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The twenty-first century may well be the time when the balance of power shifts to Brazil, Russia, India and China, nations collectively referred to as BRICs economies. These nations constitute the shape of the future, giving rise to a new world economy. Leaders in BRICs are frenetically laying the groundwork for decades of new growth. Foreign Investors are investing considerably in the emerging economies with mainly two objectives; (1) To enhance the portfolio growth and; (2) To reduce portfolio risk through efficient international portfolio diversification. This paper studies various alternative techniques for recognizing co-movement resulting among the selected developed stock markets and the emerging stock markets of the world. The leading indices of the selected stock markets are considered as proxies of the markets. Using the daily Index data from July 1, 1997 to June 30, 2008, authors examine the stock market indices of India (SENSEX), Hong Kong (HANGSENG), Mexico (MXX), Russia (RTS), Brazil (BVSP), UK (FTSE-100) and US (DJIA and NASDAQ). Co-integration technique has been employed to study the short term and long-term relationships between the market pairs. The paper explores the issues like contributions of national market volatilities, external world market volatility, and some other factors influencing the correlation between stock market returns.
In this paper, we analyse historical stock market volatility and co-movement behaviour of three emerging markets and three developed economies from January 2001 to December 2012. We find evidence that the sample of emerging economies exhibits higher stock market volatility during the study period and these volatilities increases during the global financial crisis (GFC). There is also evidence that our sample of the emerging economies exhibit higher level of stock market co-movement behaviour during the study period, for example Indonesia and Malaysia exhibit higher R-square values during 2007-2012. However, we do not find any evidence of a statistically significant correlation coefficient between the volatility measures and the co-movement measures for our sample developed and emerging countries, except for Indonesia. Therefore, it is concluded that both these market models capture different aspects of stock market behaviour.
Creating a profitable investment portfolio seems to be the challenging query faced by any investor. In an emerging economy like India, investors believe that picking an investment option is tedious as we have a wide variety of stocks from various sectors which witness sharp price movements resulting in volatility. The National Stock Exchange of India has formed several sectoral indices in order to provide a rational outlook to investors on the performance of various sectors. All these sectoral indices were created with high quality stocks from the respective sectors, which is extremely useful in identifying profitable investment opportunities for investors. This study is intended to form some investment strategies based on sectoral performance of stocks. Contrarian and momentum strategies are two major investment strategies widely debated by investment strategists across the world. All sectoral indices provided by N S E have been considered for the study. The period of study is between April 2009 and March 2015. The sectoral indices were studied on the notion that the test result will give a clear cut picture on the investment strategies to be adopted with stocks of various sectors. Results of the study confirm that short term contrarian effect exists in Metals, Auto, Banking and Energy sectors. So the investors should employ adequate are while investing with such sectors for the short term. In case of long term investments, due care should be employed while selecting stocks from the media sector. In addition to these observations, the test results produced evidence on the subsistence of momentum effect in the Indian stock market. Here buy 'past winners' and sell 'past losers' can generate extra profit.
This article investigates the effects of interest rates volatility on stock market returns and volatility using weekly returns on the 15 selected public sector Banks namely Allahabad Bank, Andhra Bank, Bank of Baroda, Bank of India, Canara Bank, Corporation Bank, Dena Bank, Indian Overseas Bank, Oriental Bank of Commerce, Punjab National Bank, State Bank of India, Syndicate Bank, UCO Bank, Union Bank of India, and Vijaya Bank over the period from 1st April 2004 to 31st Dec 2005.The 'market model' is a standard framework for measuring the sensitivity of an individual stock to fluctuations in the market index. In this paper, we have used an 'augmented market model' which estimates, the elasticity of returns on the stock against returns on the index. This regressor used in this model can be interpreted as the return on a portfolio where the long bond is purchased, using borrowed funds at the short rate. Augmented model with interest rates and assuming a student's t-distribution for error terms is used to test these relationships.The return on selected banks and market return required for the study are obtained from the National Stock Exchange website. We created time-series of notional bond returns on the 28-day and the 10-year zero coupon bond, priced off the NSE Zero Coupon Yield Curve for short tem and long term returns respectively.The results indicate that interest rates have a strong positive power for stock returns and. weak predictive power for volatility. We find that for 9 of the 15 banks in our sample, over 25% of equity capital would be gained or lost in the event of a 200 bps move in the yield curve. The stock market sensitivities suggest that there is strong heterogeneity across banks in India in their interest rate exposure. The stock market is unaware of interest rate risk when valuing bank stocks. i.e. a weak predictive power for volatility.
Up-to-Date Research Sheds New Light on This Area Taking into account the ongoing worldwide financial crisis, Stock Market Volatility provides insight to better understand volatility in various stock markets. This timely volume is one of the first to draw on a range of international authorities who offer their expertise on market volatility in devel
Economic status of India is greatly imitated by the introduction of new economic policy in 1991. The Indian Capital Market has perceived a marvelous progression. There was an outburst of investor interest during the nineties and an equity cult emerged in the country. Foreign Exchange Regulations Act is one such legislation in this direction. An important recent development has been the entry of Foreign Institutional Investors as participants in the primary and secondary markets for industrial securities. In the past several years, investments in developing countries have increased remarkably. Among the developing countries, India has received considerable capital inflows in recent years. We apply the GARCH (1, 1) (General Autoregressive Conditional Heteroscedasticity) framework to on selected representative stock indices. The findings reveal that the GARCH (1, 1) model successfully captures nonlinearity and existence of volatility. The analysis suggests indicates a long persistence of volatility in Indian stock market especially National Stock Exchange (NSE) of India. The preliminary analysis of data set suggests that volatility in the Indian stock market is time varying in nature, persist to form clusters and has a long memory process. These findings of the data characteristics have been consistent with previous studies of Indian markets and justify the application of GARCH type models. The detailed analysis shows that the TGARCH (1,1) model outperforms in estimating, predicting and forecasting the stock market volatility.
The Bombay stock exchange, Hong Kong Stock Exchange, Tokyo Stock Exchange & Shanghai Stock Exchange are among the oldest exchanges in Asia. The Study was carried out with objective to examine the causal linkages among equity markets to better understand how shocks in one market are transmitted to other markets. The study was done by taking data from 1/3/2000 to till 4/6/2011. The study was done by taking stock price data of BSE, HANGSENG, TSE & SSE. Various analytical tools such as correlation, unit root test (ADF test) and granger causality test were applied in study to find co movement & dependency of Indian market over selected markets. The correlation of daily prices gives an outcome that BSE is highly correlated with Hangseng & SSE. The granger causality test reveals an outcome that BSE is not granger cause by any of the selected market. Over all it can conclude that the selected markets are not much depending on each other.
This monograph is intended for an advanced undergraduate or graduate course of engineering and management science. as well as for persons in business. industry. military or in any field. who want an introductory and a capsule look into the methods of group decision making under multiple criteria. This is a sequel to our previous works entitled "Multiple Objective Decision Making--Methods and Applications (No. 164 of the Lecture Notes). and "Multiple Attribute Decision Making--Methods and Applications (No. 186 of the Lecture Notes). Moving from a single decision maker (the consideration of Lecture Notes 164 and 186) to a multiple decision maker setting introduces a great deal of complexity into the analysis. The problem is no longer the selection of the most preferred alternative among the nondominated solutions according to one individual's (single decision maker's) preference structure. The analysis is extended to account for the conflicts among different interest groups who have different objectives. goals. and so forth. Group decision making under multiple criteria includes such diverse and interconnected fields as preference analysis. utility theory. social choice theory. committee decision theory. theory of voting. game theory. expert evaluation analysis. aggregation of qualitative factors. economic equilibrium theory. etc; these are simplified and systematically classified for beginners. This work is to provide readers with a capsule look into the existing methods. their characteristics. and applicability in the complexity of group decision making.
We investigate how corporate stock returns respond to geopolitical risk in the case of South Korea, which has experienced large and unpredictable geopolitical swings that originate from North Korea. To do so, a monthly index of geopolitical risk from North Korea (the GPRNK index) is constructed using automated keyword searches in South Korean media. The GPRNK index, designed to capture both upside and downside risk, corroborates that geopolitical risk sharply increases with the occurrence of nuclear tests, missile launches, or military confrontations, and decreases significantly around the times of summit meetings or multilateral talks. Using firm-level data, we find that heightened geopolitical risk reduces stock returns, and that the reductions in stock returns are greater especially for large firms, firms with a higher share of domestic investors, and for firms with a higher ratio of fixed assets to total assets. These results suggest that international portfolio diversification and investment irreversibility are important channels through which geopolitical risk affects stock returns.