Time varying integration amongst the South Asian equity markets: An empirical study

Figures & data

Table 1. Description about benchmark equity indices of SAARC Countries

Country	Benchmark Index	Description
BANG	Dhaka Index	Dhaka Index was the benchmark index of Bangladesh before it was discontinued from 1 August 2013. Now DSE Broad Index (DSEX) is a broad market index and is designed to reflect the broad Bangladesh market performance
IND	Nifty 50 Index	Benchmark stock index for Indian economy tracking diversified 50 stock index accounting for 13 sectors of the economy
NEP	NEPSE Index	Benchmark stock index of Nepal
MALD	MASIX Index	Benchmark stock index of Maldives
PAK	KSE 100 Index	Benchmark stock index for Pakistan economy tracking diversified 100 stock index on market capitalization
SRI	Sri Lanka 20 Index	The S&P Sri Lanka 20 Index is market capitalization-weighted and provides liquid exposure to the Sri Lanka Market

Note: BANG, IND, NEP, MALD, PAK and SRI denote Bangladesh, India, Nepal, Maldives, Pakistan and Sri Lanka, respectively.

Table 2. Fundamental determinants of equity market integration

Category	Variable	Measurement	Reference studies	Data source
Macro	GDP growth rate	Annual Real GDP growth rate (%)	Vo and Daly (2007), Guesmi et al. (2013) and Ng et al. (2013)	World Bank
	GDP per capita	Real GDP per capita	Vo and Daly (2007) and Ng et al. (2013)	World Bank
	Index of Industrial Production	Log (IIP)	Büttner and Hayo (2011) and Guesmi et al. (2013)	CEIC Asia Database
	Current Account Balance	Current account as % of GDP	Guesmi et al. (2013)	World Bank
	Inflation Rate	Annual Growth rate of GDP Deflator (%)	Vo and Daly (2007) and Huoy and Goh (2007)	World Bank
	Short term Interest Rate	Repo rate (%)	Huoy and Goh (2007)and Guesmi et al. (2013)	CEIC Asia Database
	Budget Balance	Budget Balance/Surplus as % of GDP	Arfaoui and Abaoub (2010)	World Bank
	Govt. Debt	Gross Public Debt as % of GDP	Gill, Sugawara, and Zalduendo (2014)	World Bank
	Govt. Tax Revenues	Tax Revenue as % of GDP	Vo and Daly (2007)	World Bank
	Foreign Direct Investment	Net FDI as % of GDP	Ng et al. (2013)	World Bank
	Foreign Indirect Investment	Net FII as % of GDP	Ng et al. (2013)	World Bank
	Governance Index	Arithmetic Mean of 6 Broad dimensions of governance	Vo and Daly (2007) and Ng et al. (2013)	World Governance Indicators, Authors Calculation
	Volatility of Forex Rate	EGARCH(1,1) based Conditional volatility estimate of FX Rate	Huoy and Goh (2007) and Guesmi et al. (2013)	Bloomberg, Authors calculations
	Liquidity Risk	Money Supply (M2) to Total Reserves	Brunnermeier, Nagel, and Pedersen (2008)	World Bank
Trade	Trade Tariff	Trade Tariff as % of Duty	Huoy and Goh (2007) and Guesmi et al. (2013)	WEF Global Competitive Index
	Total Trade	Total Trade as % of GDP	Vo and Daly (2007) and Guesmi et al. (2013)	World Bank
	Trade Intensity	Total Trade of country i with India/ Total trade of India	Huoy and Goh (2007)	World Bank, Authors calculation
Market	Market Size	Market Capitalization as %of GDP	Vo and Daly (2007) and Arfaoui and Abaoub (2010)	World Bank
	Stock Market Efficiency	Stock Market Turnover Ratio	Vo and Daly (2007) and Narayan, Sriananthakumar, and Islam (2014)	World Bank
	Volatility of Market Return	EGARCH(1,1) based Conditional volatility estimate of market return	Abad and Chuli´a (2014)	Bloomberg, Authors calculations
	Domestic Growth Opportunities	PE ratio of the sample market index	Bekaert et al. (2005)	Bloomberg
	Local Stock Market Conditions	Dividend Yield of the sample market index	Huoy and Goh (2007) and Guesmi et al. (2013)	Bloomberg

Table 3. Descriptive Statistics of sample return series

Country	Mean	Stdev	Max	Min.	Skew	Kurt	JB	LB	Arch LM	Obs.
BANG	0.0017	0.0159	0.0871	−0.2615	−3.16	58.01	193,340* [0.00]	31.52* [0.00]	134.13* [0.00]	1373
IND	0.0004	0.0162	0.1633	−0.1305	−0.22	9.92	10,290* [0.00]	35.50* [0.00]	105.03* [0.00]	2463
MALD	0.0000	0.0319	0.5557	−0.3372	2.99	75.66	641,279* [0.00]	74.45* [0.00]	0.0079 [0.93]	2682
NEP	0.0011	0.0109	0.0528	−0.0597	0.07	4.88	1414* [0.00]	39.49* [0.00]	178.58* [0.00]	1433
PAK	0.0006	0.0140	0.0825	−0.1204	−0.83	7.09	5352* [0.00]	74.94* [0.00]	161.01* [0.00]	2486
SRI	0.0004	0.0136	0.0811	−0.0844	−0.59	22.44	7624* [0.00]	119.46* [0.00]	43.82* [0.00]	2149
USA	0.0002	0.0127	0.1104	−0.0951	−0.19	10.55	7515* [0.00]	84.96* [0.00]	134.59* [0.00]	2682

Notes: Table displays summary statistics for the daily returns over the period from 6 January 2004 to 31 March 2015.

(a) *denotes level of significance at 5%. Values in parentheses [ ] indicate the p-values.

(b) Stdev = Standard Deviation, Skew = Skewness, Kurt = Kurtosis, JB = JarqueBera, LB = Ljung Box.LB statistics for serial correlation is reported up to 12 lags.

(c) BANG, IND, MALD, NEP, PAK and SRI denote benchmark equity indices of Bangladesh, India, Maldives, Nepal, Pakistan and Sri Lanka, respectively. USA denotes MSCI USA data. Data for all the indices are in local currency.

(d) Source: Bloomberg.

Table 4. Results of the marginal specification of return series of sample countries

Rcountry i,t	Mean Eqn.			Variance Eqn.
	µ	Rcountry i,t (−1)	RUSA (−1)	ω	α	ϒ	β
BANG	0.0021* (0.00)	−0.0289 (0.03)	0.0065 (0.02)	−0.9383* (0.18)	0.3626* (0.05)	−0.0371 (0.03)	0.9238* (0.02)
IND	0.0006* (0.00)	0.0086 (0.02)	0.2780* (0.02)	−0.3985* (0.06)	0.1952* (0.02)	−0.1089* (0.01)	0.9715* (0.00)
MALD	−0.0000 (0.00)	0.0000* (0.00)	0.0000* (0.00)	−8.3115* (0.49)	0.0065* (0.03)	−0.0622* (0.02)	0.3686* (0.01)
NEP	0.0006* (0.00)	0.2152* (0.03)	−0.0040 (0.01)	−1.3115* (0.19)	0.6393* (0.07)	−0.0125 (0.04)	0.9030* (0.02)
PAK	0.0006* (0.00)	0.0811* (0.02)	0.0041 (0.01)	−0.7471* (0.09)	0.4057* (0.03)	−0.0932* (0.02)	0.9487* (0.01)
SRI	0.0002 (0.00)	0.1886* (0.02)	−0.0125 (0.01)	−0.9083* (0.13)	0.(0.04)	−0.0268 (0.02)	0.9311* (0.01)

Notes: The table summarizes the EGARCH(1,1) estimation results.

(a) Figures in ( ) includes standard error. *Indicates significance at 5% level of significance.

(b) R_countryi,t and R_USA,t denote country i’s stock index returns and US index returns, respectively.

(c) Coefficient ω measures the constant term; Coefficient ϒ measures leverage effect while Coefficient β measures persistence (GARCH effect).

Table 5. Estimation results of time invariant copula models of dependence amongst sample equity markets

		Gaussian		Student t		Clayton		Gumbel
		Value	LL	Value	LL	Value	LL	Value	LL
BANG	IND	0.00	0.00	0.00	0.08	0.00	0.01	1.11	0.81
BANG	MALD	0.02	−0.26	0.02	−0.63	0.01	−0.04	1.13	1.51
BANG	NEP	0.00	−0.01	0.01	−3.45	0.04	−0.92	1.14	1.69
BANG	PAK	−0.05	−1.38	−0.04	−2.62	0.00	0.01	1.10	2.48
BANG	SRI	0.02	−0.21	0.02	−0.79	0.03	−0.52	1.09	1.23
IND	MALD	0.02	−0.17	0.01	−1.66	0.02	−0.60	1.11	3.17
IND	NEP	0.03	−0.66	0.03	−0.19	0.00	0.00	1.12	1.79
IND	PAK	0.00	−0.02	0.00	0.07	0.01	−0.04	1.11	6.39
IND	SRI	−0.02	−0.53	−0.02	−0.47	0.00	0.01	1.11	2.88
MALD	NEP	−0.04	−1.43	−0.04	−3.12	0.00	0.01	1.19	2.60
MALD	PAK	0.02	−0.53	0.02	−12.59	0.05	−2.78	1.19	2.69
MALD	SRI	−0.01	−0.17	−0.01	−0.32	0.01	−0.06	1.16	3.12
NEP	PAK	−0.01	−0.10	−0.01	−0.40	0.00	0.00	1.14	1.09
NEP	SRI	0.00	0.00	0.00	−0.12	0.04	−0.15	1.15	1.92
PAK	SRI	0.08	−6.34	0.08	−7.94	0.09	−7.27	1.13	5.38

Notes: (a) Value denotes the dependence parameter between the sample country benchmark stock returns using the different copula models.

(b) LL denotes the log likelihood value of the dependence parameter between sample country benchmark stock returns using the different copula models.

(c) Value in bold denotes lowest negative log likelihood thereby providing the best fit copula model amongst the family of models under study.

Figure 1. Regional trade intensity of major regional blocs of the world.

Source: UNCTAD, Authors Calculations, Note: ACP is African Caribbean and Pacific group of States, MERCOSUR is trading bloc in Latin America.

Figure 2. Time Varying Copula Models Dependences between sample country’s benchmark equity returns.

Source: Authors calculations. Notes: (a) The best fit time varying copula model selected by the goodness of fit test for different family of copula models plotted alongwith its corresponding time invariant dependency measure (in red line) (b) Dependences of India- Sri Lanka and Maldives- Nepal have been depicted in large decimal numbers just to show the differences.

Table 6. Goodness of Fit test for time varying copula models of dependence amongst sample equity markets

		Gaussian	Student t	Clayton
BANG	IND	0.66	0.06	0.71
BANG	MALD	0.55	0.12	0.29
BANG	NEP	0.00	0.00	0.03
BANG	PAK	0.19	0.14	0.51
BANG	SRI	0.47	0.03	0.64
IND	MALD	0.10	0.03	0.21
IND	NEP	0.11	0.00	0.00
IND	PAK	0.43	0.01	0.47
IND	SRI	0.83	0.06	0.93
MALD	NEP	0.10	0.08	0.47
MALD	PAK	0.14	0.20	0.12
MALD	SRI	0.20	0.02	0.08
NEP	PAK	0.36	0.05	0.47
NEP	SRI	0.42	0.05	0.52
PAK	SRI	0.71	0.04	0.28

Notes: Table presents the p-values of the goodness-of-fit test for the various copula models.

(a) Large p-values (bold face numbers) indicate that the copula provides best fit to the data.

(b) Goodness of fit test could not be estimated for time varying Gumbel Copula model as it exhibits upper tail dependence, indicating that large positive joint extreme events are more likely to occur than large negative ones and the given sample series has dependences which are close to 0.

Table 7. Return spillovers across equity markets of South Asian Countries

	BANG	IND	MALD	NEP	PAK	SRI	From others
BANG	98.74	0.51	0.05	0.07	0.43	0.20	1.30
IND	0.18	94.26	0.19	1.22	1.14	3.02	5.70
MALD	0.26	0.12	98.52	0.50	0.34	0.26	1.50
NEP	0.13	0.73	0.25	98.30	0.07	0.51	1.70
PAK	0.17	2.20	0.29	0.32	96.26	0.75	3.70
SRI	0.50	3.01	0.19	0.12	0.68	95.50	4.50
Contribution to others	1.20	6.60	1.00	2.20	2.70	4.80	18.40
Contribution including own	100.00	100.80	99.50	100.50	98.90	100.30	3.10%

Notes: Table presents Diebold and Yilmaz (2012) Spillover table summary for equity markets of the South Asian countries.

(a) The diagonal entries of the matrix represent the own variance share of the sample countries and the off-diagonal elements show the cross-market spillovers.

(b) The last column of the matrix (“from others”) highlights the gross directional return spillovers to the country from rest of the countries.

(c) The second last row (“to others”) indicates the gross directional spillover from a country to rest of the countries.

Figure 3. Total Returns Spillover Graph.

Figure 4. Portfolio Equity Inflows into SAARC Countries from SAARC and ASEAN + 6 Groups.

Source: IMF CPIS, Authors Calculations. Note: All figures are end of the period and in USD millions.

Figure 5. Portfolio Equity Outflows from sample SAARC countries to SAARC and ASEAN + 6 groups.

Source: IMF CPIS, Authors Calculations. Note: (a) All figures are end of the period and in USD millions b.) There is no data for Bangladesh, Maldives, Nepal and Sri Lanka as there are no portfolio outflows from these countries to either SAARC or the ASEAN+6 region for the given years.

Figure 6. Trends in Governance Indicators of SAARC and ASEAN + 6 Countries.

Source: World Governance Indicators, Authors Calculations. Notes: (a) AUS, BRU, CAM, CHI, IND, IDN, JAP, KOR, LAO, MYS, MMR, NZ, PHLP, SING, THAI and VIET denote Australia, Brunei, Cambodia, China, India, Indonesia, Japan, Korea, Lao, Malaysia, Myanmar, New Zealand, Philippines, Singapore, Thailand and Vietnam, respectively. These countries are part of larger ASEAN+6 group.

Figure 7. Trends in Total Trade (as percentage of GDP) of SAARC and ASEAN + 6 Countries.

Source: World Bank, Authors Calculations.

Figure 8 Trends in Trade Tariff (as percentage of duty) of SAARC and ASEAN + 6 Countries.

Source: World Economic Forum (WEF), Global Competitiveness Index.

Figure 9. Trends in Market Capitalization (as percentage of GDP) of SAARC and ASEAN + 6 Countries.

Source: World Bank.

Figure 10. Trade Intensity of India (ratio of total trade with India to total trade of India).

Source: World Bank, Authors Calculations.

Vo, X. V., & Daly, K. J. (2007). Determinants of International financial integration (R. P. C. Leal, Ed.). Global Finance Conference. Coppead Graduate School of Business, Federal University of Rio de Janerio.

 Google Scholar

Guesmi, K., Nguyen, D.-K., & Teulon, F. (2013). Further evidence on the determinants of regional stock markets integration in Latin America. European Journal of Comparative Economics, 34(1), 397–413.

 Google Scholar

Ng, L., Solnik, B., Wu, E., & Zhang, B. (2013). Characterizing global financial and economic integration using cash flow expectations ( Working paper of University of Wisconsin- Milwaukee).

 Google Scholar

Büttner, D., & Hayo, B. (2011). Determinants of European stock market integration. Economic Systems, 35(4), 574–585.10.1016/j.ecosys.2010.10.004

 Web of Science ®Google Scholar

Huoy, C. W., & Goh, K. L. (2007). The Determinants of Stock Market Integration: A Panel Data Investigation. In 15th Annual Conference on Pacific Basin Finance, Economics, Accounting and Management, Ho Chi, Minh City, Vietnam, 20 & 21 July.

 Google Scholar

Arfaoui, M., & Abaoub, E. (2010). On the determinants of international financial integration in the global business area. Journal of Applied Economic Sciences, 5(3), 153–172.

 Google Scholar

Gill, I., Sugawara, N., & Zalduendo, J. (2014). The center still holds: Financial integration in the Euro Area. Comparative Economic Studies, 56, 351–375.

 Google Scholar

Brunnermeier, M. K., Nagel, S., & Pedersen, L. H. (2008). Carry trades and currency crashes. NBER Macroeconomics Annual, 23, 313–347.

 Google Scholar

Narayan, S., Sriananthakumar, S., & Islam, S. Z. (2014). Stock market integration of emerging Asian economies: Patterns and causes. Economic Modelling, 39, 19–31.10.1016/j.econmod.2014.02.012

 Web of Science ®Google Scholar

Abad, P., & Chuli´a, H. (2014). European government bond market integration in turbulent times ( IREA Working Paper 2014/24). University of Barcelona.

 Google Scholar

Bekaert, G., Harvey, C. R., & Ng, A. (2005). Market integration and contagion. The Journal of Business, 78, 39–69.10.1086/jb.2005.78.issue-1

 Web of Science ®Google Scholar

Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57–66.10.1016/j.ijforecast.2011.02.006

 Web of Science ®Google Scholar