Rank Prediction for Portfolio Management Using Artificial Neural Networks

The rank of equities is often used to determine the investment portfolio instead of prices because ranking is in general believed to be robust. In this paper, we propose a rank prediction method for portfolio management using ANN. While an ANN requires a large dataset to train the model, the sample size is usually insufficient in stock market data. Therefore, the proposed method uses data augmentation and an ensemble ANN model. In the simulation study, the proposed method shows 13 percentage of performance improvement from the other methods to predict the profit rank of equities in South-East Asian market.