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Considerations When Selecting the Best Trading Platform for Buy-Side in Asia Pacific

Data Science and AI

By Manu Sharma  |  November 7, 2019

If one were to pick a single overarching theme prevalent on buy-side trading desks across APAC in recent years, it would likely be one of consolidation by the formation of centralized dealing teams. These teams are tasked with multi-asset class, geographically dispersed trading responsibilities with clear expectations of both preserving and producing alpha amidst a volatile market backdrop.

Trading centers in Europe and North America have led this act of consolidation, so it’s not surprising that their peers in APAC would eventually follow. When compared to APAC, the European and American markets—despite a high degree of fragmentation—are relatively more liquid and transparent than many of their APAC counterparts, allowing trading desks to access liquidity and achieve best execution more seamlessly, across listed and OTC instruments.

By nature of its sheer breadth—APAC spans 11 time zones and 10 markets; there are easily dozens of nuances unique to the region that comprises a stark contrast between the listed and OTC world. It might therefore be naïve to assume that a fully homogeneous trading solution can cater to all aspects of trading pan-APAC. Be that as it may, let us for a moment indulge and try to break things down into a set of core issues that need to be addressed to try and form a solution that mirrors that of our peers on the other side of the world while addressing nuances particular to us.

The 3 Core Issues That Lie at The Heart of it All

Insight graphics – The 3 Core Issues That Lie at the Heart of It All – 1 – R2

Mirage of Liquidity: Depending on the instrument, a trader could find herself at a crossroads leading to various execution venues—all offering competitive spreads. The further one goes to a given venue, the quicker they might find that the liquidity disappears, forcing them onto another venue with quite possibly the same or similar outcome. Each round trip, of course, adds to the overall cost of execution. This holds true across listed and OTC instruments with the silver lining being that the issue is less prominent in developed APAC markets as opposed to emerging ones.

Quality of Execution: The above point on liquidity necessarily adds pressure on the quality of execution; regardless of the choice of venue, one must carefully select and analyze modes of entry. While different algos offer different levels of flexibility to best suit a particular type of trading behavior, one must realize that all other participants are likely using same or similar algos and hence what may have been perceived as an advantage, is little more than a prerequisite. Adding to the complexity in APAC is the prominence of voice-based trading in emerging markets, where the lack of choice around execution venue makes it increasingly difficult to execute orders without causing adverse market impact.

Lack of Consistent Post-Trade Analysis: While traders in listed markets have long relied on benchmarks to measure their performance, this concept is relatively new to the OTC world. The inherent complexity brought by a lack of transparency in the market makes it difficult to create benchmarks to accurately and consistently measure execution costs. Even if one manages to settle on a reasonable set of benchmarks, the yardstick is significantly different between listed and OTC world making it harder to evaluate the desk’s performance coherently and consistently.

The Market Needs an EMS with 3 Crucial Traits

Insight graphics – The Market Needs an EMS with 3 Crucial Traits – 1 – R3

With the above landscape as our backdrop, it should be no surprise that buy-side traders require sophisticated and powerful tools that can help them navigate these challenges head-on while remaining compliant with a variety of complex operational and regulatory requirements. When we step back and analyze what is required of such a platform, a clear picture emerges.

Integrated: The EMS needs to offer full integration to multiple OMS with an ability to dynamically communicate with supporting third-party applications for analytics, compliance, and downstream trade processing. The system needs to be fueled by multiple streams of data both static and in real time and must have the ability to use different sources of data for different situations. It must offer connectivity not only to all brokers, but also to alternative pools of liquidity including crossing networks, ECNs, Dark Pools, broker IOIs, direct bank connections, and more.

Automated: The EMS must be able to analyze active orders in prevailing market conditions and offer decision support on how to optimally execute them. The system should be able to analyze a set of orders against a variety of different lenses (order size, available liquidity, market conditions, PM instructions—to name a few) and determine which among them are suitable for an automated style of execution. Automation can be either off-the-rack (such as via an Algo Wheel) or a more bespoke process informed by Post Trade TCA data for the specific instrument, with an ability to mimic the behavior of a human trader so as not to be easily gamed. If possible, automation should be applicable across asset classes with the flexibility of taking in market-specific inputs and adapting execution destinations depending on the situation (brokers, ECNs, venues, or a combination). The intelligence, when applied judiciously, should “clear out the noise” so that the trader can focus on more complex, less liquid orders that require careful discretion and finesse that only a human trader can bring.

Customized: The two points above would look different for different individuals, let alone contrasting firms, and thus at the heart of what’s required most is customization. In this way, today’s best-of-breed EMS should not be thought of as an “off-the-rack” suit, which is often ill-fitting. Rather, it should be considered a beautifully-crafted bespoke suit, tailored to the body of the person wearing it—making it just the right fit for the individual.


To sum things up, with trading desks continuing the trend of consolidation, they are striving to find a trading solution that’s both fit-for-purpose for today’s challenges, but flexible and nimble enough to meet future needs as the markets we trade and how we trade them continue to evolve as a response to geopolitics, regulations, and opportunities. We are only at the tip of the iceberg for finding ways to apply Artificial Intelligence, Machine Learning, and Natural Language Processing to the trading desk and one imagines that it won’t take long for whatever we define as cutting edge today, to become obsolete tomorrow. So whatever technology path we chose, we should choose one on the basis that it allows us to be nimble enough to adapt to market changes and flexible enough to adapt future innovations into existing processes.

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Manu Sharma

Head of Trading Sales, APAC

Mr. Manu Sharma is the Trading Solutions Head of APAC Sales at FactSet. In this role, he is responsible for growing the Electronic Trading franchise for FactSet throughout the region. Mr. Sharma brings 12 years of industry experience to the role, which promoted the best practices of multi-asset electronic trading for Bloomberg. During his tenure, he successfully advanced the electronification of complex trading workflows across numerous markets in the region, capturing market share for their multi-asset class trading solutions. Mr. Sharma earned a Master of Science in Global Finance from New York University.


The information contained in this article is not investment advice. FactSet does not endorse or recommend any investments and assumes no liability for any consequence relating directly or indirectly to any action or inaction taken based on the information contained in this article.