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College of Computer Science and Engineering
Systems Engineering Department
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Presents a Seminar on
"Quantitative Trading Using Artificial Intelligence"
Date: Wednesday, 14th April, 2021
Time: 3:00 pm – 4:00 pm (KSA Time)
Location: MS Teams Click here to join
Speaker:
Mr. Ali Ahmed Al-Ameer
Graduate Student,
System Engineering Department - (KFUPM)
Abstract:
This seminar discusses securities and cryptocurrency trading using artificial intelligence (AI) in the sense that it focuses on performing Exploratory Data Analysis (EDA) on selected technical indicators before proceeding to modelling, and then to develop more practical models by introducing new reward objective function that maximizes the returns during training phase. The results of EDA reveal that the complex patterns within the data can be better captured by discriminative classification models and this was endorsed by performing back-testing with trading two assets using Artificial Neural Network (ANN) and Random Forests (RF) as discriminative models against their counterpart Naïve Bayes as a generative model. To enhance the learning process, the new reward objective function is utilized to retrain the ANN with testing on AAPL, IBM, BRENT CRUDE and BTC using auto-trading strategy that serves as the intelligent unit, and the results indicate this function superiorly outperforms the conventional cross-entropy used in predictive models.
Speaker Bio:
Ali Al-Ameer received his BEng degree in Electrical & Electronics Engineering from The University of Leeds, UK in 2015. Ali is pursuing his Master of Science Degree in Systems & Control Engineering at KFUPM with special focus on Artificial Intelligence and Machine Learning applications for Systems Identification. The focus is particularly on modelling intelligent agents that can quantitatively trade different assets robustly under wide range of market conditions.
All faculty, researchers and graduate students are invited to attend.
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Systems Engineering Department, College of Computer Sciences and Engineering
Telephone: +966 (13) 860 2988, Email: c-se@kfupm.edu.sa, Website: www.kfupm.edu.sa/departments/se/
Copyright © 2014 King Fahd University of Petroleum & Minerals
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