Foreign equity flows and stock market liquidity in Kenya

Figures & data

Table 1. NSE overall market activity, 2011–2018

	Trading Volume		Foreign Investor	Foreign Investor	Market Cap.	Listed	Market
Year	Shares (Millions)	Value (US$ Billions)	Participation (%)	Ownership (%)	(US$ Billions)	Firms	Index
2011	5684.7	0.78	32.9	19.4	10.36	58	3751
2012	5464.2	0.87	49.2	21.3	10.73	61	3736
2013	7576.2	1.56	51.4	22.5	16.92	61	4784
2014	8233.4	1.16	51.1	21.3	22.87	64	5155
2015	6812.1	1.09	52.4	21.5	22.09	64	4655
2016	5813.49	1.47	67.6	21.1	20.18	66	3186
2017	7065.36	1.72	72.41	20.2	25.11	67	3711
2018	6335.82	1.76	73.67	19.97	21.62	67	3833

Source: Nairobi Securities Exchange &Capital Markets Authority (Kenya).

Table 2. Important institutional reforms from January 2011 to December 2018

Date	Institutional reforms
Jul. 2011	The NSE introduced a faster settlement cycle. Specifically, they reduced the settlement period from 4 days (T + 4) to 3 days (T + 3)
Jun. 2014	The NSE converted from a privately-owned enterprise to a publicly owned enterprise (in a process commonly known as demutualization)
Jan. 2015	The Capital Markets Authority instituted a 5% tax on stock trading capital gains.
Jun. 2015	The Capital Markets Authority removed the cap on foreign investors’ shareholding (initially capped at 75%). Now, foreign investors can acquire 100 percent shares of any firm listed at NSE.
Sep. 2015	The 5% capital gains tax was removed.
Dec. 2017	NSE introduced short selling

Note: This table provides a list of some fundamental reforms that have been undertaken to boost liquidity at the NSE over the period 2011–2018.

Table 3. Selected country comparative annual stock turnover ratios

	2010	2011	2012	2013	2014	2015	2016
Kenya	9.0	6.8	8.1	6.3			8.9
Mauritius	4.7	6.5	4.1	3.4	5.3	6.4	4.4
Nigeria	12.5	8.36	7.3	7.9	11.7
Zambia	3.11	1.59	0.73			0.76
Zimbabwe	10.1	12.9	11.3	6	10.5	7.44	4.8
South Africa	29.9	28.6	24.9	24.6	26.3	31.7	38.3
Sub-Saharan Africa	28.32	27	24.8	24.4	24.6	29.7	26.1
Middle East and North Africa	31.1	16.2	16.3	13.2	20.6	13.8	18.4
Latin America	44.6	49.1	47.3	49.9	49.9	52.2	47.6

Source: African Securities Exchange Association (ASEA, 2014) and World Bank Development Indicators (WDI, 2016)

Table 4. Summary statistics and correlation matrix

	FLOWS	MRET	MVOL	ILLIQ	HH	LM	LI
Mean	0.037	−0.004	0.023	1.141	1.755	1.439	0.503
Max	0.464	0.119	0.033	4.601	6.514	2.797	0.682
Min	−0.397	−0.105	0.016	0.179	0.521	0.601	0.331
SD	0.183	0.043	0.003	0.904	1.052	0.478	0.093
AR(1)	0.479	0.196	0.484	0.745	0.693	0.476	0.817
AR(2)	0.348	0.163	0.320	0.581	0.672	0.556	0.765
AR(3)	0.252	0.165	0.297	0.526	0.591	0.482	0.713
Correlation Matrix
FLOWS	1
MRET	0.099	1
MVOL	−0.173*	−0.077	1
ILLIQ	−0.238**	−0.109	0.482***	1
HH	−0.290***	−0.245**	0.477***	0.774***	1
LM	0.071	0.111	0.375***	0.694***	−0.439*	1
LI	0.124	0.244**	−0.426***	−0.765***	−0.673*	−0.873*	1
N	96	96	96	96	96	96	96

Note: Table 4 reports the summary statistics and correlation matrix for the aggregate market variables and foreign flows. FLOWS denote the net foreign equity inflows scaled by the aggregate market capitalization. MRET is the equally weighted monthly average returns for the sample (48) stocks. MVOL is the monthly average standard deviations of stock returns (for sample stocks). ILLIQ, HH, LM and LI are liquidity measures explained in appendix A. The sample period spans January 2011 to December 2018. The *, **, *** represent respectively, the 10%, 5%, and 1% significance level.

Figure 1. Cumulative net purchases and market index.

Figure 2. Net foreign purchases and stock market liquidity.

Table 5. Unit root test results

	ADF			PP
Variable	Intercept	Trend & Intercept	Decision	Intercept	Trend & Intercept	Decision
FLOWS	−4.485	−4.549	I(0)	−4.539	−4.496	I(0)
MRET	−8.827	−8.782	I(0)	−8.972	−8.932	I(0)
MVOL	−5.5625	−6.623	I(0)	−5.659	−6.69	I(0)
lnVIX	−3.120	−3.229	I(0)	−3.141	−3.382	I(0)
lnILLIQ	−2.217	−2.316	I(1)	−3.965	−4.162	I(0)
lnHH	−1.608	−2.492	I(1)	−2.497	−4.157	I(0)
lnLM	−3.798	−3.842	I(0)	−6.158	−6.437	I(0)
lnLI	−2.261	−2.309	I(1)	−2.477	−3.645	I(0)
Critical Values
1%		−3.662			−3.648
5%		−2.964			−2.958
10%		−2.614			−2.612

Figure 3. Impulse response functions of foreign flows, liquidity, and market returns.

Figure 3. Continued.

Table 6. Forecast error variance decomposition

Liquidity Measure	Month	FLOWS	MRET
ILLIQ	1	1.72	0.04
	3	4.76	10.66
	6	9.47	15.82
	12	24.62	18.85
HH	1	0.67	9.29
	3	2.76	25.78
	6	13.56	29.45
	12	31.02	28.06
LM	1	1.95	2.19
	3	2.41	13.74
	6	4.56	16.52
	12	10.94	18.97
LI	1	0.43	16.67
	3	1.26	44.97
	6	11.52	50.12
	12	31.12	45.34

Figure 4. IRFs-alternative measure of foreign equity flow.

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Table

	lnILLIQ			lnHH			lnLM			lnLI
	FLOWS	MRET	lnILLIQ	FLOWS	MRET	lnHH	FLOWS	MRET	lnLM	FLOWS	MRET	lnLI
FLOWS(−1)	0.39	−0.01	0.02	0.41	−0.01	0.06	0.39	−0.01	0.06	0.40	−0.01	0.00
	[3.58]	[−0.41]	[0.16]	[3.65]	[−0.40]	[0.53]	[3.69]	[−0.43]	[0.65]	[3.57]	[−0.48]	[0.19]
FLOWS(−2)	0.11	0.06	−0.28	0.10	0.06	−0.08	0.11	0.06	−0.13	0.13	0.06	0.04
	[0.95]	[2.07]	[−2.25]	[0.83]	[2.04]	[−0.69]	[0.99]	[2.06]	[−1.43]	[1.07]	[2.05]	[1.65]
FLOWS(−3)	0.08	0.07	0.09	0.07	0.07	−0.21	0.10	0.06	0.00	0.07	0.07	0.00
	[0.66]	[2.35]	[0.74]	[0.59]	[2.34]	[−1.74]	[0.86]	[2.31]	[−0.04]	[0.64]	[2.43]	[−0.07]
MRET(−1)	−0.17	0.02	−1.35	−0.15	0.01	−1.58	0.02	0.03	−1.35	−0.04	0.01	0.55
	[−0.40]	[0.22]	[−2.95]	[−0.32]	[0.12]	[−3.42]	[0.06]	[0.34]	[−3.86]	[−0.07]	[0.08]	[5.94]
MRET(−2)	0.44	0.11	−0.51	0.36	0.09	−0.57	0.59	0.08	0.18	0.61	0.10	0.13
	[1.02]	[1.07]	[−1.12]	[0.79]	[0.82]	[−1.23]	[1.42]	[0.79]	[0.53]	[1.29]	[0.89]	[1.42]
MRET(−3)	0.25	0.13	−0.31	0.01	0.14	−0.02	0.17	0.19	0.18	0.16	0.20	−0.01
	[0.58]	[1.23]	[−0.67]	[0.02]	[1.36]	[−0.04]	[0.39]	[1.88]	[0.52]	[0.35]	[1.85]	[−0.08]
lagged LIQ (−1)	0.03	0.01	0.47	0.04	−0.01	0.18	0.21	−0.03	0.07	−0.46	0.12	0.12
	[0.26]	[0.29]	[4.61]	[0.34]	[−0.46]	[1.61]	[1.64]	[−0.88]	[0.63]	[−0.84]	[0.90]	[1.07]
lagged LIQ (−2)	0.06	−0.01	0.01	−0.10	0.01	0.39	0.09	0.06	0.39	0.05	−0.22	0.31
	[0.61]	[−0.28]	[0.06]	[−1.04]	[0.25]	[3.85]	[0.75]	[2.08]	[4.08]	[0.11]	[−1.94]	[3.23]
lagged LIQ (−3)	−0.14	0.01	0.37	0.02	0.01	0.23	−0.33	−0.01	0.31	0.33	0.07	0.40
	[−1.57]	[0.67]	[3.81]	[0.15]	[0.56]	[2.20]	[−2.79]	[−0.49]	[3.17]	[0.64]	[0.59]	[4.02]
C	0.01	−0.03	−0.20	0.02	−0.03	0.10	0.03	−0.05	0.01	0.04	−0.02	0.10
	[0.10]	[−0.87]	[−1.44]	[0.18]	[−0.89]	[0.69]	[0.20]	[−1.32]	[0.09]	[0.21]	[−0.34]	[2.35]
MVOL	1.33	0.53	14.23	1.38	0.68	4.97	0.34	1.17	8.64	−0.14	1.12	−1.44
	[0.23]	[0.38]	[2.27]	[0.23]	[0.46]	[0.79]	[0.05]	[0.82]	[1.79]	[−0.02]	[0.79]	[−1.21]
Adj. R-squared	0.20	0.14	0.75	0.19	0.14	0.76	0.25	0.18	0.54	0.19	0.17	0.82

This table presents the regression results of VAR (3) models (for the four liquidity measures, ILLIQ, HH, LM, and LI). The endogenous variables are market liquidity, net foreign equity purchases, and market returns. Market volatility, VIX, market conditions, and monthly seasonal dummies are applied as exogenous in the system. Particularly, the table provides; regression coefficients, t-statistics (in square brackets), and the adjusted R-square. The data relate to 48 sample NSE stocks over the period from January 2011 to December 2018.