- v1.0 Version
- 277 Download
- 3.3mb File Size
- 1 File Count
- 12th July 2019 Create Date
- 12th July 2019 Last Updated
- Liquidity Fragmentation: An Evolving Challenge
- A Current Picture of Smart Order Routing
- The Case for Adaptive Trading Technologies
- Machine Learning & Smart Order Routing
"Liquidity fragmentation, the phenomenon of multi-listing
of an instrument on different venues, creates deeper and
broader markets and lowers transaction costs. Despite
the benefits, it has become a major challenge to market
participants from buy-side to sell- side institutions, as it has
led to a more complex trading landscape. Some of the tools
used to address this problem have been in place for a long
period, while others are new to the market.
Smart Order Routing (SOR), which is undeniably the best
solution to tackle liquidity fragmentation, has been around
for over a decade. SOR is also increasingly the critical
element in the building of any trade automation technology.
Current SORs - both the simplistic rule-based and the newer
generation using a liquidity seeking algorithmic approach -
are offered by bulge-brackets and some vendors with a wide
range of capabilities and limitations.
This whitepaper provides an update on our previous Smart
Order Routing whitepaper and looks at the innovation in
this domain. In addition, this paper is written as Artificial
Intelligence (AI), and more precisely Machine Learning (ML),
are rapidly reshaping the IT landscape. We will naturally look
at the areas of application for ML in SOR and more broadly
in automated trading."
Quod Financial presents in our latest Smart Order Routing whitepaper the rapidly changing landscape for Automation and Order Routing. How AI/ML (Machine Learning) applies in SOR and more broadly in Automated Trading.