IBM and JPMorgan Chase Use of Quantum Algorithms in Finance
Quantum algorithms for financial derivatives
Points to note…
+ In the finance industry, options, or more generally financial derivatives, are contracts that give their owner the right, but not the obligation, to buy or sell some underlying security or set of securities at pre-defined conditions, such as time or price. They’re used in hedging strategies to manage financial risk, or to speculate on future market performance. Just in 2018, more than 13 billion option contracts were traded worldwide.
We are at the very beginning of this new quantum computing journey. Although we are making progress on a number of applications that may benefit from quantum computing, today’s use cases, like our option pricing research, are only the tip of the iceberg.
+ In a recent research paper on Option Pricing Using Quantum Computers that my colleagues at IBM and I published in collaboration with scientists at JPMorgan Chase, we developed a generic approach to map option contracts to quantum circuits. The algorithms use today’s small, noisy quantum computers to conceptually demonstrate a speed-up for pricing and analysis of the performance of a simple option. This speed-up may allow financial institutions to significantly reduce computation times and cost and increase the number of what-if scenarios and sensitivities that can be analysed in a given time once large enough quantum hardware becomes available.
+ Quantum computing, because of its unique exponential compute properties that operate in a completely different way from today’s classical computers, may help significantly increase the efficiency of these calculations by achieving a quadratic speed-up over classical Monte Carlo simulations.
Source: THE PAYPERS. Stefan Woerner, Quantum algorithms for financial derivatives…
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