CHAPTER 4: RESULTS AND DISCUSSIONS 4.1 Evolution of monetary policy and development of the Vietnam’s stock market
4.3 Research results on the impact of monetary policy on liquidity of Vietnam stock market
4.3.1 Overview of securities market liquidity in Vietnam
From Figure 4.5, liquidity ratios (traded volume, liquidity ratio and stock turnover ratio)increased gradually from 2009 to 2010. Total traded value increased sharply from April 2009 to 17.631 trillion dong and reached the highest level in the whole period of 86.3 trillion dong in October 2009. Liquidity tends to increase, especially from 2012 to 2016, showing that the liquidity of Vietnam’s stock market has been improved in width and depth.
Figure 4.5. Liquidity in the stock market of Vietnam
Source: author’s calculation 4.3.2 Descriptive statistics of the variables in the VAR model
Table 4.1 Descriptive statistics of the variables in the VAR model
Variable Mean Median Max Min St. dev Skewness Kurtosis No. obs
IP_SA 12,23 10,79 39,74 0,11 7,55 1,47 5,31 180
CPI_SA 8,03 6,80 29,62 0,00 6,28 1,57 5,27 180
M2_SA 25,12 23,63 51,18 10,37 8,38 0,77 3,35 180
IR 6,73 6,51 18,65 0,54 3,51 1,08 4,13 180
SR 0,94 -0,11 41,55 -26,11 9,84 0,81 5,40 180
ZEROS 4,49 4,45 22,22 0,00 5,38 1,34 4,42 180
TURNOVER 3,21 2,74 13,37 0,11 2,03 1,74 7,56 180
TV 1.90E+13 1.48E+13 8.28E+13 2.18E+10 1.89E+13 0,85 2,85 180 MLI 3.93E+05 5.11E+04 9.40E+06 1.09E+03 8.80E+05 6,58 63,30 180 LR 1.96E+11 1.29E+11 9.09E+11 1.06E+09 2.23E+11 1,14 3,33 180
AILLIQ 2,42 0,98 16,40 0,11 3,35 2,18 7,43 180
Source: Extract from Eviews 8.0 software
0 20,000 40,000 60,000 80,000 100,000
2002M1 2003M1 2004M1 2005M1 2006M1 2007M1 2008M1 2009M1 2010M1 2011M1 2012M1 2013M1 2014M1 2015M1 2016M1
Tỷ đồng TV
0 5 10 15 20 25
2002M1 2002M11 2003M9 2004M7 2005M5 2006M3 2007M1 2007M11 2008M9 2009M7 2010M5 2011M3 2012M1 2012M11 2013M9 2014M7 2015M5 2016M3
% Zeros
0 200 400 600 800 1,000
2002M1 2003M1 2004M1 2005M1 2006M1 2007M1 2008M1 2009M1 2010M1 2011M1 2012M1 2013M1 2014M1 2015M1 2016M1
LR
0.0000 0.0010 0.0020 0.0030 0.0040
2002… 2003… 2004… 2005… 2006… 2007… 2008… 2009… 2010… 2011… 2012… 2013… 2014… 2015… 2016…
MLI
0 5 10 15
2002M1 2002M12 2003M11 2004M10 2005M9 2006M8 2007M7 2008M6 2009M5 2010M4 2011M3 2012M2 2013M1 2013M12 2014M11 2015M10 2016M9
Turnover
0 5 10 15 20
2002M2 2002M12 2003M10 2004M8 2005M6 2006M4 2007M2 2007M12 2008M10 2009M8 2010M6 2011M4 2012M2 2012M12 2013M10 2014M8 2015M6 2016M4
Ailliq
Table 4.9 shows that the stock returns of the stock market has a minimum value of - 26.11% and a maximum of 41.55% during the study period. The variables reflecting the liquidity of the stock market include Turnover, TV and LR, and illiquidity variables including Zeros, MLI and Ailliq were calculated according to the formulas in Chapter 3. All data were collected and have normal distribution creating 180 observations, suitable for use in the VAR model in time series data analysis.
4.3.3 Stationarity, differencing of data and lag order of the models
The results in Table 4.10 show that most variables are stationary at base level, except for money supply and interbank rates. Thus, to ensure that the variables used are stationary, the first differencing of the variables that are not stationary at base level is performed. The results show that the variables not stationary at base level are stationary after being first differenced with 1% significance level.
Table 4.10 Results of the ADF and PP tests of the variables in VAR model
Variable Level Differenced Conclusion
ADF test PP test ADF test PP test
Zeros -4,9717*** -11,3724*** I(0)
LR -14,0837*** -23,9088*** I(0)
LR -10,2733*** -11,7968*** I(0)
TV -13,3127*** -25,5438*** I(0)
MLI -6,1684*** -4,9772*** I(0)
Turnover -13,7046*** -14,0208*** I(0)
Ailliq -9,8265*** -9,8256*** I(0)
SR -2,0751 -2,5923* -11,7516*** -11,9321*** I(1) IR -1,2655 -2,6524* -7,6133*** -10,7506*** I(1)
M2 -3,4358** -10,9083*** I(0)
IPI -2,6178* -2,6421* I(0)
CPI -2,6178* -2,6421* I(0)
Note: *, **, *** denotes significance at 10%, 5% and 1%
Source: Extracted from Eviews 8 Table 4.11 shows that the optimal lag order of VAR models is chosen according to AIC and FPE standards, as follows:
Table 4.11 Optimal lag order selection for VAR Models
Model Variables Optimal lag order to be
selected
VAR01 IPI, CPI, M2, IR, SR, ZEROS 2
VAR02 IPI, CPI, M2, IR, SR, LR 2
VAR03 IPI, CPI, M2, IR, SR, TV 2
VAR04 IPI, CPI, M2, IR, SR, MLI 2
VAR05 IPI, CPI, M2, IR, SR, TURNOVER
2
VAR06 IPI, CPI, M2, IR, SR, AILLIQ 3
Source: Author Summary from Eviews 8.0 Software Tests for the VAR model include verifying the overall stability of the model by finding the inverse root of characteristic polynomial AR and tests of autocorrelation of residuals. The results show that all solutions of polynomials are in the unit circle, indicating that the VAR models are stable. At the same time, the results show that there is no correlation between the residuals in the model (Appendix C1 to C5).
4.3.4 The results of estimating the impact of monetary policy on each liquidity characteristic of Vietnam’s stock market
Analyzing the impulse response function, we see the impact of monetary policy factors on liquidity characteristics including instantness, width, depth and elasticity of the market (Table 4.12).
Table 4.12 Direction of impacts of monetary policy factors on liquidity of Vietnam stock’s market
Liquidity
character Proxy Output Inflation Stock
return Interbank rate Money supply
Instantness ZEROS + - - 0 -
Width TV + - + 0 +
LR + - + - +
Depth Turnover + 0 + 0 +
MLI + 0 - + 0
Elasticity AILLIQ + 0 - 0 -
Note: sign (-): opposite effect, sign (+): same effect, (0): no impact Table 4.12 shows that liquidity measures of the market (TV, LR and Turnover) are proportional to M2 money supply and are almost unresponsive to changes in interbank rates. Meanwhile, iliquidity variables (Zeros, MLI and AILLIQ) fluctuated in inverse direction to the increase in M2 money supply and show less response to the increase of
interbank rates. This implies that when SBV loosens (tightens) monetary policy by increasing (decreasing) money supply, it will increase (reduce) liquidity of the stock market.
In addition, inflation has the opposite effect on all liquidity variables, indicating that the liquidity of the stock market will be reduced when there is an increase in consumer price index (inflation variable). Meanwhile, industrial output growth is positively correlated with the variables that represent the breadth and depth of the stock market.
The results of variance decomposition show that the money supply and interbank rates explain 8% - 10% of volatility of liquidity (or illiquidity) after a period of 9-12 months. The remaining variables explain 6% - 9% of volatility of liquidity variables within shorter window (only 3 months). This result shows that the monetary policy affects the liquidity of Vietnam’s stock market but the impact is not great.
It can be seen that the SBV has been continually changing its policies from loosening to tightening, and vice versa, especially in the period from 2007 to 2011, which caused significant impacts on stock price and liquidity of the stock market. As the stock market's liquidity decreases, the mobilization of capital of listed companies will become more challenging. Therefore, it is difficult for the stock market to play its role as a medium and long term capital mobilization channel for the economy.
In addition, the results of the study show that when there is a shock to inflation, the liquidity measures have decreased and the measure of liquidity has increased.
Consequently, continuing to maintain a stable long-term inflation rate of the SBV is essential not only to support the growth of the economy, but also to promote liquidity in the stock market.
Conclusion of Chapter 4
In this chapter, the dissertation presents the implementation of monetary policy by the State Bank of Vietnam, the evolution of the stock market and discussion of the research results.