Forecasting stock prices in the New York stock exchange

Abstract. Stock price prediction is one of the most relevant aspects in a stock market and world economies. Price is an important variable of concern where this sector since economic and market conditions vary over time. Efficient methods are needed to describe the trends and characteristics of stock prices. The performance of different time series models for analysis of stock prices is provided to determine the feasibility of techniques for the generation of results in the wake of economic decisions. Historical time series of monthly average price of stocks for Callon, Chesapeake, General Electric and Encana in the oil and gas sector of the New York Stock Exchange were analysed for the period 2012-2019. It was discovered that the New York Stock Exchange follows a random walk. A random walk implies uncertainty. Uncertainty implies high risk. Risk is directly related to profit. The fitted autoregressive integrated moving averages model used for forecasting shows that the predicted average stock price for the period 2021-2024 for Callon, Chesapeake, General Electric and Encana may reach United States Dollars 12.14, United States Dollars 7.34, United States Dollars 21.69 and United States Dollars 23.90, respectively. Therefore, cautious trading in the New York Stock Exchange was recommended for high profits to be achieved.Keywords. Convergence; Integration; Modelling; Stationarity; Variation.JEL. C5, C22, C32, E27, E32

Domestic Credit to the Private Sector and Economic Growth in Cameroon

The indispensability of a strong private sector to economic growth and development has been proven severally in empirical research. Nevertheless, different finance theories have assigned varied degrees of importance to private sector performance measures like credit provision and capital accumulation among on economic growth and development. This paper examines the relationship between domestic credit to the private sector by commercial banks, and economic growth in Cameroon, using data extracted from the World Development Indicators over the period 1961 – 2019 inclusive. Three time series models are used in the empirical analysis. Findings from our empirical analysis indicate that the high GDP will positively influence domestic credit to private sector by commercial banks and economic growth in Cameroon. Inflation and Capital have an insignificant negative impact on domestic credit to private sector by commercial banks and economic growth in Cameroon. This work therefore recommends guided increase of credit to private sector in Cameroon by Commercial banks like an instrument for growth and development in Cameroon in particular and the CEMAC zone in general.