Unlock faster, smarter portfolio optimization with Wipro’s hybrid quantum-finance solution.
Traditional portfolio optimization involves solving large-scale quadratic programming problems with constraints. As the number of assets grows, the complexity becomes exponential, making real-time optimization impractical on classical systems.
Why Quantum Computing
Quantum algorithms such as Quantum Approximate Optimization Algorithm (QAOA) and Quantum Annealing are well-suited for combinatorial optimization problems. They can efficiently explore the solution space to identify near-optimal asset allocations under multiple constraints, thus leveraging the power of quantum computing.
Quantum Advantage:
- Speed: Faster convergence compared to classical solvers for large portfolios.
- Flexibility: Handles complex constraints like sector exposure and ESG compliance.
- Impact: Enables dynamic rebalancing and scenario-based optimization in volatile markets.
Our Solution
We developed a prototype leveraging QAOA on a hybrid quantum-classical framework. Tested on simulated portfolios, it demonstrated significant improvements in optimization time and solution quality compared to traditional methods. The quantum circuit execution produced a distribution asset allocations and the associated risk/reward patterns. A portfolio analyst can use this to decide the allocation of capital to the assets from the universe, which is typically done every quarter or on need basis.
