All posts by Nick Garrow, Chief Strategy Officer

The rise of buy-side multi-asset trading requires firms to streamline data processing, execution workflows and risk management across different markets. Automation can help make operations more scalable, but success in multi-asset trading depends on understanding which processes can be standardized and where specific market context is essential for trading performance.  

At September’s TT Connect event in London, a buy-side-led panel discussed the move to multi-asset trading environments and the role of automation. Here are my key takeaways from the discussion. 

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Demand for raw computing power, or “compute,” has kept pace with, and in some cases outstripped, the rapid growth of AI. That has created a new source of volatility, and with it, a new source of investment. The financialization of the chips that power AI’s LLMs means that the graphics processing unit (GPU) is on its way to becoming a mainstream trading opportunity. The hardware itself stays physical, but by hedging the price and time of its rental, firms can turn an unpredictable cost into a manageable one: classic financial risk transfer.

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European power and gas markets are evolving rapidly, as exchanges continue to introduce new products and market structures. One important upcoming change is the European Energy Exchange’s (EEX’s) migration of the EEX Gas Spot market to a new trading engine, with implementation expected in 2027. For many energy trading firms, this could bring disruption, integration costs and operational risk. 

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Artificial intelligence (AI) is rapidly transforming how firms process and analyze data. For traders, the deployment of AI alongside cloud-based infrastructure is creating new efficiencies in everything from risk management to alpha generation. At the recent TT Connect: The Evolution of Execution event in London, industry experts discussed how advances in AI and data management were reshaping how they approached global markets. 

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