We discuss the economic reasons why the predictions of price and return statistical moments in the coming decades, in the best case, will be limited by their averages and volatilities. That limits the accuracy of the forecasts of price and return probabilities by Gaussian distributions. The...

In this study, we evaluate the effectiveness of three popular econometric models ARIMA, MIDAS, and VAR for forecasting quarterly GDP in Madagascar. Our analysis reveals that ARIMA provides the most accurate forecasts among the three models, indicating its superiority in predicting the...

The article proposes a demand function to project the quarterly private consumption of the System of National Accounts. The input variables of this function are the CPI/Wage Index ratio and the real GDP. Since all these variables are cointegrated, an error correction model (ECM) is used to...

This paper investigates the estimation of the Value-at-Risk (VaR) across various probability levels for the log-returns of a comprehensive dataset comprising four thousand crypto-assets. Employing four recently introduced Adaptive Conformal Inference (ACI) algorithms, we aim to provide robust...

The aim of this analysis is to predict whether an National Basketball Association (NBA) player will be active in the league for at least 10 years so as to be qualified for NBA's full retirement scheme which allows for the maximum benefit payable by law. We collected per game statistics for...

We assessed three important criteria of forecastability—simplicity, certainty, and variability. Climate is complex due to many causal variables and their variable interactions. There is uncertainty about causes, effects, and data. Using evidence-based (scientific) forecasting principles, we...

The problem of classifying trades as buys or sells is examined. I propose estimated quotes for midpoint and bid/ask tests and a modeling approach to classification. Prevailing quotes are estimated using flexible approximations to the distribution for delays of quotes relative to trade...

Emerging literature after the global financial crisis of 2007-08 have highlighted the important role of financial conditions as they provide a comprehensive snapshot of the overall economic health and stability. Following this, many academic researchers, central banks and international...

Agrochemicals are crucial for modern agriculture, but improper use can cause nonpoint source pollution (NPS), harming water quality and health. Despite recognizing agriculture as a major NPS contributor, policies lag in addressing it. Current literature identifies three main approaches to...

Non-Gaussian state-space models arise in several applications, and within this framework the binary time series setting provides a relevant example. However, unlike for Gaussian state-space models — where filtering, predictive and smoothing distributions are available in closed form — binary...