Quantitative Trading
Quantitative Trading
King’s Capital’s Quants leverage cutting-edge computational and quantitative techniques to develop our trading algorithms. Our Quantitative Trading reports not only provide insight into our work, but also feature educational deep-dives into intriguing problems at the intersection of computer science, mathematics and finance.
Our Work
The Quest for Optimal Arbitrage Opportunities
Aimed at second-year computer science students, this deep dive explores the idea behind arbitrage trading and it explores various computational methods to find optimal cross-currency arbitrage opportunities, including an analysis of the algorithms and a discussion on the feasability of arbitrage trading.
Learn about how the problem can be formulated using graph theory or linear programming, and understand how methods from depth-first search and negative-weight cycle detection to the network simplex method and quantum computing can be applied to detect optimal arbitrage opportunites.
Click here to read the deep dive.
Aman Bilkhoo - Head of Quantitative Trading - Deep Dive, Nov 2023
Dynamic Asset Allocation: Optimisation with Mean Reversion
Aimed at second-year economics students, this deep dive delves into the concept of mean reversion in finance and microeconomics, highlighting its crucial role in dynamic asset allocation (DAA) strategies. It explores how prices and returns tend to move back towards the mean over time, guiding investment and firm decision-making.
Click here to read the deep dive.
Pablo Meijer - Quantitative Trading Associate - Deep Dive, Nov 2023
Meet the Team
Our current team (L to R) is:
Aman Bilkhoo - Head of Quantitative Trading
Pablo Meijer - Quantitative Trading Associate