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Recent news coverage and analyst reports* have noted the continued preference of equity options market participants for negotiating complex, sizable options transactions using voice and instant message systems rather than monolithic cash-equities style crossing networks, which have been introduced into the options markets in recent years.


This post discusses the evolution of instant message systems in recent years and the broadening of their collaboration, work flow optimization and liquidity management functionality, which has made these systems not only sticky, but indispensible among high-touch market users.  


Moreover, this robust functionality is prompting buy and sell-side market participants to expand the ways in which instant-message systems are used.  For example, a U.S.-based equity options market maker recently implemented an enhanced instant message system to rework their pricing and risk management engines. The result was a 30 to 60-fold increase in the speed in which the firm prices markets, from nearly a minute previously to less than a second now.




The original instant message systems used to communication and negotiate complex products and source liquidity have evolved to include an integrated set of powerful tools that support the familiar instant message chat screen, but extend their functionality greatly.  For many front-office users, these tools, which include liquidity and client management blotters as well as monitors, which aggregate incoming and outgoing message data, have eclipsed the chat screen in terms of utility and sheer power.


Equity Options Market Maker Case


As discussed above, large-scale equity options traders find voice and instant message systems optimal for negotiating trade elements and sourcing liquidity. This preference is driven, in part, by the intuitive, natural communications modes of these two formats. Given the popularity of instant messaging, however, it is common for a market maker in equity options to have many, often several dozen, instant message windows open on his or her desktop.  To deal with this flood of disaggregated chat, market makers deploy various ad hoc methods to prioritize the windows by client importance or highest priority stocks, for example.


Despite these methods, a market maker’s main challenge is continuously sorting through the torrent of incoming messages to find the orders that he or she could most profitably price, buy or sell.


Once an order message is selected, e.g., to price a specified options structure, the market maker would manually load the details into his or her pricing model and risk systems to generate a price, which would then be sent to respond to the original query. All of these steps add time, usually  30 seconds to one minute. In addition to delay, these steps add complexity and the opportunity for error to the process.     


In this case, the market maker ABC Trading** implemented an instant-message based transaction collaboration system to collect and aggregate all instant messages coming in from brokers, clients and other market participants into a consolidated market view. The system’s specially built language parsers extract product and price details embedded in instant message text and convert them machine-readable data. The data flows into the firm’s pricing and risk engines via an API, enabling a price to be generated instantly.  The market maker, who can now see all trade opportunities on a single blotter, now prices optimal trade opportunities with a single mouse click.


Traditionally, ABC Trading would have seen a price request and selectively chosen a few that they thought were interesting and manually inputted the data into their systems. This process involved inputting multiple fields and could take anywhere from 30 seconds to 1 minute. The new solution slashes response times to sub-second.



·        Trader visually monitors dozens of IM chat boxes with feeds from

o   Brokers

o   Dealers

o   Fund managers

·        Trader selects most promising opportunities to price

·        Trader manually enters product details into pricing and risk engines

·        Trader receives price

·        Trader manually enters price and responds to broker or counterparty

Total time: >30 seconds to 1 minute



·        All IM messages from brokers, dealers and fund managers are fed via API into trade collaboration system

·        Product and pricing information is automatically extracted by parser and fed through API into pricing and risk engines

·        All product, pricing and broker/counterparty identification are displayed on a consolidated blotter to market maker

·        Market maker selects best opportunities, clicks to respond to broker or counterparty

Total time: <1 second


By vastly compressing the time it takes to process incoming messages, as well as the time to respond, ABC Trading routinely became the first responder to pricing requests. They immediately noted they were winning a significantly higher percentage of available deals, which generated a multiple of their previous trading revenue. In addition, because of the automated nature of the pricing, the firm’s traders can monitor and assess all opportunities as opposed to guessing which ones might be an opportunity.


Additional benefit is the accuracy of the pricing increases as well due to the automated nature of submitting the relevant data.


*A version of this post was posted previously at Tabb Forum, which analyzed this phenomenon.

**the actual client name is withheld at their request.


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