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Forecasting Nigerian Stock Market Returns Using Arima And Artificial Neural Network Models, Godknows M. Isenah, Olusanya E. Olubusoye
Forecasting Nigerian Stock Market Returns Using Arima And Artificial Neural Network Models, Godknows M. Isenah, Olusanya E. Olubusoye
CBN Journal of Applied Statistics (JAS)
The study reports empirical evidence that artificial neural network based models are applicable to forecasting of stock market returns. The Nigerian stock market logarithmic returns time series was tested for the presence of memory using the Hurst coefficient before the models were trained. The test showed that the logarithmic returns process is not a random walk and that the Nigerian stock market is not efficient. Two artificial neural network based models were developed in the study. These networks are TECH (4-3-1) and TECH (3-3-1)whose out-of-sample forecast performance was compared with a baseline ARIMA (3,0,1) model. The results obtained in the …
Modeling And Forecasting Currency In Circulation For Liquidity Management In Nigeria, Alvan Ikoku
Modeling And Forecasting Currency In Circulation For Liquidity Management In Nigeria, Alvan Ikoku
CBN Journal of Applied Statistics (JAS)
This paper presents forecasts of currency in circulation prepared for liquidity management at the Central Bank of Nigeria. Forecasts were produced using ARIMA, ARIMA with structural variables, VAR and VEC models. The performance of the forecasts was then evaluated under a rolling forecast scenario, where the estimation sample is augmented by one observation and the forecast sample is brought forward. The evaluation of the forecasts was based on average performance over a number of rolling forecasts. We found that the most accurate models were mixed models with structural as well as ARIMA components, augmented by seasonal and dummy variables. We …