333 citations · 608 across the 18 of their papers we have counts for
21 papers
CAST: A Cross-Asset State-Space Trading System for Drawdown Control in Stock Markets
Yu Peng, Matloob Khushi, Josiah Poon
Managing drawdown, the peak-to-trough decline in an investment portfolio's value, is a precondition for long-term survival in practical investment management. However, mainstream s…
CryptoGAT: Are Time Series Models Effective for Cryptocurrency Forecasting?
Yu Peng, Matloob Khushi, Josiah Poon
Cryptocurrency price prediction is a significant challenge in quantitative investment. In recent years, time series models have made significant progress in financial forecasting t…
Benchmarking for Public Health Surveillance tasks on Social Media with a Domain-Specific Pretrained Language Model
Usman Naseem, Byoung Chan Lee, Matloob Khushi +2
A user-generated text on social media enables health workers to keep track of information, identify possible outbreaks, forecast disease trends, monitor emergency cases, and ascert…
Learning Non-Stationary Time-Series with Dynamic Pattern Extractions
Xipei Wang, Haoyu Zhang, Yuanbo Zhang +4
The era of information explosion had prompted the accumulation of a tremendous amount of time-series data, including stationary and non-stationary time-series data. State-of-the-ar…
Clustering and attention model based for intelligent trading
Mimansa Rana, Nanxiang Mao, Ming Ao +3
The foreign exchange market has taken an important role in the global financial market. While foreign exchange trading brings high-yield opportunities to investors, it also brings…
Benchmarking for Biomedical Natural Language Processing Tasks with a Domain Specific ALBERT
Usman Naseem, Adam G. Dunn, Matloob Khushi +1
The availability of biomedical text data and advances in natural language processing (NLP) have made new applications in biomedical NLP possible. Language models trained or fine tu…
Feature importance recap and stacking models for forex price prediction
Yunze Li, Yanan Xie, Chen Yu +3
Forex trading is the largest market in terms of qutantitative trading. Traditionally, traders refer to technical analysis based on the historical data to make decisions and trade.…
Classifying vaccine sentiment tweets by modelling domain-specific representation and commonsense knowledge into context-aware attentive GRU
Usman Naseem, Matloob Khushi, Jinman Kim +1
Vaccines are an important public health measure, but vaccine hesitancy and refusal can create clusters of low vaccine coverage and reduce the effectiveness of vaccination programs.…
Text Mining of Stocktwits Data for Predicting Stock Prices
Mukul Jaggi, Priyanka Mandal, Shreya Narang +2
Stock price prediction can be made more efficient by considering the price fluctuations and understanding the sentiments of people. A limited number of models understand financial…
A Survey of Forex and Stock Price Prediction Using Deep Learning
Zexin Hu, Yiqi Zhao, Matloob Khushi
The prediction of stock and foreign exchange (Forex) had always been a hot and profitable area of study. Deep learning application had proven to yields better accuracy and return i…
Feature Learning for Stock Price Prediction Shows a Significant Role of Analyst Rating
Jaideep Singh, Matloob Khushi
To reject the Efficient Market Hypothesis a set of 5 technical indicators and 23 fundamental indicators was identified to establish the possibility of generating excess returns on…
SMOTE-ENC: A novel SMOTE-based method to generate synthetic data for nominal and continuous features
Mimi Mukherjee, Matloob Khushi
Real world datasets are heavily skewed where some classes are significantly outnumbered by the other classes. In these situations, machine learning algorithms fail to achieve subst…
Wavelet Denoised-ResNet CNN and LightGBM Method to Predict Forex Rate of Change
Yiqi Zhao, Matloob Khushi
Foreign Exchange (Forex) is the largest financial market in the world. The daily trading volume of the Forex market is much higher than that of stock and futures markets. Therefore…
Event-Driven LSTM For Forex Price Prediction
Ling Qi, Matloob Khushi, Josiah Poon
The majority of studies in the field of AI guided financial trading focus on purely applying machine learning algorithms to continuous historical price and technical analysis data.…
Portfolio Optimization with 2D Relative-Attentional Gated Transformer
Tae Wan Kim, Matloob Khushi
Portfolio optimization is one of the most attentive fields that have been researched with machine learning approaches. Many researchers attempted to solve this problem using deep r…
BioALBERT: A Simple and Effective Pre-trained Language Model for Biomedical Named Entity Recognition
Usman Naseem, Matloob Khushi, Vinay Reddy +3
In recent years, with the growing amount of biomedical documents, coupled with advancement in natural language processing algorithms, the research on biomedical named entity recogn…
GA-MSSR: Genetic Algorithm Maximizing Sharpe and Sterling Ratio Method for RoboTrading
Zezheng Zhang, Matloob Khushi
Foreign exchange is the largest financial market in the world, and it is also one of the most volatile markets. Technical analysis plays an important role in the forex market and t…
Wavelet Denoising and Attention-based RNN-ARIMA Model to Predict Forex Price
Zhiwen Zeng, Matloob Khushi
Every change of trend in the forex market presents a great opportunity as well as a risk for investors. Accurate forecasting of forex prices is a crucial element in any effective h…
Open source tools for management and archiving of digital microscopy data to allow integration with patient pathology and treatment information
Matloob Khushi, Georgina Edwards, Diego Alonso de Marcos +3
Virtual microscopy includes digitisation of histology slides and the use of computer technologies for complex investigation of diseases such as cancer. However, automated image ana…
Benchmarking database performance for genomic data
Matloob Khushi
Genomic regions represent features such as gene annotations, transcription factor binding sites and epigenetic modifications. Performing various genomic operations such as identify…
Mining Temporal Evolution of Knowledge Graph and Genealogical Features for Literature-based Discovery Prediction
Nazim Choudhury, Fahim Faisal, Matloob Khushi
Literature-based knowledge discovery process identifies the important but implicit relations among information embedded in published literature. Existing techniques from Informatio…