Thesis Abstract

This project aims to optimize distributed computing algorithms for real-time financial trading to enhance the speed and efficiency of trading platforms. The project will focus on leveraging parallel processing and distributed computing techniques to handle large volumes of financial data and execute trading strategies with minimal latency. By optimizing the algorithms used for market analysis, order execution, and risk management, the project seeks to improve the overall performance and competitiveness of financial trading systems. The project will contribute to the advancement of algorithmic trading capabilities, enabling traders to make informed decisions and capitalize on market opportunities in real time.

Thesis Overview