A Fuzzy Framework for Realized Volatility Prediction: Empirical Evidence From Equity Markets
Journal of Forecasting, EarlyView.ABSTRACT This study introduces a realized volatility fuzzy time series (RV‐FTS) model that applies a fuzzy c‐means clustering algorithm to estimate time‐varying c$$ c $$ latent volatility states and their corresponding membership degrees. These memberships are used to construct a fuzzified volatility estimate as a weighted average of cluster centroids.
Shafqat Iqbal, Štefan Lyócsa
wiley +1 more source
Artificial Intelligence Informed Hydrogel Biomaterials in Additive Manufacturing. [PDF]
GelsZhang Z, Tao ZZ, Du R, Huo R, Zheng X.
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Inverse solution of process parameters in gear grinding using hierarchical bayesian physics informed neural network (HBPINN). [PDF]
Sci RepZhang Q +5 more
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Unifying Summary Statistic Selection for Approximate Bayesian Computation. [PDF]
Stat ComputHoffmann T, Onnela JP.
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Artificial Intelligence and Predictive Modelling for Precision Dosing of Immunosuppressants in Kidney Transplantation. [PDF]
Pharmaceuticals (Basel)Altynova S +5 more
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AttSCNs: A Bayesian-Optimized Hybrid Model with Attention-Guided Stochastic Configuration Networks for Robust GPS Trajectory Prediction. [PDF]
Entropy (Basel)Jin XB, Wang YQ, Kong JL, Bai YT, Su TL.
europepmc +1 more source
Bayesian-optimized machine learning boosts actual evapotranspiration prediction in water-stressed agricultural regions of China. [PDF]
Sci RepElbeltagi A +8 more
europepmc +1 more source
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