Difference between revisions of "Machine Learning/Finance"
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Revision as of 07:14, 12 July 2021
Machine Learning
The importance of machine learning in finance continues to grow.
Growth in fixed income futures algorithmic trading at JP Morgan has accelerated rapidly in 2020 as buy-side traders globally turned to the investment bank's machine learning-equipped algos to grapple with intense market volatility.
Speaking to The TRADE, Peter Ward, global head of futures and options electronic execution at JP Morgan, explains that while the volatility contributed to recent growth, adoption of futures algo trading has picked up pace with clients significantly in the last few years.
Since 2016, futures volumes traded via algos at JP Morgan has increased 40% year-on-year. In fact, algos now comprise almost 20% of the bank's total futures trading flow, up significantly from roughly 4-5% in 2016 and 2017, figures seen by The TRADE have revealed.
The period of intense volatility in 2020 due to the global pandemic played a key role in the cumulative buy-side adoption of futures algos as traders became more accustomed to on-screen execution and liquidity.
