The convergence of structure and behaviors of the equities and FX markets presents opportunities for those firms that identify them and can focus on how best to exploit them. At the heart of what’s needed is a cross-asset trading system that incorporates the same functionality components across both asset classes while still supporting the asset-class-specific logic.
But what are the key elements of design required of trading systems that can address equally the needs and nuances of both asset classes and their constituent instrument and product sets?
Three key components provide the base level of capabilities that can form the foundation of a trading system that meets the needs across both FX and equities:
1. Market connectivity with built-in pre-trade risk controls
2. Client execution and hedging algorithms with associated transaction cost analysis (TCA)
3. Pricing and market-making logic
Because the core venues of global FX and equity markets largely do not share hosting facilities, firms using low-latency connections to pursue high frequency trading strategies will enjoy few opportunities to share colocation, data feed and feedhandler infrastructure across both asset classes.
Rather, firms active in both markets are much more likely to be able to take advantage of both markets’ embrace of FIX connectivity. Although flow FX trading venues and FX liquidity providers have historically used proprietary APIs, FIX connectivity has become the industry standard for both venues and their participants, both in standard FIX formats and the lower-latency, smaller-bandwidth simple binary encoding (SBE) format.
This shift away from proprietary APIs to FIX was remarkably fast in FX, compared with other market segments, driven by adoption by both trading venues seeking efficiencies, and buy-side firms’ increasing propensity to invest in their own execution management systems (EMSs) and resultant awareness of connectivity costs.
At the same time, the similarities between FX and equities – in terms of both market structure and matching methodologies – the pre-trade risk controls required for both markets have become largely aligned.
Aligning pre-trade risk controls based on order type or matching methodology offers greater consistency than categorising by asset class. This means that it’s no long necessary to implement and maintain separate pre-trade risk management tools for each asset class within a multi-asset class trading system, allowing a single platform to be shared across both equities and FX trading.
Those seeking to explore how to exploit the commonalities between FX and equities markets are also helped by the fact that client execution and hedging algorithms available for cross-asset trading systems do very similar things. Well known algorithms like volume-weighted average price (VWAP), time-weighted average price (TWAP), icebergs and implementation shortfall are applicable to both FX and equities markets.
Similarly, transaction cost analysis (TCA) methodologies applicable to both FX and equities are often differentiated only by the data sources and reference data they draw upon. TCA structures based on pre-trade data analysis, cost and risk estimation, and optimization techniques are equally applicable to both markets.
Finally, pricing and market-making logic are key determinants. While pricing models for FX and equity instruments differ significantly, particularly in the derivatives space, firms operating in both markets can benefit from consolidating their pricing engines. For instance, pricing engines with the ability to price equities derivatives typically meet all the prerequisites for FX price-making, having similar needs for high-level computational resource and similar data pre-requisites.
These differences in pricing models are, from the perspective of the trading desk, concealed behind similar work flows for client price determination and distribution across both the FX and equities markets. In equities derivatives, firms must quote on a multitude of instruments simultaneously, all of which have the same underlying instrument. In FX, the specifics of credit and settlement risk for each client result in a multitude of prices for the same underlying instrument.
Factors driving order flow can apply equally to equities and FX with implications for trading system design. Where pricing drives trade flow – for instance, where market-makers quote a price or continuous prices based on their counterparty’s request to do so – the shared challenges include moving from a core price to a client-specific price, creating a quote as part of RFQ, request for stream (RFS) or request for market (RFM) requests and the considerations relevant for determining the longevity of any given price. Or else, in markets where trade flow derives from firm orders, executing firms need to be able to push client orders onto a platform, and decide at what point to commit to the trade.
Market-makers are further challenged by the need to protect their franchises. As part of this, they need to ensure that their quoting obligations do not expose them to unnecessary risk. As FX and equities markets converge, market-makers’ approaches across these asset classes become similar.
As FX prices firm up – as the use of last look falls out of favour – the validation logic more strongly resembles that used for equities derivatives, wherein orders and quotes are firm. FX market-makers need to ensure that they are as proficient in sending out good prices for currencies trades as they are for equity derivatives.
To realize these synergies, the speed of the markets requires that firms use automated protection logic. While there is no universally accepted approach, the key considerations here are:
These design elements and considerations apply to both FX and equity markets. Firms seeking to take advantage of the ongoing convergence of these asset classes can therefore benefit from taking them into account when designing and implementing trading systems for use across both instrument sets.
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