Heteroscedasticity describes a situation where risk (variance) changes with the level of a variable. In financial models, ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Abstract: Forecasting future values in multivariate time series is a critical challenge in many application domains, such as agriculture, transportation, energy, etc. Recently, Large Language Models ...

Lotfy, A. (2026) A Digital Accounting Framework for Enhancing Solvency and Financial Evaluation in Non-Bank Financial ...

Legal Environment, Corporate Governance, Financial Performance, SACCOS, Institutional Theory Share and Cite: Mbegu, S. (2026) Legal Environment and SACCOS Financial Performance in Mbeya, Tanzania: ...

Harvard University is providing seven free online courses in data science, each running for eight to nine weeks and requiring ...

The line between human and artificial intelligence is growing ever more blurry. Since 2021, AI has deciphered ancient texts ...

Real-world time series often exhibit a non-stationary nature, degrading the performance of pre-trained forecasting models. Test-Time Adaptation (TTA) addresses this by adjusting models during ...

Abstract: ARIMA, LSTM, and GRU are examined in this study, while COVID-19 trends and financial time series are also examined. A traditional statistical model, such as ARIMA, has long been used to ...

Toto is a foundation model for multivariate time series forecasting with a focus on observability metrics. This model leverages innovative architectural designs to efficiently handle the ...