Through the smartTrade LiquidityAggregator™, traders can choose to utilize a personalized combination of how they want to internally virtualize the external world through their choice of how to aggregate liquidity, tier prices to their clients, create dark pools, manage cross-border trading etc. to provide for best execution.
LiquidityAggregator can maintain the calculation of ratios of flows for each exchange and recalibrate the ratio, both as orders are consumed and as defined ratios change. For example, a firm that wants to calculate a 21-day Median Daily volume for purposes of splitting non-marketable orders over exchanges can use LiquidityAggregator for the 21-day calculation and in conjunction with LiquidityOrchestrator can real-time-reassess the market and execute the split of the quantity following a rule defined by the customer using the volume ratio given by the MDV numbers in the aggregator.
LiquidityAggregator can first maintain the calculation of ratios of flows for each exchange and recalibrate the ratio both as orders are consumed and as defined ratios change. For example, a firm that wants to calculate a 21-day Median Daily volume for purposes of splitting non-marketable orders over exchanges can use LiquidityAggregator for the 21-day calculation and in conjunction with LiquidityOrchestrator real-time reassess the market and execute the split of the quantity following a rule defined by the customer using the volume ratio given by the MDV numbers in the aggregator.
LiquidityCrosser provides first for a deeper interaction with a firm’s flow to maximize internal crossing possibilities before sending orders to the market at high speeds. While LiquidityCrosser is a true internal market with a highly customizable matching engine, it is not driven by events, but it does leverage flow that exists within a firm to keep best execution inside whenever possible. LiquidityCrosser can be used in combination with LiquidityOrchestrator to set rules on the matching criteria, trading partners and how the flow will be executed. LiquidityOrchestrator also manages and reconciles the ‘child’ orders to the original source order to prove best execution. In high-frequency trading environments, this can otherwise be a very onerous task.
LiquidityCrosser provides for a deeper interaction with an organization’s flow to maximize internal crossing possibilities before sending orders to the market at high speeds. It is a true internal market with a highly customizable matching engine. Instead of being driven by events, it leverages flow that exists within a firm to keep best execution inside whenever possible. LiquidityCrosser is used in combination with LiquidityOrchestrator to set rules on the matching criteria, trading partners, and how the flow will be executed. It also manages and reconciles the ‘child’ orders to the original source order to prove best execution. In a high-frequency trading environment, this can otherwise be a very onerous task.
The matching engine for the workflow process of RFQ’s. Working with the RFQ process, a smartTrade Technologies client can set a specific time for a quote to be manually responded to (negotiation); if it is not, then the quote will automatically be sent to an auto-pricer or to the market (using the smartTrade SOR).
smartTrade Technologies can create the internal market where traders have the access to the lots available in the market. They can provide the high-touch to clients and lots that cannot be filled in the manual process, can be routed to the market.
smartTrade Technologies can provide for the normalization of RIC codes so that an internal virtual order book can be created. From this order book, clients can trade any number of securities including corporates, CDSs, and Swaps.
LiquidityCrosser offers firms the ability to determine whom they want to trade with within their own organization, including retail and institutional clients. LiquidityCrosser can have multiple pools of matching and flow can be redirected to the organization if it cannot be matched peer-to-peer. The LiquidityConnect component of the STTP platform then provides for the normalized communication between the clients and the organization to eliminate the challenges of on-boarding clients.
Clients can use smartTrade’s Liquidity Management System to create Dark Pools or do systematic internalization in multiple asset classes.
Orders within the LiquidityAggregator can be flagged as either dark or visible and are managed at the engine level. If an order is flagged as dark, it will appear in the internal books and can be consumed, but will not appear in the published books. If an order is flagged as visible, it will appear in both the internal and published books and can be consumed in both. The flagging of orders from dark to visible can be changed by the organization. Additionally, the smartTrade engine can provide this functionality to both the smartTrade customer firm and the customer’s clients. For example, if Broker A has implemented the Liquidity Management System, they can decide to manage the dark book functionality within their organization or they can offer out to their customers the ability to determine where they want their order to reside.
Using the LiquidityCrosser crossing engine, traders can determine the matching criteria and with whom they want to trade. The system provides a flexible method to rank orders according to configurable matching criteria. The way in which bids and offers are ranked and the definition of “equality” or “match” are not fixed – they can be defined and later redefined as business needs change. LiquidityCrosser supports multiple types of crossing, including continuous or scheduled, multiple types of orders and multiple types of execution conditions. LiquidityCrosser combines with LiquidityAggregator, delivering full flexibility in the how a firm’s books are aggregated and crossed.
In addition to creating internal dark pools for a firm, the smartTrade platform can probe external dark pools for liquidity using LiquidityOrchestrator. A smart order router, LiquidityOrchestrator continually reassesses the state of the market and recomputes orders as it sends IOIs to various dark pools. As orders are executed, LiquidityOrchestrator continued to probe those pools where liquidity has been found while monitoring simultaneously those pools where liquidity was not originally found, but may subsequently present itself. LiquidityOrchestrator will actively manage the lifecycle of the entire order and reconcile the ‘child’ orders back to the original source order. Used in conjunction with LiquidityCrosser,
LiquidityOrchestrator and LiquidityCrosser work together to internally cross orders while interacting with external dark pools, maximizing the opportunity to internalize without sacrificing best execution. LiquidityCrosser provides first for a deeper interaction with a firm’s flow to maximize internal crossing possibilities before sending orders to the market at high speeds. While LiquidityCrosser is a true internal market with a highly customizable matching engine, it is not driven by events, but it does leverage flow that exists within a firm to keep best execution inside whenever possible. LiquidityCrosser can be used in combination with LiquidityOrchestrator to set rules on the matching criteria, trading partners and how the flow will be executed. LiquidityOrchestrator also manages and reconciles the ‘child’ orders to the original source order to prove best execution. In high-frequency trading environments, this can otherwise be a very onerous task.
Certain securities can be traded on exchanges in multiple countries, thereby adding a higher degree of complexity in providing for best execution, taking into account an FX component and the exchange location.
LiquidityOrchestrator supports cross border trading. It enables firms to set their routing criteria regardless of where the exchange is located and what the base currencies at that exchange.
Then the system uses the LiquidityAggregator to derives the specific foreign currency price, i.e., CAD, STG, Euro using the original USD price and the FX spot rate.
The aggregator then creates a book with depth that integrates all the specific FX currency prices to create USD derived quotes.
Using LiquidityOrchestrator, a firm can then set the routing rules for the exchange that has the best price, taking into account the FX component.
smartTrade provides functionality for firms to make markets in a variety of instruments, aggregating and consuming prices via the LiquidityAggregator, integrating with internal proprietary pricing engines, and distributing customized pricing streams to clients.
Customers can create and customize sophisticated matrices to control the distribution of market data and prices to their various types of clients. Prices can be distributed with custom spreads and limits over any messaging infrastructure. Data can be distributed to an unlimited number of downstream users at extremely low latency.
Working with an institution’s internal risk system, LiquidityDistributor can consume the liquidity stacks for further distribution to the institution’s clients. Prices can be sent in any size; whole, half or decimal pips and can be quoted in inverse quote conventions. Custom spreads and limits can be applied either on a group basis or an individual spread basis and can be changed on the fly. Clients can be moved from one group to another group dynamically. Ladders can be distributed to the institution’s clients on a “size by price” basis including “best-average” or “worst.”
LiquidityDistributor supports the distribution of both full market data streams and incremental snapshots. It can also conflate the data to preserve system resources.
In addition to the price distribution functionality, clients can implement smartTrade’s LiquidityCrosser for matching and the LiquidityOrchestrator for smart order routing to build out a complete single dealer platform. The LiquidityCrosser is a matching engine that fills the institution’s client orders (i.e. FOK) based on the liquidity in the books at low latencies. The LiquidityOrchestrator manages not only the internal routing between books, it also manages the RFQ process of routing the request to either an auto-quoting engine or for a Manual Quote. In the event of complex instruments with multiple legs, the LiquidityOrchestrator can disaggregate the different leg components and route them accordingly (manual or automatic).
This use case describes the needs for the FX eCommerce division of a multi-national bank.
This client had legacy FX trading platform, but it was inadequate to support their growing FX business.
This bank’s global FX traders sourced liquidity regionally, and could not access each others’ order flow for internalization. This resulted in:
The system automatically hedged positions with market orders routed to only a couple ECNs, and they lacked algorithmic capabilities to maximize internalization before routing to the markets. These unsophisticated routing strategies were hurting their risk management effectiveness.
Their pricing engine wasn’t moving prices after a client traded against the price, allowing predatory traders to hammer their system, creating unnecessary risk and reducing the profitability of the FX business.
The client wanted to aggregate prices from a variety of ECNs and single banks along with the liquidity from their global trading operations to create a single global pool accessible and executable around the globe.
They developed their own pricing engine, which accessed the aggregated price feeds. They needed a liquidity distribution system that could take the base price created by the pricing engine, adjust spreads based on internal positions and client type, and distribute the custom pricing to clients. The pricing distributor also needed to intelligently update prices based on a client’s trading activity, market prices, and the bank’s current risk positions.
They also needed a smart order router that could help them manage the flow, ensure best execution, and route orders based on their custom execution algorithms while integrating the routing with a matching engine that would allow them to maximize opportunities to internalize customer flow.
They needed to become independent from their brokers and have their own connectivity in place without the hassle of maintaining the connection technology.
Opportunity cost: This bank has a strong in-house FX trading and technology expertise. They realized that a number of other priorities would need to shift in order to commit the resources for internal build.
Time to market: When they evaluated smartTrade in a proof of concept, they realized that they could deliver an FX eCommerce solution faster using smartTrade than if they developed in house.
Total cost of ownership: As a Java shop, they liked the idea of using Java because they knew the cost of resources for integration, customization, and maintenance would be lower than for other solutions that used non-standard languages.
Commoditized technology: The bank recognized that certain parts of an FX ecommerce system are commodities. They wanted to focus their team on building the “special sauce” such as pricing that provide competitive advantage while using off-the-shelf components for the non-differentiated portions of the system.
The client used the following smartTrade components:
This bank was able to implement their FX eCommerce system in four months, building on the proof of concept provided by smartTrade. They needed very little support, relying on smartTrade only for an initial training session and a minimal amount of consultation on installation, setup and design.