Optimize your algo trading models: Tick data best practices

As the financial world seeks to optimize proprietary pricing and trading strategies, the huge volume of tick data demands models that can deal with multi-asset class data and incorporate ancillary data for insights and risk profiling in real-time.

We’re excited to host this webinar alongside ICE, a global leader in cross asset market data, pricing and analytics. We’ll discuss different approaches to optimizing your algo trade models using real-time & historical data analytics . If you’re making fast decisions using large tick data volumes, then this webinar will help equip you with the tools you need to optimize your tick environment. We’ll explore:

• The most valued features and functions of a real-time analytical platform.
• Technologies available to build a high performance, flexible DataOps environment to derive maximum value out of your tick data.
• Backloading historical data to validate trading models before deploying them to production using real-time data.
• The market trends amongst buy-side and sell-side, and the importance of high-quality market data to an alpha-generating model across listed and OTC assets.

Hosted by:

• Nick Laurence, Vice President Marketing, KX

Guest Speaker:

• Martin Haines, Managing Director, Asia, KX
• Leon Liang, Director, Feeds Business Development, ICE Data Services