Associate Professor, Indian Institute of Technology (IIT), Madras
Project Overview
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 interpolation, and clustering techniques. The project will enhance understanding of the stock market, provide investors with an edge, and enable the development of new theoretical models, which will be of interest to researchers in statistics and probability.
Associate Professor, Indian Institute of Technology (IIT), Madras
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