The project aims to propose hybrid methods for predicting stock returns, automating the choice of assumptions and developing models based on available data. This involves combining conventional time series models with stable noises, fractal interpola
Section: Mathematical Sciences (Research Project)
Related:
LOW-COST HYBRID
LOW-COST HYBRID YIELDING DAMPERS AND ML-BASED FRAGILITY MODELING FOR SEISMIC STRENGTHENING OF NON-DUCTILE RC OGS FRAMES
Research Project › Engineering Sciences
Development of
Development of Device for nondestructive estimation of tender coconut water volume
Research Project › Engineering Sciences
Estimation of
Estimation of Financial Models Parameters using the Deep Gaussian Process Regression
Research Project › Mathematical Sciences
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