Salmon price forecasting : a comparison of univariate and multivariate forecasting methods

From the two tests on simulated time series (chapter 5.1) and real data for forest (chapter 5.2) it seems reasonable to conclude that ARIMA is the best alternative among formal

We propose a new holistic approach to societal forecasting that builds upon recent breakthroughs in statistical analysis of large-scale historical data, the qualitative

Abstract—We present a framework based on machine learning for reducing the problem size of a short-term hydrothermal scheduling optimization model applied for price forecasting..

This indicates a period in which the model including the curvature factor has a better performance than the autoregressive model when forecasting unemployment three

The results show large statistical significant improvements in point forecasting of Bitcoin and Ethereum when using combinations of univariate models and in density forecasting

In contrast, the literature on multivariate forecasting is dominated by traditional statistical model comparison and variable selection (e.g. Chan et al. Little attention has

In contrast, the literature on multivariate forecasting is dominated by traditional statistical model comparison and variable selection (e.g. Chan et al. Little attention has

Thus, this study presents a novel approach to forecasting daily Bitcoin price using both with and without model re-estimation at each step while comparing ARIMA and