comparison study between islamic and conventional stock market in malaysia

Analysis on Comparative Study

between Islamic and

Conventional Stock Market

in Malaysia

By

Rininta Nurrachmi

Introduction

Literature Review

Model & Methodology

The Findings

Conclusion

Introduction

825 Shariah compliant securities, 166 Islamic unit trust funds from total of 597 Bursa Malaysia joint forces with FTSE group in index measurement Global Financial Crisis FBM KLCI - 13.67% FBM Hijr - 13.77% Q1, 2008 FBM Emas - 15.99% Bersih Rally 2.0 in July 2011 FBM KLCI - 6.56% FBM Hijr - 6.77% August 2011 FBM Emas - 7.44% Previous studies were conducted during the global financial crisis

11. To Explore the Existence of

Cointegration and Direction of

Causality

2. To Compare the Volatility during the period 2007-

2012

Literature

Review

March 1960 – Malaysian Stock Market

April 1999 – Shariah Index KLSE

26 June 2006 – Bursa Malaysia joint forces with FTSE Group

21 May 2007 – FBM Hijrah Index

22 January 2007 – FBM Emas Shariah Index

October 2012 – FBM Small Cap Shariah Index

Malaysian Stock Market

1. Tabak&Lima(2001) Stock Market in Latin America & the US (Indices for countries stock market benchmark)

2. Cho & Ogwang (2006) Stock Market in Canada (TSX Composite Index vs TSX Venture Composite Index

3. Ramona&Razvan(2009)Stock Market in Romania (BET vs RASDAQ-C)

4. Albaity&Mudor (2012) DJINA (Dow Jones Industrial Average) vs FBM KLCI

No cointegration & Unidirectional SR

Causality

The Relationship in Conventional Stock Market

The market is efficient & there is different characteristic of listed company

1. Albaity & Ahmad (2008) Stock Market in Malaysia (KLCI vs KLSI). Data in 1999 - 2005

2. Hengchao&Hamid (2011) Stock Market in US, Japan, China,Malaysia, Indonesia. Data in 2007-2010

3. Chapakia&Sanrego (2007) Stock Market in Malaysia (Shariah index, Composite index, 3-months Treasury bill rate. Data in 1999 - 2003

There is existence cointegration & bidirectional (feedback) causality

No cointegration

1. Hakim & Rashidian (2002) Stock Market in the US (DJIMI, the Wilshire 5000, and the three-month T-Bill ). Data in 2001-2002

2. Beik & Wardhana (2011) Stock Market in Indonesia, Malaysia and the US. Data in 2006-2008

The Relationship between Islamic & Conventional Stock Market

Volatility Level between Islamic & Conventional Stock Market

1. Yusuf – Majid (2007) Stock Market in Malaysia (RHBII vs KLCI). Data in 1992-2000

2. Sukmana – Kholid (2009) Stock Market in Indonesia (JICC vs JAKISL). Data in 2001-2009

3. Akhtar, et al (2012) Stock Market in 9 Islamic and 37 non-Islamic countries. Data in 2007-2010

4. Chiadmi – Ghaiti (2012) Standard and Poor 500 Indices. Data in 2006-2011

Islamic stock market was less volatile compare to its counterpart

1. Amanina – Safiih (2010) Stock Market in Malaysia (KLSI vs index of financial sector, consumer sector, the construction sector, the trade/service sector and plantation sector). Data in 1990-2010

2. Ibnrubbian (2012) Stock Market in Saudi Arabia. Index from Banking, Industrial, Cement, Service and Agricultural sector. Data in 2002-2008

3. Romli et, al (2012) Stock Market in Malaysia (FBM Hijrah & FBM Emas Shariah vs FBM KLCI) . Data in 2007-2010

Islamic stock market was more volatile compare to its counterpart

Theoretical Framework

Cointegration & Causality Direction

Vector Autoregressive (VAR)

There is presence of cointegration &

bidirectional

There is absence of cointegration &

unidirectional SR Causality

Volatility Comparison

ARCH/GARCH (1,1)

Islamic Stock market has

lower volatility

Islamic stock market has

higher volatility

Model

and

Methodology

𝐿𝑛(𝐶)𝑡= 𝛼0 + 𝛼1𝐿𝑛(𝐶)𝑡−1 + 𝛼2𝐿𝑛(𝐻)𝑡−1 + 𝛼3𝐿𝑛(𝐸)𝑡−1 + 𝜀𝑡𝐶

𝐿𝑛(𝐻)𝑡= 𝛽0 + 𝛽1𝐿𝑛(𝐶)𝑡 + 𝛽2𝐿𝑛(𝐶)𝑡−1 + 𝛽3𝐿𝑛(𝐻)𝑡−1 + 𝛽2𝐿𝑛(𝐸)𝑡−1 + 𝜀𝑡

𝐻 𝐿𝑛(𝐸)𝑡= 𝛾0 + 𝛾1𝐿𝑛(𝐶)𝑡 + 𝛾2𝐿𝑛(𝐻)𝑡 + 𝛾3𝐿𝑛(𝐶)𝑡−1 + 𝛾4𝐿𝑛(𝐻)𝑡−1 + 𝛾5𝐿𝑛(𝐸)𝑡−1 + 𝜀𝑡

𝐸

𝑳𝒏(𝑪)𝒕= 𝜷𝟎 + 𝜷𝟏𝑳𝒏(𝑯)𝒕 + 𝜷𝟐𝑳𝒏(𝑬)𝒕 + 𝜺𝒕

Time Series Data from 5 June 2007 to 28 December 2012 (Daily Index , N= 1376)

Islamic Stock Market FBM Hijrah , FBM Emas SI Conventional Stock Market FBM KLCI

Methodology

Unit Root

Augmented Dickey

Fuller (ADF)

Philip Perron

(PP)

Cointegration Test

Johansen (variable

more than 2)

Causality Test

Short Run Granger

Causality test

Volatility Measurement

Descriptive Analysis

ARCH LM test

ARCH – GARCH

(1,1)

The Findings - 1 The existence of cointegration

and causality direction

ADF PP

Variables No Trend Trend No Trend Trend

(A)Level

Ln(Composite) -0.585669 -1.765736 -0.546347 -1.785986

Ln(Hijrah) -0.673868 -1.552335 -0.649713 -1.504275

Ln(Emas) -0.675609 -1.701642 -0.698035 -1.684282

(B) First Difference

Ln(Composite) -19.81999*** -19.86281*** -33.20673*** -33.21401***

Ln(Hijrah) -33.06682*** -33.08833*** -33.05329*** -33.05729***

Ln(Emas) -32.78544*** -32.82133*** -32.88004*** -32.90799***

Note : *** 1% sig level

All indices contain unit root at level The Variable is stationary at first difference with 1% significance level

Null

Hypothesis

Trace Max Eigenvalue Trace Max Eigenvalue

CR CV (10%) CR CV (10%) CR CV (5%) CR

CV

(5%)

𝑟 = 0 22.29727 27.066 16.539 18.892 22.29727 29.797 16.539 21.131

𝑟 ≤ 1 5.758269 13.428 4.928501 12.296 5.758269 15.494 4.928501 14.26

𝑟 ≤ 2 0.829768 2.7055 0.829768 2.7055 0.829768 3.8414 0.829768 3.8414

Trace statistic < Critical values Maximum Eigenvalue statistic < Critical values There is no cointegration in the variables or there is no long run relationship between Islamic stock market with its counterpart

Note : CR = Cointegration Rank Test, CV = Critical Value The lag order specified is 1 based on Akaike Information Criteria

<

<

<

<

<

<

<

<

<

<

<

<

Null Hypothesis F-Statistic Probability

LNHIJRAH does not Granger Cause LNCOMPOSITE 3.81989 0.05085

LNCOMPOSITE does not Granger Cause LNHIJRAH 4.37959 0.03656**

LNEMAS does not Granger Cause LNCOMPOSITE 3.44695 0.06358

LNCOMPOSITE does not Granger Cause LNEMAS 4.56083 0.03289**

LNEMAS does not Granger Cause LNHIJRAH 3.80930 0.05117

LNHIJRAH does not Granger Cause LNEMAS 2.84118 0.09210

FBM KLCI

FBM Hijrah Index

FBM Emas

Shariah Index

Note : ** 5% sig level

In the short run granger causality, the statistics show that FBM KLCI

causes FBM Hijrah Index and FBM Emas

Shariah Index

Unidirectional SR Causality

The Findings - 2 Volatility Comparison

-10

-8

-6

-4

-2

0

2

4

6

2007 2008 2009 2010 2011 2012

RCOMPOSITE

-12

-8

-4

0

4

8

2007 2008 2009 2010 2011 2012

RHIJRAH

-12

-8

-4

0

4

8

2007 2008 2009 2010 2011 2012

REMAS

FBM KLCI (Returns) FBM Hijrah Index (Return)

FBM Emas Shariah Index

(Return)

Mean 0.018999 0.025062 0.018516

Median 0.053322 0.057426 0.056589

Maximum 4.350636 4.641286 4.158901

Minimum -9.496810 -10.49478 -10.70320

Std. Dev. 0.863988 0.946926 0.906991

Skewness -1.080658 -1.069366 -1.385491

Kurtosis 16.04194 17.10215 19.64100

Observation 1376 1376 1376

ARCH Test:

F-statistic 37.57417 Prob. F(1,1325) 0.000000

Obs*R-squared 36.59319 Prob. Chi-Square(1) 0.000000

ARCH Test:



ARCH Test:



A Simple AR (1) Model and Testing for ARCH (1) effect for FBM Emas Shariah Index

A Simple AR (1) Model and Testing for ARCH (1) effect for FBM Hijrah Index

A Simple AR (1) Model and Testing for ARCH (1) effect for FBM KLCI

Obs*R-Square > 0.05

There is Heteroscedacity in

the variables

ARCH Test:



ARCH Test:



ARCH Test:



Testing for ARCH (6) effects on FBM Emas Shariah Index

Testing for ARCH (6) effects on FBM Hijrah Index

Testing for ARCH (6) effects on FBM KLCI

Obs*R-Square > 0.05

There is Heteroscedacity in

the variables

Variable C ARCH

(𝜶)

GARCH

(𝜷) ( 𝜶 + 𝜷)

FBM KLCI 0.010709 0.13918 0.855041 0.994221

FBM Hijrah Index 0.007442 0.101616 0.895314 0.99693

FBM Emas Shariah Index 0.011712 0.147977 0.85006 0.998037

All variables have high volatility and FBM Emas Shariah Index has the highest volatility

Conclusion

No Cointegration & There is

unidirectional SR Causality

1st Objective 2nd Objective

Islamic stock market is more volatile compare to its

counterpart

Conclusion

comparison study between islamic and conventional stock market in malaysia

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