Terra Quantum And Cirdan Capital Use Quantum Software For Enhanced Exotic Option Pricing

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Insider Brief

  • Terra Quantum and Cirdan Capital report they developed a faster algorithmic method to price exotic options.
  • Exotic options, such as multi-asset autocallable options, are complex financial instruments that provide investors with alternative strategies for managing risk and maximizing returns.
  • Simulations are often used to determine prices of exotic options, but they are computationally expensive.
  • Image: Quantum Trading AI

PRESS RELEASE — Terra Quantum, a leading quantum technology company, and Cirdan Capital, a London-based investment bank, announce their joint efforts in creating tangible business value using quantum software. They have successfully developed a faster algorithmic method to price exotic options, such as multi-asset autocallable options, by leveraging Terra Quantum’s proprietary algorithms.

Exotic options, like the ones mentioned, lack analytical solutions, and usually require Monte Carlo simulations to determine their prices. These simulations are widely used in the Financial Services industry but can be computationally expensive. Terra Quantum’s approach, utilizing its specialized quantum software based on Tensor Networks, offers a significant advantage in calculating highdimensional integrals and solving complex partial differential equations involved in option pricing. Importantly, this approach can be run on classical compute infrastructure, providing a competitive advantage over the industry standard Monte Carlo methods. For instance, these option pricing calculations achieved a 75% pricing speedup compared to the benchmark, utilizing the equivalent compute infrastructure for both approaches. As Terra Quantum’s approach evolves with large-scale quantum computing hardware, this speedup is expected to further increase.

The increased speed provided by Terra Quantum’s approach enables traders, risk managers, and banks to evaluate their books and structured product portfolios more efficiently while reducing the time and cost associated with cloud compute usage. Additionally, Terra Quantum’s solution improves the speed and computational efficiency of calculating risk parameters, commonly referred to as the ‘Greeks’.

Considering the estimated total outstanding notional value of exotic options at around $1 trillion and the need for larger trading entities to regularly price multiple option types, this speedup is expected to significantly reduce the compute costs, potentially saving several million dollars annually.

“Our work with Cirdan Capital provides a glimpse on the power of quantum software for the financial services industry, running on classical hardware today, and on large scale quantum hardware in the near future,” said Markus Pflitsch, CEO of Terra Quantum. “As quantum hardware matures, leveraging tensor networks for trading could provide further advantage in terms of speed.”

“Speeding up options pricing can enable trading desks in volatile markets to assess their risks faster by valuing their books more often during the day, resulting in better identification of intra-day market imbalances, while also helping them reduce their computational costs significantly.” said Antonio de Negri, the CEO of Cirdan Capital.

The collaboration of Cirdan Capital and Terra Quantum showcases how existing, quantum- compatible mathematical models can provide a market edge for financial institutions today, while effectively preparing them for future quantum-powered applications.

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James Dargan is a writer and researcher at The Quantum Insider. His focus is on the QC startup ecosystem and he writes articles on the space that have a tone accessible to the average reader.

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The Future of Materials Discovery: Reducing R&D Costs significantly with GenMat’s AI and Machine Learning Tools

When: July 13, 2023 at 11:30am

What: GenMat Webinar

Picture of Jake Vikoren

Jake Vikoren

Company Speaker

Picture of Deep Prasad

Deep Prasad

Company Speaker

Picture of Araceli Venegas

Araceli Venegas

Company Speaker

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