Human Decision Making Will Determine use of Quantum Computing in Finance
Quantum computing, the new frontier of finance
Selected notes ~
+ The evolution of modern finance was closely linked to the evolution of computers, communications, and financial mathematics. Two main changes happened in the 1970s with the beginning of derivative trading and after the crisis of 2007 with the massive introduction of fintech.
A major new change is now in sight through the possible implementation of quantum computers. Instead of binary bits – the classic elementary unit of information – quantum computing uses qubits (quantum bits), obtained by the superposition of binary states. This would allow them to process a much larger amount of information thousands of times faster than classical computers.
+ Derivatives pricing started with the celebrated Black and Scholes equation and formulas in 1974, followed by a wealth of mathematical methods to compute the prices of derivatives. Still, even the 1980s derivative pricing required supercomputers, giving big firms a major competitive advantage – before the 2007 crisis, the trading volume was close to 1 trillion dollars a day. The prevailing opinion was that derivatives had enabled us to complete financial markets so that any stream of cash flows could be engineered. This belief was shattered by the 2007 financial crisis, which showed that hedging can be perfect only as long as counterparties stay solvent.
+ What would be the importance of quantum supremacy for finance and economics? First, quantum computing would make current cryptographic techniques unsafe. Methods and algorithms will have to be changed. Post-quantum cryptography, or quantum-resistant cryptography, is a flourishing sector of study both in academia and with firms involved in cryptography. Some firms already offer products for post-quantum cryptography, which will be big business.
+ The search space of quantum computers could be thousands of time larger than the search space considered by current computers. It would become feasible to synthesise a design from specifications and machines could become more “creative” through the ability to explore an immense range of possible design solutions. In the fields of finance and economics, quantum computing could lead to analysing a large space of heterogeneous data to make financial and predictions and understanding economic phenomena.
+ Amid such hope, caution is necessary: financial and economic data are truly complex, and analysis will not necessarily lead to more accurate predictions given the complexity of data. The complexity and non-stationarity of data might defy analysis. In other words, it is questionable if the use of quantum computing will reduce uncertainty.
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