From my colleagues in Group Innovation: press release yesterday on their POC with IBM on using QC to optimise bond quotation. The team is more generally exploring real-world use cases. For example, their previous POCs studied keeping tokenised gold cryptographically safe (the bank has been offering tokenised gold to Hong Kong customers, backed by bullion) and hardening cryptographic keys.
[UPDATE paper, thanks Carlos!] Enhanced fill probability estimates in institutional algorithmic bond trading using statistical learning algorithms with quantum computers
[Press release] HSBC demonstrates world's first-known quantum-enabled algorithmic trading with IBM | HSBC News
Working with a team from IBM, HSBC leveraged an approach that utilised quantum and classical computing resources to deliver up to a 34 percent improvement in predicting how likely a trade would be filled at a quoted price, compared to common classical techniques used in the industry.
| arXiv.org |
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| Enhanced fill probability estimates in institutional algorithmic bond trading using statistical learning algorithms with quantum computers |
| The estimation of fill probabilities for trade orders represents a key ingredient in the optimization of algorithmic trading strategies. It is bound by the complex dynamics of financial markets with inherent uncertainties, and the limitations of models aiming to learn from multivariate financial time series that often exhibit stochastic properties with hidden temporal patterns. |
| View this on arXiv.org > |
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| HSBC |
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| HSBC demonstrates world's first-known quantum-enabled algorithmic trading with IBM | HSBC News |
| HSBC announces the world's first-known empirical evidence of the potential value of quantum computers for solving real-world problems in algorithmic bond trading. |
| View this on HSBC > |
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Kara K.W. Byun
Head of Fintech
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