Faculty of Economics and Business

Is Technical Analysis Profitable and Capable for Stock Price Prediction in Bursa Malaysia?

Kelvin Lee Yong Ming

Master of Science 2016

Faculty of Economics and Business

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UNIVERSITI MALAYSIA SARAWAK

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Is Technical Analysis Profitable and Capable for Stock Price Prediction in Bursa Malaysia?

Kelvin Lee Yong Ming

A thesis submitted

In fulfillment of the requirements for the degree of Master of Science (Finance)

Faculty of Economics and Business UNIVERSITI MALAYSIA SARAWAK

2016

i

DECLARATION

The work entitled Is Technical Analysis Profitable and Capable for Stock Price Prediction in Bursa Malaysia? is to the best of the author‟s knowledge that of the author except where due reference is made. The thesis has not been accepted for any degree and is not concurrently submitted in candidature of any other degree.

________________________ ___________________________

(Date submitted) (Student‟s signature) Kelvin Lee Yong Ming 15020073

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ACKNOWLEDGEMENTS

First and foremost, I would like to express my deepest appreciation to my supervisor, Associate Professor Dr. Mohamad Jais for his supervision, guidance, valuable comments, and support toward the completion of this Master Thesis. I would be unable to complete this thesis without his advices, guidance and supervisions.

Next, I would like to thank my co-supervisor, Mr. Bakri Abdul Karim for his valuable comment. In addition, I would particularly like to express my sincere appreciation to my lovely family members for their encouragement, moral support and financial support.

Besides that, I would also like to thank my friend, Chan Chia Wen for putting up with me through what must have seemed like a never-ending journey.

Lastly, my thanks go to my faculty, Faculty of Economics and Business (FEB) for their resources provided to assist me in completing my master thesis.

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ABSTRACT

This study aims to test the ability of technical analysis for predicting the stock price and generating profits. This study employed two of the technical analysis indicators, namely Variable Moving Average (VMA) rules and Elliott Wave Principle incorporated with Fibonacci sequences. Generally, over the full sample period, this study found that VMA rules were useful technical indicator in analysing the medium capitalization stocks and generating higher return. Besides that, VMA rules are further tested through the sub-sample test, out-of-sample test and regression analysis.

Throughout the sub-sample test and out-of-sample test, this study also strengthens the evidence that VMA rules is successfully generating returns based on the medium capitalization stocks. Generally, this study found that 5 days was the most appropriate short term moving average for the analysis of the medium capitalization stocks. In addition, this study found that the signals emitted by all the VMA rules have significant relationship with the stock returns. As for Elliott Wave Principle incorporated with Fibonacci sequences indicator, this study found that the stock price movements of large capitalization can be predicted accurately as the prediction error during the impulsive wave is significantly less than 10 percent. However, the Elliott Wave Principle incorporated with Fibonacci sequences indicator is only successful in predicting the stock price movement during the pre- and post-crisis periods through the sub-sample test.

Keywords: Variable Moving Average, Elliot Wave Theory, Fibonacci Principle

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Adakah Analisis Teknikal Menguntungkan dan Mampu untuk Ramalan Harga Saham di Bursa Malaysia?

ABSTRAK

Kajian ini bertujuan untuk menguji keupayaan analisis teknikal dalam meramalkan harga saham dan menjana keuntungan. Kajian ini menggunakan dua petunjuk analisis teknikal, iaitu kaedah Purata Bergerak Berubah (VMA) dan prinsip Elliott Wave digabungkan dengan urutan Fibonacci. Secara umumnya, sepanjang tempoh sampel penuh, kajian ini mendapati bahawa kaedah VMA berguna dalam menganalisis saham permodalan sederhana dan menjana pulangan yang lebih tinggi.

Selain itu, kaedah VMA juga diuji melalui ujian sub-sampel, ujian luar sampel dan analisis regresi. Melalui ujian sub-sampel dan ujian luar sampel, kajian ini juga menguatkan bukti bahawa kaedah VMA berjaya menjana pulangan berdasarkan saham permodalan sederhana. Secara umumnya, kajian ini mendapati bahawa 5 hari merupakan purata bergerak berjangka pendek yang sesuai untuk analisis saham permodalan sederhana. Selain itu, kajian ini mendapati bahawa isyarat yang dipancarkan oleh semua peraturan VMA mempunyai hubungan signifikan dengan pulangan saham. Bagi petunjuk prinsip Elliott Wave digabungkan dengan urutan Fibonacci, kajian ini mendapati bahawa pergerakan harga saham permodalan besar boleh diramalkan dengan tepat kerana ralat ramalan semasa gelombang impulsif adalah kurang daripada 10 peratus. Walau bagaimanapun, petunjuk prinsip Elliott Wave digabungkan dengan urutan Fibonacci hanya berjaya dalam meramalkan pergerakan harga saham sebelum dan selepas krisis melalui ujian sub-sampel.

Kata Kunci: Purata Bergerak Berubah, Prinsip Elliott Wave, Urutan Fibonacci

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TABLE OF CONTENTS

DECLARATION...………...………..……….i

ACKNOWLEDGEMENTS…....…………..…………...………..……....ii

ABSTRACT……...………...………..……...iii

ABSTRAK ………...………...………iv

TABLE OF CONTENTS………...………..………v

LIST OF TABLES………...…………...………...…….x

LIST OF FIGURES………...……….….xvi

LIST OF ABBREVIATION...……….………..xvii

CHAPTER 1: INTRODUCTION ... 1

1.0 Introduction ... 1

1.1 Technical Analysis ... 4

1.2 History of Malaysian Stock Market ... 5

1.3 Background of the study ... 6

1.4 Problem Statement ... 11

1.5 Objectives of the Study ... 14

1.5.1 General Objective ... 14

1.5.2 Specific Objectives ... 14

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1.6 Significance of the Study ... 15

1.7 Scope of the Study ... 16

1.8 Summary of the Study ... 17

CHAPTER 2: LITERATURE REVIEW ... 18

2.0 Introduction ... 18

2.1 Overview of Technical Analysis ... 19

2.2 Dow Theory ... 20

2.3 Empirical Issue... 21

2.4 The Technical Trading Rules Literatures ... 22

2.4.1 Earlier Studies ... 22

2.4.2 Moving Average Rules ... 26

2.4.3 Elliott Wave Principle and Fibonacci Sequences ... 42

2.5 Technical Trading Rules in the Context of Malaysian Stock Market ... 45

2.6 Summary ... 47

CHAPTER 3: METHODOLODY ... 48

3.0 Introduction ... 48

3.1 Data Description and Data Collection ... 48

3.2 Technical Trading Rules ... 50

3.2.1 Moving Average Rules ... 50

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3.2.2 Elliott Wave Theory ... 57

3.2.3 Fibonacci Numbers ... 60

3.3 Sub-sample test ... 65

3.4 Out-of-sample test ... 66

3.5 Regression Analysis ... 66

3.5.1 Hypothesis Development ... 67

3.5.2 Description of Variables ... 68

3.5.3 Empirical Model and the Method Used ... 69

3.6 Hypothesis of the Study ... 70

3.7 Summary ... 71

CHAPTER 4: RESULTS ... 72

4.0 Introduction ... 72

4.1 Descriptive Statistics ... 72

4.2 Test Results of the Variable Moving Average (VMA) Rules ... 75

4.2.1 Returns on “Buy” and “Sell” Signals According to the Firms‟ Capitalization and Firms‟ Sector ... 76

4.2.2 Sub-Sample Test ... 78

4.2.3 Profits of VMA rules ... 89

4.2.4 Out-of-Sample Test ... 94

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4.3 Test Results of the Elliott Wave Theory Incorporated with Fibonacci

Sequences ... 103

4.3.1 Stock Price Prediction Error According to Firms‟ Capitalization ... 103

4.3.2 Stock Price Prediction Error According to Firms‟ Sector ... 105

4.3.3 T-test on the Stock Price Prediction Error ... 109

4.4 Regression Analysis ... 111

4.4.1 Interpretation of Results According to the Firm Capitalization ... 111

4.4.2 Interpretation of Results According to the Firm Sector ... 118

4.5 Summary ... 144

4.5.1 Variable Moving Average (VMA) Trading Rules ... 144

4.5.2 Elliott Wave Theory Incorporated with Fibonacci Sequences ... 147

4.5.3 Regression Analysis ... 148

CHAPTER 5: DISCUSSION ... 149

5.0 Introduction ... 149

5.1 Summary for hypotheses... 149

5.2 Discussion of empirical results for the Variable Moving Average …...…164

(VMA) rules 5.3 Discussion of empirical results: Elliott Wave Theory………....169

incorporated with Fibonacci Sequences 5.4 Discussion of empirical results: Regression Analysis ... 170

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5.5 Summary ... 171

CHAPTER 6: CONCLUSIONS AND RECOMMENDATION ... 172

6.0 Introduction ... 172

6.1 Conclusion ... 172

6.2 Future research ... 173

6.3 Limitations ... 174

6.4 Recommendations ... 174

REFERENCES ... 175

APPENDICES ... 184

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LIST OF TABLES

TABLE TITLE PAGE

Table 1.1 Malaysia Key Economic Indicator (2005-2012)………...9 Table 1.2 Comparison of Asean Stock Market (Year 2013)………..10 Table 4.1 Descriptive Statistics of the Daily Stock Returns for Each...……….73

Stock Classification (According to the Capitalization) from 3^rd January 2005 to 31^st December 2012

Table 4.2 Descriptive Statistics of the Daily Stock Returns for Each…………74 Stock Classification (According to the Sector) from

3^rd January 2005 to 31^st December 2012

Table 4.3 Result of Variable Moving Average (VMA) Rules………...76 According to Firms‟ Capitalization

Table 4.5 Result of Variable Moving Average (VMA) Rules………...79 According to Firms‟ Capitalization (Sub-Sample Test)

Table 4.6 Result of Variable Moving Average (VMA) Rules………...84 According to Firms‟ Sector (Sub-Sample Test)

Table 4.7 Trading profits for the top performing VMA rules According…...91 to the firms‟ capitalization

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Table 4.8 Trading profits for the top performing VMA rules According…...93

to the firms‟ sector Table 4.9 Out of Sample Test - Small Capitalization Firms……...……..…….95

Table 4.10 Out of Sample Test - Medium Capitalization Firms...……..……….95

Table 4.11 Out of Sample Test - Large Capitalization Firms…...………..…….95

Table 4.12 Out of Sample Test – Construction Sector………...………..97

Table 4.13 Out of Sample Test – Consumer Sector……...………..97

Table 4.14 Out of Sample Test – Finance Sector……...………..97

Table 4.15 Out of Sample Test – Hotel Sector……….98

Table 4.16 Out of Sample Test – Industrial Sector………...………...98

Table 4.17 Out of Sample Test – Infrastructure Sector………...……….98

Table 4.18 Out of Sample Test – Mining Sector………...…………...99

Table 4.19 Out of Sample Test – Plantation Sector………...………..99

Table 4.20 Out of Sample Test – PN17 Sector………...………..99

Table 4.21 Out of Sample Test – Properties Sector……….…..100

Table 4.22 Out of Sample Test – REITs Sector……….………100

Table 4.23 Out of Sample Test – Technology Sector……….………100

Table 4.24 Out of Sample Test – Trading/Service Sector………..……101

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Table 4.25 Stock Price Prediction Error – Based on Firm Capitalization……..108 Table 4.26 Stock Price Prediction Error – Based on Firm Sector………….….108 Table 4.27 T-Statistics of the Stock Price Prediction Error – Based…………..110

on Firm Capitalization

Table 4.28 T-Statistics of the Stock Price Prediction Error – Based…………..110 on Firm Sector

Table 4.29 Result of OLS Regression Analysis for Small……..……..……….113 Capitalization Stocks

Table 4.30 Result of OLS Regression Analysis for Medium…..……..……….115 Capitalization Stocks

Table 4.31 Result of OLS Regression Analysis for Large……….117 Capitalization Stocks

Table 4.32 Result of OLS Regression Analysis for………119 Construction Stocks

Table 4.33 Result of OLS Regression Analysis for………121 Consumer Stocks

Table 4.34 Result of OLS Regression Analysis for………123 Finance Stocks

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Table 4.35 Result of OLS Regression Analysis for………125 Hotel Stocks

Table 4.36 Result of OLS Regression Analysis for………127 Industrial Stocks

Table 4.37 Result of OLS Regression Analysis for………129 Infrastructure Stocks

Table 4.38 Result of OLS Regression Analysis for………131 Mining Stocks

Table 4.39 Result of OLS Regression Analysis for………133 Plantation Stocks

Table 4.40 Result of OLS Regression Analysis for………135 PN17 Stocks

Table 4.41 Result of OLS Regression Analysis for………137 Properties Stocks

Table 4.42 Result of OLS Regression Analysis for………139 REITs Stocks

Table 4.43 Result of OLS Regression Analysis for………141 Technology Stocks

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Table 4.44 Result of OLS Regression Analysis for………143 Trading/Service Stocks

Table 5.1 Table of Hypothesis (VMA Rules) ………..151 – Full Sample Period

Table 5.2 Table of Hypothesis 1 (VMA Rules) Based on………152 Different Sub Sample Periods

Table 5.3 Table of Hypothesis 2 (VMA Rules) Based on………155 Different Sub Sample Periods

Table 5.4 Table of Hypothesis 3 (VMA Rules) Based on………157 Different Sub Sample Periods

Table 5.5 Table of Hypothesis (VMA Rules).………..………..…..158 – Out-of-Sample Period

Table 5.6 Table of Hypothesis………...……..159 (Elliott Wave Incorporated with Fibonacci Sequences)

– Full Sample Period

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Table 5.7 Table of Hypothesis 4………...……..160 (Elliott Wave Incorporated with Fibonacci Sequences)

Based on Different Sub Sample Periods

Table 5.8 Table of Hypothesis 5………...……..161 (Elliott Wave Incorporated with Fibonacci Sequences)

Based on Different Sub Sample Periods

Table 5.9 Table of Hypothesis (Regression Analysis) – Hypothesis 6…..…..162 Table 5.10 Result of Variable Moving Average (VMA) Rules……….165

According to Medium Capitalization Stocks

Table 5.11 Result of Variable Moving Average (VMA) Rules……….…168 According to Medium Capitalization Stocks

during Different Sub-Sample Periods

Table 5.12 Result of Elliott Wave Theory incorporated with……….…...169 Fibonacci Sequences According to

Large Capitalization Stocks

xvi

LIST OF FIGURES

FIGURE TITLE PAGE

Figure 1.1 Total number of listed companies in Malaysia………..……...7 Figure 1.2 Daily KLCI Index (2005 - 2012)………..……8 Figure 3.1 Fundamental Form of Elliott‟s Wave………...…..57

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LIST OF ABBREVIATION

ASE Athens Stock Exchange

ASEAN Association of Southeast Asian Nations

DJIA Dow Jones Industrial Average

EMH Efficient Market Hypothesis

FMA Fixed Moving Average

FSSTI FTSE Straits Times Index

GDP Gross Domestic Product

IMA Increasing Moving Average

JCI Jakarta Composite Index

KLCI Kuala Lumpur Composite Index

KLSE Kuala Lumpur Stock Exchange

LB Lower Band

LMA Long Moving Average

MA Moving Average

MACD Moving Average Convergence Divergence

MOM Momemtum

MSE Malayan Stock Exchange

xviii

PCOMP Philippine Composite Index

RSI Relative Strength Index

S&P 500 Standard and Poor 500

SBC Swiss Bank Corporation

SES Stock Exchange of Singapore

SET Stock Exchange of Thailand

SEM Stock Exchange of Malaysia

SEMS Stock Exchange of Malaysia and Singapore

ShA Shanghai A Index

ShB Shanghai B Index

SzA Shenzhen A

SzB Shenzhen B

SMA Short Moving Average

SO Stochastic Oscillator

TRB Trading Breakout

UB Upper Band

VMA Variable Moving Average

1 CHAPTER 1 INTRODUCTION

1.0 Introduction

Stock market performance often acts as the reflection of a country‟s economic growth and strength (Adebola & Dabalan, 2011). Economic, political and psychological factors are highly interrelated factors that affect the stock market (Yao, Tan, & Poh, 1999) and lead to the change of traders‟ attitude (Metghalchi, Hajilee, & Hayes, 2013). The analysis for the stock market basically can be divided into two main types which are (i) Fundamental Analysis and (ii) Technical Analysis.

However, this study is focusing only on the technical analysis as all the major brokerage firms provide the technical commentaries and advisory services on the basis of technical analysis (Han et al., 2013).

The term “technical analysis” is described as a general heading for a wide range of trading techniques or strategies(Brock, Lakonishok, & LeBaron, 1992), in which each of the technical trading rules followed the common philosophy that prediction of the future stock prices can be done by using the past prices (McKenzie, 2007). Technical analysis, as defined by Vasiliou, Eriotis, and Papathanasiou (2008), is a method of evaluating securities by analyzing the statistics generated by market activity. On the other hand, a clearer definition of technical analysis had been made by Charussaengsuriya and Tharnpipat (2012). They stated that technical analysis is a method to analyze the stock‟s behavior by looking for the appropriate purchase price

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or sale price (buy signal or sell signal) based on the analysis of the stock prices, quantities, time period, and trend prediction.

In addition, Isakov and Hollistein (1999) stated that there are two approaches for the technical analysis. Firstly, it is purely graphical as it looks for patterns in the historical data. Secondly, the trading rules derived on the basis of filters apply to historical data. Technical analysis also has a pretty long history which dates back to the early 1600s where the Japanese rice traders conduct their trading in the Dojima Rice Exchange in Osaka (Nison, 2001). According to Nison (2001), Munehisa Homma was the first and most famous person in Japan who predicted the future price movement by using the past prices, as huge fortune rice trading amassed him during 1700s. Then, it evolved into what we known today as the candlestick chart.

The tedium in the complex mathematical manipulations of the technical analysis also had been taken out as the introduction of electronics aided the development of technical analysis (Wong, Manzur & Chew, 2010).

However, skepticism about the usefulness of technical analysis never ends, although technical analysis has been widely used and accepted by practitioners.

Along with the statement above, Zhu and Zhou (2009) pointed out three reasons to further explain the skepticism situation. First, they argued that there was no theoretical basis that exists for the technical analysis. Second, earlier theoretical studies completely rule out the profitability of technical analysis as the studies often assumed the random walk model for the stock price. Third, there were mixed and inconclusive empirical findings presented by previous studies.