Forecasting banking system liquidity is crucial for the effective monetary policy implementation. This study investigates the effectiveness of various econometric and machine learning models in predicting the autonomous factors of banking system liquidity. The research compares widely used...

Forecasting banking system liquidity is crucial for the effective monetary policy implementation. This study investigates the effectiveness of various econometric and machine learning models in predicting the autonomous factors of banking system liquidity. The research compares widely used...

Business failure prediction has become crucially important for today's firms, enabling them to reduce financial risks and make informed decisions. This study uses a dataset of 6819 companies and 96 financial and macroeconomic variables to present a comparative analysis of machine learning (ML)...

In Bayesian inference, predictive distributions are typically in the form of samples generated via Markov chain Monte Carlo or related algorithms. In this paper, we conduct a systematic analysis of how to make and evaluate probabilistic forecasts from such simulation output. Based on proper...