forecasting. In De Prado’s 2018 book, it was argued that by using returns we lose memory of time series. In order to verify this …

MAEs of 1.20m/s and 1.42m/s which are lower than forecasting errors based on day-to-day persistence by 14.6% and 13 … improvements on the performance of the simple persistence model. As an alternative approach, we propose here the use of abductive ….83 between actual and predicted values. The model achieves an improvement of 8.2% reduction in MAE compared to hourly persistence …

Time series forecasting is an important area of forecasting in which past observations of the same variable are … models, autoregressive (AR) techniques, moving averages (MA) etc. Recent research activities in forecasting also suggested … that artificial neural networks can be used as an alternative to traditional linear forecasting models. This study will …

This paper contains a forecasting exercise on 30 time series, ranging on several fields, from economy to ecology. The …

Neural network, financial time series, approximation, forecasting. - Neuronale Netze, Finanzzeitreihen, Prognose …