ggggg

4.5 Autoregressive models: Such models like autoregressive (AR) model and the
exponential generalized autoregressive conditional heteroskedasticity (EGARCH)
model are useful to test the impact of Brexit on the dynamic linkages and
causal relationships among the selected stock markets.

Table
12 depicts  the results of the empirical
analysis with AR(1)–EGARCH(1,1)  models
during        pre-Brexit period. All the
coef?cients  of the EGARCH term (?) , all
coefficients of asymmetric effects (?) 
and GED parameter estimates have been 
found to be  statistically
signi?cant at the 1% level. Since each of these values  is less than 
2, hence we can conclude that 
tails of the error terms are heavier than tail of the normal
distribution. Evidently it  indicates the
existence of ARCH effects. Moreover, this table 
indicates the diagnostics statistics of analysis of the AR–EGARCH
models—the Q(s) and the Q 2(s) . The Q statistic at lag s, Q(s), is
a test statistic for the null hypothesis that there is no autocorrelation up to
order s for standardized residuals; it is asymptotically distributed as
chi-square, with the degrees of freedom equal to the number of autocorrelation
less the number of parameters. The Q 2(s)  is that for squared residuals . Result of
this paper accepted the null hypothesis of no autocorrelation up to order 20
for standardized residuals and standardized squared residuals over all the
selected countries, which supports the speci?cation of each model. 

We Will Write a Custom Essay Specifically
For You For Only $13.90/page!


order now

Tables
13 describes  the sample cross-correlations
(during  pre-Brexit period) of the
standardized residuals and standardized squared residuals. Evidently the
statistical significance of the cross-correlation of the standardized residuals
and that of the squares of  standardized
residuals  imply there is evidence of
causality in mean  and variance
respectively. As per the results obtained, it is clear that there is a close
relationship in mean between the stock market in UK and the stock markets in
selected developing countries in Asia. Moreover, feedback dependency in mean
has been observed with India and China with respect to UK. However, no feedback
has been found for Russia and Japan. Further causality in variance has been
found for all the selected Asian countries except Russia.  It is to be noted that for causality in
variance, feedback also has been found for India and China as like as causality
in mean. Thus, it can be concluded that before Brexit, there is a dynamic
linkage (in mean as well as in variance) between the UK and the selected developing
countries in Asia.

Table -12 : Results of empirical analysis of the AR–EGARCH
models  before Brexit  period.               (February  23,
2016 to  June 23,2016)

 

UK

China

Russia

Japan

India

Model

AR(1)-EGARCH(1,1)

AR(1)-EGARCH(1,1)

AR(1)-EGARCH(1,1)

AR(1)-EGARCH(1,1)

AR(1)-EGARCH(1,1)

Mean
Equation

a0

0.0004
(0.0002)

0.0015 (0.0003)
**

0.0017 (0.0004)
**

0.0018
(0.0006)
**

0.0013 (0.0002)
**

a1

– 0.0646
(0.0336)

0.0455
(0.0349)

0.0478
(0.0358)

0.0462
(0.0366)

0.0489
(0.0358)

Variance
Equation

?

-0.3336 (0.0813) **

-0.3324 (0.1224)**

-0.8125 (0.1523) **
 

-0.5789 (0.2237)**
 

– 1.11561
(0.2556) **
 

?1

0.2191 (0.0374) **
 

0.1713 (0.0458) **

0.2223 (0.0482) **

0.2683 (0.0412) **

0.2512
(0.0541) **

?1

-0.1475 (0.0311) **

-0.0422 (0.0246) **

-0.2087 (0.0352) **

-0.1268 (0.0313) **

-0.1656 (0.0389) **

?1

0.8765 (0.0281) **

0.9762 (0.0261) **

0.8555 (0.0283) **

0.9785 (0.0261) **

0.8995 (0.0291) **

GED parameter

1.4429
(0.0905)**

1.5479
(0.0907)**

1.4328
(0.0911)**

1.6422
(0.0955)**

1.4722
(0.0885)**

Diagnostic

Q(20)

16.429
[0.690]

18.173
[0.536]
 

12.251
[0.922]
 

17.872
[0.571]

19.385
[0.217]
 

Q2(20)

13.724
[0.792]

26.028
[0.209]

11.278
[0.944]
 

8.575
[0.956]
 

16.708
[0.706]
 

Data Source:

https


Result: Computed using E-Views.                                                                                            
** Statistical signi?cance at 0.01 level of significance.                                          

Note: The figures in ()  and []represent  standard errors &  p -values respectively. Q(20) symbolically
indicates Ljung–Box Q statistic. 

 

 

 

Table -13: Test
statistics for causality-in-mean and variance before Brexit  period. 
(February  23, 2016 to  June 23,2016)

M1
(causality-in-mean)

 

M2
(causality-in-variance)

 

India -> UK
13.9222**

UK -> India
11.9239**

India -> UK
19.7732**

UK -> India
23.6739**

Japan -> UK
0.9239

UK -> Japan
22.4536**

Japan -> UK
0.9239

UK -> Japan
17.8731**

Russia -> UK
0.7201

UK -> Russia
17.9288**

Russia -> UK
0.9239

UK -> Russia
0.9239

China -> UK
18.9554**

UK -> China
27.7769**

China -> UK
20.8736**

UK -> China
21.9999**

Data Source:

https


Result: Computed using E-Views.                                                                                            
** Statistical signi?cance at 0.01 level of significance.

 Results of table 11 and table 12 can be represented,
in a logical block diagram in figure-1 and in figure-2  as follows.

Japan

 

India

 

Japan

 

India

 

                                                                                                               

                                                                                                                                              

 

 

China

 

Russia

 

China

 

Russia

 

                                                                                                                    

 

   Figure-1 :  Logical Block Diagram               Figure-2 :  Logical Block Diagram                                                                                                                                         
for Causality in Mean (pre-Brexit)            for Causality in Variance
(pre-Brexit)

 

 

 

 

 

 

 
For post-Brexit, the same type of analysis has been done and table 14
and table 15 have been found. Results of table 14 and table 15
can be represented, in a logical block diagram in figure-3 and in figure-4  as follows.

Japan

 

India

 

Japan

 

India

 

                                                                                                               

                                                                                                                                              

        UK

 

 

 

China

 

Russia

 

China

 

Russia

 

                                                                                                                    

 

   Figure-3 :  Logical Block Diagram               Figure-4 :  Logical Block Diagram                                                                                                                                         
for Causality in Mean (post-Brexit)            for Causality in Variance
(post-Brexit)

 

Table -14 : Results of empirical analysis of the AR–EGARCH
models  after  Brexit 
period.               (March 30, 2017 to  September 29,2017)                        

 

UK

China

Russia

Japan

India

Model

AR(1)-EGARCH(1,1)

AR(1)-EGARCH(1,1)

AR(1)-EGARCH(1,1)

AR(1)-EGARCH(1,1)

AR(1)-EGARCH(1,1)

Mean
Equation

a0

0.0014
(0.0007)

0.0013
(0.0004)
**

0.0013
(0.0005)
**

0.0012
(0.0003)
**

0.0011
(0.0008)
**

a1

– 0.0546
(0.0326)

0.0475
(0.0339)

0.0422
(0.0353)

0.0461
(0.0375)

0.0535
(0.0351)

Variance
Equation

?

-0.3831 (0.0711) **

-0.3374 (0.1204)**

-0.8421 (0.1123) **
 

-0.5319 (0.2230)**
 

– 1.1562
(0.2552) **
 

?1

0.2181 (0.0365) **
 

0.1793 (0.0471) **

0.2723 (0.0412) **

0.2613 (0.0433) **

0.1517
(0.0581) **

?1

-0.1445 (0.0316) **

-0.0472 (0.0206) **

-0.2067 (0.0358) **

-0.1238 (0.0817) **

-0.1336 (0.0341) **

?1

0.8705 (0.0381) **

0.9062 (0.0267) **

0.8512 (0.0263) **

0.9005 (0.0265) **

0.8325 (0.0294) **

GED parameter

1.4489
(0.0985)**

1.5779
(0.0903)**

1.4558
(0.0917)**

1.6523
(0.0935)**

1.4121
(0.0885)**

Diagnostic

Q(20)

17.425
[0.690]

16.178
[0.536]
 

15.259
[0.922]
 

16.874
[0.571]

18.665
[0.217]
 

Q2(20)

14.724
[0.592]

16.028
[0.609]

13.988
[0.844]
 

18.599
[0.946]
 

15.798
[0.636]
 

Data Source:

https


Result: Computed using E-Views.                                                                                            
** Statistical signi?cance at 0.01 level of significance.                                         

Note: The figures in ()  and []represent  standard errors &  p -values respectively. Q(20) symbolically
indicates Ljung–Box Q statistic. 

Table -15: Test
statistics for causality-in-mean and variance after Brexit  period. 
(March 30, 2017 to 
September 29,2017)

M1
(causality-in-mean)

 

M2
(causality-in-variance)

 

India -> UK
0.5274

UK -> India
0.7254

India -> UK
0.5232

UK -> India
0.6537

Japan -> UK
0.9559

UK -> Japan
0.4226

Japan -> UK
0.9239

UK -> Japan
15.2571**

Russia -> UK
0.6204

UK -> Russia
0.8213

Russia -> UK
0.4259

UK -> Russia
0.9255

China -> UK
16.8854**

UK -> China
0.7551

China -> UK
0.5126

UK -> China
0.9849

Data Source:

https


Result: Computed using E-Views.                                                                                            
** Statistical signi?cance at 0.01 level of significance.

 

Thus remarkable difference has been
found in pre-Brexit and post-Brexit periods. Hence it can be concluded that
Brexit definite has a high impact on stock markets in Asia. More
specifically,  this paper shows the
enough evidence that Brexit made the dynamic linkages among selected stock
markets weak by eliminating the causality relations in mean and in variance (as
evident from figure 1, figure 2, figure 3 and figure 4).

 

 

 

 

5.
Conclusion

After verifying the
influence of Brexit on selected stock markets, the present paper uses  the test developed by Hong (2001) to
investigate the causal relationships of stock markets  in mean and variance between the selected
developing Asian countries  and the
United Kingdom. In particular, the paper focused on the impact of  Brexit, on the short term dynamic linkages
between the stock prices of the selected countries. Our empirical results
indicated that the international transmission of stock prices between the
selected developing countries in Asia and the United Kingdom  signi?cantly weakened in both the mean and
variance after the event of Brexit. This findings definitely  will change in both retail investors as well
as institutional investors  behavior due
to  the happening of Brexit and provide
guidance to them for managing  portfolio
diversification over different stock markets in the world. The findings of this
paper may shift funds gradually from stock markets to other financial markets
such as commodities market or gold market in the post-Brexit period.

Leave a Reply

Your email address will not be published. Required fields are marked *