— Derived Data Analytics —

Defining Derived Data Analytics.

Derived data analytics are computed or extrapolated from other existing data. They are often created by cross-referencing and/or combining various data sets and applying mathematical calculations to the resulting data set.

For example, DIH offers over 400 metrics based on level 3 depth of book data. These metrics are derived from every single insert, modify, execute or delete order message across every venue, available at daily and intra-day resolution. Such metrics capture the fullest picture of market quality, liquidity, volatility, spreads, order resting times, fill probabilities, and much more.

Derived data analytics for global equities, fixed income, derivatives, and crypto - DIH

How Firms Use Derived Data Analytics.

Institutional market participants use derived data analytics for various tasks, including:

  • Manage risks associated with securities in their portfolios
  • Gain insights into the overall market
  • Develop and back-test trading strategies

For example, there is a myriad of ways to use our Trend Capture Analytics:

  • Analyze, compare and validate holdings & investment ideas.
  • Identify new investment opportunities across markets and sectors.
  • Tactically select & allocate across markets, regions, and sectors so you are not out of sync with prevailing stock trends.
  • Improve your risk models and fine-tune exposure to individual holdings & portfolios by spotting in time underperformers.
  • Be alerted to stock trend reversals.

No matter what the use case, having accurate analytics is important.