On the volatility of daily stock returns of Total Nigeria Plc: evidence from GARCH models, value-at-risk and backtesting
Abstract This study investigates the volatility in daily stock returns for Total Nigeria Plc using nine variants of GARCH models: sGARCH, girGARCH, eGARCH, iGARCH, aGARCH, TGARCH, NGARCH, NAGARCH, and AVGARCH along with value at risk estimation and backtesting. We use daily data for Total Nigeria Pl...
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doaj-bb51ad7e387a426c96dd7720f523ecbd2020-11-25T03:35:37ZengSpringerOpenFinancial Innovation2199-47302020-03-016112510.1186/s40854-020-00178-1On the volatility of daily stock returns of Total Nigeria Plc: evidence from GARCH models, value-at-risk and backtestingNgozi G. Emenogu0Monday Osagie Adenomon1Nwaze Obini Nweze2Department of Statistics, Federal PolytechnicDepartment of Statistics, Nasarawa State Univ ersityDepartment of Statistics, Nasarawa State Univ ersityAbstract This study investigates the volatility in daily stock returns for Total Nigeria Plc using nine variants of GARCH models: sGARCH, girGARCH, eGARCH, iGARCH, aGARCH, TGARCH, NGARCH, NAGARCH, and AVGARCH along with value at risk estimation and backtesting. We use daily data for Total Nigeria Plc returns for the period January 2, 2001 to May 8, 2017, and conclude that eGARCH and sGARCH perform better for normal innovations while NGARCH performs better for student t innovations. This investigation of the volatility, VaR, and backtesting of the daily stock price of Total Nigeria Plc is important as most previous studies covering the Nigerian stock market have not paid much attention to the application of backtesting as a primary approach. We found from the results of the estimations that the persistence of the GARCH models are stable except for few cases for which iGARCH and eGARCH were unstable. Additionally, for student t innovation, the sGARCH and girGARCH models failed to converge; the mean reverting number of days for returns differed from model to model. From the analysis of VaR and its backtesting, this study recommends shareholders and investors continue their business with Total Nigeria Plc because possible losses may be overcome in the future by improvements in stock prices. Furthermore, risk was reflected by significant up and down movement in the stock price at a 99% confidence level, suggesting that high risk brings a high return.http://link.springer.com/article/10.1186/s40854-020-00178-1VolatilityReturnsStocksTotal petroleumAkaike information criterion (AIC)GARCH |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ngozi G. Emenogu Monday Osagie Adenomon Nwaze Obini Nweze |
spellingShingle |
Ngozi G. Emenogu Monday Osagie Adenomon Nwaze Obini Nweze On the volatility of daily stock returns of Total Nigeria Plc: evidence from GARCH models, value-at-risk and backtesting Financial Innovation Volatility Returns Stocks Total petroleum Akaike information criterion (AIC) GARCH |
author_facet |
Ngozi G. Emenogu Monday Osagie Adenomon Nwaze Obini Nweze |
author_sort |
Ngozi G. Emenogu |
title |
On the volatility of daily stock returns of Total Nigeria Plc: evidence from GARCH models, value-at-risk and backtesting |
title_short |
On the volatility of daily stock returns of Total Nigeria Plc: evidence from GARCH models, value-at-risk and backtesting |
title_full |
On the volatility of daily stock returns of Total Nigeria Plc: evidence from GARCH models, value-at-risk and backtesting |
title_fullStr |
On the volatility of daily stock returns of Total Nigeria Plc: evidence from GARCH models, value-at-risk and backtesting |
title_full_unstemmed |
On the volatility of daily stock returns of Total Nigeria Plc: evidence from GARCH models, value-at-risk and backtesting |
title_sort |
on the volatility of daily stock returns of total nigeria plc: evidence from garch models, value-at-risk and backtesting |
publisher |
SpringerOpen |
series |
Financial Innovation |
issn |
2199-4730 |
publishDate |
2020-03-01 |
description |
Abstract This study investigates the volatility in daily stock returns for Total Nigeria Plc using nine variants of GARCH models: sGARCH, girGARCH, eGARCH, iGARCH, aGARCH, TGARCH, NGARCH, NAGARCH, and AVGARCH along with value at risk estimation and backtesting. We use daily data for Total Nigeria Plc returns for the period January 2, 2001 to May 8, 2017, and conclude that eGARCH and sGARCH perform better for normal innovations while NGARCH performs better for student t innovations. This investigation of the volatility, VaR, and backtesting of the daily stock price of Total Nigeria Plc is important as most previous studies covering the Nigerian stock market have not paid much attention to the application of backtesting as a primary approach. We found from the results of the estimations that the persistence of the GARCH models are stable except for few cases for which iGARCH and eGARCH were unstable. Additionally, for student t innovation, the sGARCH and girGARCH models failed to converge; the mean reverting number of days for returns differed from model to model. From the analysis of VaR and its backtesting, this study recommends shareholders and investors continue their business with Total Nigeria Plc because possible losses may be overcome in the future by improvements in stock prices. Furthermore, risk was reflected by significant up and down movement in the stock price at a 99% confidence level, suggesting that high risk brings a high return. |
topic |
Volatility Returns Stocks Total petroleum Akaike information criterion (AIC) GARCH |
url |
http://link.springer.com/article/10.1186/s40854-020-00178-1 |
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