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Rodgers Makwinja, Seyoum Mengistou, Emmanuel Kaunda, Tena Alemiew, Titus Bandulo Phiri, Ishmael Bobby Mphangwe Kosamu and Chikumbusko Chiziwa Kaonga
Forecasting, using time series data, has become the most relevant and effective tool for fisheries stock assessment. Autoregressive integrated moving average (ARIMA) modeling has been commonly used to predict the general trend for fish landings with incr...
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Omer Ahmed Sayed Mohamed,Faiza Omer Mohammed Elmahgop
Pág. 209 - 215
This study investigates asymmetry in the effect of the exchange rate on the Sudanese stock market prices. We applied the Nonlinear ARDL model by Shin et al. (2014) to monthly data for the period from September 2003 to September 2019, using inflation, mon...
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Ifuero Osad Osamwonyi,Godfrey Ayegbeni Audu
Pág. 357 - 373
This study investigates the long term relationship between the behaviour of stock markets during the 2008 crisis and some selected international macroeconomic variables using information from January 2005 to December 2015. The procedures of the Autoregre...
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Olga Rumyantseva, Andrey Sarantsev and Nikolay Strigul
Forecasting of forest dynamics at a large scale is essential for land use management, global climate change and biogeochemistry modeling. We develop time series models of the forest dynamics in the conterminous United States based on forest inventory dat...
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Leandro dos Santos Maciel,Rosangela Ballini
Pág. 66 - 84
Bitcoin has attracted the attention of investors lately due to its significant market capitalization and high volatility. This work considers the modeling and forecasting of daily high and low Bitcoin prices using a fractionally cointegrated vector autor...
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