The calculation of beta coefficient of some companies posted up Hanoi stock exchange

Nguyễn Văn Huy và Đtg Tạp chí KHOA HỌC & CÔNG NGHỆ 117(03): 119 - 123 119 THE CALCULATION OF BETA COEFFICIENT OF SOME COMPANIES POSTED UP HANOI STOCK EXCHANGE Nguyen Van Huy * , Ngo Thi Huyen Trang College of Economics and Business Administration – TNU SUMMARY On the stock market, information about listed companies as profits, risks and other important information is calculated and published daily in the market to help investors consider, weight out investment decisions. One of the important parameter reflecting the risk of stocks is the beta coefficient (β). Base on the database of three garment and textile companies posted up on Hanoi Stock Exchange, the study computed beta coefficient of each company. The result shows that TNG stocks are lots of prospects and have smallest volatility, safety group, less risky compared to other stocks in the same industry such as TET, NPS. Key words: Beta coefficient, stock returns, risk, garment and textile INTRODUCTION * Vietnam‟s stock market had come into operations since July 28 th , 2000 with the first session at the center of Ho Chi Minh City Stock Exchange. After more than 12 years of operation, Vietnamese stock market has achieved significant growth. Up till now, Vietnamese stock market has 2 stock exchanges which are HOSE (Ho Chi Minh Stock Exchange) and HNX (Hanoi Stock Exchange) have 105 active stock companies with about 716 security ticker. On the stock market, information about listed companies as profits, risks and other important information is calculated and published daily in the market to help investors consider, weight out investment decisions. One of the important parameter reflecting the risk of stocks is the beta coefficient (β). Beta coefficient is the coefficient measuring the known volatility or a measure of systematic risk of a security or a portfolio which is relevant to the overall market. The purpose of this paper is to calculate the Beta coefficient of three garment and textile companies which are TNG Trading and Investment Joint Stock Company, Northern Textiles and Garments Joint Stock Company (TET) and Phu Thinh – Nha Be Garment joint Stock Company (NPS) posted up Hanoi Stock Exchange. * Tel: 0949 275666, Email: huytueba@gmail.com BETA COEFFICIENT Beta, also known as the beta coefficient, which is the coefficient measuring the known volatility is a measure of systematic risk of a security or a portfolio relative to the overall market. Beta coefficient is a key parameter in the capital asset pricing model (CAPM). Beta is calculated based on the regression analysis and you can think of beta as the tendency and the degree of reaction to the volatility of the stock market. In finance, the Beta (β) of a stock or portfolio is a number describing the correlated volatility of an asset in relation to the volatility of the benchmark that said asset is being compared to. The formula for Beta The actual definition of beta is: Where is the covariance between the return on asset and the return on the market portfolio and is the variance of the market. One useful property is that the average beta across all securities, when weighted by the proportion of each security‟s market value to that of the market portfolio, is 1. That is: Nguyễn Văn Huy và Đtg Tạp chí KHOA HỌC & CÔNG NGHỆ 117(03): 119 - 123 120 Table 1. Characteristics of Beta Value of beta Interpretation Asset generally moves in the opposite direction as compared to the index Movement of the asset is uncorrelated with the movement of the benchmark Movement of the asset is generally in the same direction as, but less than the movement of the benchmark Movement of the asset is generally in the same direction as, and about the same amount as the movement of the benchmark Movement of the asset is generally in the same direction as, but more than the movement of the benchmark Where is the proportion of security s market value to that of the entire market and is the number of securities in the market. Equation is intuitive, one you think about it. If you weight all securities by their market values, the resulting portfolio is the market. By definition, the beta of the market portfolio is 1. That is, for every 1 percent movement in the market, the market must move 1 percent- by definition. Beta is also referred to as financial elasticity or correlated relative volatility, and can be referred to as a measure of the sensitivity of the asset‟s returns to market returns, its non-diversifiable risk, its systematic risk, or market risk. On an individual asset level, measuring beta can give clues to volatility and liquidity in the marketplace. In fund management, measuring beta is thought to separate a manager‟s skill from his or her willingness to take risk. The beta coefficient was born out of linear regression analysis. It is linked to a regression analysis of the returns of a portfolio (such as a stock index) (x-axis) in a specific period versus the returns of an individual asset (y- axis) in a specific year. The regression line is then called the Security characteristic line (SCL). Yt = α + βx + ε α is called the asset‟s alpha and β is called the asset‟s beta coefficient. Both coefficients have an important role in Modern portfolio theory. Standard Deviation ) Stock Volume Source: Zvi Bodie, Alex Kane, Alan J. Marcus, “Investments”. 8th Ed., [279–318] Significance of Beta coefficients The stock‟s beta coefficient, said its profit rate volatility compared to market returns. Coefficient can be a positive or a negative. The stock has a positive number coefficient, its profits positively relationship with market income. Conversely, stocks with negative values will have a relationship in the opposite direction to the market. METHODOLOGY We downloaded data about the trading price of 3 listed companies during the period from 28/12/2006 to 30/12/2012 on HNX. Apply single index model for the price of 3 figures on HNX securities taken in the period to find Entire risks Nonsystematic risks Systematic risks Nguyễn Văn Huy và Đtg Tạp chí KHOA HỌC & CÔNG NGHỆ 117(03): 119 - 123 121 their beta coefficients. First, the last price of trading session we calculate the rate of change of the price the next day than the day before, that‟s the level of profitability of the stock that day. Profitability of the day is calculated by the following formula: Ri = x 100 Then, using the least squares method to estimate beta. Specifically, here we use the Slope function in excel with Ri is the return of stock i and RM is the return of the HNX- Index on the day, or to use SPSS regression between rate rates of return on stock i and the profitability of the market. Based on the calculation results of the 3 stocks on HNX, we can know the attributes listed companies in the group yet groups: the group of high-risk stocks, stocks with medium risk, the group of low-risk stocks. In our opinion, the group of high risks stocks are stocks with a beta greater than 1.2. That is, stocks with large price fluctuations than 20% compared with the general volatility of the HNX-Index. So, this group is suitable for adventurous investors want higher profits and not risk-averse. Stocks with average risk stocks with beta coefficients ranging from 0.8 to 1.2. That is, this group‟s share price may fluctuate in the range of less than 20% compared with the general volatility of the market. So, this is the group of stocks with the balance of risk and return. Stocks are less risky stocks with a beta less than 0.8. These stocks are considered safe. That is, if the market goes down, the stocks in this group decreased less. However, in exchange for benefits from investing in stocks is not high. RESULTS Table 2 reports the number of stocks traded, the mean, the standard deviation, the skewness, the excess kurtosis, the first order serial correlation and the number of times a stock is not normally distributed for three stocks, the total market index and three sub periods from November 2007 to October 2012 of TNG, from April 2010 to October 2012 of TET and from October 2006 to October 2012 of NPS. The standard deviation represents the volatility of stocks. Table 4.1 shows that the average volatility of the volatility of the three stocks: TNG: 4,1%; TET: 3,5% and NPS: 4,7%. The volatility of stocks is the highest NPS and the stocks TNG, TET smaller volatility. The skewness and excess kurtosis says something about the position and form of the distribution of the ordinary stock returns. If a distribution in positively skewed the ordinary returns of a stock are characterized by many small losses and some extreme gains the reverse is true for negatively skewed ordinary returns. In table 1 the biggest difference in skewness in between the average skewness of the 3 stocks, which is TET and the total market skew of -0,35. This means that the stock are characterized on average by more small losses and few very high gains and the total market index is characterized by many small gains and few extreme losses. With the Kurtosis NPS shares have Kurtosis: 49 greater than 3 should have a very high kurtosis. The stock TNG and TET co kurtosis respectively is 1.65 and 2.64 less than 3 should is flat Table 2: Descriptive Statistics of TNG, TET and NPS Descriptive Statistics TNG TET NPS Mean -0.00048 -0.00081 0.00128 Standard Error 0.0012 0.0013 0.0012 Count 1305 703 1521 Skewness 0.37 -0.35 2.55 Standard Deviation 0.042 0.035 0.047 Nguyễn Văn Huy và Đtg Tạp chí KHOA HỌC & CÔNG NGHỆ 117(03): 119 - 123 122 Sample Variance 0.0018 0.0012 0.0022 Kurtosis 1.65 2.64 49.01 Using the data collected of Stocks TNG (from 2008 to 2012), TET (from 2010 to 2012), NPS (from 2007 to 2012) and the formula for Beta: The study used the SLOPE formula in Excel use to determine the beta of three stocks, and after the results are calculated as follows: Beta of TNG: β = 0.179; Beta of TET: β = 0.003; Beta of NPS: β = 0.159. After beta calculation, we can see that all three betas are in the range of 0 <β < 1, it can tell us that the movement of the asset is generally in the same direction as, but less than the movement of the market. So if there is a big change in the market, the beta of TET will move a little in compare with 2 other betas (TNG and NPS). Furthermore, looking at the third beta of the stocks we know that all 3 stocks with the safety group under 0.8 Beta. There is very little variation with changes in the market, ie if the market is reduced to little effect on the stock price of three stocks. TNG shares have the largest beta, it tells us that the volatility of the stock return of TNG is greater than two remaining companies is TET and NPS. It says stocks TNG may yield the highest return among three stocks. Stocks TET is little volatility, so the profitability is very low. CONCLUSION AND IMPLICATIONS TNG stocks are lots of prospects compared to other stocks in the same industry as TET, NPS as we have analyzed above. Stocks of TNG has smallest volatility index in the three stocks index level and has index of the highest profits. In summary, the stocks TNG, we believe that in the long term, it may be profitable for investors if the current price does not reflect the actual value. Stocks TNG is consistent with all these new investors, stocks of TNG in the safety group, less risk and stability in stocks TNG bring for investors. The transaction price is an index reflecting all information about the company‟s operations. But in Vietnam, the price is only a small part of the business, largely due to the impact from supply and demand for shares of speculators. In particular, investors sentiment as “herd”, or “crowd effect" always strongly dominant stocks prices. Therefore, beta is calculated from the price can‟t speak of business risk. The second is the market portfolio. In this article, main indicators used are HNX-Index with 3 shares represented the textile industry is TNG, TET and NPS. This index is not enough to create a market portfolio, because this list is not fully companies in the field of textile and garment industries. Therefore, the volatility of the portfolio is not accurate assessment of the volatility of textile industry in the economy. The stocks listed on the stock exchanges is too short, the longest is since the end of 2006, so price data is not long enough to be able to conduct regression beta coefficient found accurate. With the above restrictions, beta hardly meaningful if calculated at this stage. However, the beta is still very useful if we use it properly. Come back to the essence of the first beta, which is a statistical tool that measures the ability of the stock volatility than the volatility of the market. We can use the beta as an indicator in technical analysis. Accordingly, when the beta starts exceeded 1, if HNX index increased, the signs will be the time to buy because the stock price will increase by the increase in the market index. Conversely, if the index should be decreased because the value of securities sold will reduction by the decrease of the index. REFERENCES 1. Markowitz, H.M. (March 1952). “Portfolio Selection”. The Journal of Finance 7 (1): [77]. 2. Horcher, Karen A. (2005). “Essentials of financial risk management”. John Wiley and Sons. [1–3]. 3. Ross, Stephen. (1976). “The Arbitrage Theory of Capital Asset Pricing”. “Journal of Economic Theory 13 (December)”: [341-60]. Nguyễn Văn Huy và Đtg Tạp chí KHOA HỌC & CÔNG NGHỆ 117(03): 119 - 123 123 4. “Stock Basics”, Investor Guide.com. 5. Zvi Bodie, Alex Kane, Alan J. Marcus, “Investments”. 8th Ed., [279–318] 8. Klarman, Seth; Williams, Joseph (1991). "Beta". “Journal of Financial Economics 5 (3)”: [117] 9. French, Craig W. (2003). "The Treynor Capital Asset Pricing Model". “Journal of Investment Management 1 (2)”: [60–72] 10. Arnold, Glen (2005). “Corporate financial management” (3. ed. ed.). “Harlow: Financial Times/Prentice Hall.” [354]. 11. Breeden, Douglas (September, 1979). "An intertemporal asset pricing model with stochastic consumption and investment opportunities". “Journal of Financial Economics 7” (3): [265–296]. 12. Fama, Eugene F. and Kenneth French (1992). “The Cross-Section of Expected Stock Returns”. “Journal of Finance” [427-466]. 13. Ross, Westerfield, Jaffe, Jordan. “Corporate Finance Core Principles & Applications”. 2st Ed.., [324 – 365]. 14. Nguyen Ngoc Vu (2010), “The calculation of ß coefficient of some companies posted up at HNX”, Journal of science and technology, University of Danang. No. 2 (37) TÓM TẮT TÍNH TOÁN HỆ SỐ BETA CỦA MỘT SỐ CÔNG TY NIÊM YẾT TRÊN SÀN CHỨNG KHOÁN HÀ NỘI (HNX) Nguyễn Văn Huy*, Ngô Thị Huyền Trang Trường Đại học Kinh tế & Quản trị Kinh doanh – ĐH Thái Nguyên Trên thị trƣờng chứng khoán, thông tin của các công ty niêm yết nhƣ lợi nhuận, rủi ro và các thông tin khác đƣợc tính toán và công bố hàng ngày trên thị trƣờng giúp các nhà đầu tƣ xem xét và đƣa ra quyết định đầu tƣ. Một trong những tham số phản ánh rủi ro của cổ phiếu là hệ số beta. Dựa trên dữ liệu của 3 công ty may mặc niêm yết trên sàn chứng khoán Hà Nội, nghiên cứu tính toán hệ số beta cho từng công ty. Nghiên cứu chỉ ra rằng cổ phiếu TNG có nhiều triển vọng, ít biến động, vào nhóm an toàn, ít rủi ro khi so sánh với các cổ phiếu trong cùng ngành nhƣ TET và NPS. Từ khóa: Hệ số beta, lợi nhuận cổ phiếu, rủi ro, các công ty may mặc Ngày nhận bài:16/12/2013; Ngày phản biện:31/12/2013; Ngày duyệt đăng: 17/3/2014 Phản biện khoa học: TS. Đỗ Đình Long – Trường Đại học Kinh tế & Quản trị Kinh doanh - ĐHTN * Tel: 0949 275666, Email: huytueba@gmail.com