Academic Publications
Peer-reviewed research published at IEEE conferences. Focus areas: machine learning, stock market prediction, and deep learning for financial time series.
In IEEE CCWC 2023 by Omor Al Tanim et al.2023A Multi-modal Deep Learning Approach for Predicting Dhaka Stock Exchange
DeepDse forecasts closing prices on the Dhaka Stock Exchange by combining a Transformer encoder with LSTM and GRU layers. It is trained on almost 2 million rows of DSE trading data from 2007 to 2022, enriched with gold, silver, oil and US dollar prices and a set of technical indicators. Across 11 stocks from different sectors, the combined model had the lowest RMSE of every architecture we tested.
- In IEEE IEMCON 2022 by Omor Al Tanim et al.September 2022
A Hybrid Method based on Machine Learning to Predict the Stock Prices in Bangladesh
We predict next-day closing prices on the Dhaka Stock Exchange with a hybrid model. A stacked LSTM forecasts the price, a GARCH(9,13) model forecasts volatility, and a linear regression combines both with moving averages and daily returns. Trained on over a million rows of DSE data from 2007 to 2020, the hybrid beat linear regression and the stacked LSTM on 10 of the 11 stocks we tested.
