BETA CALCULATION ALTERNATIVES USING IHSG AND LQ45 ON PROPERTY AND REAL ESTATE, FINANCE, MINING AND MISCELLANEOUS SECTORS JSX CASE:

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1 BETA CALCULATION ALTERNATIVES USING AND ON PROPERTY AND REAL ESTATE, FINANCE, MINING AND MISCELLANEOUS SECTORS JSX CASE: FINAL PROJECT By Aryo Fajar Syaifulloh Undergraduate Program School of Business Management Institut Teknologi Bung

2 ARYO FAJAR SYAIFULLOH Date of Final Examination: August 10 th, 2007 Date of Graduation: October 27 th, 2007 Undergraduate Program, Institut Teknologi Bung, 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 expected to gain high profit also. The whole stocks movement/fluctuation is represented by a market index which is called. Besides there is a market index, that only consisted by the top 45 of the most liquid stock which had has a big market share, called LQ 45. In this final project, both 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, or? 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 real estate, finance miscellaneous for the January 2002 to December 2006 period. From the calculated results, it is shown that both market index,, can be used to determine the expected return of property real estate stock. For finance miscellaneous, could determine better than on the contrary, determine better than 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 volume, 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,, Index. i

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4 ARYO FAJAR SYAIFULLOH Tanggal Ujian Akhir: 10 Agustus 2007 Tanggal Wisuda: 27 Oktober 2007 Program Sarjana, Institut Teknologi Bung, 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. Selain terdapat pula indeks pasar yang hanya terdiri dari 45 saham terlikuid dan memiliki pangsa pasar yang besar yaitu. 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 atau. 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 Hasil dari penghitungan yang dilakukan didapat bahwa untuk memperkirakan keuntungan saham properti dan real estate, kedua indeks pasar dan sama-sama dapat digunakan. Untuk sektor keuangan aneka industri, memprediksi lebih baik dibingkan. Sebaliknya, untuk sektor pertambangan, memprediksi lebih baik dibingkan dengan. 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. iii

5 Kata Kunci: Capital Asset Pricing Model (CAPM), Beta ( ), Volatilitas, Perkiraan Keuntungan,, Index. iv

6 VALIDATION PAGE BETA CALCULATION ALTERNATIVES USING AND ON PROPERTY AND REAL ESTATE, FINANCE, MINING AND MISCELLANEOUS SECTORS JSX CASE: By: ARYO FAJAR SYAIFULLOH ID No: Undergraduate Program School of Business Management Institut Teknologi Bung Validated By Deddy P. Koesrindartoto Ph.D NIP: v

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8 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 Management in Bung Institute of Technology. The final project theme is Beta Calculation Alternatives Using on Property Real Estate, Finance, Mining Miscellaneous Sectors, JSX Case: 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 informations through this final project. Thank you very much for the time the opportunity 2. Mrs. Trimulyati Budiman for the private interview. Thank you for the time the opportunity 3. My family that never missed to support encourage me all the time, Papa, Mama, Mba Arie, Mba Ewiq, Mas Doddy, Mba Tyas, Mas Is, Mas Manik, Mba Mala, Mas Berry, Ma, Bian, Dita, Chelsea relatives especially Mas Kholiq for your time accompany me. Love you all 4. My beloved person, Astri family also Chi-G Iyong for the support, discussion, knowledge especially about statistics SPSS the time through happy sad moments also her family that encourage me a lot vii

9 5. Mr. Dedy Kurniawan, MSM student, thank you very much for your time in taught me about statistics how to operate SPSS 13.0 software. 6. Budi, Hardi Bedi as my housemate. Thank you for the support, discussion 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 supports me. 10. Ardhi Agung Pradhana as my partners that gives a lot of information, sharing, discussion comment to this final project 11. Intan Pramesti, Dimas Werhaspati, Widita Rarasati, Maharani Putri, Aryo Pratomo all my SBM friends, thank you for the support all the moments 12. My closest friends, Tito Defri who always support me 13. SBM administration staff librarian, Mr. Iwan, Mr. Yayad, Mrs. Ikum, Mr. Rajab Mrs. Wiwik that help me a lot in supporting any documents needed 14. Mr. Juddy Mulyadi Mrs. Eti that letting me working the final project at their house also thank you for the delicious meal I realize there still a lot of weaknesses in this final project, therefore needed criticism suggestions. I hope this final project could give insight about Indonesian Capital Market. Bung, August 5 th, 2007 Aryo Fajar Syaifulloh viii

10 LIST OF CONTENTS ABSTRACT (ENGLISH). ABSTRAKSI (INDONESIA)... VALIDATION PAGE... FOREWORD LIST OF CONTENTS.. LIST OF FIGURES.. LIST OF TABLES LIST OF SYMBOLS LIST OF APPENDIXES.. CHAPTER I INTRODUCTION Background Problem Identification The Importance of Problem Solving Problem Limitation 1.5 Writing Sequence.. CHAPTER II LITERATURE STUDY Capital Asset Pricing Model (CAPM) Risk-Free Interest Rate Beta 2.4 Risk Systemic Risk Unsystemic Risk. 2.5 Diversification Covariance. 2.7 Variance 2.8 Market Index. i iii v vii ix xiii xv xix xxi ix

11 2.8.1 Indeks Harga Saham Gabungan () Sector Indeces Statistical Theory T-test Hypothesis Simple Linear Regression F-test Hypothesis (Upper-Tail Test).. CHAPTER III METHODOLOGY. 3.1 Flow Diagram Methodology. 3.2 Research Object Definition Problem Identification Objectives. 3.5 Hypothesis Formulation Literature Study Data Collection. 3.8 Data Analysis Test Hypothesis Conclusion Recommendation... CHAPTER IV DATA COLLECTION AND ANALYSIS. 4.1 Data Collection Property Real Estate Sector Finance Sector Mining Sector Miscellaneous Sector Index SBI Rate. 4.2 Data Analysis Data Output x

12 4.3.1 Output Property Real Estate Sector Output Finance Sector Output Mining Sector Output Miscellaneous Sector Test Hypothesis Property Real Estate Sector Finance Sector Mining Sector Miscellaneous Sector.. CHAPTER V CONCLUSION AND RECOMMENDATION Conclusion. 5.2 Recommendation REFERENCES APPENDIX xi

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14 LIST OF FIGURES Figure 2.1 The Markowitz Efficient Frontier.. 5 Figure 2.2 Types Classifications of Risk. 8 Figure 2.3 Fu Rejection Areas. 14 Figure 3.1 Flow Diagram Methodology Figure 4.1 Property Real Estate Graph from January 2002 until December Figure 4.2 Finance Graph from January 2002 until December Figure 4.3 Mining Graph from January 2002 until December Figure 4.4 Miscellaneous Graph from January 2002 until December Figure 4.5 Graph from January 2002 until December Figure 4.6 Index Graph from January 2002 until December Figure 4.7 SBI Rate Graph from January 2002 until December Figure 4.8 Δ Δ Graph in Determining Expected Return in Property Real Estate Sector Period January 2002 until December Figure 4.9 Δ Δ Graph in Determining Expected Return in Finance Sector Period January 2002 until December xiii

15 Figure 4.10 Δ Δ Graph in Determining Expected Return in Mining Sector Period January 2002 until December Figure 4.11 Δ Δ Graph in Determining Expected Return in Miscellaneous Sector Period January 2002 until December xiv

16 LIST OF TABLES Table 4.1 Summary Calculation from Sectoral Market Indexes Actual Return on Mining Sector 27 Table 4.2 Summary Calculation of Beta Calculation Expected Return using on Mining Sector. 30 Table 4.3 Descriptive Statistic of data in Property Real Estate Sector Period January 2002 until December Table 4.4 Statistic Test Result of Mean Differences in Property Real Estate Sector Period January 2002 until December 2006 Table 4.5 Model Fitness of in Property Real Estate Sector Period January 2002 until December Table 4.6 Analysis Variance result of in Property Real Estate Sector Period January 2002 until December Table 4.7 Regression result of in Property Real Estate Sector Period January 2002 until December Table 4.8 Descriptive Statistic of data in Finance Sector Periode January 2002 until December Table 4.9 Statistic Test Result of Mean Differences in Finance Sector Period January 2002 until December xv

17 Table 4.10 Model Fitness of in Finance Sector Period January 2002 until December Table 4.11 Analysis Variance result of in Finance Sector Period January 2002 until December Table 4.12 Regression result of in Finance Sector Period January 2002 until December Table 4.13 Descriptive Statistic of data in Mining Sector Periode January 2002 until December Table 4.14 Statistic Test Result of Mean Differences in Mining Sector Periode January 2002 until December 2006 Table 4.15 Model Fitness of in Mining Sector Period January 2002 until December Table 4.16 Analysis Variance result of in Mining Sector Period January 2002 until December Table 4.17 Regression result of in Mining Sector Period January 2002 until December Table 4.18 Descriptive Statistic of data in Miscellaneous Sector Periode January 2002 until December Table 4.19 Statistic Test Result of Mean Differences in Miscellaneous Sector Period January 2002 until December Table 4.20 Model Fitness of in Miscellaneous Sector Period January 2002 until December xvi

18 Table 4.21 Analysis Variance result of in Miscellaneous Sector Period January 2002 until December Table 4.22 Regression result of in Miscellaneous Sector Period January 2002 until December Table 5.1 Summary of Market Index Choice for Each Industry 49 xvii

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20 LIST OF SYMBOLS E ( Ri ) = expected return R f = risk-free rate of interest E ( Rm ) = expected return of the market im = beta coefficient 2 S = sample variance x = arithmetic mean = sigma 2 S p = pooled variance 2 S 1 = variance of the sample taken from population 1 n = sample size x i = ith value of the variable X y i = ith value of the variable Y = approximately equal to = delta = variance = mean H 0 = null hypothesis H 1 = alternative hypothesis df = degree of freedom Fu = upper limit xix

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22 LIST OF APPENDIXES Appendix A: Critical Values of F.. 55 Appendix B: Member of Index Appendix C: SBI Rate Appendix D: Summary of Beta Calculation Expected Return using. 63 Appendix E: F-Test, Variance Calculation 73 xxi

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