Financial Modeling and Quantum Computing Economics
M Mishra Tirathkumar, Prashant I. Vadikar, Ashok Gadi Parthi
The world of finance is in flux again, and one of the reasons for this is due to quantum computers. This chapter, investigates the ways that financial thinking has grown over the years, and the role computers have played in that growth. Development of models such as Markowitz’s portfolio theory, Monte Carlo simulation and the Black-Scholes model, impacted the way modern finance operates. This was later pushed even further by high frequency trading. Now a new change is taking place as quantum approaches begin to enter the game. Quantum computing started as a collection of theoretical concepts. People like Feynman, Benioff ,Deutsch, Grover and Shor played major role in the development of the founding ideas. these founding ideas eventually led to the real machines, like International Business Machines’ (IBM’s) Q System One and Google’s Sycamore. Even though these devices are limited at this time, they have paved the way for new types of financial applications. For example, Monte Carlo for quantum, can bring forward the risk calculations quicker. Portfolio optimisation can be tried out by Quantum Approximate Optimization Algorithm (QAOA) or quantum annealing. Some researchers are using the quantum machine learning tools to detect fraud as well. Others are trying out pricing models for complex derivatives. Many large financial companies are already active in this field. John Pierpont Morgan (JPMorgan), Goldman Sachs, Wells Fargo, Hongkong and Shanghai Banking Corporation (HSBC), Mastercard and Banco Bilbao Vizcaya Argentaria (BBVA) have all been conducting experiments or partnerships. Small companies are also active, such as fintech firms such as Multiverse Computing. The governments are taking notice as well. The United States of America, the European Union, China and India have commenced major programs (like the US National Quantum Initiative and India’s National Quantum Mission), given that they recognize quantum technology as a major economical opportunity, as well as a strategic necessity. A lot of current work mixes classical and quantum methods. Most companies run small pilot tests, build hybrid algorithms, or work inside simulation platforms because fully reliable quantum computers do not exist yet. There are also many issues to deal with. Noise in the hardware, difficulty scaling up, challenges in translating financial problems into quantum formats, and questions about regulation all remain. There are ethical worries as well. Quantum tools could give some players an unfair advantage, weaken existing cryptographic systems, or increase the gap between countries and institutions. In the end, the message is simple. Large, fault-tolerant quantum computers may take time to arrive, but waiting too long is risky. Firms that start learning, testing, and training now will be in a much stronger position later. Quantum computing is no longer a far-off dream.
CRC Press eBooks•Jul 13, 2026•0 citations