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Safe Haven Assets During the COVID-19 Pandemic : a study of safe haven aspects of gold and Bitcoin in U.S. financial marketsMelin, Erik, Pettersson, Albert January 2022 (has links)
This paper explores the possibility of gold and Bitcoin acting as safe haven investments during the Corona pandemic. To answer the research question the authors use OLS-, GARCH-, and TGARCH-models. The S&P 500 stock- and S&P U.S. Aggregate bond-indexes are used as a measure of the performance on U.S. stock- and bond-market. Safe haven assets have a negative beta during turbulent times and therefore the period of 2020-01-01 to 2022-03-31 will be analyzed. A period of five years leading up to the pandemic as well as the turbulent time period will be used as an average to enable comparison between regular and trying times. The results conclude that neither Bitcoin nor gold can be viewed as safe haven assets. However, it is found that both assets can work as diversifiers in the two markets.
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MODELLING AND FORECASTING INFLATION RATES IN GHANA: AN APPLICATION OF SARIMA MODELSAIDOO, ERIC January 2010 (has links)
Ghana faces a macroeconomic problem of inflation for a long period of time. The problem in somehow slows the economic growth in this country. As we all know, inflation is one of the major economic challenges facing most countries in the world especially those in African including Ghana. Therefore, forecasting inflation rates in Ghana becomes very important for its government to design economic strategies or effective monetary policies to combat any unexpected high inflation in this country. This paper studies seasonal autoregressive integrated moving average model to forecast inflation rates in Ghana. Using monthly inflation data from July 1991 to December 2009, we find that ARIMA (1,1,1)(0,0,1)12 can represent the data behavior of inflation rate in Ghana well. Based on the selected model, we forecast seven (7) months inflation rates of Ghana outside the sample period (i.e. from January 2010 to July 2010). The observed inflation rate from January to April which was published by Ghana Statistical Service Department fall within the 95% confidence interval obtained from the designed model. The forecasted results show a decreasing pattern and a turning point of Ghana inflation in the month of July.
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