ANALYSTS RECOMMENDATION: LEE SIAU MEI ONG CHIA YEE OOI WAN CHONG

112 Pages·2012·4.56 MB·English

by  Jason Tan

ANALYSTS RECOMMENDATION:
A RIPPLE EFFECT THAT DOES NOT LAST

LEE SIAU MEI
ONG CHIA YEE
OOI WAN CHONG
POH YU XIONG
TAN JASON

BACHELOR OF FINANCE (HONS)

UNIVERSITI TUNKU ABDUL RAHMAN

FALCULTY OF BUSINESS AND FINANCE
DEPARTMENT OF FINANCE

AUGUST 2012
ANALYSTS RECOMMENDATION:
A RIPPLE EFFECT THAT DOES NOT LAST

BY

LEE SIAU MEI
ONG CHIA YEE
OOI WAN CHONG
POH YU XIONG
TAN JASON

A research project submitted in partial fulfillment of the
requirement for the degree of

BACHELOR OF FINANCE (HONS)

UNIVERSITI TUNKU ABDUL RAHMAN

FALCULTY OF BUSINESS AND FINANCE
DEPARTMENT OF FINANCE

AUGUST 2012
Copyright @ 2012
ALL RIGHTS RESERVED. No part of this paper may be reproduced, stored in a
retrieval system, or transmitted in any form or by any means, graphic, electronic,
mechanical, photocopying, recording, scanning, or otherwise, without the prior
consent of the authors.

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DECLARATION

We hereby declare that:
(1) This undergraduate research project is the end result of our own work and
that due acknowledgement has been given in the references to ALL
sources of information be they printed, electronic, or personal.

(2) No portion of this research project has been submitted in support of any
application for any other degree of qualification of this or any other
university, or learning.

(3) Equal contribution has been made by each group member in completing
the research project.

(4) The word count of this research report is 9993 words.

Name of Student: Student ID: Signature:

1. Lee Siau Mei 09ABB02895
2. Ong Chia Yee 10ABB01150
3. Ooi Wan Chong 10ABB01581
4. Poh Yu Xiong 10ABB01693
5. Tan Jason 10ABB00829

Date: 30 August 2012

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ACKNOWLEDGEMENT

It has been a great journey completing this final year project. What started off as a
burden eventually became one of the most exciting projects that we have
undertaken. The process was both grueling and exciting, but it wasn‟t short of
reward and presented us one of the greatest learning experiences.

We would like to take this opportunity to extend our utmost gratitude towards our
family. Without their support and encouragement, we could not have possibly
made it this far. They have been the most understanding and supportive
throughout this period.

To our supervisor, Mr. Wong Chin Yong. No words can describe how thankful we
are to him. He has been the most generous, wisdom and advices, throughout the
completion of this project. He has always been able to find time for us in his busy
schedule. We are greatly indebted.

Last but not least, the people who made this project possible, the group members.
One of the most exciting parts about this project was the forging of a bond
between all group members. All the sacrifices made have finally came to an end,
an interesting product of hard work and determination. Thanks.

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Table of Contents
Copyright Page ii
Declaration iii
Acknowledgement iv
Table of Contents v
List of Table vii
List of Figures viii
Abstract ix
CHAPTER 1 INTRODUCTION
1.1 Research Background 1-3
1.2 Problem Statement 3-5
1.3 Research Objective 5-6
1.4 Research Question 6
1.5 Significance of Study 6
1.6 Chapter Layout 7

CHAPTER 2 LITERATURE REVIEW
2.1 Investment Value of Equity Analyst Report 8-10
2.2 Market Impact of Equity Analyst Report 11-12
2.3 Effect of Transaction Volume 12-13
2.4 Hypotheses Development 13
2.5 Conclusion 14

CHAPTER 3 RESEARCH METHODOLOGY
3.1 Graphical Event Study 15-16
3.2 Jensen‟s Measure to Observe the Effect of Analyst
Recommendation on Abnormal Return of Stocks 16-18
3.3 Econometric Method
3.3.1 GARCH Model 19-20
3.3.2 EGARCH Model 20-21
3.4 Diagnostic Checking
3.4.1 ARCH Test to Detect Heteroscedasticity 21
3.4.2 Ljung-Box Test to Test for Autocorrelation 22
3.5 Data Sources and Description 22-23
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CHAPTER 4 RESULT AND INTERPRETATION
4.1 Market Impact of Equity Analyst Recommendation
4.1.1 Graphical Analysis of Stock Return
Reaction of Companies That Receive
Favorable Recommendation, 4-week
Study and 5-day Study 24-29
4.1.2 Graphical Analysis of Stock Volume
Reaction to Analyst Recommendation,
4-week Study and 5-day Study 29-31
4.2 Effect of Analyst‟s Recommendation on Stock
Return
4.2.1 GARCH Model 32
4.2.2 EGARCH Model 32
4.3 Interpretation of Results
4.3.1 CBSA 37
4.3.2 CENSOF 38
4.3.3 ENG 38
4.3.4 GPACKET 39
4.3.5 JCY 39
4.3.6 MPI 39-40
4.3.7 NOTION 40
4.3.8 UNISEM 40
4.3.9 Discussion of Result 41
4.4 The Effect of Transaction Volume on Return of
Stocks and Analyst‟s Recommendation 41-42

CHAPTER 5 CONCLUSION
5.1 Summary of result 44-45
5.2 Policy recommendation 45-46
5.3 Recommendations for Future Researches 46-47
Reference 48-50
Appendix 51-102

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LIST OF TABLES

Table 3.1 Percent of Buy Recommendation 23
Table 3.2 List of Companies and Recommendations Received 23
Table 4.1 Performance Analysis of Individual Recommendation 29
Table 4.2 Regression result of Ordinary Least Square (OLS) 33
Table 4.3 Regression result of Generalized Auto Regression
Conditional Heteroskedasticity (GARCH) 34
Table 4.4 Regression result of Exponential Generalized Auto
Regression Conditional Heteroskedasticity (EGARCH) 35
Table 4.5 Combined regression result of GARCH and EGARCH 36
Table 4.6 Regression result of equation 3.5 43

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LIST OF FIGURES

Figure 1.1 KLSE Annual Transactions 2
Figure 3.1 Daily Returns of CBSA 19
Figure 4.1 Line Graph of CBSA 25
Figure 4.2 Line Graph of CENSOF 25
Figure 4.3 Line Graph of ENG 26
Figure 4.4 Line Graph of GPACKET 26
Figure 4.5 Line Graph of JCY 27
Figure 4.6 Line Graph of MPI 27
Figure 4.7 Line Graph of NOTION 28
Figure 4.8 Line Graph of UNISEM 28
Figure 4.9 Average Daily Trading Volumes of Stocks Recommended
by Analyst 30
Figure 4.10 Average Weekly Trading Volumes of Stocks
Recommended by Analyst 30

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Abstract

When investing, analyst recommendation provide guide as to what stocks to
invest in. Analyst made these recommendations after conducting thorough
research on the said company. We test the effectiveness of the recommendations
in terms of market impact and investment value. Our sample includes companies
from the technology sector of Kuala Lumpur Stock Exchange that received
favorable recommendations from the year 2007 to 2011. We find that the effects
of analyst recommendations were short lived; the effect dissipated in the matter of
days. Furthermore, transaction volume on the publication day increased
substantially, showing that recommended stocks were heavily transacted on the
day of publication. Stocks that received favorable recommendation does not
exhibit abnormal return or receive excess return due to recommendations. Lastly,
we find that recommendations coupled with high transaction volume produces
better result than company that receives favorable recommendation only.

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