Quantum Computing Will Revolutionize Wall Street

Posted on by Faiz

The history of finance began with the history of money and computational methodologies have always been the corner stone of the finance industry since prehistoric times. In recent history with the proliferation of AI adoption, these financial computational methodologies are able to synthesize higher volumes of data to simulate more accurate outcomes accounting for interventions of random marco- and micro-economic variables however conventional/classical computers are encountering longer run times due to the higher volumes of data and limitation of classical circuits that use bits.

Quantum computing, powered by the qubits’ superposition and entanglement properties will be able to significantly enhance simulations run times because quantum computers require less number of operations to run quantum algorithms than the best classical computer alternatives.

The superposition property gives quantum computers super powers that will allow them to solve probability-based tasks that would previously have been impossibly hard for conventional counterparts in realistic timeframes. What’s the quantum computing advantage gained? According to quantum experts, if the problem at hand was a game of soccer, adding quantum computers to the mix is like allowing footballers to also use their hands to get the ball into the net.

Banks are making large quantum computing investments to capitalize on the gamer change quantum computer characteristics where quantum algorithms can optimize their stock market predictions, risk management and trading capabilities:

Stock Market Predictions

Quantum computer can effectively simulate the stock market behavior encoded in the braiding of stocks using a topological quantum computer. In a typically topological quantum computation process the trajectories anyons (quasiparticles in a 2D space) are manipulated according to the braiding of stocks and the outcome reflects the probability of the future state of stock market.

Better Risk Management (e.g. Monte Carlo Simulation)

Financial services institutions are under increasing pressure to balance risk, hedge positions more effectively, and perform a wider range of stress tests to comply with regulatory requirements (e.g. Basel II). Liquidity management, derivatives pricing, and risk measurement can be complex and calculations difficult to perform, making it hard to properly manage the costs of risk on trades. Today, Monte Carlo simulations—the preferred technique to analyze the impact of risk and uncertainty in financial models—are limited by the scaling of the estimation error which can be overcome using a quantum computer. In the face of more sophisticated risk-profiling demands, higher compliance costs and rising regulatory hurdles, the data-processing capabilities of quantum computers may speed up risk scenario simulations with higher precision, while testing more outcomes.

Quicker, More Profitable Trades

Goldman Sachs research recently noted, as and when quantum computers are rolled out, they are far more likely to be deployed on crunching options pricing conundrums. In the future, instead of a simple either/or dichotomy trade execution, quantum computers will evaluates all possible solutions simultaneously allowing evaluate and store all feasible solutions simultaneously requiring a smaller number of operations to reach a solution.

Today, at the leading edge of the quantum revolution, companies such as IBM, Microsoft, and Google are building quantum computers that aim to do things that classical computers cannot do or could only do in thousands of years and the financial industry is taking notice. Big banks like JPMC, HSBC are introducing teams to think exclusively about how quantum computing will affect their business as most banks know a quantum banking revolution is upon us.

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