International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Volatility Estimation Using ARCH, GARCH, EGARCH & TARCH Models From Global Index.

Author(s) Amit Prakash Pawar
Country India
Abstract Last one century we have seen volatility has supremacy in the stock market because volatility creates greed and fear in our mind. Greed and fear have significantly attracted large numbers of buyers and sellers. Due to this reason market gets a new trend. Over the past few decade the focus of GARCH modelling of stock market volatility has been highlighted. Over the last decade there has been a lot of study on the GARCH model in the developed economy. These papers are mainly talking about numerous volatility models, and the ability to predict and hold the specific features of conditional differences about experienced financial data. In my paper, I chosen the three basic models such as GARCH, EGARCH and TARCH which are the family members of ARCH model. At the same time, I find performance estimates of different market, I use three different distributions on error term such as Normal Distribution, Student-t Distribution and General Error Distribution (GED). Finally, the question is arising which model is considering as best model? To find out the best model I took AIC and BIC values because the guideline suggest that lower the value better the model. Here, I take several important global stock markets indexes which have healthy volatility: DOW JONE’s daily index (USA), FTSE100 daily index (UK), HANG SENG daily index (Hong Kong), NIKKEI daily index (Japan) and NIFTY daily index (India).
Keywords Key words: clustering volatility, conditional variance; ARCH, GARCH, EGARCH and TARCH; normal distribution, Student-t distribution, GED distribution, AIC and BIC.
Field Mathematics > Statistics
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-11-13
DOI https://doi.org/10.36948/ijfmr.2025.v07i06.60340
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E-ISSN 2582-2160
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