Whitepaper: Buy-side usage of Level 3 data analytics for algorithmic performance

Buy-side usage of Level 3 data analytics for algorithmic performance

Today, data and analytics play an increasingly important role in the workflows of all capital market participants to uncover hidden patterns in the data that can be used to predict the future market moves. However, utilizing vast data sets for alpha generation is both labor and capital intensive as firms lack in-house resources to manipulate large data sets and face prohibitive cost of acquiring and analyzing the data.

The next 12-18 months will be critical for all firms looking to embrace data and analytics to help drive increased risk-adjusted returns and should come as no surprise that many investment firms are looking to partner with third parties to outsource data and analytics generation.

For our latest whitepaper, in collaboration with WBR Insights, we surveyed 100 Heads of Data, Chief Data Officers, Data Scientists to find out how buy-side participants use predictive data and analytics in their daily trading decisions to improve alpha generation and mitigate risk.

Our survey found that:

  • High quality data has become a commonly utilized commodity by most market participants - 74% of respondents say they use Level 3 data in their research program
  • Of the  respondents not using Level 3 data in their research programs – nearly 75% said the main reason was its inaccessibility 
  • 64% of respondents said that at least 50% of their investment in new data and analytics capabilities will be from buying-in these capabilities
  • 41% of respondents saying that they will increase their budget allocations significantly for third-party data as a key element of their quantitative research
  • Over 80% of respondents said they already are or are very likely to embrace cloud for their data and analytics generation and processing over the next 12 - 18 months 


You can read our press release here or click below to download the Whitepaper.

 Download the WBR whitepaper for the full findings