Analytics for intraday trading data

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The Toronto Stock Exchange has chosen to partner with the Data Science Laboratory at Ryerson University and to provide access to most of its proprietary intraday trading data. This raw data contains information about trades, quotes and brokers occurring on a nanosecond time scale. Today, there is a real demand from customers not just to buy the raw data, but to buy analytics products that provide insights into the raw data. This demand for analytics comes from investing institutions, custodian banks, broker-dealers and other market participants that are building their analytics teams. The most sought after analytics product by TSE customers is analytic insights into trading strategies. Stock markets around the worlds such as the New York Stock Exchange (NYSE) are responding to this demand by developing analytics products. Our industrial partner - the Toronto Stock Exchange - is the ninth largest exchange in the world by market capitalization. In order to keep up with the pace of innovation, the Toronto Stock Exchange needs to develop analytics capabilities and analytics products. To respond to this demand, this proposal is a collaborative effort to convert raw intraday trading data into analytics insights about trading strategies. The Data Science Laboratory will apply novel algorithms such as evolutionary clustering to provide analytics insights into trading strategies. The end product will be a proof of concept showing the conversion of raw intraday trading data from the Toronto Stock Exchange into analytics insights of trading strategies using intelligent algorithms. Ultimately, the Toronto Stock Exchange will be in a position to provide analytics products to market participants and market regulators.