Limit order book (LOB) data has long been a source of fascination and frustration for market makers and high-frequency traders. The log of bids and offers in the market undoubtedly contains pertinent information about the next tick in the price of an asset. But the data is so voluminous that it is cumbersome to analyse using traditional techniques. Quants at the Oxford-Man Institute are using deep learning to tackle this problem. Our guest for this episode of Quantcast is Stefan Zohren, an associate professor at the Oxford-Man Institute and principle quant in charge of futures and foreign exchange execution research at Man Group’s central trading division. He has been working on the project with Zihao Zhang and Stephen Roberts at the Oxford-Man Institute.
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