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Stock Market Volatility Analysis: A Case Study of TUNindex

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  • NEIFAR, MALIKA
Abstract
Volatility is directly associated with risks and returns. This study aims to examine the volatility characteristics on Tunisian stock market index (5 days a weak TUNindex) that include clustering volatility, leptokurtosis, and leverage effect. The first objective is then to use the GARCH type models to estimate volatility of the daily returns series, consisting of 2191 observations from 01/02/2011 to 19/11/2019, with no significant weekdays effect. We use both symmetric and asymmetric models. The main findings suggest that the symmetric GARCHM and asymmetric TGARCH /APGARCH models can capture characteristics of TUNindex whereas EGARCH reveals no significant support for leverage effect existence. Looking at news impact curves, GJR model appears to be relatively better than other models. However, the volatility of stock returns is more affected by the past volatility than the related news from the previous period. The second objective is to use GARCHM- X S models to capture the effect of macro-economic instability via exchange rate growth and exchange rate volatility. For policy, GARCHM-XS2 turned to be the best model. The macroeconomic environment should be favourable to ensure growth in the stock market. Policies to reduce volatility in the the economy (more stable exchange rate) are a necessity for stock market.

Suggested Citation

  • Neifar, Malika, 2020. "Stock Market Volatility Analysis: A Case Study of TUNindex," MPRA Paper 99140, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:99140
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    References listed on IDEAS

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    More about this item

    Keywords

    Tunisia; Stock Market; Tunindex; Volatility; Symmetric and Asymmetric GARCH Models; GARCH; TGARCH; GARCH-M; EGARCH; GARCHM-XS; Leverage Effect.; Risk Premium; Stability.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
    • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance

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