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CHAPTER 3 
 
Data and Methodology 
 
3.0 Introduction 
This chapter describes the approaches that have been applied to gather 
necessary information, it includes the data analysis, methodology description and the 
expected result.  
 
3.1 The data 
The data used in this study consist of the monthly closing of stock indices, 
Such as monthly Shanghai Stock Exchange (SHSE) composite index, monthly 
Shenzhen Stock Exchange (SZSE) composite index and monthly banking sector index 
price, monthly Shanghai Interbank Offered Rate (SHIBOR) be the interest rate, 
monthly average real effective exchange rate; and the change of inflation rate is 
measured by the monthly consumer price index (CPI), monthly money supply which 
is measured by monthly growth rate of M2. All data cover September 2007 to June 
2012 and sample size has 58 observations. And these data are obtained from 
International Financial Statistics of the International Monetary Fund and Financial 
Statistics of the Federal Reserve Board and Statistics and Analysis Department of The 
People’s Bank of China and State Statistics Bureau of China. 
 
3.2 Methodology 
This study will use logarithmic method that come from Jeyanthi and Willian 
(2010) to calculate each return of Shanghai stock market, Shenzhen stock market and 
return of banking industry sector. The generalized least squares (GLS) regression 
analysis estimates the effect of interest rate (INT), inflation rate (INF), exchange rate 
(EX) and money supply (MS) change on banking industry stock return. First of all, 
following Moade Shubita and Adel Al-Sharkas (2010), the study uses the formula: 

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24 
INFt= (CPIt-CPIt-1)/CPIt-1 to calculate the change of inflation rate. And then it will 
do the correlation testing between these four macro-economic factors, if some of 
factor has strong relationship with the other factor, then they will be apart.
Banking industry sector stock return is calculated using logarithmic method as 
follows: 
R
t 
= (lnp
B
t
– lnp
B
t-1
) * 100 
Where:
R
t
= Banking industry sector index return at month t, is the proxy for banking industry 
stock return at month t 
p
B
t 
= Banking industry sector closing index at month t 
p
B
t-1 
= Banking industry sector closing index at month t-1 
Ln = Natural logarithm
Market Returns is calculated using logarithmic method as follows: 
Shanghai stock exchange market return: 
MRSH
t
= (lnp
SH
t
– lnp
SH
t-1 
) * 100
Where: 
MRSH
t
= Shanghai stock exchange market return at the period t 
P
SH
t
= Shanghai stock exchange closing index at month t 
P
SH
t-1
= Shanghai stock exchange closing index at month t-1 
Ln = Natural logarithm 
Shenzhen stock exchange market return: 
MRSZ
t
= (lnp
SZ
t
– lnp
SZ
t-1
) * 100
Where: 
MRSZ
t
= Shenzhen stock exchange market return at the period t 
P
SZ
t
= Shenzhen stock exchange closing index at month t 
P
SZ
t-1
= Shenzhen stock exchange closing index at month t-1 
Ln = Natural logarithm 
Generalized least squares (GLS) regression: 
There are several method that can be used to measure the impact of 

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25 
macroeconomic variables on banking industry stock return, for example, Mohammad 
and Orouba (2006) used both OLS and GLS to examine the impact of interest rate, 
market risk, inflation on bank stock returns. A multi-factor model is designed to test 
the impact of four macroeconomic factors on the stock return. The model is estimated 
with generalized least squares (GLS) regression analysis, because the study employ 
the time series data as the sample, then for dealing with the serial correlation, the 
study will use GLS. 
R
t 
= a
0
+ a
1
INF
t 
+a
2
EX
t
+ a
3
MS
t
+ a
4
INT
t 
+ e (1) 
where : 
R
t 
= Banking industry stock return at the period t 
a
0 
= the intercept term 
a
1
… a
4 
= the coefficient of each variable for period t 
INF
t
= monthly inflation rate at time t, which calculate by monthly CPI, and the 
formula is
INF
t
= (CPI
t
-CPI
t-1
)/CPI
t-1 
EX
t
= exchange rate at time t, the exchange rate is the monthly average real effective 
exchange rate
MS
t 
= money supply at time t, here using growth rate of monthly M2 to present, and 
the formula is
MS
t
= (MS
t
- MS
t-1
)/ MS
t-1
*100% 
INT
t
= monthly interest rate at time t, here using monthly Shanghai interbank offered 
rate to present 
e = error term 
The second model is designed to test the impact of four macroeconomic factors on the 
Shanghai stock exchange market return. 
MRSH
t 
= b
0
+ b
1
INF
t 
+b
2
EX
t
+ b
3
MS
t
+ b
4
INT
t 
+ e (2) 
Where: 
MRSH
t 
= Shanghai stock exchange market return at the period t 
b
0 
= the intercept term 

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26 
b
1
… b
4 
= the coefficient of each variable for period t 
INF
t
= monthly inflation rate at time t, which calculate by monthly CPI, and the 
formula is
INF
t
= (CPI
t
-CPI
t-1
)/CPI
t-1 
EX
t
= exchange rate at time t, the exchange rate is the monthly average real effective 
exchange rate
MS
t 
= money supply at time t, here using growth rate of monthly M2 to present, and 
the formula is
MS
t
= (MS
t
- MS
t-1
)/ MS
t-1
*100% 
INT
t
= monthly interest rate at time t, here using monthly Shanghai interbank offered 
rate to present 
e = error term 
The third model is designed to test the impact of four macroeconomic factors on the 
Shenzhen stock exchange market return. 
MRSZ
t 
= c
0
+ c
1
INF
t 
+c
2
EX
t
+ c
3
MS
t
+ c
4
INT
t 
+ e (3) 
where : 
MRSZ
t 
= Shenzhen stock exchange market return at the period t 
c
0 
= the intercept term 
c
1
… c
4 
= the coefficient of each variable for period t 
INF
t
= monthly inflation rate at time t, which calculate by monthly CPI, and the 
formula is
INF
t
= (CPI
t
-CPI
t-1
)/CPI
t-1 
EX
t
= exchange rate at time t, the exchange rate is the monthly average real effective 
exchange rate
MS
t 
= money supply at time t, here using growth rate of monthly M2 to present, and 
the formula is
MS
t
= (MS
t
- MS
t-1
)/ MS
t-1
*100% 
INT
t
= monthly interest rate at time t, here using monthly Shanghai interbank offered 
rate to present 

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27 
e = error term 
The fourth model is designed to test the impact of four macroeconomic factors on the 
banking industry stock return when adding the control factor such as Shanghai stock 
exchange market return. 
R
t 
= d
0
+ d
1
INF
t 
+d
2
EX
t
+ d
3
MS
t
+ d
4
INT
t 
+d
5
MRSH
t
+ e (4) 
where: 
R
t 
= Banking industry stock return at the period t 
d
0 
= the intercept term 
d
1
… d
5 
= the coefficient of each variable for period t 
INF
t
= monthly inflation rate at time t, which calculate by monthly CPI, and the 
formula is
INF
t
= (CPI
t
-CPI
t-1
)/CPI
t-1
EX
t
= exchange rate at time t, the exchange rate is the monthly average real effective 
exchange rate
MS
t 
= money supply at time t, here using growth rate of monthly M2 to present, and 
the formula is
MS
t
= (MS
t
- MS
t-1
)/ MS
t-1
*100% 
INT
t
= monthly interest rate at time t, here using monthly Shanghai interbank offered 
rate to present 
MRSH
t 
= Shanghai stock exchange market return at the period t 
e = error term 
The fifth model is designed to test the impact of four macroeconomic factors on the 
banking industry stock return when adding the control factor such as Shenzhen stock 
exchange market return. 
R
t 
= f
0
+ f
1
INF
t 
+f
2
EX
t
+ f
3
MS
t
+ f
4
INT
t 
+f
5
MRSZ
t
+ e (5) 
where: 
R
t 
= Banking industry stock return at the period t 
f
0 
= the intercept term 
f
1
… f
5 
= the coefficient of each variable for period t 

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28 
INF
t
= monthly inflation rate at time t, which calculate by monthly CPI, and the 
formula is
INF
t
= (CPI
t
-CPI
t-1
)/CPI
t-1
EX
t
= exchange rate at time t, the exchange rate is the monthly average real effective 
exchange rate
MS
t 
= money supply at time t, here using growth rate of monthly M2 to present, and 
the formula is
MS
t
= (MS
t
- MS
t-1
)/ MS
t-1
*100% 
INT
t
= monthly interest rate at time t, here using monthly Shanghai interbank offered 
rate to present 
MRSZ
t 
= Shenzhen stock exchange market return at the period t 
e = error term