The investment-uncertainty relationship in the oil and gas industry

Ahmadi, Maryam; Manera, Matteo; Sadeghzadeh, Mehdi

doi:10.1016/j.resourpol.2019.101439

Cited by 16 publications

(13 citation statements)

References 75 publications

(107 reference statements)

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“…The study concluded that the dominant role of oil price is one of the engines driving economic growth in Nigeria. Ahmadi et al (2018), studied the relationship between investment and uncertainty in the United States oil and gas industry using the SVAR-GARCH model. Their results revealed that oil market uncertainty lowers investment only when it is caused by global consumption demand shocks, while market uncertainty is found to have a negative effect on investment with a one-year lag.…”

Section: Literature Reviewmentioning

confidence: 99%

“…While Zhang et al (2019) proposed soft consensus cost models for Group Decision Making (GDM) processes to aid decision makers in investment purposes in the financial market because it consider cost from both perspectives of a moderator and individual experts. Ahmadi et al (2018) identified three characteristics associated with making investment decisions to be the cost of an investment, the uncertainty over likely future profits and the seeking of additional information in order to reduce this uncertainty. These are provided by stockbrokers, accountants, financial analysts, financial econometricians and financial time series analysts by sometime based on experiences of the financial market over the years which may be subjective and not scientific.…”

Section: Introductionmentioning

confidence: 99%

“…Nigeria is oil dependent (Adenomon 2016) and a major player in the oil market (Ahmadi et al 2018) Investors who may be attracted to the Nigeria market should be guided by the literature that draws attention to volatile oil prices (Adeniyi 2011;Abdulkareem and Abdulkareem 2016). Despite volatility of oil prices, investors in Nigeria continue to invest in the stock of oil companies such as Total Nigeria Plc.…”

Section: Introductionmentioning

confidence: 99%

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On the volatility of daily stock returns of Total Nigeria Plc: evidence from GARCH models, value-at-risk and backtesting

2020

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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.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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On the volatility of daily stock returns of Total Nigeria Plc: evidence from GARCH models, value-at-risk and backtesting

2020

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“…This situation in developing countries has made investors to paly safe in investment uncertainty. Ahmadi et al (2018) identified three characteristics of investment decision as Cost of investment, uncertainty over future profits and seeking for additional information to reduce uncertainty. These and many more are provided by stock brokers, accountants, financial analyst and financial econometricians and financial time series analysts.…”

Section: Introductionmentioning

confidence: 99%

“…Nigeria as a country that depended more on oil (Adenomon, 2016) and a major player in the oil market (Ahmadi et al, 2018), investors in Nigeria have invested and are still investing in stock of oil company such as Total Petroleum Company of Nigeria.…”

Section: Introductionmentioning

confidence: 99%

On the Volatility of Daily Stock Returns of Total Petroleum Company of Nigeria: Evidence from GARCH Models, Value-at-Risk and Backtesting

Emenogu¹,

Adenomon²,

Obinna³

2018

Preprint

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Total Nigeria Plc is a Marketing and Services subsidiary of Total; a multinational energy company operating in more than 130 countries and committed to providing sustainable products and services for its customers. For over 50 years, Total Nigeria  Plc  has  remained  the  leader  in  the  downstream  sector  of  the  Nigerian  oil  and  gas  industry. This study investigated the volatility of the stock price of Total Petroleum Nigeria plc using nine (9) GARCH models namely sGARCH, gjrGARCH, eGARCH, iGARCH, aPARCH, TGARCH, NGARCH, NAGARCH and AVGARCH. We also investigated the Value-at-Risk (VaR) and Backtesting of the Models. The aim actually of this study is to boost the confidence of the shareholders and investors of the Total Nigeria plc. To achieve this, daily stock price for Total petroleum Nigeria plc from secondary was collected from January 2nd 2001 to May 8th 2017. . The study used both normal and student t innovations, using Akaike Information Criterion (AIC) to select the best model, for normal innovations for log returns and cleansed log returns of Total plc, the eGARCH and sGARCH models performed best respectively, while NGARCH model performed best for student t innovation for both log returns and cleansed returns of Total plc. The persistence of the models are stable except in few cases where iGARCH, eGARCH where not stable. Also for student t innovation, the sGARCH and gjrGARCH fails to converge. The mean-reverting number of day for the returns of Total Nigeria plc differs from model to model. Evidence from the VaR Analysis revealed from the selected models revealed that the Risk of VaR losses is high at 99% confidence level, slightly high at 95% confidence level and better at 90% confidence level. Although The Duration-Based Tests of independence conducted revealed that the models are correctly specified since in all cases the null hypotheses were accepted. This means that the probability of an exception on any day did not depends on the outcome of the previous day. Finally, both the unconditional (Kupiec) and conditional (Christoffersen) coverage tests for the correct number of exceedances for both Total stock returns and cleansed returns. The tests revealed rejection of the models at 1% level of significance. This confirms that unconditional (Kupiec) and conditional (Christoffersen) coverage tests for the correct number of exceedances are reliable compared to the Duration-Based Tests of independence. Therefore we recommend that shareholders and investors in Total Nigeria plc are to remain and continue to investment in Total Nigeria plc because if there is any form of losses, the price of the stock has the potentials to improve in the future. Again, though the risk is high at 99% confidence level, this in line with the financial theory that states that an asset with high expected risk would pay higher return on the average.

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