In this work, it is planned to create a real time algorithmic trading prototype. This prototype is designed as a system that generates data in itself and uses this data, and also can use real market data when necessary. Models in this system will generate artificial market data and portfolio analysis and optimization techniques will be examined using algorithmic trading techniques. In this system, various areas of finance engineering such as pricing, simulation, risk analysis and optimization wil be used. The prototype is designed as a flexible system in that modules can be developed and new modules can be added.

Here are some keywords and topics related to this project: Logistic Regression, SVM (Support Vector Machine), Decision Trees, Random Forest, Artificial Neural Networks, kNN (k-Nearest Neighbour), Combinatorial Probability, Stochastic Processes, Probability Theory, Mathematical Programming and Optimization, Statistics, Simulation and Algorithms, Numerical Methods and Error Analysis,

Collaborators

• Ömür Uğur, Institute of Applied Mathematics, METU (Director)
• Özge Tekin, Institute of Applied Mathematics, METU  (Researcher)
• Ezgi Aladağlı, Institute of Applied Mathematics & Department of Mathematics, METU (Researcher)
• Onur Enginar, Institute of Applied Mathematics, METU  (Researcher)
• Burcu Aydoğan, Institute of Applied Mathematics, METU  (Researcher)

Funded by DAP-705-2018-2783, May 11, 2018 - May 11, 2019.