How accurate is machine learning in stock market forecasting?
artificial intelligence and machine learning
Today we look at research by Ernest Chan, Haoyu Fan, Sudarshan Sawal, and Quentin Viville of PredictNow.ai.
Conditional Portfolio Optimization: Use machine learning to adapt capital allocation to market regimes!
“Conditional portfolio optimization is a portfolio optimization technique that adapts to market regimes through machine learning. Traditional portfolio optimization techniques take as input summary statistics of historical constituent returns, which have been optimal in the past. It generates a portfolio, which may not be optimal in the future.Machine learning can coordinate the optimization of a number of market functions and suggest the optimal portfolio under the current market regime.”
Dr. Ernest Chan said of the study:
“Optimization in the past was about finding the best solutions in the past. By using machine learning and big data, we can optimize for the future. Our CPO methodology is , shows how the current market and macroeconomic regime can be taken into account when optimizing for the future.”
Read the full paper:
Conditional Portfolio Optimization: Using Machine Learning to Adapt Capital Allocation to Market Regimes by Ernest Chan, Haoyu Fan, Sudarshan Sawal, Quentin Viville :: SSRN
How accurate is machine learning in stock market forecasting?
