Quantum Optimisation in DeFi Market with Blockchain

Primary supervisor

Terrence Mak

Co-supervisors

  • Jimmy Lee (Chinese University of Hong Kong)
  • Anthony Chan (DeFi Entrepreneur/Specialist)

DeFi (Decentralised Finance) [Link] provides financial instruments and services through smart contracts on block chain systems. Comparing to traditional finance systems, DeFi eliminates the need of brokerages, exchanges, or banks as intermediates, and allows users to perform various financial activities including lend/borrow funds, trade cryptocurrencies, and earn interests. 

 

Similar to traditional financial markets, financial traders in DeFi make financial/trading decisions in trading. Time is of essence, many of the financial/trading decisions are required to be made in a relatively short time frame, especially with a decentralised financial market operating on block chains. With the growth of DeFi markets, crypto currencies, and block chain systems, the underlying computational optimisation problems to compute the financial/trading decisions are becoming more and more challenging. 

 

Quantum computing is an emerging field of computer science utilising quantum mechanics to solve and tackle computational problems in a completely different paradigm, comparing to today's Von Neumann architecture approach. With recent decades of research, some quantum approaches (e.g., Shor’s Factorisation Algorithm and the Harrow–Hassidim–Lloyd algorithm) have shown exponential speed up over classical approaches/algorithms in solving computational problems. However, quantum computing is still relatively new and there are many known  (and unknown/undiscovered) hardware/practical challenges and limitations. 

 

This research project aims to study and implement:

  • Mathematical optimisation models for financial decision optimisation problems that can be solved by Quantum Annealing Machines

 

 

 

Aim/outline

Aims:

  • Devise mathematical optimisation formulations to model various DeFi trading decision problems
  • Study various simplification and approximation methods to perform model simplification and reduction
  • Capable to solve DeFi trading problems with Quantum Annealing Simulators and Machines.

Required knowledge

Requirement

  • Proficient and solid in:
    • Python, or any other comparable programming languages
    • Discrete mathematics
  • Excited and eager to learn:
    • Modelling skills and techniques for different class of mathematical optimisation problems, including:
      • Constraint programs
      • Mixed-integer linear programs, and
      • Quadratic unconstrained binary optimization
    • DeFi trading decision problems
  • Willing to:
    • Work with external partners and specialists