WBR Insights recently published a survey of buy-side firms, and these takeaways caught my eye:
So why are so many buy-side firms looking for such granular price data?
In a Word: Competition
Buy-side firms have always looked for an advantage in the marketplace, and data sets that are less readily available can be happy hunting grounds.
Some definitions may be helpful before we dive deeper:
Level 1 Top of Book Data: Shows you the best bid (the maximum price a buyer is willing to pay) and offer (the minimum price at which a seller is willing to sell) in an order book, along with the last traded price. If you just want to know the best available price in the order book or calculate simple metrics like VWAP, Level 1 data should suffice.
Level 2 Depth of Book Data: Goes further by showing you the aggregated order volume by price. The number of price levels is typically limited to five (5) or so levels. Level 2 data is good for understanding the overall order book behavior. For example, you can find imbalances of buyers and sellers.
Level 3 Depth of Book Data: Allows you to see the complete order book with all price levels. Most important, Level 3 does not aggregate orders in any way. You can see each individual order and its place in queue. Level 3 depth of book data enables you to understand the behavior of an individual order, including your own orders. For example, you can determine the probability of an order filling, its resting time in the order book, and other order queue dynamics.
Who Exactly Uses Level 3 Depth of Book Data and Why?
It’s not just systematic quant funds or HFT firms that are using this data. Fundamentals-driven firms with much longer time horizons see the value in such granular price data.
I know this first-hand because DIH (in conjunction with our partner, BMLL Technologies) offers Level 3 depth of book data for global equities, ETFs and futures.
Firms tell us it is critical that they can measure the performance of an order’s execution pre-trade, during the execution, and immediately post-trade.
They also need to be able to generate statistics to assess both market quality and important risk metrics that impact trading performance. For example, they want to know the impact of their order on the price. Or how many levels down the order book will they need to go to fill an order of a given dollar volume (often referred to as “sweep to fill”)?
Sometimes the use cases are alpha discovery, but even more so the focus is on risk management.
Level 3 Data Is Finally Accessible and Affordable
There’s another reason more firms are using Level 3 depth of book data. Now they can.
Advancements in cloud computing (it’s secure, faster, and cheaper) have made it possible for firms to benefit from fine granular price data without taking on the huge burden of building and maintaining the infrastructure to store and analyze these huge data sets. They can simply log in from a Web browser to access and analyze the data.
What about you? Are you using or thinking about using Level 3 depth of book data? I’d love to hear your thoughts.
If you’d like a copy of the WBR Insights’ survey, please email me and I’ll send it along to you.
Also, please connect with DIH on LinkedIn and Twitter.
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Tom Myers is the founder of Data In Harmony (DIH), a data consultant and provider. DIH help firms find the data they need, validate & clean data, integrate data, and monetize their data. DIH also provides a wide variety of financial and alternative data, as well as data engineering tools.