Hannah Baum

Aqua POV – from JP Morgan

April 2021 in Algo of the Month

With Hannah Baum, Head of EMEA eFICC sales at J.P. Morgan

In what ways does the strength and experience of JP Morgan’s market making franchise put it a good position to meet the increasing demand for algorithmic FX trading?

JPMorgan has one of the largest and most sophisticated eFX franchises on the street. In certain pairs, flows are as large as volume traded on the primary market. Our wide distribution network spans across all regions and client sectors resulting in a wide breadth of client flow. JPMorgan algo participants benefit from the ability to offset natural client interest in an undisclosed manner which reduces their overall market impact. In addition, our market making research is factored into the algorithmic liquidity seeking execution which increases the accuracy and effectiveness of the order.

What steps have you taken to help clients become more comfortable with FX algo execution?

We have recently launched a pre trade analytics tool giving clients access to a number of real time benchmarks. Features include liquidity profiles by currency pair, a real time volume gauge and fill distribution transparently displayed, all allowing clients to make informed decisions at the point of order entry and during the life of the order. We’ve started publishing aggregated observations based on empirical data following certain market events to evidence the value of algo execution vs risk transfer . This allows clients to better assess the effectiveness of algorithmic execution in different market conditions. As well as providing clients with JPMorgan TCA on demand, we support independent TCA providers. This is complimented by the full eSales coverage service which includes the monitoring of orders, a constant dialogue during execution regarding the performance and data driven conversations post trade.

What are the key benefits that clients are getting from using your FX algos?

We offer a breadth of strategies across a wide range of currency pairs and crosses. JPMorgan’s large electronic market making franchise gives us a deep understanding of the market microstructure which helps determine optimal algo participation within the ECNs. Our internalisation network offers a unique pool made up of genuine reciprocal risk. In addition we are able to leverage our cross asset algorithmic research to build and enhance the offering. The enhanced transparency offering through real time tools and TCA reports allow clients to make more informed decisions in a bid to improve their execution quality whilst lowering their overall transaction costs.



  • The Aqua POV is a dynamic, liquidity seeking algorithm that adapts to specific market conditions.
  • It increases its participation during times of high liquidity and slows execution when conditions reverse.
  • The order takes advantage of different liquidity scenarios to manage market impact through specific user parameters.
  • It uses a real time volume estimation


  • The algo’s main objective is to participate at the optimal point of liquidity and frequency to minimize market impact while managing the associated time risk.
  • The urgency parameter allows the user to easily control market impact vs market/time risk.


  • It can be used for any currency at any time of day.


  • Multi asset: Aqua is a successful strategy already used in our cash Equities and Futures market.
  • Easy to use: Only one parameter necessary ‘urgency’
  • Adaptive: to real time market liquidity conditions.
  • Urgency allows users to easily control market impact vs market/time risk, adapting both the speed of execution and trading trajectory to real time conditions.
  • A data driven approach to order routing maximizes fill rates while limiting information dissemination.