Quantifying Long-Term Volatility for Developed Stock Markets: An Empirical Case Study Using PGARCH Model on Toronto Stock Exchange (TSX)

Kumar Santosh, Meher Kumar Bharat, Ramona Birau, Mircea Laurentiu Simion, Anand Abhishek and Singh Manohar
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Kumar Santosh: Department of Commerce, Darshan Sah College, Katihar (Under Purnea University, Purnia), India
Meher Kumar Bharat: PG Department of Commerce, Purnea University, Purnia, Bihar, India
Ramona Birau: Faculty of Economic Science, University Constantin Brancusi, Targu-Jiu, Romania
Mircea Laurentiu Simion: University of Craiova, Doctoral School of Economic Sciences, Craiova, Romania
Anand Abhishek: PG Department of Economics, Purnea University, Purnia, Bihar, India
Singh Manohar: Department of Commerce, Government Autonomous PG College, Chhindwara, Madhya Pradesh

Economics and Applied Informatics, 2023, issue 2, 61-68

Abstract: High frequency data is a recent entrant to the world of statistics as they relate to the markets. This study measures the volatility of S& P / Toronto index by utilizing the GARCH family models (EGARCH, TGARCH, MGARCH and PGARCH models) using a daily database counted 7636 observations. The empirical results for the selected index for the whole-time frame show that it is volatile, and the PGARCH is a better-fitted model with the student's t distribution. Positive shocks have a greater impact on conditional volatility than negative shocks, according to the data. These extra analyses can be supplied to further corroborate their results and provide useful information for economic thespians interested in adding Toronto stock market index to their investment portfolios.

Keywords: Volatility; Forecasting; PGARCH model; GARCH; Developed stock market (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:ddj:fseeai:y:2023:i:2:p:61-68

DOI: 10.35219/eai15840409338

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