At Qfinity Labs, we focus on quantum computing research and develop artificial intelligence for analyzing financial markets and acting upon the analysis, by generating profitable and adaptive trading portfolios/strategies.
6 Uses for Quantum Computers in Finance
High Frequency Trading (HFT)
Neural Network AI
Security And Risk Assessment
Development Of Complex Quantum Algorithms
What does our "QA" trading algorithm analyze?
Due to availability of high end quantum technology, our “QA” series of trading algorithms can analyze extremely large sizes of data from the 4 categories below to make the perfect trading decision.
These are the 4 most popular uses of Quantum Computers in Finance.
Using quantum computers to train and develop machine learning algorithms could help solve complex problems more quickly. Machine Learning uses advanced algorithms that parse data, learns from it, and use those learning to discover meaningful patterns of interest
Quantum computing processing power could cut AI model training exponentially, and increase the speed of informed decision making dramatically. This is extremely useful when writing neural network algorithms for trading.
Quantum computers may potentially find the best solution among varying weighted options more efficiently than classical computers, and could provide advantage in areas such as portfolio optimization, risk analysis, and Monte-Carlo-like applications.
Many computationally intensive problems exist, such as optimization of financial portfolios or the risk analysis of such portfolios. For some of these problems, quantum computing may have the potential to achieve a significant advantage compared to classical computing.