Quantum computing is poised to provide significant advantages in running Monte Carlo simulations, a type of algorithm that’s already widely used in the finance industry.
Monte Carlo simulations take repeatedly random samples to figure out the likelihood of different uncertain outcomes. Like rolling the dice at the namesake casino, Monte Carlo algorithms generate random numbers to determine the range of possible outcomes and their probabilities.
The additional processing power of quantum computers has the potential to make Monte Carlo algorithms much more powerful than anything that is possible with classical computing.
Why use quantum computing for Monte Carlo simulations?
Quantum computers are known to be the world’s best random number generators. When NASA first claimed to achieve quantum supremacy in 2019, the assertion was based on the ability to generate truly random numbers in a fraction of the time required by even the most powerful conventional supercomputers.
Quantum computers can analyze all possible states in a more comprehensive and efficient way. This significantly improves on the capabilities of their classical counterparts at handling high degrees of complexity, because the Monte Carlo simulation’s accuracy improves with the number of parameters and possibilities it runs.
Quantum computers also have another important advantage over classical computation–they can handle all-to-all connectivity, surpassing the limits of point-to-point connectivity. For example, when comparing two time series to each other, a quantum computer running a Monte Carlo algorithm can compare one entire series to the other, whereas classical computers can only compare one point at a time. Analyzing events in this way can reveal deeper trends, in less time, than on classical computers.
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How better Monte Carlo simulations can make better financial models
Because quantum computers make it possible to perform more comprehensive probabilistic analysis, Monte Carlo simulations run on them will be able to model financial markets without stripping out any of the complexity between the multitude of variables that interact within them.
Not only can this provide much more useful data for financial models, but when combined with the all-to-all connectivity it offers exciting possibilities to uncover germane patterns that exist where researchers and analysts might not even have known to look when researching with classical algorithms. That in turn will likely allow analysts to gain a competitive edge over markets by optimizing decisions for minimizing risk profiles and maximizing profitability.
For example, let's say we want to compare the performance of the S&P 500 vs. the Dow Jones Industrial Average over a certain period of time. Classical computers will be able to analyze the relationship between specific, given data points. This is useful, but has blindspots–it only shows the relationship between the data points chosen for analysis. In contrast, a quantum computer can look at all of the relationships that exist between all of the available data points during that time period. That is a much more comprehensive view of the relationship between the two indexes.
Conclusion
In addition to increased processing power, quantum computing can offer additional advantages over running Monte Carlo algorithms on classical computers. Even beyond comparing two similar datasets, quantum computers can also put together disparate data types— something classical computers struggle with. Data sources range from unstructured text and images to databases and spreadsheets—all of which increase data ingestion before running analysis. That can further optimize tasks like predictive analytics, anomaly detection, and more.
As quantum computing technology advances even further in the coming years, it promises to be increasingly adept and building superior Monte Carlo algorithms for financial modeling. To avoid missing out, forward-thinking companies are already making plans to take full advantage of quantum computing.
To learn more about the potential applications of quantum computing to the Finance industry: