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Application of unsupervised feature selection, machine learning and evolutionary algorithm in predicting stock returns : a study of Indian firms

Chaudhuri, Tamal D.; Ghosh, Indranil; Eram, Shahira - In: The IUP journal of financial risk management : IJFRM 13 (2016) 3, pp. 22-46

Persistent link: https://www.econbiz.de/10011634896

Fractal investigation and maximal overlap discrete wavelet transformation (MODWT)-based machine learning framework for forecasting exchange rates

Ghosh, Indranil; Chaudhuri, Tamal D. - In: Studies in microeconomics 5 (2017) 2, pp. 105-131

Persistent link: https://www.econbiz.de/10012023833

A hybrid approach to forecasting futures prices with simultaneous consideration of optimality in ensemble feature selection and advanced artificial intelligence

Ghosh, Indranil; Chaudhuri, Tamal D.; Alfaro-Cortés, … - In: Technological forecasting & social change : an … 181 (2022), pp. 1-21

Persistent link: https://www.econbiz.de/10013417269

Predicting Stock Returns of Mid Cap Firms in India – An Application of Random Forest and Dynamic Evolving Neural Fuzzy Inference System

Datta Chaudhuri, Tamal - 2016

The paper examines the pattern of stock returns of mid cap Indian companies over a period of time and proposes frameworks for predictive modelling. Ten features are identified as predictors of stock returns. Subsequently two Machine Learning models, Random Forest and Dynamic Neural Fuzzy...

Persistent link: https://www.econbiz.de/10013002339