer goods sector, while exchange rate has negative effect to stock return of property and real estate sector. The result shows that the inflation rate, exchange rate, and interest rate have a bigger effect on stock return of property and real estate sector than consumer goods sector.
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iv LIST OF CONTENTS
CHAPTER 1: INTRODUCTION __________________________________________ 1
A. Background ________________________________________________________ 1 B. Problem Formulation ________________________________________________ 6 C. Research Objectives _________________________________________________ 8 D. Usefullness of the Research ___________________________________________ 8
CHAPTER 2: LITERATURE REVIEW ____________________________________ 13
A. Fundamental of Capital Market _______________________________________ 13 1. History of Indonesian Capital Market _________________________________ 13 2. Capital Market Definition __________________________________________ 14 3. Capital Market Instrument __________________________________________ 15 B. Investment ________________________________________________________ 16 C. Stock Rate of Return ________________________________________________ 19 D. Risks ____________________________________________________________ 21 E. Inflation __________________________________________________________ 23 1. Relationship between inflation rate and stock return ______________________ 27 F. Interest Rate _______________________________________________________ 26 2.6.1 Relationship between interest rate and stock return ____________________ 27 2.6.2 SBI (Sertifikat Bank Indonesia) Rate _______________________________ 28 G. Exchange Rate ____________________________________________________ 30
H. Previous Researches ________________________________________________ 31 I. Research Framework and Hypotheses __________________________________ 37
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v
CHAPTER 3: RESEARCH METHODOLOGY ______________________________ 40
A. Data Collection ____________________________________________________ 40 1. Unit of Analysis and Research Sampling _______________________________ 40 2. Types of Data ____________________________________________________ 41 B. Research Models ___________________________________________________ 41 3.3 Operational Variable _______________________________________________ 42 3.3.1 Stock’s Rate of Return __________________________________________ 42 3.3.2 Inflation Rate __________________________________________________ 43 3.3.2 Exchange Rate _________________________________________________ 44 3.3.2 Interest Rate ___________________________________________________ 45 3.4 Data Analysis Technique ____________________________________________ 45 3.4.1 Normality Test _________________________________________________ 46 3.4.1.1 Jarque-Bera Test of Normality _________________________________ 47 3.4.2 Classical Assumption Test _______________________________________ 48 3.4.2.1 Heteroscedastic Test _________________________________________ 50 3.4.2.2 Autocorrelation Test _________________________________________ 53 3.4.2.3 Multi-Collinearity Test _______________________________________ 54 3.4.3 Hypothesis Test ________________________________________________ 55 3.4.3.1 T Test ____________________________________________________ 55 3.4.3.2 F Test ____________________________________________________ 55 3.4.3.3 R Square (R2) Test __________________________________________ 56 3.4.4.4 Adjusted R Squared Test _____________________________________ 56 3.5 Research Design __________________________________________________ 57
CHAPTER 4: RESEARCH FINDINGS AND ANALYSIS _____________________ 58
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vi
4.2 Descriptive Statistic ________________________________________________ 59 4.3 Normality Test ____________________________________________________ 60 4.4 Classical Assumption Test ___________________________________________ 62 4.4.1 Heteroscedasticity Test __________________________________________ 62 4.4.2 Auto-Correlation Test ___________________________________________ 64 4.4.3 Multi-Collinearity Test __________________________________________ 65 4.5 Multiple Linear Regression Model ____________________________________ 66 4.6 Hypothesis Testing ________________________________________________ 67 4.6.1 T-Test _______________________________________________________ 67 4.6.2 f Test ________________________________________________________ 81 4.6.3 R-Squared (R2) ________________________________________________ 81 4.6.4 Adjusted R-Squared ____________________________________________ 82 4.7 The comparison between macroeconomic factors’ influences towards the
stock’s return on consumer goods and property and real estate sector _________ 83
CHAPTER 5: CONCLUSION AND IMPLICATIONS ________________________ 84
5.1 Conclusion ______________________________________________________ 84 5.2 Implication of Study _______________________________________________ 85 5.2.1 For the Investor ________________________________________________ 85 5.2.1 For the Researcher ______________________________________________ 85 5.3 Limitation _______________________________________________________ 86
REFERENCES
APPENDIX I
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vii LIST OF FIGURES
2.1 Indonesia Interest Rate _____________________________________________ 29 2.2 Research Model ___________________________________________________ 39 3.1 Research Framework _______________________________________________ 57 4.1 Histogram Residual, Consumer Goods Sector ___________________________ 61 4.2 Histogram Residual, Property and Real Estate Sector _____________________ 61
4.3 Graph of Ex. Rate & Stock Return Movement 1 __________________________ 69 4.4 Graph of Inflation Rate & Stock Return Movement 1 _____________________ 71 4.5 Graph of SBI Rate & Stock Return Movement 1 _________________________ 73 4.6 Graph of Exchange Rate & Stock Return Movement 2 ____________________ 76 4.7 Graph of Inflation Rate & Stock Return Movement 2 _____________________ 78 4.8 Graph of SBI Rate & Stock Return Movement 2 _________________________ 80
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viii LIST OF TABLES
2.1 Indonesia Interest Rate _____________________________________________ 29 2.2 Research Model ___________________________________________________ 39 1.3 Research Objectives ________________________________________________ 8 1.4 Research Benefits __________________________________________________ 8 1.4 Research Benefits __________________________________________________ 8 4. Descriptive Statistics ________________________________________________ 59 4.2 Heteroscedasticity Test for Property and Real Estate Sector ________________ 63 4.3 Auto-Correlation Test for Consumer Goods Sector _______________________ 63 4.4 Auto-Correlation Test for Property and Real Estate Sector _________________ 64 4.5 Multi-Collinearity Test _____________________________________________ 65 4.6 Multi-Collinearity Test _____________________________________________ 65 4.7 Multi-Collinearity Test _____________________________________________ 67 4.8 Output Multiple Linear Regression Property and Real Estate Sector _________ 74 4.9 Comparison of Coefficient Regression _________________________________ 83
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ix LIST OF FORMULAS
2.1 Simple Returns ___________________________________________________ 19 2.2 Continously Compounded Return _____________________________________ 20 2.3 Consumer Price Index ______________________________________________ 24 2.4 Wholeseller Price Index _____________________________________________ 24 2.5 Inflation Rate _____________________________________________________ 25 2.6 Relationship between nominal and interest rate __________________________ 27 2.7 Capital Price Index Model ___________________________________________ 35 2.8 Multi Index Model _________________________________________________ 36 3.1 Model 1 _________________________________________________________ 41 3.2 Model 2 _________________________________________________________ 41 3.3 Continously Compounded Method ____________________________________ 42 3.4 Inflation Rate _____________________________________________________ 43 3.5 Change in Inflation Rate ____________________________________________ 43 3.6 Change in Exchange Rate ___________________________________________ 44 3.7 Change in Interest Rate _____________________________________________ 45 3.8 Jarque-Bera Test of Normality _______________________________________ 47 3.9 Zero Mean Value of Disturbance _____________________________________ 48 3.10 Homoscedasticity or equal variance of ui ______________________________ 49
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x
3.12 Zero covariance between ui and Xi ____________________________________ 49
3.13 Regression Model ________________________________________________ 51 3.14 Auxiliary Regression Model ________________________________________ 51 3.15 Chi Square Distribution ____________________________________________ 52 3.16 R-Squared Test __________________________________________________ 56
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“In the name of Allah, the Most Gracious, the Most Merciful....
All praise be to God alone, the Lord of all the world, the All-Merciful, the Ever Mercy-giving, and the Master of the Day of Judgement.
You alone we worship, and You alone we ask for help.
Guide us on the right path,
The path of whom You have blessed, not of those who incur You anger, nor of those who go astray...”
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Consumer Goods Return Date Consumer Goods Index Price Consumer Goods Return 12/30/2005 280.928
1/31/2006 288.583 0.026884331 2/28/2006 292.458 0.013338327 3/31/2006 293.905 0.004935519 4/28/2006 328.354 0.110835709 5/31/2006 294.929 -0.107357645 6/30/2006 299.316 0.014765222 7/31/2006 313.201 0.045345285 8/31/2006 331.074 0.055496758
9/29/2006 343.543 0.03697037
10/31/2006 349.721 0.017823408
11/24/2006 347.347 -0.006811413
12/29/2006 392.458 0.122105245
1/31/2007 390.251 -0.005639403 2/28/2007 385.22 -0.012975522 3/30/2007 385.827 0.001574483 4/30/2007 391.795 0.015349661
5/31/2007 411.99 0.050260333
6/29/2007 324.964 -0.23728467 7/31/2007 453.843 0.334036916 8/31/2007 415.462 -0.088360169 9/28/2007 421.425 0.014250672
10/31/2007 429.804 0.019687465
11/30/2007 426.853 -0.006889599
12/28/2007 436.039 0.021291997
1/31/2008 438.132 0.004788546 2/29/2008 430.084 -0.018539696 3/31/2008 405.011 -0.060066311
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4/30/2008 394.385 -0.026586638
5/30/2008 414.54 0.049841882
6/30/2008 398.285 -0.040001642 7/31/2008 390.81 -0.018946321 8/29/2008 396.007 0.013210379 9/29/2008 381.36 -0.037688077
10/31/2008 321.919 -0.16944385
11/28/2008 320.9 -0.003170413
12/30/2008 326.843 0.018350385
1/30/2009 337.847 0.033113197 2/27/2009 346.155 0.024293521
3/31/2009 351.269 0.01466566
4/30/2009 381.322 0.082091851 5/29/2009 433.732 0.128782669 6/30/2009 495.732 0.133608626 7/31/2009 591.202 0.176122294 8/31/2009 559.178 -0.055689904 9/30/2009 597.628 0.066500639 10/30/2009 575.396 -0.037909987
11/30/2009 625.728 0.083857272
12/30/2009 671.305 0.070307807
1/29/2010 699.783 0.041546708
2/26/2010 717.932 0.02560457
3/31/2010 738.141 0.027760006
4/30/2010 821.588 0.10710419
5/31/2010 889.807 0.079765532
6/30/2010 959.04 0.074928199
7/30/2010 1,001.30 0.043122649 8/31/2010 1,005.91 0.004595432 9/30/2010 1,176.56 0.15670104
10/29/2010 1,179.98 0.00290171
11/30/2010 1,070.01 -0.097826604 12/30/2010 1,094.65 0.022765686
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Property and Real Estate Return Date Property and Real Estate Index Price Property and Real Estate Return
12/29/2005 64.12
1/31/2006 70.484 0.094629406
2/28/2006 71.33 0.011931263
3/31/2006 79.331 0.106311977
4/28/2006 88.956 0.114512893
5/31/2006 81.352 -0.089356447
6/30/2006 77.433 -0.049372372
7/31/2006 77.942 0.006551914
8/31/2006 78.985 0.013293001
9/29/2006 83.775 0.058876673
10/31/2006 90.316 0.075179998
10/24/2006 90.467 0.001670511
12/29/2006 122.918 0.306532323
1/31/2007 123.101 0.00148769
2/28/2007 136.185 0.101009099
3/30/2007 143.243 0.050528233
4/30/2007 168.687 0.163502438
5/31/2007 201.037 0.175444044
6/29/2007 211.718 0.05176623
7/31/2007 247.47 0.156034162
8/31/2007 225.648 -0.0923131
9/28/2007 242.834 0.073401819
10/31/2007 247.309 0.018260485
11/30/2007 232.089 -0.063517648
12/28/2007 251.816 0.081577743
1/31/2008 229.563 -0.09252116
2/29/2008 229.517 -0.000200401
3/31/2008 195.603 -0.159890006
4/30/2008 177.721 -0.09587219
5/30/2008 184.272 0.036198022
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7/31/2008 174.699 0.035962585
8/29/2008 164.414 -0.060676856
9/29/2008 142.421 -0.143600177
10/31/2008 101.346 -0.340247055
11/28/2008 105.632 0.041420951
12/30/2008 103.489 -0.020496029
1/30/2009 96.026 -0.074846339
2/27/2009 96.558 0.005524876
3/31/2009 99.742 0.032442988
4/30/2009 112.318 0.118747282
5/29/2009 130.986 0.153756313
6/30/2009 144.787 0.10017325
7/31/2009 159.975 0.099753856
8/31/2009 157.959 -0.012682047
9/30/2009 162.285 0.027018543
10/30/2009 153.985 -0.052498854
11/30/2009 143.635 -0.069579836
12/30/2009 146.8 0.021795757
1/29/2010 153.491 0.044570817
2/26/2010 150.231 -0.021467824
3/31/2010 166.378 0.102088199
4/30/2010 182.123 0.090419975
5/31/2010 154.504 -0.164462297
6/30/2010 163.384 0.055883272
7/30/2010 168.259 0.029401201
8/31/2010 170.904 0.015597536
9/30/2010 192.768 0.120385398
10/29/2010 202.413 0.048822771
11/30/2010 203.223 0.003993734
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Data of Exchange Rate
Year Month Sell Buy Mid Change
2005 December 9879 9781 9830
2006 January 9442 9348 9395 -0.0443
February 9276 9184 9230 -0.0176
March 9120 9030 9075 -0.0168
April 8819 8731 8775 -0.0331
May 9266 9174 9220 0.05071
June 9347 9253 9300 0.00868
July 9115 9025 9070 -0.0247
August 9146 9054 9100 0.00331
September 9281 9189 9235 0.01484
October 9156 9064 9110 -0.0135
November 9211 9119 9165 0.00604
December 9065 8975 9020 -0.0158
2007 January 9135 9045 9090 0.00776
February 9206 9114 9160 0.0077
March 9164 9072 9118 -0.0046
April 9128 9038 9083 -0.0038
May 8872 8784 8828 -0.0281
June 9099 9009 9054 0.0256
July 9232 9140 9186 0.01458
August 9457 9363 9410 0.02438
September 9183 9091 9137 -0.029
October 9149 9057 9103 -0.0037
November 9423 9329 9376 0.02999
December 9466 9372 9419 0.00459
2008 January 9337 9245 9291 -0.0136
February 9096 9006 9051 -0.0258
March 9263 9171 9217 0.01834
April 9280 9188 9234 0.00184
May 9365 9271 9318 0.0091
June 9271 9179 9225 -0.01
July 9164 9072 9118 -0.0116
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September 9425 9331 9378 0.02458
October 11050 10940 10995 0.17242
November 12212 12090 12151 0.10514
December 11005 10895 10950 -0.0988
2009 January 11412 11298 11355 0.03699
February 12040 11920 11980 0.05504
March 11633 11517 11575 -0.0338
April 10767 10659 10713 -0.0745
May 10392 10288 10340 -0.0348
June 10276 10174 10225 -0.0111
July 9970 9870 9920 -0.0298
August 10110 10010 10060 0.01411
September 9729 9633 9681 -0.0377
October 9593 9497 9545 -0.014
November 9527 9433 9480 -0.0068
December 9447 9353 9400 -0.0084
2010 January 9412 9318 9365 -0.0037
February 9382 9288 9335 -0.0032
March 9161 9069 9115 -0.0236
April 9057 8967 9012 -0.0113
May 9226 9134 9180 0.01864
June 9128 9038 9083 -0.0106
July 8997 8907 8952 -0.0144
August 9086 8996 9041 0.00994
September 8969 8879 8924 -0.0129
October 8973 8883 8928 0.00045
November 9058 8968 9013 0.00952
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Data of SBI Rate
Year Month
SBI
Rate Change
2005 December 0.1275
2006 January 0.1275 0
February 0.1274 -0.0008
March 0.1273 -0.0008
April 0.1274 0.00079
May 0.125 -0.0188
June 0.125 0
July 0.1225 -0.02
August 0.1175 -0.0408
September 0.1125 -0.0426
October 0.1075 -0.0444
November 0.1025 -0.0465
December 0.0975 -0.0488
2007 January 0.095 -0.0256
February 0.0925 -0.0263
March 0.09 -0.027
April 0.09 0
May 0.0875 -0.0278
June 0.085 -0.0286
July 0.0825 -0.0294
August 0.0825 0
September 0.0825 0
October 0.0825 0
November 0.0825 0
December 0.08 -0.0303
2008 January 0.08 0
February 0.0793 -0.0088
March 0.0796 0.00378
April 0.0799 0.00377
May 0.0831 0.04005
June 0.0873 0.05054
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August 0.0928 0.00542
September 0.0971 0.04634
October 0.1098 0.13079
November 0.1124 0.02368
December 0.1083 -0.0365
2009 January 0.0977 -0.0979
February 0.0874 -0.1054
March 0.0821 -0.0606
April 0.0764 -0.0694
May 0.0725 -0.051
June 0.0695 -0.0414
July 0.0671 -0.0345
August 0.0658 -0.0194
September 0.0648 -0.0152
October 0.0649 0.00154
November 0.0647 -0.0031
December 0.0646 -0.0015
2010 January 0.0645 -0.0015
February 0.0641 -0.0062
March 0.0632 -0.014
April 0.0625 -0.0111
May 0.0637 0.0192
June 0.0629 -0.0126
July 0.067 0.06518
August 0.067 0
September 0.0645 -0.0373
October 0.0645 0
November 0.065 0.00775
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Data of Inflation Rate
Year Month Inflation Change in Inflation
2005 December -0.04
2006 January 1.36 -35
February 0.58 -0.573529412
March 0.03 -0.948275862
April 0.05 0.666666667
May 0.37 6.4
June 0.45 0.216216216
July 0.45 0
August 0.33 -0.266666667
September 0.38 0.151515152
October 0.86 1.263157895
November 0.34 -0.604651163
December 1.21 2.558823529
2007 January 1.04 -0.140495868
February 0.62 -0.403846154
March 0.24 -0.612903226
April -0.16 -1.666666667
May 0.10 -1.625
June 0.23 1.3
July 0.72 2.130434783
August 0.75 0.041666667
September 0.80 0.066666667
October 0.79 -0.0125
November 0.18 -0.772151899
December 1.10 5.111111111
2008 January 1.77 0.609090909
February 0.65 -0.632768362
March 0.95 0.461538462
April 0.57 -0.4
May 1.41 1.473684211
June 2.46 0.744680851
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August 0.51 -0.627737226
September 0.97 0.901960784
October 0.45 -0.536082474
November 0.12 -0.733333333
December -0.04 -1.333333333
2009 January -0.07 0.75
February 0.21 -4
March 0.22 0.047619048
April -0.31 -2.409090909
May 0.04 -1.129032258
June 0.11 1.75
July 0.45 3.090909091
August 0.56 0.244444444
September 1.05 0.875
October 0.19 -0.819047619
November -0.03 -1.157894737
December 0.33 -12
2010 January 0.84 1.545454545
February 0.30 -0.642857143
March -0.14 -1.466666667
April 0.15 -2.071428571
May 0.29 0.933333333
June 0.97 2.344827586
July 1.57 0.618556701
August 0.76 -0.515923567
September 0.44 -0.421052632
October 0.06 -0.863636364
November 0.60 9
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EVIEWS 5 OUTPUT (Consumer Goods Sector)
MULTIPLE REGRESSION Dependent Variable: Y Method: Least Squares Date: 02/07/11 Time: 16:04 Sample: 2006M01 2010M12 Included observations: 60
Variable Coefficient Std. Error t-Statistic Prob.
C 0.016385 0.008014 2.044428 0.0456
X1 -0.693450 0.226342 -3.063726 0.0034
X2 3.36E-05 0.001505 0.022330 0.9823
X3 -0.483347 0.223922 -2.158550 0.0352
R-squared 0.286679 Mean dependent var 0.022268
Adjusted R-squared 0.248466 S.D. dependent var 0.067858
S.E. of regression 0.058827 Akaike info criterion -2.764084
Sum squared resid 0.193796 Schwarz criterion -2.624461
Log likelihood 86.92251 F-statistic 7.502025
Durbin-Watson stat 2.016865 Prob(F-statistic) 0.000263
AUTO CORRELATION TEST
Breusch-Godfrey Serial Correlation LM Test:
F-statistic 0.150862 Probability 0.860328
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White Heteroskedasticity Test:
F-statistic 1.985143 Probability 0.084204
Obs*R-squared 11.00974 Probability 0.088076
DESCRIPTIVE STATISTICS
Y C X1 X2 X3
Mean 0.022268 1.000000 -0.000831 -0.483316 -0.011012 Median 0.003819 1.000000 -0.003781 -0.076498 -0.007476 Maximum 0.193360 1.000000 0.172425 9.000000 0.130793 Minimum -0.169444 1.000000 -0.098840 -35.00000 -0.105425 Std. Dev. 0.067858 0.000000 0.037145 5.192304 0.036939
Skewness 0.352901 NA 1.717417 -5.028711 0.705108
Kurtosis 3.747713 NA 10.70772 34.36123 6.116995
Jarque-Bera 2.643079 NA 178.0175 2711.697 29.26092 Probability 0.266724 NA 0.000000 0.000000 0.000000
Sum 1.336056 60.00000 -0.049875 -28.99897 -0.660716 Sum Sq.
Dev. 0.271681 0.000000 0.081406 1590.641 0.080504
Observations 60 60 60 60 60
MULTI-COLLINEARITY TEST Dependent Variable: X1
Method: Least Squares Date: 02/07/11 Time: 16:09 Sample: 2006M01 2010M12 Included observations: 60
Variable Coefficient Std. Error t-Statistic Prob.
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X2 0.001321 0.000863 1.530626 0.1314
X3 0.373475 0.121341 3.077900 0.0032
R-squared 0.170209 Mean dependent var -0.000831
Adjusted R-squared 0.141094 S.D. dependent var 0.037145 S.E. of regression 0.034425 Akaike info criterion -3.851354 Sum squared resid 0.067550 Schwarz criterion -3.746637
Log likelihood 118.5406 F-statistic 5.846004
Durbin-Watson stat 1.836991 Prob(F-statistic) 0.004905
Dependent Variable: X2 Method: Least Squares Date: 02/07/11 Time: 16:09 Sample: 2006M01 2010M12 Included observations: 60
Variable Coefficient Std. Error t-Statistic Prob.
C -0.601305 0.700757 -0.858079 0.3944
X1 29.87945 19.52107 1.530626 0.1314
X3 -12.97014 19.63019 -0.660724 0.5115
R-squared 0.039652 Mean dependent var -0.483316
Adjusted R-squared 0.005956 S.D. dependent var 5.192304 S.E. of regression 5.176819 Akaike info criterion 6.174965
Sum squared resid 1527.569 Schwarz criterion 6.279683
Log likelihood -182.2490 F-statistic 1.176746
Durbin-Watson stat 1.268507 Prob(F-statistic) 0.315656
Dependent Variable: X3 Method: Least Squares Date: 02/07/11 Time: 16:09 Sample: 2006M01 2010M12
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Included observations: 60
Variable Coefficient Std. Error t-Statistic Prob.
C -0.010978 0.004512 -2.432994 0.0181
X1 0.381592 0.123978 3.077900 0.0032
X2 -0.000586 0.000887 -0.660724 0.5115
R-squared 0.142669 Mean dependent var -0.011012
Adjusted R-squared 0.112587 S.D. dependent var 0.036939 S.E. of regression 0.034797 Akaike info criterion -3.829852
Sum squared resid 0.069018 Schwarz criterion -3.725135
Log likelihood 117.8956 F-statistic 4.742714
Durbin-Watson stat 0.862207 Prob(F-statistic) 0.012437
0 1 2 3 4 5 6 7 8 9
-0.10 -0.05 -0.00 0.05 0.10 0.15
Series: Residuals
Sample 2006M01 2010M12 Observations 60
Mean -4.97e-18 Median -0.005805 Maximum 0.145997 Minimum -0.105790 Std. Dev. 0.057312 Skewness 0.487487 Kurtosis 2.684504 Jarque-Bera 2.625284 Probability 0.269108
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EVIEWS 5 OUTPUT (Property and Real Estate Sector)
MULTIPLE REGRESSION Dependent Variable: Y Method: Least Squares Date: 02/07/11 Time: 10:59 Sample: 2006M01 2010M12 Included observations: 60
Variable Coefficient Std. Error t-Statistic Prob.
C 0.008209 0.011062 0.742136 0.4611
X1 -1.065215 0.312405 -3.409723 0.0012
X2 -0.000461 0.002077 -0.221818 0.8253
X3 -0.898840 0.309064 -2.908261 0.0052
R-squared 0.369993 Mean dependent var 0.019215
Adjusted R-squared 0.336243 S.D. dependent var 0.099661 S.E. of regression 0.081195 Akaike info criterion -2.119578
Sum squared resid 0.369190 Schwarz criterion -1.979955
Log likelihood 67.58735 F-statistic 10.96265
Durbin-Watson stat 1.908693 Prob(F-statistic) 0.000009
AUTO CORRELATION TEST
Breusch-Godfrey Serial Correlation LM Test:
F-statistic 0.587759 Probability 0.559086
Obs*R-squared 1.278303 Probability 0.527740
Test Equation:
Dependent Variable: RESID Method: Least Squares
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Date: 02/07/11 Time: 10:57
Presample missing value lagged residuals set to zero.
Variable Coefficient Std. Error t-Statistic Prob.
C 0.000104 0.011158 0.009328 0.9926
X1 0.009653 0.322981 0.029888 0.9763
X2 -0.000342 0.002124 -0.161050 0.8727
X3 0.030717 0.315445 0.097378 0.9228
RESID(-1) 0.039112 0.138929 0.281525 0.7794
RESID(-2) 0.141898 0.137328 1.033283 0.3061
R-squared 0.021305 Mean dependent var 6.94E-19
Adjusted R-squared -0.069315 S.D. dependent var 0.079104 S.E. of regression 0.081800 Akaike info criterion -2.074447
Sum squared resid 0.361324 Schwarz criterion -1.865012
Log likelihood 68.23341 F-statistic 0.235103
Durbin-Watson stat 2.037779 Prob(F-statistic) 0.945374
White Heteroskedasticity Test:
F-statistic 0.538939 Probability 0.776195
Obs*R-squared 3.450216 Probability 0.750581
MULTI-COLLINEARITY TEST Dependent Variable: X1
Method: Least Squares Date: 02/07/11 Time: 11:01 Sample: 2006M01 2010M12 Included observations: 60
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C 0.003920 0.004661 0.841008 0.4039
X2 0.001321 0.000863 1.530626 0.1314
X3 0.373475 0.121341 3.077900 0.0032
R-squared 0.170209 Mean dependent var -0.000831
Adjusted R-squared 0.141094 S.D. dependent var 0.037145
S.E. of regression 0.034425 Akaike info criterion -3.851354
Sum squared resid 0.067550 Schwarz criterion -3.746637
Log likelihood 118.5406 F-statistic 5.846004
Durbin-Watson stat 1.836991 Prob(F-statistic) 0.004905
Dependent Variable: X2 Method: Least Squares Date: 02/07/11 Time: 11:02 Sample: 2006M01 2010M12 Included observations: 60
Variable Coefficient Std. Error t-Statistic Prob.
C -0.601305 0.700757 -0.858079 0.3944
X1 29.87945 19.52107 1.530626 0.1314
X3 -12.97014 19.63019 -0.660724 0.5115
R-squared 0.039652 Mean dependent var -0.483316
Adjusted R-squared 0.005956 S.D. dependent var 5.192304
S.E. of regression 5.176819 Akaike info criterion 6.174965
Sum squared resid 1527.569 Schwarz criterion 6.279683
Log likelihood -182.2490 F-statistic 1.176746
Durbin-Watson stat 1.268507 Prob(F-statistic) 0.315656
Dependent Variable: X3 Method: Least Squares Date: 02/07/11 Time: 11:02 Sample: 2006M01 2010M12
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Included observations: 60
Variable Coefficient Std. Error t-Statistic Prob.
C -0.010978 0.004512 -2.432994 0.0181
X1 0.381592 0.123978 3.077900 0.0032
X2 -0.000586 0.000887 -0.660724 0.5115
R-squared 0.142669 Mean dependent var -0.011012
Adjusted R-squared 0.112587 S.D. dependent var 0.036939
S.E. of regression 0.034797 Akaike info criterion -3.829852
Sum squared resid 0.069018 Schwarz criterion -3.725135
Log likelihood 117.8956 F-statistic 4.742714
Durbin-Watson stat 0.862207 Prob(F-statistic) 0.012437
Descriptive Statistics
Y X1 X2 X3
Mean 0.019215 -0.000831 -0.483316 -0.011012
Median 0.024407 -0.003781 -0.076498 -0.007476
Maximum 0.306532 0.172425 9.000000 0.130793
Minimum -0.340247 -0.098840 -35.00000 -0.105425
Std. Dev. 0.099661 0.037145 5.192304 0.036939
Skewness -0.521612 1.717417 -5.028711 0.705108
Kurtosis 5.198717 10.70772 34.36123 6.116995
Jarque-Bera 14.80669 178.0175 2711.697 29.26092
Probability 0.000609 0.000000 0.000000 0.000000
Sum 1.152927 -0.049875 -28.99897 -0.660716
Sum Sq. Dev. 0.586010 0.081406 1590.641 0.080504
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Normality Test
0 2 4 6 8 10 12 14
-0.1 -0.0 0.1 0.2
Series: Residuals
Sample 2006M01 2010M12 Observations 60
Mean 6.94e-19 Median 0.001880 Maximum 0.238803 Minimum -0.167392 Std. Dev. 0.079104 Skewness 0.363828 Kurtosis 3.382237 Jarque-Bera 1.688972 Probability 0.429778
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1
CHAPTER 1
INTRODUCTION
A. Background
Investment is the commitment of money or capital to the purchase of
financial instruments or other assets so as to gain profitable returns in the form of
interest, income (dividends), or appreciation (capital gains) of the value of the
instrument (Sullivan,2003). It is related to saving or deferring consumption.
Investment is involved in many areas of the economy, such as business
management and finance no matter for households, firms, or governments.
Investment comes with the risk of the loss of the principal sum. The investment
that has not been thoroughly analyzed can be highly risky with respect to the
investment owner because the possibility of losing money is not within the
owner's control. The fundamental principle of investment‟s risk is the more risks
possible, the higher return we receive. The level of risk, especially in Indonesian
Capital Market is mainly affected by economics and political factors. Therefore,
to make an investment decision, investors need to be carefully analyzing the
investment‟s instrument they are most likely to choose. This analysis aims to
minimize the risk of the investment.
According to Bodi, Kane, and Marcus (2007, p.112) in their books “Investment”, there are two types of risks that commonly faced by the investor when investing
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2
their money; systematic and unsystematic risk. Interest rates, recession and wars
all represent sources of systematic risk because they affect the entire market and
cannot be avoided through diversification. While unsystematic risk is company or
industry specific risk that is inherent in each investment. Systematic risk can be
mitigated only by being hedged, while unsystematic risk can be reduced through
appropriate diversification.
Analyses of the financial markets are broadly divided between two schools of
thought; fundamental and technical analysis (Graham, et al: 1999). Fundamental
analysis is a method of evaluating the intrinsic value of a company, and hence the
share price, by researching and examining the corporate financial statements, the
business itself, industry outlook and so on. Conventional wisdom dictates that the
price of a stock that is trading for less than its intrinsic value should rise and the
price of a stock that is trading for higher than its intrinsic value should fall
(Chong, 2006). On the other hand, Technical analysis is a method of evaluating
future price of a stock based on statistical analysis of past behaviors of the stock.
Behaviors of stock include trading volume, moving averages, price trends and
other types of charts. Technical analysis assumes that the price chart frequently
anticipates news and other fundamental events before they become public
knowledge. It is used by market analysts to identify the beginning of an uptrend,
entry point, beginning of a downtrend and the exit point.
After the financial crisis hit Indonesia in 1998, the macroeconomic condition of
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3
investor prefers investing in the form of deposit rather than in stock market.
Inflation also rose and thus makes the exchange rate of Indonesian Rupiah to US
dollar dropped. On the article publish by daily news agency Reuters1, this
condition is likely to be happened again in 2008. This crisis is the effect resulted
from subprime mortgage case in US in 2007. The immediate cause or trigger of
the crisis was the Fed policy to decrease the interest rate which peaked in
approximately 2005–2006 (Lahart, 2007). Already-rising default rates on "subprime" and adjustable rate mortgages (ARM) began to increase quickly
thereafter. As banks began to increasingly give out more loans to potential home
owners, the housing price also began to rise. In the optimistic terms the banks
would encourage the home owners to take on considerably high loans in the belief
they would be able to pay it back more quickly overlooking the interest rates.
Once the interest rates began to rise in mid 2007 the housing price started to drop
significantly in 2006 leading into 2007. In many states like California refinancing
became more difficult. As a result the number of foreclosed homes began to rise
as well.
The Global Financial Crisis brings a negative impact of other countries, and
Indonesia is one that is affected also. Based on the report publish by Bank
Indonesia, during this crisis, the exchange rates of Indonesian Rupiah to US dollar
1 Three top economists agree 2009 worst financial crisis since great depression;
risks increase if right steps are not taken. (February 29, 2009). Reuters.
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4
decline significantly to Rp 12,000/ US$. On October 9-10 2008, many stocks in
Jakarta Stock Exchange are being suspended because of market‟s overreaction. It seems like the Financial Global Crisis will harm the economic conditions of a
country, as well as its stock market.
The unstable macroeconomic conditions could affect the stock price in a stock
market. According to Bodi, Kane, and Marcus (2007 P.226) in their books
“Investment” the macroeconomic factors that affect the stock price are; interest rate, inflation, and exchange rate. The stock price that is influenced by the cyclical
factors such as stock on property and real estate industries will be affected more
than the stock price on the other industries that is not influenced by cyclical
factors, such as consumption goods industries.
The interest rate influences the choice of investment choosed by investor. The
raise of interest rate makes investor tend to invest their money in the form of
deposit, rather than in stock market which has higher risk. The higher rate of
interest will bring a negative significant effect to the property and real estate
sector because it depends on the mortgage. In contradictory, if the interest rates
fell, and the mortgage also fell, the willingness of investor to buy property is
raised. This happens in United States when the Fed decreases their interest rate
and triggers the people to buy houses with lower mortgage. This condition makes
the performance of property and real estate sector increase, because the amount of
houses sold are also increased. However, when the Fed increases back the interest
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makes the performance of the property and real estate sector declining.
Fundamentally, the decreasing performance of a company will lead to the
decreasing of its stock price in the stock market.
Inflation, as an unpredictable macroeconomic indicator also influences the
performance of the stock in the market. Inflation is the raise of overall goods and
services in an economy over period of time (Mankiw, 2007). The raise of overall
goods and services will create the declining demand of secondary and tertiary
product, such as property and real estate, because the people will try to fulfill their
basic needs first. This makes the stock price on property and real estate sector will
be more affected than the stock price on consumption goods, theoretically.
The exchange rate of Indonesian Rupiah to US Dollar depreciated when the crisis
occurred. This condition caused a huge damage to major industries in Indonesia,
especially for those who finance their company by borrowing fund from foreign
country. They have to pay more for their debt and this will make the performance
of their company weaken and thus make their stock prices decrease. Exchange
rate also influences the foreign investor‟s decision to invest their money in
Indonesian stock market. Foreign investors are allowed to invest their money in
certain limitation. When the exchange rates change, foreign investor must rethink
their decision to invest carefully and this will influence the stock price as a whole.
As the condition described above, this research try to examine the macroeconomic
factors, especially interest rate, inflation, and exchange rate, that will influence the
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stock which less influenced by cyclical factors. This research aims to help investor
to make the best decision regarding the choice of stocks when the economic
condition is unstable.
B. Problem Formulation
A country‟s capital market plays a significant role in determining the
growth of that particular country. There are many research conducted in various
countries, using various types of data to prove that theory, which later will be
explored on the next part of this research. But so far the result of this study is still
inconclusive. Every market is different and dynamic and that makes some
researches resulted in the opposite way of theory. The choice of method analysis
also influences the result of the research. Therefore, the writer desires to prove the
negative effect of macroeconomic factors, such as interest rate, inflation, and
exchange rate to the stock return in Indonesia‟s capital market.
This research chooses the property and real estate sector and consumer goods
sector as the object of research. The reason behind this choice is because both
sectors differ in terms of the level of cyclical factors‟ influence. Consumer goods
are become the sample of this research because this sector are less likely to be
influenced by cyclical factors so it can be a good comparator to the property and
real estate sector, which is considerably more influenced by cyclical factors.
Based on the two factors, we will see how macroeconomics variables affect the
performance of the stock on consumption goods sector and property and real
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Based on the consideration above, this research aims to answer these following
questions:
1. How the interest rate, inflation, and exchange rate are influences the
performance of a stock on consumption goods and property and real estate
sector in Indonesia stock exchange?
2. How much the influence of interest rate, inflation, and exchange rate
affected the performance of stock on consumption goods and property and
real estate sector in Indonesia stock exchange?
C. Research Objectives
The objectives of this research are:
1. To identify the influence of interest rate, inflation, and exchange rate to the
performance of stock on consumption goods sector and property and real
estate sector in Indonesia stock exchange.
2. To determine the extent to which interest rate, inflation and exchange rate
influence the performance of stock on consumption goods sector and
property and real estate sector in Indonesia stock exchange.
D. Usefullness of the Research
In general, this research is expected to provide the significant contribution to investors especially the individual investors to have new insights regarding the
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perfect time to invest in the capital market given a current macroeconomic circumstances. This eventually will help investor in obtaining their investments‟ risks manageable, which eventually will help in the improvement of the social economics circumstances. Specifically, the benefits of research is diveded into three scope of areas, which are:
1. For the Author
As for the author, this research is expected to enrich the author‟s knowledge about investment in capital market, as well as macroeconomic
knowledges. This reserach is also expected to become a medium to
implement lessons learned during the author‟s study in the university. 2. For the Investor
As for the investor, this research attempts to help investor in increasing
their knowledge about macroeconomic condition before they choose to
invest in the capital market. By examining the condition, investors could
forecast their return in capital market. Thus, this is expected to help
investor minimize the risk of their investmrnt.
3. For academic purposes
This research aims to add the literature study for investor who wishes to
know the influence of macroeconomic factors, such as interest rate,
inflation, and exchange rate to the rate of return in consumption good
stocks and property and real estate stock. This study can be used as a
consideration before selecting the most appropriate stock for investor.
Also, This research aims to add understanding for other researcher who
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9
CHAPTER 2
LITERATURE REVIEW
A. Fundamental of Capital Market
1. History of Indonesian Capital Market
The capital market in Indonesia has actually existed long before the
Independence of Indonesia. The first stock exchange in Indonesia was established
on 1912 in Batavia during the Dutch colonial era. At that time, the exchange was
established for the interest of the Dutch East Indies (VOC).
During that era, the capital market grew gradually, and even became inactive for a
period of time due to various conditions, such as the World War I and II, power
transition from the Dutch government to Indonesian government, etc.
Indonesian government reactivated its capital market in 1977, and it grew rapidly
ever since, along with the support of incentives and regulations issued by the
government.
The milestone of Indonesian capital market occurred in 2007, where Surabaya
Stock Exchange merged with Jakarta Stock Exchange and thus change the name
to become Indonesia Stock Exchange (IDX). This merger is expected to boost the
performance of Indonesian capital market in the future2.
2
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2. Capital Market Definition
The Capital Market is a market for several long-term investment
instruments which can be traded, whether in the form of debt or self-own capital
(equity) (Darmadji and Hendy, 2001). Capital market enables corporations to
issue the security in the form of certificate of indebtedness (bond) or the
certificate of ownership (stock). Through the existence of capital market, this
would be possible for the parties who has surplus of fund (lender) to move their
fund to another parties who are deficit in fund (borrower). The parties who have
the surplus of fund can invest their money to the parties who are deficit with the
expectation to get the return, while the issuer (in this case the corporate) can
utilize the fund for its interest to make its business growth without depending on
the operational activity of the corporate.
Capital market has many advantages which can be categorized as economic
advantage and financial advantage. On the economic side, capital market is
expected to boost economic activity because capital market is becoming a funding
alternative for the corporations so that the corporations can operate in the higher
scale which eventually can increase its revenue and prosperity of the society.
While in the financial side, capital market is expected to become the source of
financing (long term) for the corporations and enable investor to diversify its
investment.
3. Capital Market Instrument
Stock exchange instrument consist of promissory notes that can be traded
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Indonesia Stock Exchange (IDX) are classified into three types; stocks, bonds, and
rights3.
a) Stock
The capital stock of a business entity represents the original capital paid
into or invested in the business by its founders. Stock typically takes the
form of shares of either common stock or preferred stock. As a unit of
ownership, common stock typically carries voting rights that can be
exercised in corporate decisions. They include the right to receive dividend
payments typically from earnings, if authorized by the board of directors
and the power to sell the stock (liquidity rights) and realize capital gains
on public trading markets or in private transactions. On the other hand,
preferred stock differs from common stock in that it typically does not
carry voting rights but is legally entitled to receive a certain level of
dividend payments before any dividends can be issued to other
shareholders.
b) Rights
Rights are the right given to the old shareholder to buy new additional
shares issued by a particular company.
3
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c) Bond
Bond is a debt security, in which the authorized issuer owes the holders a
debt and, depending on the terms of the bonds, is obliged to pay interest
(the coupon) and/or repay the principal at later date, termed maturity. A
bond is a formal contract to repay borrowed money with interest at fixed
intervals.
B. Investment
Investment is putting money into something with the hope of profit. More
specifically, investment is the commitment of money or capital to the purchase of
financial instruments or other assets so as to gain profitable returns in the form of
interest, income (dividends), or capital gain appreciation of the value of the
instrument (Sullivan, 2003). It is related to saving or deferring consumption.
Investment is involved in many areas of the economy, such as business
management and finance no matter for households, firms, or governments. An
investment involves the choice by an individual or an organization, such as a
pension fund, after some analysis or thought, to place or lend money in a vehicle,
instrument or asset, such as property, commodity, stock, bond, financial
derivatives (e.g. futures or options), or the foreign asset denominated in foreign
currency, that has certain level of risk and provides the possibility of generating
returns over a period of time (Graham et al., 1991).
Investor usually assesses their risk before making an investment decision. They
assess the expected profitability return they will earn from the investment. In the
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investor. There are many factors that make investment‟s return somehow
unpredictable. Because of these factors, investor needs to make a comprehensive
analysis before they make an investment decision to minimize the risks. The
analysis could be a fundamental analysis or technical analysis.
Generally, there are two different styles and types of investors that exist in the
stock market; investors use the stock market to build their investment portfolio so
that they can see a long term profit that takes place over a long period of time, and
investor who just using the stock market to make money quickly for a short period
of time, which is called a "trader". The first type of investor has a short term
orientation while the second type has a long term orientation.
Investor in capital market must analyze the factors that could influence the change
of stock price. Stock prices definitely change over the course of time. Some can
increase rapidly and make investors a fortune, whereas others can lose a lot of
value quickly and bankrupt investors. Stock prices change because of the
economics of market forces, and the supply and demand for the stock (Coleman,
2006). This is all based on personal perception. If people think that a company
will do better in the future, this will raise the demand and price of the stock, and if
they think a company will do worse, this will lower the demand and price of the
stock.
The change of stock price is influenced by many factors. Some studies have
concluded that company fundamentals such as earning and valuation multiple are
major factors that affect stock prices. Other indicated that inflation, economic
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most influencing factors of stock prices (Bodie, 2007). News or information also
affects the change in stock price. Positive news about a company can increase
buying interest in the market while a negative press release can ruin the prospect
of a stock. Nevertheless, investor could not only rely on the news when
attempting to predict stock price. It is the overall performance of the company
that matters more than news. It is always wise to take a wait and watch policy in a
volatile market or when there is mixed reaction about a particular stock.
In capital market, there is term named „market efficiency concept‟ which
mentions the degree to which stock prices reflect all available and relevant
information. In 1900, Louis Bachelier made an important contribution to the
formalism of classical economics with a theory that says trading strategies based
only on observed price changes cannot succeed. Markets are moved by news and
since, by definition, news cannot be predicted (or it would not be news), price
movement cannot be anticipated. Consequently, price data are not linked and price
series follow a geometric Brownian random walk, whereby market prices are
log-normal distributed, i.e. the differences of the logarithms of prices are Gaussian
distributed.
There are three categories of market efficiency concept (Elton, et al: 2007)
1. Weak Form Efficiency: In this form of market efficiency, no investor can
earn excess returns by developing trading rules based solely on historical
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2. Semi-Strong Form Efficiency: In this form of market efficiency, no
investor can earn excess returns from using trading rules based on any
publicly available information.
3. Strong Form Efficiency: In this form of efficiency, no investor can earn
excess returns using any information whether publicly available or not.
As every casual follower of financial news knows, stock prices rise and fall in
response to earnings and revenues (Yee, 2001). Positive information regarding
expected Earnings per Share (EPS) will boost the stock price and vice versa.
C. Stock Rate of Return
Capital Market Theory explains the behavior of investor in making an
investment decision. Investor will consider two most important factors when
making an investment decision; risk and return. A stock‟s rate of return is gained from the dividend paid annually or capital gain or margin from the purchase-sell
activity.
Chris Brooks (2002 p.154) in his book, Introductory of Econometrics for Finance
explain two methods in calculating return gained from capital gain margin; simple
return and continuously compounded returns. The formula of each method is as
follows:
Simple returns:
�
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Continuously compounded return
(2.2)
Where,
Rt = Simple returns on t period
rt = Continuously compoundedreturns on t period
Pt = Stock Price on t period
Pt-1 = Stock Price on t-1 period
Investor will make an investment decision to buy a particular stock if a stock‟s
rate of return forecasted to be increased in the future. In this condition, investor
will gained more return than they‟re required rate of return. When a stock‟s return
is predicted to up, it will increase the demand from investor to that particular stock
and automatically increase the stock price. On the other hand, when a stock‟s
return is predicted to decrease, it will also decrease the demand from investor to
that particular stock and resulted in the decrease of stock price as well. Investor
will tend to sell the stocks which not meet their required rate of return. Here we
can see a linear correlation between a stock‟s rate of return and stock‟s price. D. Risks
Despite considering a stock‟s return, investor who wishes to invest their
money on capital market must also define the risk of the stock. In one definition,
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present problems that must be immediately addressed (Hubbard, 2009). While
others said that risk is the uncertainty about rate of return in the future (Bodie et
al: 2007). Risks that faced by investors are strongly related to the fluctuation of
stock price. According to Yan Yee Chong (2006, p. 75) in his books Investment
Risk Management, risks are classified into several types:
a. Business Risk
Business risk is the potential for loss of value through competition,
mismanagement, and financial insolvency. There are a number of
industries that are predisposed to higher levels of business risk (airlines,
railroads, steel, etc).
b. Credit and Country Risk
Credit risk is the risk that firm unable to deal with its obligations, and
therefore the asset will become unprofitable. Country risk refers to the risk
that a country will change the rules under which its financial system
operates in some way that affects that country‟s native financial instrument
and assets; country risk is also known as political risk.
c. Interest
The raise of interest rate will decrease the demand of stocks investment
because people will prefer to invest in the form of deposits. This resulted
in the decreasing of stock price.
d. Market Risk
Market risk is risk associated with daily fluctuations in stock price. Market
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are likely to fluctuate greatly in stock price, whereas assets with low
volatility are more immune to fast, large price changes. Volatility is
important in the stock world for a variety of reasons. The more volatile a
stock, the more potential for profit there may exist (which is why some
investors focus on identifying growth stocks, which have the capability for
explosive growth), but at the same time, there is also the possibility of
dramatic loss. The less volatile the investment, the less on average the
return will be to that investment.
e. Liquidity Risk
The final type of risk associated with stock market transactions is liquidity
risk. Liquidity risk refers to risk that the stock will not be able to be traded
fast enough to avoid or loss or capitalize on a potential profit. Liquidity
risk can be avoided by making sure the daily volume of share trading is
above a certain level.
Generally, risk is calculated by the deviation of the actual return from the required
rate of return (expected return) as a result of success/failure of an investment. Risk
of a stock can be measured by its variance or standard deviation. With the risk of
uncertainty, investors not only need to calculate the return of a stock but also the
risks associated with it.
There are two types of risks that commonly faced by the investor when investing
their money; systematic and unsystematic risk. Interest rates, recession and wars
all represent sources of systematic risk because they affect the entire market and
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industry specific risk that is inherent in each investment. Systematic risk can be
mitigated only by being hedged, while the amount of unsystematic risk can be
reduced through appropriate diversification.
E. Inflation
In economics, inflation is a rise in the general level of prices of goods and
services in an economy over a period of time (Blanchard, 2000). The rise of
general prices of goods and services does not merely caused inflation if it is only
happen in a moment of time. Therefore, inflation is at least measured by monthly
basis. If in one month the rise of general price of goods and services are
continuously, a country can be claimed to have an increase in inflation rate.
Inflation rate is the percentage change in the price index from the preceding
period (Mankiw, 2007). Another longer period to measure inflation is by yearly,
or quarter-yearly basis. Still According to Mankiw in his books, Theory of
Macroeconomic, there are several macroeconomic indicators that can be used to
measure an inflation rate within a period;
a. Consumer Price Index (CPI)
The consumer price index is a measure of the overall costs of the goods
and services brought by a typical consumer. Inflation rate can be measured
by applying the following formula:
� � � �
(2.3) b. Wholesale Price Index
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If consumer price index measure inflation rate from the perspective of the
consumers, wholesale price index measure inflation rate from the
perspective of the producers. Wholesale price index measures the cost of a
basket of goods and services. Inflation rate can be measured by applying
the following formula:
�
(2.4)
c. GDP Deflator
Two previously discussed indicators have some limitation in measuring
inflation rate. Both indicators only measure some goods and services in
some cities, and it does not reflect the overall goods and services produced
and consumed within a country. Therefore, economist uses GDP deflator
to measure inflation rate more precisely. GDP Deflator is the ratio of
nominal GDP to real GDP. Because nominal GDP is current output valued
at current prices and real GDP is current output valued at base-year prices,
GDP deflator reflects the current level of prices relatives to the level of
prices in the base year. Interest rate calculation using GDP deflator can be
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� � � �
(2.5) Theoretically, inflation has a negative relationship with the stock return. This
phenomenon is caused by:
a. Cost-push inflation
When the cost of production increases, a company‟s ability to fulfill the
demand from the customer is decrease. This will cause an aggregate
supply. Aggregate supply is the total volume of goods and services
produced by an economy at a given price level. When there is a decrease
in the aggregate supply of goods and services stemming from an increase
in the cost of production, cost-push inflation occurred. Cost-push inflation
basically means that prices have been “pushed up” by increases in costs of
any of the four factors of production (labor, capital, land or
entrepreneurship) when companies are already running at full production
capacity. With higher production costs and productivity maximized,
companies cannot maintain profit margins by producing the same amounts
of goods and services. As a result, the increased costs are passed on to
consumers, causing a rise in the general price level (inflation).
b. Demand-pull inflation
Demand-pull inflation occurs when there is an increase in aggregate
demand, categorized by the four sections of the macroeconomic:
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sectors concurrently want to purchase more output than the economy can
produce, they compete to purchase limited amounts of goods and services.
1. Relationship between inflation and stock return
Inflation influences the purchasing power of the individuals in some
extend. Brealey and Meyer (2000) exposes that inflation has a negative
inlfluences to the stock performance in capital market. When inflation rate
increase, the price of overall goods and services increase as well. Thus will make
individuals loose their ability to invest in capital market. They prefer to fulfill
their basic needs first before making an investment. The capital matket will suffer
because of this condition. The price of overall stocks in the capital market will
decrease and thus make the return of the stock decrease as well.
F. Interest Rate
According to Mankiw (2007, p. 297), an interest rate is the rate at which
interest is paid by a borrower for the use of money that they borrow from a lender.
It is consist of two types, real and nominal interest rate. In finance and economics
nominal interest rate or nominal rate of interest refers to the rate of interest before
adjustment for inflation (in contrast with the real interest rate); or, for interest
rates "as stated" without adjustment for the full effect of compounding (also
referred to as the nominal annual rate). An interest rate is called nominal if the
frequency of compounding (e.g. a month) is not identical to the basic time unit
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rate minus the inflation rate. It is the rate of interest an investor expects to receive
after subtracting inflation.
The relationship between real and nominal interest rates can be described in the
equation (Brealey and Meyer, 2000)
�
(2.6)
Where r is the real interest rate, i is the inflation rate, and R is the nominal interest
rate.
1. Relationship between interest rate and stock return
Interest rate are important variables in for macroeconomic to understand
because they link the economy of the present and the economy of the future
through their effects on saving and investment (Mankiw, 2007 p.369). Keynes
reanalyzed about the effect of interest rate on investment decision. The increase of
interest rate could increase the exchange rate, but this can make the price of stock
decrease. Keynes also stated the negative relationship between interest rate and
stock price. This happen because if the interest rate increases, people tend to
invest their money in the form of deposit, and thus make investment in capital
market weakened.
The relationship between interest rate and investment decision also explained by
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interest rate increase, the cost of investment will increase and thus make
company‟s profit decrease. A decrease in profit will make a dividend for the
stockholder decrease too, which affected the stock price to be decreasing as well.
2. SBI (Bank Indonesia Certificate) Rate
In the past two centuries, interest rates have been variously set either by
national governments or central banks. In Indonesia, the interest rate is set by the
Central Bank of Indonesia, namely BI rate. The SBI Rate is announced by the
Board of Governors of Bank Indonesia in each monthly Board of Governors
Meeting. It is implemented in the Bank Indonesia monetary operations conducted
by means of liquidity management on the money market through SBI Rate to
achieve the monetary policy operational target.
The monetary policy operational target is reflected in movement in the Interbank
Overnight (O/N) Rate. It is then expected that bank deposit rates will track the
movement in interbank rates, with bank lending rates following suit.
While other factors in the economy are also taken into account, Bank Indonesia
will normally raise the BI Rate if future inflation is forecasted ahead of the
established inflation target. Conversely, Bank Indonesia will lower the BI Rate if
future inflation is predicted below the inflation target.
The benchmark interest rate in Indonesia was last reported at 6.50 percent. In
Indonesia the interest rate decisions are taken by The Central Bank of Republic of
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central banks lend or discount eligible paper for deposit money banks, typically
shown on an end-of-period basis. From 2005 until 2010, Indonesia's average
interest rate was 8.76 percent reaching an historical high of 12.75 percent in
December of 2005 and a record low of 6.50 percent in August of 2009. The graph
below represents the interest rate in Indonesia from December 2005 to August
2009.
Figure 2.1 (Indonesia Interest Rate)
G. Exchange Rate
According to Jeff Madura (2007, p.78), exchange rate between two
countries specifies how much one currency is worth in terms of the other. It is the
value of a foreign nation‟s currency in terms of the home nation‟s currency.
According to traditional approach, exchange rates lead stock prices. This approach
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since a decrease in stock prices reduces domestic wealth, which leads to lower
domestic money demand and interest rates (Aydemir and Demirhan, 2009). Also,
the decrease in domestic stock prices leads foreign investors to lower demand for
domestic assets and domestic currency. These shifts in demand and supply of
currencies cause capital outflows and the depreciation of domestic currency. On
the other hand, when stock prices rise, foreign investors become willing to invest
in a country‟s equity securities. Thus, they will get benefit from international
diversification. This situation will lead to capital inflows and a currency
appreciation (Granger et al. 2000;Pan et al. 2007).
Exchange rates can affect stock prices not only for multinational and export
oriented firms but also for domestic firms. For a multinational company, changes
in exchange rates will result in both an immediate change in value of its foreign
operations and a continuing change in the profitability of its foreign operations
reflected in successive income statements. Therefore, the changes in economic
value of firm‟s foreign operations may influence stock prices. Domestic firms can
also be influenced by changes in exchange rates since they may import a part of
their inputs and export their outputs. For example, a devaluation of its currency
makes imported inputs more expensive and exported outputs cheaper for a firm.
Thus, devaluation will make positive effect for export firms (Aggarwal, 1981) and
increase the income of these firms, consequently, boosting the average level of
stock prices (Wu, 2000).
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Stock return will get effected by the fluctuation of exchange rate in a
country (Wu, 2000). When the exchange rate fluctuates, foreign investor
will get atrratcted to invest their money in capital market. Thus will make
the price of stock corrected.
H. Previous Research
In 2004, Maysami, et al. made a research about relationship between selected macroeconomic variables and the Singapore Stock Market Index (STI),
as well as with various Singapore Exchange Sector Indices-the finance index, the
property index, and the hotel index. This research used VCEM model proposed by
Johansen(1990) which allows for testing cointegration in a whole system of
equations in one stop, without requiring a specific variable to be normalized. The
research‟s data is the monthly time-series which is obtained from the PublicAccess Time-Series system, an online service by the Singapore Department
of Statistics. And the SES All-S Equities indicies figures are obtained from the
Singapore Statistics published by the Singapore Department of Statistics. The
study concludes that the Singapore‟s stock market and the property index form cointegrating relationship with changes in the short and long-term interest rates,
industrial production, price levels, exchange rate and money supply
(macroeconomics variables).
Gay (2008) conducted a research about effect of macroeconomic variables on stock market return for four emerging economies: Brazil, Russia, India and China.
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moving-averages at the one-month MA(1), three-month MA(3), six-month
MA(6), and twelve-month MA(12) for the lagged dependent of stock market price
and the two intervening variables of exchange rate and oil price. Available
monthly data for stock market price index, exchange rate, and oil price between
1999:03 to 2006:06 for Brazil, Russia, India, and China from the Organization for
Economic Cooperation and Development (OECD) is used in this study, which
will provide 90 observations per variable for each BRIC for a total of 1,080
observations. This study concludes that no significant relationship was found
between respective exchange rate and oil price (Macroeconomic variables) on the
stock market index prices of either BRIC country, this may be due to the influence
other domestic and international macroeconomic factors on stock market returns,
warranting further research. Also, there was no significant relationship found
between present and past stock market returns, suggesting the markets of Brazil,
Russia, India, and China exhibit the weak-form of market efficiency.
Wan Mahmood (2009) from Universiti Teknologi Mara Trengganu, Malaysia, examine the dynamics relationship between stock prices and economic variables
in six Asian-Pacific selected countries of Malaysia, Korea, Thailand, Hong Kong,
Japan, and Australia. The monthly data on stock price indices, foreign exchange
rates, consumer price index and industrial production index that spans from
January 1993 to December 2002 are used. This study performed two cointegration
tests of Engle and Granger (1987) and Johansen and Juselius as his method. The
results indicate the existing of a long run equilibrium relationship between and
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Australia. As for short run relationship, all countries except for Hong Kong and
Thailand show some interactions. The Hong Kong shows relationship only
between exchange rate and stock price while the Thailand reports significant
interaction only between output and stock prices. An accurate estimation of these
relationships enables investors to make effective investment decisions. At the
same time, it helps policy makers in designing policies to encourage more capital
inflows into the respective countries‟ capital market.
Pakistani scholar, Ahmad et al. (2010) performed a study that examines the relationship between stock return, interest rate and exchange rates in Pakistani
economy. For this, the data of short term interest rate, exchange rate (Rs/US $)
and stock market returns (KSE-100) over the period of 1998-2009 is collected. A
multiple regression model is applied to test the significance of change in interest
rate and exchange on stock returns. The results show that both the change in
interest rate and change in exchange rate has a significant impact on stock returns
over the sample period.
Kandir (2008) investigates the role of macroeconomic factors in explaining Turkish stock returns. A macroeconomic factor model is employed for the period
that spans from July 1997 to June 2005. Macroeconomic variables used in this
study are, growth rate of industrial production index, change in consumer price
index, growth rate of narrowly defined money supply, change in exchange rate,
interest rate, growth rate of international crude oil price and return on the MSCI
World Equity Index. This study uses data for all non-financial firms listed on the
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77 B. Implication of Study
1. For the Investor
As for the investor, this researcher is expected to add information for the investor as their considerations when choosing investment, especially in the capital market. Investors must aware of the macroeconomic conditions in a country which could influence the performance of the stocks before deciding to choose the investment instrument in order to minimize risks. When a country‟s economic condition seem to be unstable, investors must be aware of their choice of investment especially in the capital market.
2. For the Business Player
The business player must carefully examined the real macroeconomic condition before they decided to do their Initial Public Offering (IPO) in the capital market. Business player must be able to forecast the macroeconomic condition which will effect the performance of the stock price of their company. When economic is doing good, the stock price will get the positive influence and vice versa.
3. For the Researcher
As for the researcher, this research is expected to add literatures study in these topics. However, the writer suggest the future researcher to complete this research by using more sectors as sample to get the better model of how those macroeconomic variables influence the capital market as a whole.
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78 C. Limitation
The writer realizes that there are still many limitation of this study. This research is not using the individual samples of a company, and so the results of this research describe a general condition of a sector, and not focusing on the companies on that sector specifically. This research only highlights the macroeconomic factors that influence the return, and not focusing on the micro factors of company individually.
This research is also only using 2 sectors, as a comparison of one to each other. If this research use more sectors, perhaps this research could provide a better description of the influence of macroeconomic factors (exchange rate, inflation rate, and SBI rate) to the performance of the stock in Indonesian capital market. At the end, the writer wishes that the lack of this research could be improved by another researcher in the future.
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