Time series forecasting requires simplifying complex environments into quantifiable variables. These simplifications, while ...

Fuzzy time series forecasting models represent a versatile and robust class of predictive techniques that address uncertainty and non-linearity in data. By utilising fuzzy set theory, these models ...

Deployed internally at Ant International to manage cashflow and FX exposure on an hourly, daily and weekly basis, Falcon TST has achieved accuracy rates of over 90%, and cut the company’s FX costs by ...

Microsoft has unveiled the Phi-4 series, the latest iteration in its Phi family of AI models, designed to advance multimodal processing and enable efficient local deployment. This series introduces ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

1. Difference Equations -- 2. Lag Operators -- 3. Stationary ARMA Processes -- 4. Forecasting -- 5. Maximum Likelihood Estimation -- 6. Spectral Analysis -- 7 ...