Iceberg Order Detection is an important topic in liquidity analysis – one of the most actual and difficult questions in the financial world. Anton Antonov, a Lead Quantitative Analyst at dxFeed, is going to discuss this topic at the 6th annual Quant Insights Conference. 

dxFeed proposed a method for detecting and predicting native (managed by the exchange) and synthetic (managed by market participants) iceberg orders on the Chicago Mercantile Exchange. The icebergs extracted from historical data tapes are used to train a model based on the Kaplan–Meier estimator, accounting for orders that were canceled after a partial execution. The model is utilized to predict the total size of newly detected icebergs. Out-of-sample validation is performed on the full order depth data; performance metrics and quantitative estimates of the hidden volume are presented.

Do you want to know more? Join dxFeed breakout section at 10:20-10:40 EST, 12th November.

Book free ticket here