BETA CALCULATION ALTERNATIVES USING IHSG AND LQ45 ON PROPERTY AND REAL ESTATE, FINANCE, MINING AND MISCELLANEOUS SECTORS JSX CASE: 2002 – 2006
FINAL PROJECT
By Aryo Fajar Syaifulloh 19004105
Undergraduate Program School of Business and Management Institut Teknologi Bandung
ARYO FAJAR SYAIFULLOH 19004105 Date of Final Examination: August 10th, 2007 Date of Graduation: October 27th, 2007 Undergraduate Program, Institut Teknologi Bandung, 2007 Thesis Advisor: Deddy P. Koesrindartoto, Ph.D
ABSTRACT
Stock is one of the investment facilities that many investors are interested about. The stock’s value is dynamically fluctuated, therefore stock can be counted as a high risk investment and expected to gain high profit also. The whole stocks movement/fluctuation is represented by a market index which is called IHSG. Besides IHSG there is a market index, that only consisted by the top 45 of the most liquid stock and which had has a big market share, called LQ 45. In this final project, both IHSG and LQ45 becomes an indicator to determine the expected return of a sectoral stock. It is interesting to know which market index that can be used to determine the expected return of a sectoral stock more precise, IHSG or LQ45? Because by knowing the better option, not only investor could minimize the risk that would be taken but also could maintain the expected return at a high point. To reveal that matter above, in this final project, hypothesis testing are being done by taking the data from time series method with a CAPM approach on the daily closing price of a sectoral stocks of mining, property and real estate, finance and miscellaneous for the January 2002 to December 2006 period. From the calculated results, it is shown that both market index, IHSG and LQ45, can be used to determine the expected return of property and real estate stock. For finance and miscellaneous, LQ45 could determine better than IHSG and on the contrary, IHSG determine better than LQ45 on the mining sector. For the further research, it is recommended to perform a research that concern more about individual stocks that are followed with analysis, including market capitalization and volume, and also to review how far this research method (CAPM) can be used to determine the expected return if there are more data is being added, is there any change or not.
Keywords: Capital Asset Pricing Model (CAPM), Beta ( ), Volatility, Expected Return, IHSG, LQ45 Index.
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ARYO FAJAR SYAIFULLOH 19004105 Tanggal Ujian Akhir: 10 Agustus 2007 Tanggal Wisuda: 27 Oktober 2007 Program Sarjana, Institut Teknologi Bandung, 2007 Pembimbing: Deddy P. Koesrindartoto, Ph.D
ABSTRAKSI
Saham merupakan salah satu sarana investasi yang banyak diminati oleh para investor. Value dari saham berfluktuatif sangat dinamis. Oleh karena itu, saham tergolong investasi yang beresiko tinggi yang diharapkan membawa profit yang besar pula. Pergerakan keseluruhan saham direpresentasikan oleh sebuah indeks pasar yang disebut IHSG. Selain IHSG terdapat pula indeks pasar yang hanya terdiri dari 45 saham terlikuid dan memiliki pangsa pasar yang besar yaitu LQ45. Dalam penulisan tugas akhir ini, kedua indeks pasar ini menjadi indikator untuk menentukan perkiraan keuntungan pada sebuah saham sektoral. Merupakan hal yang menarik untuk mengetahui indeks pasar manakah yang dapat memperkirakan keuntungan sebuah saham sektoral yang lebih tepat, apakah IHSG atau LQ45. Karena dengan mengetahui hal tersebut, investor dapat meminimasi resiko yang dihadapi dan diharapkan keuntungan yang didapat tetap tinggi. Untuk mengetahui hal tersebut, dalam penulisan tugas akhir ini dilakukan penelitian uji hipotesis dengan mengambil data dari analisis waktu berkala dengan pendekatan CAPM terhadap harga penutupan saham sektoral pertambangan, properti dan real estate, keuangan, dan aneka industri per harinya selama periode Januari 2002 hingga Desember 2006. Hasil dari penghitungan yang dilakukan didapat bahwa untuk memperkirakan keuntungan saham properti dan real estate, kedua indeks pasar IHSG dan LQ45 sama-sama dapat digunakan. Untuk sektor keuangan and aneka industri, LQ45 memprediksi lebih baik dibandingkan IHSG. Sebaliknya, untuk sektor pertambangan, IHSG memprediksi lebih baik dibandingkan dengan LQ45. Untuk penelitian lebih lanjut, disarankan agar penelitian mengkaji lebih lanjut terhadap saham-saham individual dengan disertai analisis yang meliputi pangsa pasar dan volume dan juga mengkaji sejauh mana metode penelitian ini (CAPM) dapat dipergunakan untuk memperkirakan keuntungan dengan melakukan penambahan data, apakah terjadi perubahan pada hasil atau tidak.
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Kata Kunci: Capital Asset Pricing Model (CAPM), Beta ( ), Volatilitas, Perkiraan Keuntungan, IHSG, LQ45 Index.
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VALIDATION PAGE BETA CALCULATION ALTERNATIVES USING IHSG AND LQ45 ON PROPERTY AND REAL ESTATE, FINANCE, MINING AND MISCELLANEOUS SECTORS JSX CASE: 2002 – 2006
By: ARYO FAJAR SYAIFULLOH ID No: 19004105
Undergraduate Program School of Business and Management Institut Teknologi Bandung
Validated By
Deddy P. Koesrindartoto Ph.D NIP: 999 059 102 v
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PREFACE
Assalamu’alaikum Wr. Wb. First of all I would like to thank God for the never ending blessed so I can through all the processes in doing this final project. The final project is a requirement to fulfil the bachelor degree at School of Business and Management in Bandung Institute of Technology. The final project theme is Beta Calculation Alternatives Using IHSG and LQ45 on Property and Real Estate, Finance, Mining and Miscellaneous Sectors, JSX Case: 2002 – 2006. In doing this final project, there are a lot of contributions from many sides, so in this occasion I would like to give my special thanks to: 1. Mr. Deddy P. Koesrindartoto Ph.D as my supervisor who guide me a lot with the inputs, comments, discussions, knowledges and informations through this final project. Thank you very much for the time and the opportunity 2. Mrs. Trimulyati Budiman for the private interview. Thank you for the time and the opportunity 3. My family that never missed to support and encourage me all the time, Papa, Mama, Mba Arie, Mba Ewiq, Mas Doddy, Mba Tyas, Mas Is, Mas Manik, Mba Mala, Mas Berry, Manda, Bian, Dita, Chelsea and relatives especially Mas Kholiq for your time accompany me. Love you all 4. My beloved person, Astri and family and also Chi-G and Iyong for the support, discussion, knowledge especially about statistics and SPSS and the time through happy and sad moments and also her family that encourage me a lot
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5. Mr. Dedy Kurniawan, MSM student, thank you very much for your time in taught me about statistics and how to operate SPSS 13.0 software. 6. Budi, Hardi and Bedi as my housemate. Thank you for the support, discussion and all the moment that we have been through 7. Mr. Iwan for the SBI Rate data 8. Mr. Hanif for the sectoral stocks data 9. Jazzy that always accompanies and supports me. 10. Ardhi Agung Pradhana as my partners that gives a lot of information, sharing, discussion and comment to this final project 11. Intan Pramesti, Dimas Werhaspati, Widita Rarasati, Maharani Putri, Aryo Pratomo and all my SBM friends, thank you for the support and all the moments 12. My closest friends, Tito and Defri who always support me 13. SBM administration staff and librarian, Mr. Iwan, Mr. Yayad, Mrs. Ikum, Mr. Rajab and Mrs. Wiwik that help me a lot in supporting any documents needed 14. Mr. Juddy Mulyadi and Mrs. Eti that letting me working the final project at their house and also thank you for the delicious meal
I realize there still a lot of weaknesses in this final project, therefore needed criticism and suggestions. I hope this final project could give insight about Indonesian Capital Market. Bandung, August 5th, 2007 Aryo Fajar Syaifulloh
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LIST OF CONTENTS
ABSTRACT (ENGLISH)……………………………………….
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ABSTRAKSI (INDONESIA)…………………………………...
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VALIDATION PAGE…………………………………………...
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FOREWORD……………………………………………………
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LIST OF CONTENTS…………………………………………..
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LIST OF FIGURES……………………………………………..
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LIST OF TABLES………………………………………………
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LIST OF SYMBOLS……………………………………………
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LIST OF APPENDIXES………………………………………..
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CHAPTER I INTRODUCTION………………………………..
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1.1 Background………………………………………....
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1.2 Problem Identification……………………………...
2
1.3 The Importance of Problem Solving…………….....
3
1.4 Problem Limitation…………………………………
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1.5 Writing Sequence…………………………………..
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CHAPTER II LITERATURE STUDY………………………....
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2.1 Capital Asset Pricing Model (CAPM)……………..
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2.2 Risk-Free Interest Rate……………………………..
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2.3 Beta…………………………………………………
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2.4 Risk…………………………………………………
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2.4.1 Systemic Risk…………………………….
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2.4.2 Unsystemic Risk………………………….
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2.5 Diversification……………………………………...
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2.6 Covariance………………………………………….
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2.7 Variance……………………………………………
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2.8 Market Index……………………………………….
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2.8.1 Indeks Harga Saham Gabungan (IHSG)...
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2.8.2 Sector Indeces……………………………
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2.8.3 LQ45……………………………………..
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2.9 Statistical Theory…………………………………..
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2.9.1 T-test Hypothesis………………………...
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2.9.2 Simple Linear Regression………………..
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2.9.3 F-test Hypothesis (Upper-Tail Test)……..
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CHAPTER III METHODOLOGY…………………………….
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3.1 Flow Diagram Methodology……………………….
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3.2 Research Object Definition………………………..
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3.3 Problem Identification……………………………..
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3.4 Objectives………………………………………….
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3.5 Hypothesis Formulation…………………………....
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3.6 Literature Study…………………………………....
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3.7 Data Collection…………………………………….
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3.8 Data Analysis……………………………………...
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3.9 Test Hypothesis…………………………………....
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3.10 Conclusion and Recommendation……………......
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CHAPTER IV DATA COLLECTION AND ANALYSIS…….
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4.1 Data Collection……………………………………..
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4.1.1 Property and Real Estate Sector……….....
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4.1.2 Finance Sector…………………………....
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4.1.3 Mining Sector…………………………….
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4.1.4 Miscellaneous Sector…………………….
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4.1.5 IHSG……………………………………...
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4.1.6 LQ45 Index……………………………....
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4.1.7 SBI Rate………………………………….
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4.2 Data Analysis……………………………………....
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4.3 Data Output………………………………………...
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4.3.1 Output Property and Real Estate Sector....
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4.3.2 Output Finance Sector……………………..
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4.3.3 Output Mining Sector……………………..
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4.3.4 Output Miscellaneous Sector……………..
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4.4 Test Hypothesis……………………………………..
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4.4.1 Property and Real Estate Sector………….
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4.4.2 Finance Sector…………………………….
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4.4.3 Mining Sector……………………………..
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4.4.4 Miscellaneous Sector……………………..
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CHAPTER V CONCLUSION AND RECOMMENDATION...
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5.1 Conclusion………………………………………….
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5.2 Recommendation…………………………………...
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REFERENCES………………………………………………....
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APPENDIX
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LIST OF FIGURES
Figure 2.1 The Markowitz Efficient Frontier……………………..
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Figure 2.2 Types and Classifications of Risk…………………….
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Figure 2.3 Fu Rejection Areas…………………………………….
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Figure 3.1 Flow Diagram Methodology…………………………...
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Figure 4.1 Property and Real Estate Graph from January 2002 until December 2006………………………………………...
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Figure 4.2 Finance Graph from January 2002 until December 2006…………………………………………………….
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Figure 4.3 Mining Graph from January 2002 until December 2006…………………………………………………….
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Figure 4.4 Miscellaneous Graph from January 2002 until December 2006………………………………………...
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Figure 4.5 IHSG Graph from January 2002 until December 2006…………………………………………………….
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Figure 4.6 LQ45 Index Graph from January 2002 until December 2006…………………………………………………….
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Figure 4.7 SBI Rate Graph from January 2002 until December 2006…………………………………………………….
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Figure 4.8 ΔIHSG and ΔLQ45 Graph in Determining Expected Return in Property and Real Estate Sector Period January 2002 until December 2006…………………………………...
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Figure 4.9 ΔIHSG and ΔLQ45 Graph in Determining Expected Return in Finance Sector Period January 2002 until December 2006
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Figure 4.10 ΔIHSG and ΔLQ45 Graph in Determining Expected Return in Mining Sector Period January 2002 until December 2006………………………………………
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Figure 4.11 ΔIHSG and ΔLQ45 Graph in Determining Expected Return in Miscellaneous Sector Period January 2002 until December 2006…………………………………..
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LIST OF TABLES
Table 4.1 Summary Calculation from Sectoral and Market Indexes Actual Return on Mining Sector…………………………
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Table 4.2 Summary Calculation of Beta Calculation and Expected Return using IHSG and LQ45 on Mining Sector……….
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Table 4.3 Descriptive Statistic of IHSG and LQ45 data in Property and Real Estate Sector Period January 2002 until December 2006………………………………………….. 37 Table 4.4 Statistic Test Result of Mean Differences IHSG and
LQ45 in Property and Real Estate Sector Period January 2002 until December 2006………………………………
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Table 4.5 Model Fitness of IHSG and LQ45 in Property and Real Estate Sector Period January 2002 until December 2006.. 38 Table 4.6 Analysis Variance result of IHSG and LQ45 in Property and Real Estate Sector Period January 2002 until December 2006………………………………………….. 38 Table 4.7 Regression result of IHSG and LQ45 in Property and Real Estate Sector Period January 2002 until December 2006……………………………………………………...
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Table 4.8 Descriptive Statistic of IHSG and LQ45 data in Finance Sector Periode January 2002 until December 2006……... 40 Table 4.9 Statistic Test Result of Mean Differences IHSG and
LQ45 in Finance Sector Period January 2002 until December 2006…………………………………………..
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Table 4.10 Model Fitness of IHSG and LQ45 in Finance Sector Period January 2002 until December 2006…………….. 41 Table 4.11 Analysis Variance result of IHSG and LQ45 in Finance Sector Period January 2002 until December 2006……..
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Table 4.12 Regression result of IHSG and LQ45 in Finance Sector Period January 2002 until December 2006…………….. 42 Table 4.13 Descriptive Statistic of IHSG and LQ45 data in Mining Sector Periode January 2002 until December 2006…..... 43 Table 4.14 Statistic Test Result of Mean Differences IHSG and
LQ45 in Mining Sector Periode January 2002 until December 2006…………………………………………
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Table 4.15 Model Fitness of IHSG and LQ45 in Mining Sector Period January 2002 until December 2006…………….. 44 Table 4.16 Analysis Variance result of IHSG and LQ45 in Mining Sector Period January 2002 until December 2006……..
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Table 4.17 Regression result of IHSG and LQ45 in Mining Sector Period January 2002 until December 2006…………….. 44 Table 4.18 Descriptive Statistic of IHSG and LQ45 data in Miscellaneous Sector Periode January 2002 until December 2006……………………………………….... 45 Table 4.19 Statistic Test Result of Mean Differences IHSG and
LQ45 in Miscellaneous Sector Period January 2002 until December 2006…………………………………...
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Table 4.20 Model Fitness of IHSG and LQ45 in Miscellaneous Sector Period January 2002 until December 2006……..
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Table 4.21 Analysis Variance result of IHSG and LQ45 in Miscellaneous Sector Period January 2002 until December 2006……………………………………….... 47 Table 4.22 Regression result of IHSG and LQ45 in Miscellaneous Sector Period January 2002 until December 2006……..
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Table 5.1 Summary of Market Index Choice for Each Industry………………………………………………… 49
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LIST OF SYMBOLS
E ( Ri )
=
expected return
Rf
=
risk-free rate of interest
E ( Rm )
=
expected return of the market
im
=
beta coefficient
S2
=
sample variance
x
=
arithmetic mean
=
sigma
S p2
=
pooled variance
S 12
=
variance of the sample taken from population 1
n
=
sample size
xi
=
ith value of the variable X
yi
=
ith value of the variable Y
=
approximately equal to
=
delta
=
variance
=
mean
H0
=
null hypothesis
H1
=
alternative hypothesis
df
=
degree of freedom
Fu
=
upper limit
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LIST OF APPENDIXES
Appendix A: Critical Values of F…………………………………..
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Appendix B: Member of LQ45 Index……………………………...
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Appendix C: SBI Rate……………………………………………...
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Appendix D: Summary of Beta Calculation and Expected Return using IHSG and LQ45……………………………….
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Appendix E: F-Test, Variance Calculation…………………………
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