Non-linear Volatility and Dynamics of the Tunisian Stock Market

Kalai Lamia; Jilani Faouzi

doi:doi:10.11648/j.ijefm.20140201.14

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Non-linear Volatility and Dynamics of the Tunisian Stock Market

Kalai Lamia, Jilani Faouzi

Published in International Journal of Economics, Finance and Management Sciences (Volume 2, Issue 1)

Received: 1 December 2013 Accepted: Published: 30 December 2013

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Abstract

Measuring and controlling risk is one of the most attractive issues in finance. With the persistence of uncontrolled and erratic stocks movements, volatility is perceived as a barometer of daily fluctuations. An objective measure of this variable seems then needed to control risks and cover those that are considered the most important. Non-linear autoregressive modeling is our first evaluation approach. In particular, we test the presence of “persistence” of conditional variance and the presence of a degree of a leverage effect. In order to resolve for the problem of “asymmetry” in volatility, the retained specifications point to the importance of stocks reactions in response to news. Effects of shocks on volatility highlight also the need to study the “long term” behavior of conditional variance of stocks returns and articulate the presence of long memory and dependence of time series in the long run. We note that the integrated fractional autoregressive model allows for representing time series that show long-term conditional variance thanks to fractional integration parameters. In order to stop at the dynamics that manage time series, a comparative study of the results of the different models will allow for better understanding volatility structure over the Tunisia stock market, with the aim of accurately predicting fluctuation risks.

Published in	International Journal of Economics, Finance and Management Sciences (Volume 2, Issue 1)
DOI	10.11648/j.ijefm.20140201.14
Page(s)	22-32
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Volatility, Asymmetry, Clustering, Stylized Facts, Leverage Effect

References

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[5]	R. Engle and G. Rivera (2006), "Semiparametric ARCH models", Journal of business and economic statistics, vol 9 (4), pp 345-359
[6]	L Hentschell (1995), "All in the family: Nesting symmetric and asymmetric GARCH models", Journal of financial economics vol 39, pp 71-104.
[7]	P. Hansen and A. Lunde (2005), "A Forecast comparaison of volatility models: does anything beat a GARCH (1.1)", Journal of Applied Econometrics; vol 20, pp 873-889.
[8]	S. Ling and M. MacAleer (2000), "Testing GARCH versus EGARCH, Statistics and finance: An inference", Imperial college Press London, pp 226-242
[9]	R. Engle and V. K. Ng (1993), "Measuring and testing the impact of News on volatility", Journal of Finance, vol 48, pp 1749-1778.
[10]	T. Bollerslev and H.O Mikkeslen (1996), "Modeling and pricing memory in stock market volatility", Journal of Econometrics, vol 73, pp 151-184.
[11]	B.Anderson and A. Lund (2002), An empirical investigation on Continuous time return equity models, Journal of Finance, vol 57, 1239-1284
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[18]	K. Bea and R. Nelson (2004), "Why are stock returns and volatility negatively correlated?" Journal of financial economics, vol 24, pp 124- 151.

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APA Style

Kalai Lamia, Jilani Faouzi. (2013). Non-linear Volatility and Dynamics of the Tunisian Stock Market. International Journal of Economics, Finance and Management Sciences, 2(1), 22-32. https://doi.org/10.11648/j.ijefm.20140201.14

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ACS Style

Kalai Lamia; Jilani Faouzi. Non-linear Volatility and Dynamics of the Tunisian Stock Market. Int. J. Econ. Finance Manag. Sci. 2013, 2(1), 22-32. doi: 10.11648/j.ijefm.20140201.14

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AMA Style

Kalai Lamia, Jilani Faouzi. Non-linear Volatility and Dynamics of the Tunisian Stock Market. Int J Econ Finance Manag Sci. 2013;2(1):22-32. doi: 10.11648/j.ijefm.20140201.14

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@article{10.11648/j.ijefm.20140201.14,
  author = {Kalai Lamia and Jilani Faouzi},
  title = {Non-linear Volatility and Dynamics of the Tunisian Stock Market},
  journal = {International Journal of Economics, Finance and Management Sciences},
  volume = {2},
  number = {1},
  pages = {22-32},
  doi = {10.11648/j.ijefm.20140201.14},
  url = {https://doi.org/10.11648/j.ijefm.20140201.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijefm.20140201.14},
  abstract = {Measuring and controlling risk is one of the most attractive issues in finance. With the persistence of uncontrolled and erratic stocks movements, volatility is perceived as a barometer of daily fluctuations. An objective measure of this variable seems then needed to control risks and cover those that are considered the most important. Non-linear autoregressive modeling is our first evaluation approach. In particular, we test the presence of “persistence” of conditional variance and the presence of a degree of a leverage effect. In order to resolve for the problem of “asymmetry” in volatility, the retained specifications point to the importance of stocks reactions in response to news. Effects of shocks on volatility highlight also the need to study the “long term” behavior of conditional variance of stocks returns and articulate the presence of long memory and dependence of time series in the long run. We note that the integrated fractional autoregressive model allows for representing time series that show long-term conditional variance thanks to fractional integration parameters. In order to stop at the dynamics that manage time series, a comparative study of the results of the different models will allow for better understanding volatility structure over the Tunisia stock market, with the aim of accurately predicting fluctuation risks.},
 year = {2013}
}

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TY  - JOUR
T1  - Non-linear Volatility and Dynamics of the Tunisian Stock Market
AU  - Kalai Lamia
AU  - Jilani Faouzi
Y1  - 2013/12/30
PY  - 2013
N1  - https://doi.org/10.11648/j.ijefm.20140201.14
DO  - 10.11648/j.ijefm.20140201.14
T2  - International Journal of Economics, Finance and Management Sciences
JF  - International Journal of Economics, Finance and Management Sciences
JO  - International Journal of Economics, Finance and Management Sciences
SP  - 22
EP  - 32
PB  - Science Publishing Group
SN  - 2326-9561
UR  - https://doi.org/10.11648/j.ijefm.20140201.14
AB  - Measuring and controlling risk is one of the most attractive issues in finance. With the persistence of uncontrolled and erratic stocks movements, volatility is perceived as a barometer of daily fluctuations. An objective measure of this variable seems then needed to control risks and cover those that are considered the most important. Non-linear autoregressive modeling is our first evaluation approach. In particular, we test the presence of “persistence” of conditional variance and the presence of a degree of a leverage effect. In order to resolve for the problem of “asymmetry” in volatility, the retained specifications point to the importance of stocks reactions in response to news. Effects of shocks on volatility highlight also the need to study the “long term” behavior of conditional variance of stocks returns and articulate the presence of long memory and dependence of time series in the long run. We note that the integrated fractional autoregressive model allows for representing time series that show long-term conditional variance thanks to fractional integration parameters. In order to stop at the dynamics that manage time series, a comparative study of the results of the different models will allow for better understanding volatility structure over the Tunisia stock market, with the aim of accurately predicting fluctuation risks.
VL  - 2
IS  - 1
ER  -

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Author Information

Kalai Lamia

Graduate Institute of Business and Accounting of Bizerta, Faculty of economic Sciences and Management of Tunisia; University of Carthage, University of Tunis El Manar
Jilani Faouzi

Graduate Institute of Business and Accounting of Bizerta, Faculty of economic Sciences and Management of Tunisia; University of Carthage, University of Tunis El Manar

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Plain Text BibTeX RIS

APA Style

Kalai Lamia, Jilani Faouzi. (2013). Non-linear Volatility and Dynamics of the Tunisian Stock Market. International Journal of Economics, Finance and Management Sciences, 2(1), 22-32. https://doi.org/10.11648/j.ijefm.20140201.14

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ACS Style

Kalai Lamia; Jilani Faouzi. Non-linear Volatility and Dynamics of the Tunisian Stock Market. Int. J. Econ. Finance Manag. Sci. 2013, 2(1), 22-32. doi: 10.11648/j.ijefm.20140201.14

Copy | Download

AMA Style

Kalai Lamia, Jilani Faouzi. Non-linear Volatility and Dynamics of the Tunisian Stock Market. Int J Econ Finance Manag Sci. 2013;2(1):22-32. doi: 10.11648/j.ijefm.20140201.14

Copy | Download

@article{10.11648/j.ijefm.20140201.14,
  author = {Kalai Lamia and Jilani Faouzi},
  title = {Non-linear Volatility and Dynamics of the Tunisian Stock Market},
  journal = {International Journal of Economics, Finance and Management Sciences},
  volume = {2},
  number = {1},
  pages = {22-32},
  doi = {10.11648/j.ijefm.20140201.14},
  url = {https://doi.org/10.11648/j.ijefm.20140201.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijefm.20140201.14},
  abstract = {Measuring and controlling risk is one of the most attractive issues in finance. With the persistence of uncontrolled and erratic stocks movements, volatility is perceived as a barometer of daily fluctuations. An objective measure of this variable seems then needed to control risks and cover those that are considered the most important. Non-linear autoregressive modeling is our first evaluation approach. In particular, we test the presence of “persistence” of conditional variance and the presence of a degree of a leverage effect. In order to resolve for the problem of “asymmetry” in volatility, the retained specifications point to the importance of stocks reactions in response to news. Effects of shocks on volatility highlight also the need to study the “long term” behavior of conditional variance of stocks returns and articulate the presence of long memory and dependence of time series in the long run. We note that the integrated fractional autoregressive model allows for representing time series that show long-term conditional variance thanks to fractional integration parameters. In order to stop at the dynamics that manage time series, a comparative study of the results of the different models will allow for better understanding volatility structure over the Tunisia stock market, with the aim of accurately predicting fluctuation risks.},
 year = {2013}
}

Copy | Download

TY  - JOUR
T1  - Non-linear Volatility and Dynamics of the Tunisian Stock Market
AU  - Kalai Lamia
AU  - Jilani Faouzi
Y1  - 2013/12/30
PY  - 2013
N1  - https://doi.org/10.11648/j.ijefm.20140201.14
DO  - 10.11648/j.ijefm.20140201.14
T2  - International Journal of Economics, Finance and Management Sciences
JF  - International Journal of Economics, Finance and Management Sciences
JO  - International Journal of Economics, Finance and Management Sciences
SP  - 22
EP  - 32
PB  - Science Publishing Group
SN  - 2326-9561
UR  - https://doi.org/10.11648/j.ijefm.20140201.14
AB  - Measuring and controlling risk is one of the most attractive issues in finance. With the persistence of uncontrolled and erratic stocks movements, volatility is perceived as a barometer of daily fluctuations. An objective measure of this variable seems then needed to control risks and cover those that are considered the most important. Non-linear autoregressive modeling is our first evaluation approach. In particular, we test the presence of “persistence” of conditional variance and the presence of a degree of a leverage effect. In order to resolve for the problem of “asymmetry” in volatility, the retained specifications point to the importance of stocks reactions in response to news. Effects of shocks on volatility highlight also the need to study the “long term” behavior of conditional variance of stocks returns and articulate the presence of long memory and dependence of time series in the long run. We note that the integrated fractional autoregressive model allows for representing time series that show long-term conditional variance thanks to fractional integration parameters. In order to stop at the dynamics that manage time series, a comparative study of the results of the different models will allow for better understanding volatility structure over the Tunisia stock market, with the aim of accurately predicting fluctuation risks.
VL  - 2
IS  - 1
ER  -

Copy | Download