Friday, September 20, 2019
Beta of BRIC Markets in Fast Growing Economies
Beta of BRIC Markets in Fast Growing Economies Beta is the risk associated with an asset in relation to the market underlined. The developing countries/emerging economies such as Brazil, Russian, India, and China (BRICs) are playing important role in the world economy as producers of goods and services. The BRIC countries are expected to grow at a rate of more than 8 percent for next several years. The main purpose of this research is to focus on these fast growing economies and work out the betas of these BRIC markets. A particular focus is given on the Indian market as India is one of the main contenders in BRIC economies. Indias GDP is expected to be 35 times of its current level. Taking into account the performance of the economy over the years and keeping in mind the study of Goldman Sachs (2003), Indian markets are predicted to be the most developed one by 2050. This report also covers the objectives and the methodology i.e. the Single Index Model, which the research will follow and finally it concludes as the stated object ives will be covered and the research will be concluded by August 2010. Introduction: Beta in general term means an assets risk in relation to the market or a benchmark. It is measured by using short-term return intervals. An asset with beta of 0 means that it is not correlated with the markets. A positive beta shows that the asset is correlated to market and it follows the market. A negative beta shows that the asset is negatively correlated to the market. Beta is known as financial elasticity or correlated volatility. Literature review: According to Hodges; Taylor ; Yoder (2003) Beta of stock and bond portfolios change drastically with time. Therefore it is difficult to find beta of for intended horizon. They prove that betas calculated from annual returns cannot be used for lond period as it changes with time. Single period betas are useful when the investment horizon matches the holding period which is considered to find the returns. Generally single index pricing is used to model the structure of returns. However, Solnik (1974), suggests that a single index model may fail to capture international and domestic risks and, hence, a multi index model which takes into consideration both factors would be more appropriate. The presence of both risks that influence assets indicate that neither a purely domestic nor purely international beta of a security would be a complete measure of systematic risk. But on the other side, Bartholdy and Riding (1994) used the Dimson and Scholes and Williams methods on NZ data to correct for beta biases. They found that the two beta-correcting methods have no add on efficiency compared to standard OLS estimators and concluded that OLS estimators are more efficient and are more closure to relevant data. We therefore adopt the simple OLS beta estimation in this study. Ragunathan; Faff; Brooks (2000) found that the relative to the domestic index, betas were always significant while the betas relative to the international indices were not always significant. The BRIC countries are expected to grow at a rate of more than 8 percent for next several years. The developing countries/emerging economies such as Brazil, Russian, India, and China (BRICs) are playing important role in the world economy as producers of goods and services and increasing capital. The four countries went through major transformational changes in their economic structure. Though BRICs countries followed a sustainable growth path to integrate them self among globalised economy. After a lot of socio-economic transformations in the twentieth century all these countries were replaced by gradual integration in the global economy in the 1980s and 1990s. In recent times, there is a surge in the global economy particularly in BRICs countries due to economic liberalisation. According to Bharadwaj (editor) the BRIC countries have many good things going in their favour. China is a leader in manufacturing powerhouse in the world and India is number one for services sector (In information technology area),while Russia and Brazil have abundant natural resources. Companies from countries like China and India have intended global ambitions various fields like information technology, industrial production, service sector, etc. BRIC countries have showed global geopolitical leadership in various regions. The new and good changes in economic policies have boosted the developing economies like China, India, Brazil and Russia. Among these countries a new economy is emerging and if the current growth level is maintained they will become the global economic player in near future. Wilson, D. and Purushothaman, R. in their paper suggest that in the coming decades large developing countries like the BRICs (Brazil, Russia, India and China) will become a great force in the world economy from its current level even above the expectations the investors currently anticipate. It is evident that from the onset of the 21st century more than a third of the worlds growth has originated in these countries. So, the rise of new powerhouse economies in the developing world can shift the equation of global economic order is predicted by Bloomberg (2007). It is also projected that the BRICs economies as a whole could be larger than the G6 in future. Thus the BRIC thesis recognizes that Brazil, Russia, India and China have changed their political systems to embrace global capitalism. Moreover, Brazil, Russia, India and China have long been a favourable destination ofà emerging market investors. By Farah, Paolo(2006) This is optimistic for economic growth and hugeà investment may come to the BRICs in coming decades. The spur in economic growth there is a great requirement of broad analysis to get the perfect image of the BRICs economic progress Kumar, Fodea (2007). That is the main purpose of this research, to find the betas of these developing economies and forecast them. In year 2006 India has been worlds second fastest growing economy. Every year at the World Economic Forum in Davos, there is a superstar. Not an individual but a Nation as a whole. One country impresses the gathering of global leaders because of a particularly smart Finance minister or a compelling tale of reform. In the decade that Ive been going to Davos, no country has captured the imagination of the conference and dominated the conversation as India in 2006.'( Fareed Zakaria, News week issue dated Mar 6, 2006) . Chinas economy has risen by almost 10 percent since 1980Indias is a tale of future, which is coming into sharp focus. In the study by Goldman Sachs (2003)shows that in coming 50 years, India will be worlds fastest growing economy (largely because of its young workforce). The report suggests that in 10 years Indias economy will be larger than Italys and in 15 years larger than that of Britains. By 2040 the worlds third largest economy. By 2050 it will be five times the size of Japans and its per capita income will have risen to 35 times its current level. Predictions like these are a treacherous business, though its worth noting that Indias current growth rate is actually higher than the study assumed. Thus we can see from the above information that there is lot of potential of making money in this BRIC economies over coming years. But care has to be taken regarding the risks and hence, I would like to carry out this project to investigate Beta of these economies. With a particular focus on the Indian economy. Objectives: The objectives of this thesis are to use the data of BRIC markets and interpret them to answer the following questions What is the beta of BRIC economies? What is the forecasted beta of the BRIC economies? What is the performance of sectors in individual economies? We hope that the outcome of this research will answer these questions and help the investors who wish to invest into these economies. Data: The data to conduct this research will be taken from Bloomberg and the exchanges of the four BRIC economies: Brazil Russia India China The focus of this research is to find the beta of these markets and compare them, the weekly prices from 2000 to 2008 will be used. Methodology: The research method of this project will be of a quantitative one. The data required will be secondary data. We will mainly interpret this data to find out beta of each market. We will further remove beta of the different sectors and compare the performance of each sector with that of whole market. Single-Index Model: For our research we will mainly use Single-Index Model. So firstly, we will use the regression equation of the Single-Index model. This can be done by using the past data of the markets and trying to find out systematic risk. As this model is linear, we can estimate the sensitivity (beta) coefficient of a security, Ri= ri-rf The regression equation is: Ri(t)= ÃŽà ±i+ ÃŽà ²iRm (t) +ei(t) Where the intercept of this equation (denoted by the greek letter alpha,ÃŽà ±) is the securitys expected return which is excess, when the excess return of the market is zero. The slope coefficient ÃŽà ²i is the beta of the security.Thus we can find beta. Beta is the securitys sensitivity to the index. The Expected Retun-Beta Relationship: As E(ei)=o we can get value of E(ri), thus we can get a new equation return-beta relationship with the help of single index model. E(Ri)= ÃŽà ±i+ ÃŽà ²iRm The above equation explains that the securitys risk premium is due to risk premium of the index. The market risk premium is multiplied by the beta or sensitivity. It is also called systematic risk premium. Any reminder is given in the form of alpha. It is also called as non market premium. To explain this in a simple example, if the value of alpha is positive which means that the security is underpriced, or in other words there is a chance to earn an extra premium. As the price of the security is brought to equilibrium the value of alpha is driven to zero. Thus this is how a relation can be established between Return and Beta. Thus by using the above Single-Index Model we can find betas of particular markets and we can also find betas of particular sectors of that market. Once this is done we can try to compare the results of that of Indian market with rest of BRIC economies. Conclusion / Expected outcome: The expected outcomes of the project research are: A beta value for BRIC economies. The forecasted beta of BRIC economies. Sector vise beta of the economy. With the help of these information investors can make a good decision regarding their investments into these booming economies. They will be able to make the most of these markets. Time Line: I will be following a time-line to complete this research. I intend to collect all my data by May using Bloomberg and the exchanges of respective markets. By June and July I will be interpreting and analyzing the collected data. I assume that I will finish this research by end of August. Refrencing: Asness, C. S. (1996) Why not 100% equities?, Journal of Portfolio Management, 22, 29à ¢Ã¢â ¬Ã¢â¬Å"34. Bartholdy, J. and A. Riding (1994), Thin trading and the estimation of betas: The efficacy of alternative techniques, Journal of Financial Research, 17/2, Summer, 241-254. Bodie, Kane, Marcus (Eds.). (2008). Investments (8th ed.) Mcgraw hill. C Kenneth Jones. (1992). Portfolio management McGraw-hill. Choi, Fu. (2005). The dual-beta model: Evidence from the new zealand stock market. Department of Finance, Waikato Management School, Dr. Avaneendra Misra. India getting better. Retrieved from http://ssrn.com/abstract=1214202 Fodea, Kumar, Perspective on economic growth of BRIC countries: A case of brazil and india. HODGES, TAYLOR, YODER. (2003). Beta, the treynor ratio, and long-run investment horizons. Applied Financial Economics, (8), 503à ¢Ã¢â ¬Ã¢â¬Å"508. KLEMKOSKY, MARTIN. THE ADJUSTMENT OF BETA FORECASTS.NO. 4(SEPTEMBER 1975). Pogue G and Solnik B. 1974. The market model applied to European common stocks: Some empirical results. Journal of Financial and Quantitative Analysis, 9:17-944. Prashanth N. Bharadwaj. (2007). BRIC Countriesà ¢Ã¢â ¬Ã¢â¬ A competitive analysis. Robert A. Levy. On the short-term stationarity of beta coefficients Financial Analysts Journal(27 (November-December 1971)), 55-62. Scholes, M. and J. Williams (1977), Estimating betas from nonsynchronous data, Journal of Financial Economics, 5, 309-327. Sromon Das. Testing the stability of beta over market phases an empirical study in the indian context. VANITHA RAGUNATHAN, ROBERT W. FAFF, ROBERT D. BROOKS. (2000). Australian industry beta risk, the choice of market index and business cycles.10, 49-58.
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