Indian Stock Market Prediction using Augmented Financial Intelligence ML
By Anishka Chauhan, Pratham Mayur, Yeshwanth Sai Gokarakonda, Pooriya Jamie, Naman Mehrotra
Rating
863
Battle Count: 340
Relevance
8/10
The paper presents multiple machine learning models for stock price prediction, which is directly applicable to quantitative trading strategies. The inclusion of human intelligence through superforecasters adds a novel dimension to traditional quantitative approaches.
Implementation Complexity
7/10
The implementation involves multiple complex machine learning models and requires integration with a system to collect and incorporate human predictions, increasing the overall complexity.
Reproducibility
3/5
The paper provides details on the models used and some implementation specifics, but lacks complete code or detailed hyperparameters.
About this paper
Methodology: Hybrid Machine Learning Models. Problem types: Time Series Forecasting, Regression.
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