Forecasting volatility of the indian stock market (Record no. 27873)
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| 000 -LEADER | |
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| fixed length control field | 03780nam a2200193Ia 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20220323144724.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 140128s9999 xx 000 0 und d |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 332 |
| Item number | KHA/FO PG |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Khadilkar Guruprasad hari |
| 245 ## - TITLE STATEMENT | |
| Title | Forecasting volatility of the indian stock market |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication, distribution, etc. | Vellanikkara |
| Name of publisher, distributor, etc. | Department of Rural Banking and Finance Management, College of Co-operation, Banking and Management |
| Date of publication, distribution, etc. | 2009 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 119 |
| 502 ## - DISSERTATION NOTE | |
| Degree type | MSc |
| 520 3# - SUMMARY, ETC. | |
| Summary, etc. | The present study on ‘forecasting volatility of the Indian stock market’ was conducted with the main objectives of examining the volatility behaviour of the Indian stock market, to forecast the sector- wise volatility of the Indian stock market and to identify the most efficient volatility forecasting model among the different models used. <br/><br/> For the study the biggest stock market in India in terms of total turnover and volume of transactions, ie, National Stock Exchange was selected. For analyzing the volatility behaviour of the Indian stock market as a whole, S&P CNX Nifty index was taken. Five companies representing five different sectors were selected for forecasting sector – wise volatility. The study used secondary data on daily close prices of individual stocks from November 1994 to October 2008, and for Nifty, daily close values, from November 1995 to October 2008 from the website of National Stock Exchange, www.nseindia.com. <br/><br/> The study revealed presence of strong volatility in the Indian stock market. The histogram drawn for the volatility of all samples showed that the distribution of volatility was not normal. There was positive skewness and all the distribution of volatility was leptokurtic. This proved the presence of high peak values (squared returns) in the sample data, exposing the evidence of volatility clustering and the possibility for prediction of future volatility.<br/><br/>While analysing sector -wise volatility, the diversified sector represented by Reliance Industries Limited showed the highest volatility compared to that of Nifty and the other sectors. In other words, Reliance is the most volatile stock among the samples selected for the study. Reliance and Infosys had good predictability of volatility in the stock market. The best identified model for forecasting the volatility of stock markets is the EWMA. Then comes AR (1) followed by MA (3), RWM and HMM. Random walk model was found suitable for the prediction of volatility of two sectors - IT (Infosys) and engineering heavy (BHEL) only. But the MAPE values of these were high. Historic mean model could not predict the volatility in the stock market with precision, for the index as well as for any of the five companies. Out of three, six, nine and twelve monthly moving averages taken for predicting the volatility three months moving average was found most suitable for all the samples. <br/><br/>Prediction of volatility using the most efficient model of EWMA identified indicated decreasing trend of volatility for the next six months, except for Infosys. The confidence limits for the Nifty and the stocks of five companies based on volatility for the sample period found that for Infosys the distribution of volatilities for the out of sample period are coming within the prefixed UCL and LCL and it ensures that the volatility is under control and predictable with high degree of precision.<br/><br/>The ever increasing market segments, advancement of technology, widening market reach and multi dimensions of stock market provide ample scope for further research in this area to the advantage of the investors and other market participants. |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Molly Joseph (Guide) |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://krishikosh.egranth.ac.in/handle/1/5810154803">https://krishikosh.egranth.ac.in/handle/1/5810154803</a> |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Theses |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Total Checkouts | Full call number | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | KAU Central Library, Thrissur | KAU Central Library, Thrissur | Theses | 18/03/2014 | 332 KHA/FO PG | 172933 | 18/03/2014 | 18/03/2014 | Theses |