This systematic review analyzes and compares the predictive power between traditional financial ratios and cash flow-based ratios in estimating performance. Although traditional ratios of return on assets and debt to equity have received extensive application, cash flow ratios are increasingly...

This paper examines the use of machine learning methods in modeling and forecasting time series with long memory through GARMA. By employing rigorous model selection criteria through simulation study, we find that the hybrid GARMA-LSTM model outperforms traditional approaches in forecasting...

Electricity price forecasting has been a topic of significant interest since the deregulation of electricity markets worldwide. The New Zealand electricity market is run primarily on renewable fuels, and so weather metrics have a significant impact on electricity price and volatility. In this...

Point forecasts of score-driven models have been shown to behave at par with those of state-space models under a variety of circumstances. We show, however, that density rather than point forecasts of plain-vanilla score-driven models substantially underperform their state-space counterparts in...

A modified dynamic model averaging framework, which allows for inferences regarding the shifting relevance and significance of explanatory variables, is employed to evaluate the in-sample performance of exchange rate models. This analysis is based on a set of 16,384 model specifications derived...