5 Algorithms Preparatory Programs

Take human bias out of the equation with automated trading. The Oxford Algorithmic Trading Programme aims to give participants a comprehensive overview and understanding of the rules that drive successful algorithmic trading strategies. The programme is led by Nir Vulkan, Associate Professor of Business Economics at Oxford Saïd, a leading authority on applied research and teaching on hedge funds. The programme also features a host of guest experts leading the systematic trading industry.

Worst and average case analysis. Recurrences and asymptotics. Efficient algorithms for sorting, searching, and selection. Data structures: binary search trees, heaps, hash tables. Algorithm design techniques: divide-and-conquer, dynamic programming, greedy algorithms, amortized analysis, and randomization. Algorithms for fundamental graph problems: minimum-cost spanning tree, connected components, topological sort, and shortest paths. Possible additional topics: network flow, and string searching. Prerequisite: 103 or 103B; 109 or STATS 116.

Convex sets, functions, and optimization problems. The basics of convex analysis and theory of convex programming: optimality conditions, duality theory, theorems of alternative, and applications. Least-squares, linear and quadratic programs, semidefinite programming, and geometric programming. Numerical algorithms for smooth and equality-constrained problems; interior-point methods for inequality-constrained problems. Applications to signal processing, communications, control, analog, and digital circuit design, computational geometry, statistics, machine learning, and mechanical engineering.

Learn about recursion, search and sort algorithms, and object-oriented programming in Python.

Unravel complex systems and visualize their interactions. Experiment and reimagine them through interventions, algorithms, models, and simulations. Communicate your understanding through powerful system visualizations.