Quantum Optimizer
Optimization problem like portfolio optimization and arbitrage are the most promising quantum application.
We are researching combinational and convex optimization for solving various NP-hard problem efficiently by using the power of quantum computing.
Monte Carlo Method
Unlike the Black-Scholes equation, which has a well-known solution for the European option, Most financial models are complex SDEs that require numerical approaches like Monte Carlo method. Quantum computer has the potential to reduce the traditional N operations to root N times to get a result with desired confidence interval.
Quantum Machine Learning
The recent trend towards large-scale models has led to the need for computing resources to make AI algorithms more efficient. Quantum computing is a strong candidate for this. Using the Quantum Rady strategy, we are conducting preliminary research to prepare for the future availability of high-performance quantum computers.
