How interrelated are MIST equity markets with the developed stock markets of the world?

Figures & data

Table 1. Summary statistics of daily data in levels

Indices	IPC	Jakarta composite	KOSPI	Istanbul national 100	S&P 500	FTSE 100	DAX	Hang Seng	STI	Nikkei 225
Number of obs.	2,610	2,610	2,610	2,610	2,610	2,610	2,610	2,610	2,610	2,610
Mean	24,033.24	2,065.62	1,418.84	1,401.84	1,200.14	5,272.46	5,571.03	17,885.94	2,530.58	11,597.27
Maximum	42,592.78	4,375.17	2,228.96	2,502.41	1,565.15	6,732.40	8,105.69	31,638.22	3,875.77	18,261.98
Minimum	5,763.87	379.35	515.24	326.64	676.53	3,287.00	2,202.96	8,409.01	1,213.82	7,054.98
Std. Dev.	10,709.66	1,182.99	453.88	539.97	181.35	775.03	1,392.51	4,725.53	616.46	2,927.65
skewness	−0.20	0.39	−0.26	−0.21	−0.34	−0.33	−0.27	−0.02	−0.28	0.79
Excess kurtosis	−1.27	−1.11	−1.17	−1.02	−0.48	−0.91	−0.90	−0.74	−0.86	−0.63
Jarque-Berra (JB) statistic	192.18	200.38	178.49	133.07	74.30	136.83	119.70	59.67	116.53	317.44
JB signif. level	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00

Table 2. Summary statistics of daily logarithmic returns

Indices	IPC	Jakarta composite	KOSPI	Istanbul national 100	S&P 500	FTSE 100	DAX	Hang Seng	STI	Nikkei 225
Number of obs.	2,609	2,609	2,609	2,609	2,609	2,609	2,609	2,609	2,609	2,609
Mean	0.0007	0.0009	0.0004	0.0005	0.0002	0.0001	0.0003	0.0003	0.0003	0.0000
Maximum	0.1044	0.0762	0.1128	0.1560	0.1096	0.0938	0.1080	0.1341	0.0753	0.1009
Minimum	−0.0727	−0.1095	−0.1117	−0.1696	−0.0947	−0.0926	−0.0743	−0.1358	−0.0870	−0.1211
Std. dev.	0.0129	0.0140	0.0145	0.0229	0.0128	0.0122	0.0148	0.0156	0.0117	0.0146
Skewness	0.0325	−0.6469	−0.4746	−0.4501	−0.2824	−0.1228	0.0142	0.0258	−0.2052	−0.7954
Excess kurtosis	6.2959	6.4738	5.8456	5.5959	10.7355	8.1924	5.5931	10.0379	5.7800	8.6711
Jarque-Berra statistic	4,309.44	4,737.97	3,812.67	3,492.22	12563.45	7,302.60	3,400.83	10953.62	3,650.11	8,448.59
JB signif. level	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000

Table 3. Bivariate Johansen test outcomes

Panel 3.1: Mexico and developed equity Markets						Panel 3.2: Indonesia and developed equity markets
Model specification		Trace statistic	5% critical value	Maximum eigen statistic	5% critical value	Model specification		Trace statistic	5% critical value	Maximum eigen statistic	5% critical value
IPC and S&P 500 indices	r = 0	3.915	15.495	3.782	14.265	Jakarta composite (JC) and S&P 500 indices	r = 0	4.065	15.495	3.886	14.265
	r ≤ 1	0.134	3.841	0.134	3.841		r ≤ 1	0.179	3.841	0.179	3.841
IPC and DAX indices	r = 0	6.346	15.495	6.055	14.265	JC composite and DAX indices	r = 0	4.352	15.495	4.352	14.265
	r ≤ 1	0.267	3.841	0.267	3.841		r ≤ 1	0.000	3.841	0.000	3.841
IPC and FTSE 100 indices	r = 0	5.007	15.495	4.944	14.265	JC and FTSE 100 indices	r = 0	5.878	15.495	5.857	14.265
	r ≤ 1	0.063	3.841	0.063	3.841		r ≤ 1	0.021	3.841	0.021	3.841
IPC and Hang Seng indices	r = 0	7.286	15.495	7.195	14.265	JC and Hang Seng indices	r = 0	5.837	15.495	5.651	14.265
	r ≤ 1	0.091	3.841	0.091	3.841		r ≤ 1	0.186	3.841	0.186	3.841
IPC and STI indices	r = 0	4.683	15.495	4.683	14.265	Jakarta composite and STI indices	r = 0	6.611	15.495	6.528	14.265
	r ≤ 1	0.000	3.841	0.000	3.841		r ≤ 1	0.083	3.841	0.083	3.841
IPC and Nikkei 225 indices	r = 0	4.634	15.495	4.622	14.265	JC and Nikkei 225 indices	r = 0	6.394	15.495	6.329	14.265
	r ≤ 1	0.012	3.841	0.012	3.841		r ≤ 1	0.065	3.841	0.065	3.841

Table 4. Bivariate Johansen test outcomes

Panel 4.1: South Korea and developed equity markets						Panel 4.2: Turkey and developed equity markets
Model specification		Trace statistic	5% critical value	Maximum eigen statistic	5% critical value	Model specification		Trace statistic	5% critical value	Maximum eigen statistic	5% critical value
KOSPI and S&P 500 indices	r = 0	4.261	15.495	3.287	14.265	Istanbul National 100 and S&P 500 Indices	r = 0	6.080	15.495	3.525	14.265
	r ≤ 1	0.974	3.841	0.974	3.841		r ≤ 1	2.555	3.841	2.555	3.841
KOSPI and DAX indices	r = 0	7.048	15.495	5.085	14.265	Istanbul National 100 and DAX indices	r = 0	14.230	15.495	11.438	14.265
	r ≤ 1	1.963	3.841	1.963	3.841		r ≤ 1	2.792	3.841	2.792	3.841
KOSPI and FTSE 100 indices	r = 0	6.582	15.495	5.026	14.265	Istanbul National 100 and FTSE 100 indices	r = 0	8.505	15.495	5.943	14.265
	r ≤ 1	1.555	3.841	1.555	3.841		r ≤ 1	2.562	3.841	2.562	3.841
KOSPI and Hang Seng indices	r = 0	9.353	15.495	7.660	14.265	Istanbul National 100 and Hang Seng indices	r = 0	10.235	15.495	7.777	14.265
	r ≤ 1	1.693	3.841	1.693	3.841		r ≤ 1	2.458	3.841	2.458	3.841
KOSPI and STI indices	r = 0	8.832	15.495	5.864	14.265	Istanbul National 100 and STI indices	r = 0	11.982	15.495	8.869	14.265
	r ≤ 1	2.967	3.841	2.967	3.841		r ≤ 1	3.113	3.841	3.113	3.841
KOSPI and Nikkei 225 indices	r = 0	6.105	15.495	5.681	14.265	Istanbul National 100 and Nikkei 225 indices	r = 0	4.695	15.495	4.339	14.265
	r ≤ 1	0.424	3.841	0.424	3.841		r ≤ 1	0.356	3.841	0.356	3.841

Figure 1. Mexico and developed markets: Recursive scaled trace statistic.

Figure 2. Indonesia and developed markets: Recursive scaled trace statistic.

Figure 3. South Korea and developed markets: Recursive scaled trace statistic.

Figure 4. Turkey and developed markets: Recursive scaled trace statistic.

Figure 5. Mexico and developed markets: Dynamic conditional correlations (Q_2,1).

Figure 6. Indonesia and developed markets: Dynamic conditional correlations (Q_2,1).

Table

	Mexico vs. US		Mexico vs. Germany		Mexico vs. UK
	IPC	S&P 500	IPC	DAX	IPC	FTSE 100
I. Returns Equations: E(yi, t/It − 1) = yi, t − ri, t
Constant	9.239e-04***	5.256e-04***	0.001***	9.409e-04***	0.001***	5.453e-04***
II. Volatility Equations: E(r^2i, t/It − 1)
Constant	2.368e-06***	1.328e-06***	3.086e-06	2.663e-06	3.072e-06***	1.251e-06***
r^2i, t − 1	0.078***	0.081***	0.084***	0.091***	0.083***	0.098***
hii, t − 1	0.908***	0.910***	0.896***	0.897***	0.897***	0.896***
III. Correlation Equation: E(εi, t εj, t/It − 1)
εi, t − 1εj, t − 1	0.018***		0.008***		0.005***
qi, j, t − 1	0.980***		0.990***		0.994***
r^2i, t − 1 + hii, t − 1	0.986	0.991	0.98	0.988	0.98	0.994
Algorithm	BFGS		BFGS		BHHH
Convergence (Iterations)	37		34		23
	Mexico vs. Hong Kong		Mexico vs. Singapore		Mexico vs. Japan
	IPC	Hang Seng	IPC	STI	IPC	Nikkei 225
I. Returns Equations: E(yi, t/It − 1) = yi, t − ri, t
Constant	9.965e-04***	6.488e-04***	0.001***	6.712e-04***	0.001***	0.000***
II. Volatility Equations: E(r^2i, t/It − 1)
Constant	3.110e-06 ***	1.542e-06***	3.181e-06***	1.182e-06***	0.000***	0.000***
r^2i, t − 1	0.090***	0.066***	0.089***	0.085***	0.094***	0.104***
hii, t − 1	0.891***	0.927***	0.891***	0.908***	0.886***	0.878***
III. Correlation Equation: E(εi, t εj, t/It − 1)
εi, t − 1 εj, t − 1	0.004^**		0.014		0.000
qi, j, t − 1	0.992***		4.731e-12		0.000
r^2i, t − 1 + hii, t − 1	0.981	0.993	0.98	0.993	0.98	0.982
Algorithm	BHHH		SIMPLEX(60) + BFGS		SIMPLEX(60) + BFGS
Convergence (iterations)	27		3		3

Table

	Indonesia vs. US		Indonesia vs. Germany		Indonesia vs. UK
	Jakarta composite	S&P 500	Jakarta composite	DAX	Jakarta composite	FTSE 100
I. Returns Equations: E(yi, t/It − 1) = yi, t − ri, t
Constant	0.002***	0.001***	0.002***	9.368e-04***	0.002***	5.526e-04***
II. Volatility Equations: E(r^2i, t/It − 1)
Constant	0.000***	0.000***	1.200e-05***	2.618e-06***	1.250e-05***	1.241e-06***
r^2i, t − 1	0.173***	0.083***	0.175***	0.091***	0.183***	0.098***
hii, t − 1	0.772***	0.903***	0.765***	0.895***	0.757***	0.895***
III. Correlation Equation: E(εi, tεj, t/It − 1)
εi, t − 1εj, t − 1	0.000		0.003		0.001
qi, j, t − 1	0.000		0.994***		0.998***
r^2i, t − 1 + hii, t − 1	0.945	0.986	0.94	0.986	0.94	0.993
Algorithm	SIMPLEX(60)+BFGS		SIMPLEX(2) + BHHH		SIMPLEX(2) + BHHH
Convergence (Iterations)	5		28		28
	Indonesia vs. Hong Kong		Indonesia vs. Singapore		Indonesia vs. Japan
	Jakarta Composite	Hang Seng	Jakarta Composite	STI	Jakarta Composite	Nikkei 225
I. Returns Equations: E(yi, t/It − 1) = yi, t − ri, t
Constant	0.001***	7.523e-04***	0.002***	6.906e-04***	0.002***	0.001***
II. Volatility Equations: E(r^2i, t/It − 1)
Constant	9.135e-06***	2.066e-06***	1.268e-05***	1.484e-06***	0.000***	0.000***
r^2i, t − 1	0.128***	0.075***	0.177***	0.087***	0.174***	0.108***
hii, t − 1	0.825***	0.916***	0.763***	0.902***	0.757***	0.871***
III. Correlation Equation: E(εi, tεj, t/It − 1)
εi, t − 1εj, t − 1	0.034***		0.026***		0.028***
qi, j, t − 1	0.948***		0.963***		0.936***
r^2i, t − 1 + hii, t − 1	0.953	0.991	0.94	0.989	0.931	0.979
Algorithm	BFGS		BFGS		BFGS
Convergence (iterations)	61		37		48