iBusiness, 2013, 5, 113-117
http://dx.doi.org/10.4236/ib.2013.53B024 Published Online September 2013 (http://www.scirp.org/journal/ib) 113
The Empirical Study about Introduction of Stock Index
Futures on the Volatility of Spot Market
Guiliang Tian, Huixiangzi Zheng
School of Business, Hohai University, China.
Received July,2013
ABSTRACT
April 16, 2010, China’ s first four Ind ex Future contr acts have been listed for trading in the stock exch ange. Stock index
futures are the world's fastest growing financial derivative products currently, and the research of them is of signifi-
cance to the development of China's financial market. Therefore, it is particularly important to concern the market op-
eration status of stock index future after its official listed. As we all know that there are linkage effects of the futures
and spot, stock index futures market will have some impact on the spot market. Based on the above point, this study
identified the Sh anghai and Shenzhen 300 stock index futures market as th e research object, focu sing on what volatility
affects the stock index futures have made on the spot market over the past 3 years. Through empirical findings, we can
evaluate the operation conditions of stock index futures market objectively. This paper applies GARCH model mainly,
and introduce dummy variables, collecting daily trading data between 16 April 2007 and 16 April 2013 on the spot
market, and studies the impact of volatility on the spot market in-depth by empirical test. The results showed that over
the past 3 years, introduction of stock index futures has reduced the volatility of the spot market which has brought a
positive impact.
Keywords: Index Future; Spot Market; Volatility; GARCH Model
1. Introduction
Stock index futures, which are based on prior agreement
between buyers and sellers, trade at a particular time in
the future, in accordance with the prior agreement of
both parties to engage in stock index trading shares of a
standardized protocol agreement. April 16, 2010, our
country's first financial derivatives - officially listed in
Shanghai and Shenzhen 300 stock index futures trading.
However, soon after its listing launched a vicious slump
appears unilateral market conditions, driving the stock
market also followed the collapse, and thus some schol-
ars have suggested that the stock index futures market
crash blame. Therefore, it is necessary to explore the
introduction of stock index futures on the volatility of the
spot market produce what kind of impact, in order to
clarify whether the stock index futures is the "culprit."
According to the impaction of stock index futures on
the spot market, scholars hold different views, and each
view has a lot of theoretical research and empirical re-
search support. Chan[1] on 1985-1987 Nikkei Stock Av-
erage daily trading data, with its day yield research ob-
ject, through the establishment of GARCH model, the
results found that the introduction of stock index futures
on the spot market is not significantly affected. Anton-
inus[2] based on FTSE 100 index tested a series of
econometric model, including unit root test, vector error
correction model, the establishment of such GARCH
model and found that the introduction of stock index fu-
tures, increased the volatility of the spo t prices stock, th at
is on the spot markets had a negative impact. Domestic
scholars Tian-cai Xing and Ge Zhang[3] based on FTSE
Xinhua A50 index futures, through the establishment of
GARCH model, analyzes its launch on the CSI 300 stock
index, the results found that the introduction of stock
index futures slightly increases the volatility of the spot
market, but this impact is very small. In 2010, they se-
lected the CSI 300 index futures trading simulation data,
through the establishment of GARCH model to test re-
sidual ARCH effects, etc., confirmed the launch of stock
index futures on the volatility of the spot market is not
greater impact. But because of the data from the simula-
tion trading system, therefore the reliability of the con-
clusions still needs to be fastidious.
From the existing research, the current domestic and
foreign scholars are mainly based on mature markets
abroad to study th e introdu ction of stock index futur es on
the spot market volatility impact on emerging markets
such like our lack of research, especially in China the

The Empirical Study about Introduction of Stock Index Futures on the Volatility of Spot Market
114
CSI 300 index futures launch date just over three years,
the research scholars are mostly simulation-based trans-
action data, and conclusions vary. Therefore, this paper
by choosing real transaction data were established befo re
and after the introduction of index futures GARCH
model, and the introduction of dummy variables, a series
of empirical tests to explore CSI 300 stock index futures
on the impact of volatility in the spot market, with certain
practical significance.
2. Research Methods
2.1. Sample Description
This data is selected April 16, 2007 to April 16, 2013 in
CSI 300 stock index futures contracts and the CSI 300
stock index daily closing price, that is listed on the CSI
300 stock index futures before and after the three years
of the corresponding stock the daily closing price of the
stock index of 1460 data. Among them, the futures data
for the selection of the main contract data, namely the
nearest month futures contracts of the daily closing price
data. In the most recent month before the contract set-
tlement date two or three days, month contract will be
converted into the main contract, and then turned to the
next nearest month futures contract closing data, and so
on, can be a continuous set of stock index futures price
time series. Data mainly comes from China Financial
Futures Exchange, and the News Finance website. In
accordance with the stock index futures launch time the
data is divided into two stages, the first stage before the
introduction of stock index futures, is from April 16,
2007 to April 16, 2010; second stage after the introduc-
tion of stock index futures, from April 16, 2010 to April
16, 2013.
2.2. Data Processing
Firstly, in order to eliminate heteroscedasticity, respec-
tively futures price and spot price series sequence loga-
rithm.
Assuming that the trading day closing price of a fu-
tures contract and the spot index closing price are de-
noted as t and t, then the natural logarithm of fu-
tures contract price series expressed as t
P Qln
t
F
P
ln
ttt
, its
logarithmic rate of return is 1 ln
F
PP

 , the
natural logarithm of stock price series expressed as
, its logarithm yields expressed as
ln
t
St Q
1
ln ln
tt
SQQ

 t .
The study object of this paper is the log return of stock
index future s and spot price rate.
2.3. Model Selection
Existence of financial time series data aggregation and
volatility heterosced asticity, OLS regression model is the
assumption that “homoscedasticity”, therefore, in the
study when the price volatility of financial products,
widely used heteroscedasticity model is the most widely
used in the 1982 Engle proposed autoregressive condi-
tional heteroskedasticity model (ARCH model), Boller-
slev deepened the ARCH model, the generalized autore-
gressive conditional heteroskedasticity model (GARCH
model), GARCH model can well reflect the aggregation
of price volatility, in the previous literature, the wide-
spread use of GARCH (1, 1) model reflects the aggrega-
tion of financial products.
This paper uses the GARCH (1, 1) model stock index
futures on the volatility of the spot market, and the in-
troduction of dummy variables in the conditional vari-
ance to reflect the CSI 300 stock index futures on the
impact of the stock market volatility, Before the intro-
duction of stock index futures, D = 0, after the introduc-
tion of stock index futures D = 1. The GARCH (1, 1)
model with the following :
The mean equation: ttt
yx




The conditional variance equation:
22
11tt
2
t

 

 
The GARCH (1, 1) model was respectively established
for the different stages, the model does not add dummy
variables.
3. Empirical Tests
We need to know the basic statistical characteristics of
the return series of CSI 300 index before the empirical
test.
From the Figure 1, we can clearly see that this series
has the cluster effect which most economic sequence
possesses. It means that the current price effected by the
prices of the previous period, which we call the ARCH
effect.
3.1. The Volatility Analysis of the Spot Price
Three Years before the Launch of CSI 300
Index Futures
1) Do the ADF test of return series of the stock index
-.10
-.05
.00
.05
.10
250 500 7501000 1250 150
0
Figure 1. The return’s volatility of stock index in whole
sample period.

The Empirical Study about Introduction of Stock Index Futures on the Volatility of Spot Market 115
First we do the ADF test of return series of the stock
index, the test result is as follows:
From the Table 1, we can see that the stationary test
results are significant, thus rejecting the null hypothesis
that the return series is stationary. Then we establish
ARMA model.
2) Establish ARMA model
a) Determine the value of p and q
Before the establishment of ARMA model, we should
see autocorrelation and partial autocorrelation chart of
the daily return series of Shanghai and Shenzhen 300
index three years before the introduction of futures. The
figure appears in several places which autocorrelation
and partial autocorrelation functions are significant,
therefore we cannot determine the value of p and q di-
rectly. Then we draw support with the AIC and SC prin-
ciple by imitating ARMA model within a 5-order.
By comparing the value of AIC and SC, we can build
ARMA(2,3) model.
b) Build ARMA(2,3) model
The following table is the output of ARMA (2,3).
As we can see from Table 2, the results of model es-
timation are good. At the 1% confidence level, in addi-
tion to the constant term, the P value of all the coeffi-
cients are less than 1%, passing the test, R ^ 2 = 50.20%.
Value of DW is around 2 which has no autocorrelation.
At this point, we remove the constant term. The expres-
sion of ARMA (2,3) model is as followings:
Table 1. The ADF test results.
t-Statistic Prob.*
ADF test -26.3974 0.0000
1% level -2.5681 0.0000
5% level -1.9412 0.0000
Significance
level
10% level -1.6164 0.0000
Table 2. Output of ARMA (2,3).
Variable Coefficient Std. Error t-Statistic Prob.
C -5.72E-06 1.31E-05 -0.4368 0.6624
AR(1) -1.0280 0.0086 -118.93 0.0000
AR(2) -0.9681 0.0086 -112.03 0.0000
MA(1) 0.0701 0.0074 9.4621 0.0000
MA(2) -0.0499 0.0078 -6.4055 0.0000
MA(3) -0.9817 0.0066 -149.81 0.0000
11112
23
1.0280 0.96810.0701
0.04990.9817
ttt
ttt
RRR
uu 
1t
u



 
 (1)
c) Do the ARCH Tests of ARMA (2,3) model
Before the establishment of GARCH model, we need
to test the ARCH effect of residuals series. We use the
method of ARCH-LM test. The result is as follows:
The result of ARCH-LM test is significant, indicating
that we can establish GARCH (1,1) model.
3) Build GARCH model
a) Build ARMA(2,3)-GARCH(1,1) model
The specific form of ARMA (2,3)-GARCH (1,1)
model is as follows:
Mean equation:
11112
23
1.0053 0.97450.0342
0.0 1 5 10 .9 8 2 4
ttt
ttt
1t
R
RR
uu

u



 

(2)
Variance equation:
22
11
0.00000538 0.06340.9279
tt
2
t



  (3)
As we can see from Figure 2: the current yield of the
spot index will be effected by yield of its lagged one pe-
riod at a strength of -1.0053, by yield of its lagged two
period at a strength of -0.97 45. The current vo latility will
be affected by the volatility of previous period at a
strength of 0.9279
b) Do the ARCH-LM test of residuals series.
Table 3. ARCH-LM test of residuals series.
F-statistic 4.7359 Probability 0.0002
Obs*R-squared 23.1165 Probability 0.0003
Table 4. Output of GARCH model.
CoefficientStd. Error z-StatisticProb.
Mean equation
AR(1) -1.0053 0.0060 -167.76 0.0000
AR(2) -0.9745 0.0052 -186.64 0.0000
MA(1) 0.0342 0.0042 8.2244 0.0000
MA(2) -0.0151 0.0061 -3.4693 0.0035
MA(3) -0.9824 0.0033 -295.86 0.0000
Variance equation
C 5.38E-06 2.74E-06 2.4586 0.0302
RESID(-1)^20.0634 0.0126 5.0356 0.0000
GARCH(-1)0.9279 0.0135 68.6766 0.0000

The Empirical Study about Introduction of Stock Index Futures on the Volatility of Spot Market
116
Table 5. Output of ARCH-LM test.
F-statistic 0.3319 Probability 0.8938
Obs*R-squared 1.6697 Probability 0.8927
The value of P is 0.8938, thus the ARCH effect of re-
siduals no longer exist, which indicates that ARMA
(2,3)-GARCH (1,1) model is fully fitted at the return
series of CSI 300 stock index.
3.2. The Volatility Analysis of the Spot Price
Three Years after the Launch of CSI 300
Index Futures
This section of the concrete steps is as above, so we will
not repeat. Establish GARCH model of returns on Spot
Index three years after the introduction of index futures
like follows:
Mean equation:
22
0.5013
tt
RR
1t


 (4)
Variance equation:
22
11
0.000014 0.04770.9036
tt
2
t



  
1t
u

(5)
As we can see: the current yield of the spot index will
be effected by yield of its lagged one period at a strength
of -0.5013. The current volatility will be effected by the
volatility of previous period at a strength of 0.9036.
3.3. Differences Analysis
Firstly, we draw the volatility chart of spot price in the
whole sample period.
From the figure, we can easily see that the volatility of
stock price has weakened three years after the introduc-
tion of stock index futures. So we can preliminary judge
that the introduction of stock index futures reduces the
volatility of the spot market.
Next, we will build a GARCH model based on the
whole sample interval, and introduce dummy variables.
Do positive and negative test of dummy variable coeffi-
cients, and see if it passed the examination to verify
whether the introduction of stock index futures reduces
the volatility of the spot market. Establishing revise
GARCH model likes follows:
Mean equation:
12
23
0.5431 0.27870.2774
0.76280.0499
ttt
ttt
RRR
uu 


 

(6)
Variance equation:
22
1
21
0.00000698 0.0345
0.95810.00000378
tt
t






 (7)
Figure 2. Volatility of whole sample period.
As we can see: the current yield of the spot index will
be effected by yield of its lagged one period at a strength
of -0.5431, by yield of its lagged two period at a strength
of 0.2787. The current volatility will be affected by the
volatility of previous period at a strength of 0.9581.
The most important, the coefficient of dummy variable
is negative, and passed the test, indicating that the intro-
duction of stock index futures reduces the volatility of
the spot market, which made a positive impact on the
spot market.
4. Conclusions and Recommendations
This article studies the impact of the introduction of
stock index futures on the volatility in the spot market by
establishing GARCH (1,1) model, and the introduction of
dummy variables, and found the stock index futures has a
slight decrease on the volatility of spot market volatility.
In order to promote the development of the stock index
futures market, reduce the negative impact to a minimum
of the future futures on the spot market may, we propose
the following comments and suggestions, mainly dis-
cussed from the two aspects include continue to improve
the spot market and strengthen the risk supervision and
management of the futures market.
4.1. Improve the Spot Market Continually
The development of stock index futures markets takes
the developed spot market as a precondition. Although
China's stock market has been so close to the interna-
tional advanced level in the technical facilities, forming
the aspect of market size, marketing supervision system,
information disclosure is also far behind, therefore, we
should strengthen the standardization of the spot market,
and promote the sharing and coordination management
of the stock market and stock index futures market.
4.2. Strengthen Risk Oversight and Management
of the Futures Market
Volatility is an important indicator to measure market

The Empirical Study about Introduction of Stock Index Futures on the Volatility of Spot Market
117
risk, the size of volatility determines the size of the mar-
ket, although the empirical test the introduction of stock
index futures in our country did not increase the volatility
of the spot market, because of the stock index futures
itself has a larger market risk, in order to continue to
promote the development of the futures market, we still
need to strengthen risk management of the stock index
futures. Combined with the actual situation of China's
market, we should mainly make the following recom-
mendations: A. Perfect market investors, strengthen in-
stitutional investors, leading the reasonable and health
investment philosophy in the market. For now, mainly
take the insurance companies, fund companies, securi-
ties companies as the main body of hedging, and en-
courage the arbitrage behavior of the market, reduce sys-
temic risk along with promote the price discovery func-
tion of futur es markets yield well and effectively. B. Im-
prove the management of various accounts. Since the
futures implement the policy o f margin, it is necessary to
strengthen the supervision of the trading margin and
clearing margin, implement the daily free debt settlement
system. At the same time, we also need to continue to
strengthen the management of the large positions system
and forced open system as well as take effectively care of
risk reserves, etc., and adopt international advanced
real-time monitoring technology to effectively circum-
vent the stock index futures market risks. C. Timely and
targeted introduce the institutional arrangements, im-
prove relevant laws and regulations, make the regulatory
abilities and adhere adapt the speed of development in
order to laid a good foundation for the entire market’s
healthy and stable development.
5. Acknowledgements
This study was funded by the National Natural Science
Foundation of China (Grant No. 41001377, 51279058)
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