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首页> 外文期刊>European Journal of Business and Management >Stochastic Forecasting and Modeling of Volatility Oil Prices in Ghana using ARIMA Time Series Model
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Stochastic Forecasting and Modeling of Volatility Oil Prices in Ghana using ARIMA Time Series Model

机译：使用ARIMA时间序列模型的加纳波动油价随机预测和建模

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摘要

Ghana’s demand for crude oil and refined petroleum products has been growing over the past decade. This growth has been driven by socio-economic and technical factors that have influenced each category of final energy use. The growing urban population is demanding new vehicles and new roads, raising the demand for energy in the transportation and all other sectors of the economy. Consequently, Oil prices rose from 2004 to historic highs in mid-2008, only to fall precipitously in the last four months of 2008 and lose all the gains of the preceding four and a half years. The steep price increase was challenging for all economies including Ghana. The high price of oil will invariably affect revenue mobilisation, expenditure, and therefore the fiscal position of government and inflation. The study is an attempt to forecast and analyse the macroeconomic impact of oil price fluctuations in Ghana using annual data from 2000-2011. It focuses on studying the feasibility forecast using nested conditional mean (ARIMA) and conditional variance (GARCH, GJR, EGARCH) family of models under such volatile market conditions. A regression based forecast filtering simulation is proposed and studied for any improvements in the forecasted results.
机译：在过去的十年中，加纳对原油和精炼石油产品的需求一直在增长。这种增长是由影响最终能源使用的每种类别的社会经济和技术因素驱动的。不断增长的城市人口需要新的车辆和新的道路，从而增加了交通运输和所有其他经济领域对能源的需求。因此，石油价格从2004年升至2008年中的历史高位，仅在2008年的最后四个月急剧下跌，并且失去了过去四年半的所有收益。急剧的价格上涨对包括加纳在内的所有经济体都构成挑战。高油价将始终影响收入动员，支出，进而影响政府的财政状况和通货膨胀。这项研究旨在使用2000-2011年的年度数据来预测和分析加纳石油价格波动对宏观经济的影响。它专注于研究在这种多变的市场条件下使用嵌套条件均值（ARIMA）和条件方差（GARCH，GJR，EGARCH）系列模型的可行性预测。提出并研究了基于回归的预测过滤模拟，以改进预测结果。

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