Download or read book Modelling and Forecasting of Volatility of Indian Stock Market written by Vishal G. Bafna and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Modeling and Forecasting of Time Varying Conditional Volatility of the Indian Stock Market written by Srinivasan Palamalai and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Volatility forecasting is an important area of research in financial markets and immense effort has been expended in improving volatility models since better forecasts translate themselves into better pricing of options and better risk management. In this direction, the present paper attempts to model and forecast the volatility (conditional variance) of the S&P CNX Nifty index returns of Indian stock market, using daily data for the period from January 1, 1996 to January 29, 2010. The forecasting models that are considered in this study range from the simple GARCH(1, 1) model to relatively complex GARCH models, including the Exponential GARCH(1, 1) and Threshold GARCH(1, 1) models. Based on out-of-sample forecasts and a majority of evaluation measures, the results show that the asymmetric GARCH models do perform better in forecasting conditional variance of the Nifty returns rather than the symmetric GARCH model, confirming the presence of leverage effect. The findings are consistent with those of Banerjee and Sarkar (2006) that relatively asymmetric GARCH models are superior in forecasting the conditional variance of Indian stock market returns rather than the parsimonious symmetric GARCH models.

Download or read book Forecasting Stock Price Volatility An Indian Perspective written by K. Prabhakaran and published by LAP Lambert Academic Publishing. This book was released on 2014-12 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book threw light on the growth and development of the stock market and observed that the development of the stock market highly depends on volatility and forecasting is an important area of research in financial market. The book measured the extent of stock price volatility in select companies of Automobile, Infrastructure, Manufacturing, Pharmaceutical and Services and identified suitable model for forecasting the volatility of the share prices in India. It evaluated the comparative ability of different statistical and econometric forecasting models in the context of Indian Stocks. Three different competing models were considered for the book and for forecasting performance of different models two forecasting error statistics viz., Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE) were used and the best model was suggested for each sector. The EGARCH model provides the most accurate forecast compared to other competing models in the book. The book also made a few observations which may help the investors to understand better about the stock market.

Download or read book Volatility Modeling and Forecasting for NIFTY Stock Returns written by Gurmeet Singh and published by . This book was released on 2016 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, an attempt has been made to model the volatility of NIFTY index of National Stock Exchange (NSE) and forecast the NIFTY stock returns for short term by using daily data ranging from January, 2000, to December, 2014, which comprises 3736 data points for the analysis by using Box-Jenkins or ARIMA model. The volatility in the Indian stock market exhibits characteristics similar to those found earlier in many of the major developed and emerging stock markets. It is shown that ARCH family models outperform the conventional OLS models. ADF test and unit root testing is done to know the stationarity of the series, later the AR(p) and MA(q) orders are identified with the help of minimum information criterion as suggested by Hannan-Rissanen. As per the analysis, ARIMA (1,0,1) model was found to be the best fit to forecast the volatility of NIFTY stock returns. The model can be used by the investors to forecast the short run NIFTY stock returns and for making more profitable and less risky investments decision.

Download or read book An Analysis of Price Volatility Trading Volume and Market Depth of Stock Futures Market in India written by Srinivasan Kaliyaperumal and published by GRIN Verlag. This book was released on 2018-03-13 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: Project Report from the year 2010 in the subject Business economics - Investment and Finance, , course: Ph. D, language: English, abstract: Every modern economy is based on a sound financial system and acts as a monetary channel for productive purpose with effecting economic growth. It encourages saving habit by throwing open and plethora of instrument avenues suiting to the individuals requirements, mobilizing savings from households and other segments and allocating savings into productive usage such as trade, commerce, manufacture etc. Thus a financial system can also be understood as institutional arrangements, through which financial surpluses are mobilized from the units generating surplus income and transferring them to the others in need of them. In nutshell, financial market, financial assets, financial services and financial institutions constitute the financial system. The activities include exchange and holding of financial assets or instruments of different kinds of financial institutions, banks and other intermediaries of the market. Financial markets provide channels for allocation of savings to investment and provide variety of assets to savers in various forms in which the investors can park their funds. At the same time, financial market is one that integral part of the financial system which makes significant contribution to the countries’ economic development. It establishes a link between the demand and supply of long-term capital funds. The economic strength of a country depends squarely on the state of financial market, apart from the productive potential of the country. The efficient allocation of fund by the capital market depends on the state of capital market. All the countries therefore focus more on the functioning of the capital market. Indian financial market has faced many challenges in the process of effecting more efficient allocation and mobilization of capital. It has attained a remarkable degree of growth in the last decade and in continuing to achieve the same in current decade also. Opening up of the economy and adoption of the liberalized economic policies have driven our economy more towards the free market. Over the last few years, financial markets, more specifically the security market were experiencing a lot of structural and regulatory changes. The major constituents of financial market are money market and the capital market catering to the type of capital requirements.

Download or read book Estimating Stock Return Volatility in Indian and Chinese Stock Market written by Vanita Tripathi and published by . This book was released on 2016 with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt: Investors step into the stock market with the objective of earning smart returns on their investments. The stock market can help in realising these goals of the investors, however, all investments are subject to risks. The origin of the risk is the uncertainty of realising the desired returns on the investment. This aspect is known as risk of the investment. This paper aims to search the best model to estimate and forecast volatility of Indian and Chinese stock market. The data for the paper is related to the two main indices of Indian Stock Market namely, SENSEX and NIFTY and two indices of Chinese stock market, namely, Shenzhen composite index and Shanghai composite index for the period July 2003 to June 2013. We applied symmetrical as well as asymmetrical GARCH models to the data. Among all the three models i.e. GARCH, EGARCH and TARCH, we found the GARCH (1,1) model as the best model to estimate and forecast the volatility of Chinese stock market for both the daily and weekly return series. For the Indian stock market, the recommended volatility estimation and forecasting model is EGARCH model that captures the leverage effect. We did not find volatility clustering and leverage effect for the monthly return series for both Indian and Chinese stock market. Thus, it is suggested to use the traditional time invariant volatility models for the monthly return series.

Download or read book Forecasting Daily Stock Volatility Using GARCH Model written by Sasikanta Tripathy and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling and forecasting the volatility of stock markets has been one of the major topics in financial econometrics in recent years. Based on the daily closing value of 23 years data, an average of 5,605 observations, for both Sensex and Shanghai Stock Exchange Composite Index, this paper makes an attempt to fit appropriate GARCH model to estimate the conditional market volatility for both Bombay Stock Exchange (BSE) and Shanghai Stock Exchange (SSE), respectively. The empirical results demonstrate that there are significant ARCH effects in both the stock markets, and it is appropriate to use the GARCH model to estimate the process.

Download or read book Volatility Modeling and Forecasting for Banking Stock Returns written by Krishna Murari and published by . This book was released on 2013 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, an attempt has been made to model and forecast the short term volatility of the Indian banking sector. A popular banking sector CNX bank index of national stock exchange of India (NSE) which includes 12 most liquid and large capitalized Indian banking stocks is used as a time series. Data have been collected since the inception of the index i.e. January 2000; a total of 3122 observations up to the period of June 2013, are used in modeling the volatility of the banking stock returns using univariate Box-Jenkins or ARIMA model. ADF test and unit root testing is done to know the stationarity of the series, later the AR(p) and MA(q) orders are identified with the help of minimum information criterion as suggested by Hannan-Rissanen. As per the analysis, ARIMA (1,0,2) model was found to be the best fit to forecast the volatility of bank stock returns. The final equation for the model is which can be helpful to the investors and speculators in taking their short run buying and selling decisions for bank stocks.

Download or read book Modelling and Forecasting the Volatility of Thin Emerging Stock Markets written by Plamen Patev and published by . This book was released on 2004 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern Portfolio Theory associates the stock market risk with volatility of the return. Volatility is measured by the variance of return but the investment community does not accepted this measure, since it weighs equally the deviations of the average return, while most investors determine the risk on the basis of small or negative returns. In the last few years the measure Value at Risk (VaR) has established itself in the practice. The issue about modelling and forecasting thin emerging stock markets risk is still open. The subject of the paper is the risk of the Bulgarian stock market. The aim of the paper is to give the investment community a model for assessment and forecasting of the Bulgarian stock market risk. The results of the research show that the SOFIX index has basic characteristics of most of the emerging stock markets, namely: high risk, significant autocorrelation, non-normality, volatility clustering. Three models have applied - RiskMetrics, EWMA with t distributed innovations and EWMA with GED distributed innovations. The EWMA with t distributed innovations and EWMA with GED distributed innovations adequately evaluate the risk of the Bulgarian stock market.

Download or read book Forecasting Financial Markets in India written by Rudra Prakash Pradhan and published by Allied Publishers. This book was released on 2009 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Papers presented at the Forecasting Financial Markets in India, held at Kharagpur during 29-31 December 2008.

Download or read book Stock Market Volatility written by Greg N. Gregoriou and published by CRC Press. This book was released on 2009-04-08 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book STOCK PRICE VOLATILITY AND FORECASTING USING ARIMA MODEL WITH REFERENCE TO SELECTED STOCKS IN NSE INDIA written by Subashini R and published by Subashini R. This book was released on 2023-02-09 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The share markets in India have created a lure for investing money by the investors. The strategy for earning big money in short time needs a lot of patience. There is no fixed formula for success in the market. The early stage of the share market was very familiar for average investor. Now the markets are wide enough to invest. There are different markets like bond market, forex market, derivative market and other specialty markets.

Download or read book Modeling and Forecasting Jakarta Stock Exchange written by Erie Febrian and published by . This book was released on 2008 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: Various techniques have been introduced by earlier academicians, from random walk model to GARCH model with its univariate and multi-variate derivations. The models have proven their strength and weakness in forecast accuracy and mean square error (MSE). On this paper, we try to conduct simulations on forecasting model for capital market. The research is aimed at finding forecast model that fits Jakarta Stock Exchange (JSX) the best. JSX is used as sample, which represents real circumstance of emerging market (microstructure).In general, outlier data is found on JSX return as the consequence of many events causing data shock. We try to compare mean model with volatility model to examine capability of a model in predicting return. Finally, we find that combination of autoregressive (AR) model, and the addition of regime independent variable, which is represented by a dummy variable, is suitable to JSX data return characteristic. This, in turn, can increase the value of R2-adj and be therefore meaningful. At the end, the assessment on the relationship between return and risk reveals that there is positive relationship between market return and the associated volatility.

Download or read book Analysing Volatility of Indian Stock Markets Using EViews written by Prashant Joshi and published by . This book was released on 2014-08-09 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Volatility Clustering in Aggregate Stock Market Returns written by Shahid Ahmed and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study is an attempt to model the volatility of stock returns in Indian market for the period 1997-2006 using GARCH, TARCH and E-GARCH. Results point out that returns exhibit persistence and volatility clustering in both NSE Nifty and BSE Sensex. Asymmetric volatility effect has been observed in both the series using TARCH and E-GARCH model. While forecasting returns it is found that GARCH-M performs better compared to alternative econometric models, namely, RW, OLS, GARCH, GARCH-M, TARCH and E-GARCH models. It is revealed that one-step ahead forecast improves by using GARCH and its variant models, which goes against the concept of random walk hypothesis. Results of this study also indicate that certain anomalies still exist which makes the stock market inefficient. In this context, SEBI is expected to play proactive role in a manner, which makes market capable to value the intrinsic price of assets.

Download or read book Non Linear Time Series Models in Empirical Finance written by Philip Hans Franses and published by Cambridge University Press. This book was released on 2000-07-27 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 2000 volume reviews non-linear time series models, and their applications to financial markets.

Download or read book Application of GARCH Models for Modeling Stock Market Volatility written by Shabarisha N. and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Return is the major attribute of an investment asset which can be construed as a random variable, and the 'variability in return' can be interpreted as volatility. Forecasting volatility and modeling it are the most prolific areas for research. This paper empirically investigates the conditional variance (volatility) pattern in Indian stock market based on financial time series data that consists of daily closing prices of CNX Nifty 50 market index for 10 years from April 2006 to March 2016. For the purpose of estimating conditional variance (volatility) in the daily returns of the index, Autoregressive Conditional Heteroskedasticity (ARCH) models are employed. Both symmetric and asymmetric models are used to capture stylized facts about CNX Nifty 50 market index returns such as volatility clustering and leverage effect. The findings of the study show that the asymmetric models are a better fit than symmetric models, confirming the presence of volatility clustering and leverage effect.