Evaluating the Volatility of Market Risk of Viet Nam Construction Industry after the Low Inflation Period 2015-2017

The Vietnam economy has gained lots of achievements after the financial crisis 2007-2011, until it reached a low inflation rate of 0.6% in 2015. This paper measures the volatility of market risk in Viet Nam construction industry after this period (2015-2017). The main reason is the vital role of the construction company group in Vietnam in the economic development and growth in recent years always go with risk potential and risk control policies. This research paper aims to figure out how much increase or decrease in the market risk of Vietnam construction firms during the post-low inflation period 2015-2017. First, by using quantitative combined with comparative data analysis method, we find out the risk level measured by equity beta mean in the construction industry is acceptable, i.e. it is little lower than (<) 1. Then, one of its major findings is the comparison between risk levels of construction industry during the financial crisis 2007-2009 compared to those in the post-low inflation time 2015-2017. In fact, the research findings show us market risk fluctuation, measured by equity beta var, during the post-low inflation time has increased moderately. Finally, this paper provides some ideas that could provide companies and government more evidence in establishing their policies in governance. This is the complex task but the research results shows us warning that the market risk volatility might be higher during the post-low inflation period 2015-2017. And our conclusion part will recommend some policies and plans to deal with it.


Introduction
Throughout many recent years, Viet Nam construction market is evaluated as one of active markets, which has certain positive effect for the economy. The development of construction industry goes parallel with real estate and construction material markets. And Vietnam construction firms take advantages of providing real estate assets with high quality but low cost.
Generally speaking, central banks aim to maintain inflation around 2% to 3%. Increases in inflation significantly beyond this range can lead to possible hyperinflation, a devastating scenario in which inflation rises rapidly out of control. Looking at (Figures 1,2), we can see the Vietnam economy has controlled inflation well. High inflation might lead to higher lending rate and harm the construction industry because of rising construction material price.
This study will calculate and figure out whether the market risk level during the post-low inflation time (2015-2017) has increased or decreased, compared to those statistics in the financial crisis time (2007)(2008)(2009)).

Research Article
Evaluating the Volatility of Market Risk of Viet Nam Construction Industry after the Low Inflation Period 2015-2017 Hypothesis 1: Comparing two (2) periods, during the financial crisis impact, the beta or risk level of listed companies in construction industry will relatively higher than those in the post-low inflation environment.

Hypothesis 2:
Because Viet Nam is an emerging and immature financial market and the stock market still in the recovering stage, there will be a large disperse distribution in beta values estimated in the construction industry.

Hypothesis 3:
With the above reasons, the mean of equity and asset beta values of these listed construction firms tend to impose a high risk level, i.e., beta should higher than (>) 1. This hypothesis is based on the context of emerging markets including Viet Nam where there lacks of sufficient information and data disclosure although it might have high growth rate.

Literature review
Fama, Eugene F., and French, Kenneth R., [1]. also indicated in the three factor model that "value" and "size" are significant components which can affect stock returns. They also mentioned that a stock's return not only depends on a market beta, but also on market capitalization beta. The market beta is used in the three factor model, developed by Fama and French, which is the successor to the CAPM model by Sharpe, Treynor and Lintner.
Dimitrov [2] documented a significantly negative association between changes in financial leverage and contemporaneous riskadjusted stock returns.
Umar [3] found that firms which maintain good governance structures have leverage ratios that are higher (forty-seven percent) than those of firms with poor governance mechanisms per unit of profit. Chen et all [4] supported regulators' suspicions that over-reliance on short-term funding and insufficient collateral compounded the effects of dangerously high leverage and resulted in undercapitalization and excessive risk exposure for Lehman Brothers. The model reinforces the importance of the relationship between capital structure and risk management. And Gunaratha [5]. evealed that in different industries in Sri Lanka, the degree of financial leverage has a significant positive correlation with financial risk.
During the financial crisis 2007-2009 in Viet Nam and global financial markets, high inflation causing high lending rates have created risks for many industries such as real estate and the whole economy. Mohamad et all [6] showed that financial risk is vital through using both return on asset and return on equity in the performance equation. This result also implied that we cannot avoid the inverse relation of financial risk and performance; therefore, bank system would be better to make a trade-off between risk and performance.
Wang et al [7] presented results showing that firms with longterm institutional investors receive significantly positive abnormal returns around the offering announcement.
Then, Gunarathna [8] revealed that whereas firm size negatively impacts on the financial risk, financial leverage and financial risk has positive relationship.
Hami (2017) showed that financial depth has been affected negatively by inflation in Iran during the observation period.
Park et al [9]. found that sentiment caused by investors' inattentiveness mainly drives the underlying potent relationship between investor sentiment and aggregate stock returns. The results accord with the notion that investor attention generally improves market efficiency.

Conceptual theories
Positive sides of low inflation: Low (not negative) inflation reduces the potential of economic recession by enabling the labor market to adjust more quickly in a downturn, and reduces the risk that a liquidity trap prevents monetary policy from stabilizing the economy. This is explaining why many economists nowadays prefer a low and stable rate of inflation. It will help investment, encourage exports and prevent boom economy.
Negative side of low inflation: it leads to low aggregate demand and economic growth, recession potential and high unemployment. Production becomes less vibrant. Low inflation makes real wages higher. Workers can thus reduce the supply of labor and increase rest time. On the other hand, low product prices reduce production motivation.
The central bank can use monetary policies, for instance, increasing interest rates to reduce lending, control money supply or the Ministry of finance and the government can use tight fiscal policy (high tax) to achieve low inflation.
Financial and credit risk in the bank system can increase when the financial market becomes more active and bigger, esp. with more international linkage influence. This affects to risk increasing in construction and real estate sector. Hence, central banks, commercial  banks, construction firms and the government need to organize data to analyze and control these risks, including market risk.

Methodology
We use the data from the stock exchange market in Viet Nam (HOSE and HNX) during the financial crisis 2007-2009 period and the post -low inflation time 2015-2017 to estimate systemic risk results. We perform both fundamental data analysis and financial techniques to calculate equity and asset beta values.
In this study, analytical research method and specially, comparative analysis method is used, combined with quantitative data analysis. Analytical data is from the situation of listed construction firms in VN stock exchange.
Specifically, stock price data is from live data on HOSE stock exchange during 3 years 2015-2017, which presents the low inflation environment. Then, we use both analytical and summary method to generate analytical results from data calculated. Finally, we use the results to suggest policy for both these enterprises, relevant organizations and government.

General data analysis
We get some analytical results from the research sample with 20 listed firms in the construction market with the live date from the stock exchange.

Empirical research findings and discussion
In the below section, data used are from total 20 listed construction industry companies on VN stock exchange (HOSE and HNX mainly). Market risk (beta) under the impact of tax rate, includes: 1) equity beta; and 2) asset beta. We model our data analysis as in the below (Table 1).
Then, looking at the (Table 4)

Discussion for Further Researches
We can continue to analyze risk factors behind the risk scene (risk fluctuation increasing, shown by equity beta var as above analysis) in order to recommend suitable policies and plans to control market

Post -low inflation period
Scenario … Scenario .. Scenario .. Analysis Financial crisis time

Conclusion and Policy Suggestion
In general, construction company group in Vietnam has been contributing significantly to the economic development and GDP growth rate of more than 6-7% in recent years. The above analysis show us that despite of market risk decreasing, risk volatility (equity beta var) is increasing during the post-low inflation period. Construction firms in Vietnam need to continue increase their corporate governance system, structure and mechanisms, as well as their competitive advantage to control risk better. Also, they need to reduce risk of quality of real estate assets and reputation risk of construction companies.
This research paper provides evidence that the market risk potential might be lower in 2015-2017 post-low inflation period (looking again chart 1 -equity beta mean values), while the ( Figure 3) also suggests that the credit growth rate increased in 2016 and slightly

2015-2017 (post -low inflation)
Statistic results Equity beta Asset beta (assume debt beta = 0) MAX  decrease in later years (2017-2018). It means that the local economy is trying to control credit growth reasonably, however we need to analyze risk factors more carefully to reduce more market risk.
Looking at the above chart 1, the result rejects the hypothesis 3 mentioning that the mean of equity and asset beta values of these listed construction firms tend to impose a little high risk level, i.e., beta should higher than (>) 1. Because the equity beta mean is lower in the post-low (L) inflation period, it supports the hypothesis 1 saying that comparing two (2) periods, during the financial crisis impact, the beta or risk level of listed companies in construction industry will relatively higher than those in the post-low inflation environment. Additionally, the above result supports the hypothesis 2 stating that because Viet Nam is an emerging and immature financial market and the stock market still in the recovering stage, there will be a large disperse distribution in beta values estimated in the construction industry.
Last but not least, as it generates the warning that the risk fluctuation might be higher in the post-low inflation period, the government and relevant bodies such as Ministry of Finance and State Bank of Vietnam need to consider proper policies (including a combination of fiscal, monetary, exchange rate and price control policies) aiming to reduce the risk volatility and hence, help the construction system as well as the whole economy become more stable in next development stage. The Ministry of Finance continue to increase the effectiveness of fiscal policies and tax policies which are needed to combine with other macro policies at the same time. The State Bank of Viet Nam continues to increase the effectiveness of capital providing channels for construction companies as we could   Finally, this study opens some new directions for further researches in risk control policies in construction system as well as in the whole economy.

Statistic results Equity beta
Asset beta (assume debt beta = 0) Equity beta Asset beta (assume debt beta = 0) Equity beta Asset beta (assume debt beta = 0)