An empirical study on impact of monetary policy on vietnamese stock market’s liquidity

Nội dung text: An empirical study on impact of monetary policy on vietnamese stock market’s liquidity

1. AN EMPIRICAL STUDY ON IMPACT OF MONETARY POLICY ON VIETNAMESE STOCK MARKET’S LIQUIDITY Ngo Thanh Huyen*1 - Do Phuong Huyen ABSTRACT: This study examines the effect of monetary policy on the liquidity of the Vietnamese stock market between November 2014 and November 2017 with a sample of 50 companies in the above period. Three liquidity measures including Amihud, Turnover and Zeros are used to measure the liquidity of the market. Two major variables of monetary policy and three liquidity measures are used in the VAR model. The results show that changes in the two main variables of monetary policy have a consistent effect on liquidity in the market. In particular, an increase in the M2 supply leads the rise of liquidity and an increase in interest rates reduces liquidity. Meanwhile, the rise of inflation reduces the liquidity of the market. Shock in the volatility of profitability reduces the liquidity of the stock market. Keywords: Liquidity, monetary policy 1. LITERATURE REVIEW 1.1. International researches Liquidity at the market level is becoming more and more focused, especially the shocks to the market liquidity situation in the past two decades. Apparently, because of the importance of liquidity to the effectiveness of financial markets and the rise of the economy, regulators often have policy moves to influence liquidity (Chordiaa, et al., 2008). From that, they have looked at the factors affecting liquidity at the macro level such as inflation, growth and monetary policy. Fernỏndez-Amador, et al.(2011) conducted a study whose data is collected from three major markets of the euro zone including Germany, France and Italy. As a result, stocks will become more liquid if participants can use cheap funding and low risk. By contrast, stocks will be less liquid if participants have difficulty in approaching funding and cope with high risk. Since monetary policy affects capital and costs, it impacts on market liquidity. They also indicated that expanded monetary policy reduces the barriers to borrow, thus it increases the liquidity of capital inflows, which raises market liquidity. In addition, Brunnermeier & Pedersen (2009), Goyenko & Ukhov (2009), Chordia, et al. (2005) found that monetary policy increased the liquidity of the market and the unexpected increase in interest rates of the Federal Reserve led to a decline in liquidity. Besides, Fujimoto (2003) studied the relationship between macroeconomic variables and liquidity for NYSE and AMEX stocks in the period ranging from 1965 to 1982. It indicated that an increase in the federal funds rate reduces liquidity of market. By contrast, a positive shock to non-borrowed reserves increases market’s liquidity. However, Woon Gyu & David (2006) who followed Pastor & Stambaugh (2003) ‘s measurement of United States equity market liquidity to measure stock market liquidity showed there is no influence from * Vietnam-Japnanese University, VNU, Hanoi, Vietnam International School, VNU, Hanoi, Vietnam
2. INTERNATIONAL CONFERENCE STARTUP AND INNOVATION NATION 207 monetary policy to the liquidity of this market. On the other hand, liquidity has an impact on monetary policy and other macro variables. 1.2. Vietnamese researches Previously, there were some authors reviewing liquidity at the market level in Vietnam. For example, Đức Minh (2010) studied some opinions on sustainable stock market development. Thanh Phong (2012) did research on impact of liquidity on profitability of listed shares on the Vietnam securities market. However, studying the effect of monetary policy variables on liquidity is not really focused. The recent investigation of Hải Lý (2015) can be considered as the very first study focusing directly on the impact of monetary policy variables on liquidity in Vietnam stock market. . The author examines the effect of monetary policy variables on market liquidity from September 2007 to November 2014 with sample of 643 companies. The results show that monetary policy has no impact on the market liquidity. Industrial output has a significant impact on market liquidity, as expected and consistent with market liquidity at all liquidity measures. Inflation also has an impact on liquidity and the effect is found to be statistically significant in three of the four liquidity measures. The rate of profitability has a strong and consistent effect on the market liquidity. 2. THEORITICAL BACKGROUND 2.1.1. Theoritical framework 2.1.1 Liquidity Liquidity is generally a concept in finance. It is an abstract concept and refers only to the extent to which an asset can be bought or sold on the market without affecting the market value of the asset, which means that liquid assets incur relatively low costs of immediate execution of trading. However, in a simple and straightforward way, it is “the ease of trading” (Amihud, et al., 2005). The stock market is considered as liquidity if it holds the conditions: always available bid and asked prices, the small difference between bid and asked prices, not very different price for an investor buying and selling a large amount of block, the larger block, the larger discount or premium (Black, 1971) The components of liquidity include: the cost of finding a trading partner, the risk premiums left over due to trading delays, opposing counterparty risks, and imperfect market risks (Kyle, 1985) There are also many liquidity measures that are commonly used, such as the sensitivity measure of prices (Amihud, 2002), market depth, frequency of yield dates equals zero (Lesmond, et al., 1999) and so on. 2.1.2 Monetary policy Monetary policy consists of the actions of a central bank, currency board or other regulatory committee that determine the size and rate of growth of the money supply, which in turn affects interest rates. Monetary policy is considered one of the first factors affecting the liquidity of the stock market. Stock markets are said to be more liquid if participants are able to access cheaper capital and find their risk is low. Since monetary policy affects both the cost of financing and the risk of holding, monetary policy affects the liquidity of the market. Many authors did research in different markets and showed results supporting that monetary policy has impact on liquidity. For instance, Goyenko & Ukhov (2009) showed that tightening monetary policy by positive shocks to the federal funds rate and negative shocks to non-borrowed reserves decreased stock market liquidity. Chordia, et al. (2005) also found that monetary policy increased the liquidity of the market and the unexpected increase in interest rates of the Federal Reserve led to a decline in liquidity. However, Woon Gyu & David (2006) indicated results that are opposite with most of study. They showed there is no influence from monetary policy to the liquidity of this market.
3. 208 HỘI THẢO KHOA HỌC QUỐC TẾ KHỞI NGHIỆP ĐỔI MỚI SÁNG TẠO QUỐC GIA 2.1.3 Industrial output Basically, industrial production is a measure of output of the industrial sector of the economy including manufacturing, mining, and utilities. The industrial production data is used in conjunction with various industry capacity estimates to calculate capacity utilization ratios for each line of business. Related to this topic, Eisfeldt (2004) supposed that a high-yielding economy leads to higher risk assets investment. As such, rebalancing transactions are more frequent. Thereby, it reduces the risk of opposing options and improves liquidity. On an experimental perspective, some authors such as Woon Gyu & David (2006) or Fernỏndez-Amador, et al. (2011) have also found a relationship between liquidity and macro variables including industrial output. 2.1.4. Inflation Inflation rate is the constant increase in price of a particular basket of goods over time, This is result of rise of government’s spending, which raises the supply of money without necessarily increasing output (Moynihan & Titley, 2000). According to Griffiths & Wall (2007), inflation rate is the change in the purchasing power of money. They suppose that the purchasing power of money will reduce when inflation rate rise. Inflation is expected to adversely affect liquidity. Goyenko & Ukhov (2009) found the impact of CPI on stock liquidity. Increasing CPI reduces the liquidity of the market. Alrabadi (2012) found no evidence of inflation effects on price differences but increased depth and volume of transactions. 2.1.5. Rate of return There are many studies and researches which have been done on the relationship between liquidity and stock returns. From a rational perspective, the authors argue that liquidity influences yield ratios through a large margin demanded by higher transaction costs (Amihud & Mendelson, 1986) In their own study, Pastor & Stambaugh (2003) showed that the larger the expected price reversal, the lower the stock liquidity will be. Spiegel & Wang (2005) pointed out the negative association between liquidity and stock returns. Bakera & Stein (2004) developed an explanatory model for an increase in liquidity forecasts lower rate of return. Watanabe (2004) reported an improvement in liquidity when the market had a sharp increase in profitability. Rhee & Wang (2009) found that the effect of a relatively consistent return on liquidity. However, some researcher showed the positive correlation between liquidity and stock returns which is actually opposite to other researches including Amihud & Mendelson (1986) and Faff & Chan (2005). 2.1.6. Volatility of rate of return The volatility of the rate of return reflects the risk side that the liquidity provider in the market faces. Benston & Hagerman (1974) showed that volatility can affect liquidity. They are based on the argument that volatility increases the implicit risk premium and thus increases the bid and ask spreads. Copeland & Galai (1983) pointed out that the standard deviation of profitability plays an important role in changing the price difference. In contrast, Subrahmanyam (1994) argued that declining liquidity may increase price volatility. In terms of empirical evidence, Chordia, et al. (2005) shows that a shock in the standard deviation increases the price difference. Kale & Loon (2011) found that the standard deviation of stock returns was positively correlated with illiquidity measures. Lesmond (2005) found that the volatility of return rates generally had a negative correlation with liquidity measures. However, Hearn & Piesse (2013) found that the volatility of return rates generally had a negative correlation with illiquidity measures. 2.2 Relationship among variables The purpose of this study is to examine the correlations and effects of two monetary policy variables (money supply M2 and interest rates), macroeconomic variables (inflation and industrial output growth)
4. INTERNATIONAL CONFERENCE STARTUP AND INNOVATION NATION 209 and market variables (rate of return and volatility) to the liquidity of the stock market. Based on a large number of studies on similar topics by previous authors, this paper will look at the correlation between monetary, market, macroeconomic variables and market liquidity in the table below: Liquidity Supported investigation Goyenko & Ukhov (2009); + Chordia, et al. (2005); Woon Money supply M2 Gyu & David (2006) Eisfeldt (2004); Woon Gyu & - David (2006); Fernỏndez- Interbank interest rates Amador, et al. (2011) Goyenko & Ukhov - (2009);Fernỏndez-Amador, et Inflation rate al. (2011) Goyenko & Ukhov (2009); + Fernỏndez-Amador, et al. Industrial output growth (2011) Amihud & Mendelson (1986); + Rate of return Faff & Chan (2005). Rhee & Wang (2009); Kale & - Loon (2011); Copeland & Galai Volatility of rate of return (1983) Table 1: Expected relationship between variables 3. DATA AND METHOD 3.1 Data description Data used to calculate liquidity measures includes stock price, volume of outstanding stocks and transaction value; and collected from stockbiz.vn and finance.vietstock.vn website. The study employs a dataset of 50 stocks with 1,850 observations. Data on macro variables are taken from various sources. The monthly money supply data was obtained from finance.vietstock.vn website. Data were collected from the website of the State Bank of Vietnam including 1 month interbank interest rate and inflation rate. Industrial output growth is obtained from the General Statistics Office of Vietnam. The study period is from November 2014 to November 2017. Table 2: Description of Data Variable Mean Std. Dev. Min Max Turnover .0025019 .0006905 .001259 .0043247 Zeros .1867527 .0473607 .1154286 .258 Amihud 496.6423 528.4891 45.50081 2303.291 Rate of return .4557291 4.144851 -8.930951 7.946293 Volatility of Rate of return 2.219044 .306367 1.702122 2.950248 Inflation rate .1913514 .3120645 -.53 .92 Indusrtrial ouput growth 177.9514 42.79307 107.6 263.6 VN interbank interest rate 7.494207 41.40219 -2.863219 252.3055 Money supply 1.366757 1.01969 -.77 4.13 We can see that the average monthly return on the stock market is .4557291. However, during the study period, there were months where losses occurred by -8.930951 and this was also the lowest return value. 7.946293 is the highest rate of return in this period. The large difference between the largest and the smallest of the market returns indicates that the market returns are quite volatile. This is also clearly demonstrated through its standard deviation of 4.144851.
5. 210 HỘI THẢO KHOA HỌC QUỐC TẾ KHỞI NGHIỆP ĐỔI MỚI SÁNG TẠO QUỐC GIA The monthly average inflation of the market is .1913514. The small difference between the largest and smallest value of the market (about 1.45) indicates that inflation was relatively stable during the study period. This is also clearly demonstrated through its standard deviation of .3120645. Industrial development is quite strong with an average of 177.9514. We can see continuous positive growth during the study period. The largest and smallest values are greater than 100. 3.2. Definition and measurement of variables In this study, three following popular measures will be used to measure liquidity. There are so many authors also used these measures such as Marshall and et al. (2013), Fong and et al.(2014) and Fernỏndez- Amador, et al. (2011) Table 3: Measurement of Liquidity variable STT Variables Measurement Authors Notes Datara, et 1 Turnover al.(1998) *R id is the change in the price Amihud of the stock i in the day d. 2 Amihud (2002) *Vid is the transaction value of stock i in the day d Lesmond, et 3 Zeros al. (1999) For daily metrics such as Turnover and Amihud, the author calculates the average value of days in the month for the monthly liquid data for each stock. Then calculating the average for all stocks of that month to get the market’s liquidity that month. Zero is the monthly data so simply take the average zeros of the stocks to be zero of the market at that month. This study uses M2 money supply growth and one-month interbank interest rates to represent monetary policy variables. Macro variables include inflation, market rate of return, industrial output growth and volatility of rate of return. Table 4: Measurement of monetary policy and macro variables STT Variables Measurement 1 Money supply growth One-month interbank 2 Taking the average value of the days in the month. interest rates 3 Inflation Monthly CPI 4 Industrial output growth Available 5 Market rate of return Average monthly rate of return of all stock in the sample 6 Volatility rate of return Average monthly standard deviation of the stocks in the sample 3.3. Econometric Method From empirical studies and results, macroeconomic variables and liquidity dimensions have interplayed. Therefore, this study uses the system of vector autoregression model equations to examine the effects of these variables on the market level with monthly data. The VAR model in this study consists of 6 endogenous variables with the p delay expressed as matrices:
6. INTERNATIONAL CONFERENCE STARTUP AND INNOVATION NATION 211 yt = c + A1 yt-1 + A2 yt-2 + + ApYt-p + ut In which, yt is the vector of 6x1 endogenous variables, c is the vector of 6x1 constants, Ai is the coefficient of 6xp, and ut is the vector of 6x1 residues. The p delay of each VAR model is determined separately. The author uses different VAR models corresponding to three liquidity measures and two currency variables. The variables in the model are as follows: Turnover Zeros Amihud R STD INF IIP VNIBOR M2_CHANGE In turn, the Turnover, Zeros and Amihud are the liquidity measures, the IIP is the growth of industrial output, representing the growth of the economy, VNIBOR is the change in the average interbank interest rate one month. STD is the volatility of the stock market. R is the average return on the market. 3.4. Hypothesis construction Monetary variables Consensus with Brunnermeier & Pedersen (2009) theory on market liquidity will increase if market participants access financing more easily and inexpensively. With the empirical results of Goyenko & Ukhov (2009), Chordia, et al. (2005) and Fernỏndez-Amador, et al. (2011), the hypothesis of monetary variables is as follows: H1: the unexpected increase in money supply led to an increase in liquidity of the market H2: the unexpected increase in interest rates reduces market liquidity Macro variables H3: Industrial output growth is used to measure the productivity of the economy. An increase in industrial output are expected to positively affect liquidity. H4: Inflation is measured by changes in the monthly consumer price index. An increase in inflation are expected to affect the opposite direction on liquidity. H5: Market return is calculated as the average monthly rate of return for all stocks in the sample. An increase in profitability are expected to affect the liquidity of the market in the same direction. H6: Volatility is measured by the average monthly standard deviation of the stocks in the sample. The rise of the standard deviation are expected to reduce the market liquidity. 4. EMPIRICAL RESULTS The stationary test results show that the variables of Turnover, Amihud, R, STD, INF, VNIBOR and M2_CHANGE whose P-value are less than 0.05 have stopped at the root level. Only the variables of Zeros and IIP whose p-values are more than 0.05 have not stopped at the root level yet. Therefore, the author proceeds to take first order difference of these non-pause sequence so that they become a stationary before entering the VAR estimation. Next, the author selects the optimal AIC based latency (Akaike Information Criterion). The optimal lag of this VAR model is 4. This means that, in the lag range of 1 to 4, the result is statistically the most significant. Therefore, the author will only focuses on the results in this lag range. The study will present the results from the VAR models described above. 4.1 Monetary policy and liquidity In this section, the author presents the responses of liquidity measures to shocks from monetary policy. Monetary policy represents money supply and interbank interest rates a month. Figure 17 shows that an increase in money supply leads to a sharp decrease in turnovers at one-month lag. This effect continues at two-months lag and decreases to 0 at three-month lag. The rise of interest rates has no impact on Turnover
7. 212 HỘI THẢO KHOA HỌC QUỐC TẾ KHỞI NGHIỆP ĐỔI MỚI SÁNG TẠO QUỐC GIA at a one-month lag. However, it increases Turnover at two-month lag, drops to 0 at three-month lag and reduces Turnover at four-month lag. Figure 2 shows that an increase in money supply drastically reduces DZeros at one-month lag, continued to stay at two-month lag and diminishes at four-month lag. The rise of interest rates has no impact on DZeros at one-month lag. However, it increases DZeros at two-month lag, continues to increase at three- month lag and gradually decreases to 0 at four-month lag. In Figure 3, the rise of money supply increases Amihud at one-month lag. However, it reduces Amihud at two-month lag, continues to stay at three-month lag and progresses to 0 at four-month lag. An increase in interest rates leads to a decrease in Amihud at the one-month lag. However, it increases Amihud at two- month lag and continues to rise and is statistically significant to a four-month lag. mh: R -> Turnover mh: STD -> Turnover .0005 .005 0 0 -.0005 -.005 -.01 -.001 0 2 4 6 8 0 2 4 6 8 step step 95% CI for irf irf 95% CI for irf irf mh: INF -> Turnover .005 mh: DIIP -> Turnover .0004 0 .0002 -.005 0 -.01 -.0002 0 2 4 6 8 step 0 2 4 6 8 step 95% CI for irf irf 95% CI for irf irf mh: VNIBOR -> Turnover mh: M2_CHANGE -> Turnover .001 .002 0 .001 -.001 0 -.002 -.001 0 2 4 6 8 0 2 4 6 8 step step 95% CI for irf irf 95% CI for irf irf Figure 1: Turnover’s impulse response 4.2 Macroeconomic variables and liquidity Figure 1 shows that an increase in industrial productivity growth does not produce any significant response to Turnover at one to three-month lag. However, at the four-month lag, an increase in industrial output leads to an increase in Turnover. On the other hand, the rise of inflation triggers the same response to turnovers at one and two-month lags, but weakens at the later lags. Results of impulse response of DZeros (Figure 2) shows that the rise of industrial output growth contributes to a decrease in DZeros one, two, three and four-month lag. An increase in inflation has no significant reaction to DZeros at one-month lag, but DZeros increases sharply at two-months lagand remains stable at three-month lag before weakening at a later lag.
8. INTERNATIONAL CONFERENCE STARTUP AND INNOVATION NATION 213 Figure 3 shows the impulse response of Amihud. The rise of industrial output causes quite a strong reaction in Amihud. However, it is interesting to note that these reactions vary greatly in lags. An increase in industrial ouput increases Amihud at one-month lag, decrease Amihud at two-month lag, then raises Amihud at three-month lag and tapers later. An increase in inflation raises Amihud in most lags. mh: R -> DZeros mh: STD -> DZeros .02 .1 .01 0 -.1 0 -.2 -.01 0 2 4 6 8 -.3 step 0 2 4 6 8 95% CI for irf irf step 95% CI for irf irf mh: DIIP -> DZeros mh: INF -> DZeros .2 .005 .1 0 0 -.1 -.2 -.005 0 2 4 6 8 0 2 4 6 8 step step 95% CI for irf irf 95% CI for irf irf mh: M2_CHANGE -> DZeros mh: VNIBOR -> DZeros .04 .02 .02 0 0 -.02 -.02 -.04 -.04 -.06 0 2 4 6 8 step 0 2 4 6 8 step 95% CI for irf irf 95% CI for irf irf Figure 2: DZeros’ impulse response 4.3 Market variables and liquidity The impulse response function shows that the increase in profitability increases Turnover at one- month lag. This response continues to be stayed for two-month and three-month lag before increasingly decreasing at four-month lag. Meanwhile, profitability rate fluctuations have the effect on Turnover which matches expectation. Specifically, when there is a sharp increase in the rate of return of the stock market, the author sees a drop in Turnover. This response is most pronounced in two-month lag until four-month lag. For the DZeros scale, the rise of the profitability ratio has almost no response at one-month lag. Next, it increases DZeros at two-month lag. However, this rise drastically reduces DZeros at three-month and four-month lag. An increase in the volatility of the rate of return makes Dzeros rise at one-month lag, continues to stay at two-month lag, and diminishes in later lags. In the Amihud scale, the rise of the stock market return rate reduces Amihud at one-month lag, progresses to zero at two-month and three-month lag, and then drastically reduces Amihud at four-month lag later.
9. 214 HỘI THẢO KHOA HỌC QUỐC TẾ KHỞI NGHIỆP ĐỔI MỚI SÁNG TẠO QUỐC GIA mh: R -> DZeros mh: STD -> DZeros .02 .1 0 .01 -.1 0 -.2 -.01 -.3 0 2 4 6 8 0 2 4 6 8 step step 95% CI for irf irf 95% CI for irf irf mh: INF -> DZeros mh: DIIP -> DZeros .2 .005 .1 0 0 -.1 -.005 -.2 0 2 4 6 8 0 2 4 6 8 step step 95% CI for irf irf 95% CI for irf irf mh: VNIBOR -> DZeros mh: M2_CHANGE -> DZeros .04 .02 .02 0 0 -.02 -.02 -.04 -.06 -.04 0 2 4 6 8 0 2 4 6 8 step step 95% CI for irf irf 95% CI for irf irf Figure 3: Amihud’s impulse response 5. CONCLUSION AND RECOMMENDATION The liquidity of the stock market has always been an interesting topic, especially the impact of monetary policy and macro variables on the liquidity of the stock market. Given the data on the prices listed on the Vietnam stock market together with the data of macro and monetary variables, the study on the effect of monetary policy on the market liquidity Vietnam stock market has been conducted. From the analysis of the above mentioned liquidity measures, this study draws some conclusions as follows. The shocks that occur in the variables representing monetary policy have had a significant and correct impact on the liquidity of the Vietnamese stock market in two of the three liquidity measures. In particular, a positive shock in a change in money supply can increase the liquidity of the stock market and vice versa. Meanwhile, the rise in interest rates reduces the liquidity of the market and vice versa. This result is considered consistent with most studies of many previous authors in the world such as Goyenko & Ukhov (2009), Chordia, et al. (2005) and Fernỏndez-Amador, et al. (2011). Therefore, the expectation of adjustments and changes in monetary policy to improve the liquidity of the stock market in Vietnam is quite real. The information outside the expected inflation also has an impact on market liquidity. This effect was found to be significant in two of the three liquidity measures. The rise of inflation reduces the liquidity of the market and vice versa. This result is similar to conclusion of some authors such as Goyenko & Ukhov
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