With Scott Kurland, Managing Director, Head of Platform Solutions, ITG and Jim Cochrane, Director, Senior Product Manager, ITG TCA for FX.
The electronification and improvement of FX workflows entered a new phase with the advent of aggregators and algorithmic trading, but challenges still remain.
Deciding where to manage that workflow, from blocking and netting to allocation functions, is increasingly complicated because firms must first determine when and how to pass some of that information downstream to third party vendors. Should they pass it from the order management system (OMS) via the execution management system (EMS) or a series of third party platforms?
Today, netting across currency pairs is often calculated in the OMS in order to minimize transaction exposure. However, we are starting to see that functionality move into the EMS, which can offer more flexibility in advanced netting and trade block formation. This upgrade in FX workflows will require the EMS to receive and interpret account and trading counterparty restriction information passed from the OMS.
The second area of workflow improvement relates to FX benchmarking and execution transparency – specifically pre-trade analytics that can help drive decisions as to when, where and how to best trade FX.
Considerable development has occurred over the past three years in pre-trade technology and pre-trade analytics, which has been made possible through the wider availability and aggregation of FX pricing and custodial data. However challenges still remain in deciphering ‘What is tradable?’ versus ‘What is shadow liquidity?’
New pre-trade FX analytics can help a trader determine expected slippage of a currency transaction based upon the method of execution and time of day traded. What we have done at ITG is cull, arrange and analyse the data en-mass in order to build a range of pre-trade tools for 38 currency pairs. We collect and store over 125 million tradable quotes daily in order to create expected volatility and spread distributions as well as cost curves in the FX market. These cost curves are used to predict slippage under normal market conditions. The volatility and spread distributions help the trader define “normal”.
This next generation of pre-trade analytic tools will provide FX traders with the ability to manage their FX transactions more actively on an expected cost basis, and in turn make more informed decisions as to where, when, how and what size FX trades to execute. For example, a trader can place a Request-For-Stream (RFS) to buy $50 million of GBP/USD and receive real-time streaming quotes back from multiple bank liquidity providers. He can simultaneously compare these to pre-trade cost estimates for this particular currency pair and size, as well as view ECN prices via a consolidated order book. This allows him to determine whether to route the trade to an ECN, trade with one of the RFS bank counterparties, or wait to trade the same or larger block size at a later time of day, when more favourable pricing might be available.
As in equities markets, pre-trade tools provide decision support; through the concept of creating referenceable price and liquidity data around volatility, volume and the type of currency pair being traded.
Concurrent with the new analytics, referenceable prices and liquidity sources for trading FX, PMs and traders are also being pressured to move towards a more active approach for trading FX. Additionally, institutional investors are now asking their managers to demonstrate best execution for FX trades to ensure unnecessary slippage isn’t occurring after the equity trade has been completed.
As such, buy-side firms are beginning to re-evaluate whether they should use the same bank historically; do they go to the bank with the best immediate price, the custodian where the equity position is held, or do they execute on a DMA basis with an ECN?
These are the same types of best-execution decisions that are currently being made in the equity markets. Arming the buy-side with similar tools and liquidity access for FX trading will help them adopt the same best practices for FX as they utilise for equity trading.
The challenge of gathering comprehensive, accurate data with reliable time stamps has been solved with the arrival of FX aggregation tools and the new openness found in the FX market. The benchmarks that ITG generates allow asset managers to estimate the value of their foreign exchange flows with greater confidence, measure implementation shortfall and provide a holistic view of their currency trading across several constituent groups in their organization. Compliance and “best execution” measures are merely the beginning. Our goal is to assist asset managers in driving transaction costs towards zero optimize their FX flows within a multi-asset trading dimension.
One area still needing significant study is in the matching of an equity trade or any underlying asset with the corresponding foreign exchange transaction. Should a buy-side firm hedge each equity transaction in real or near-real-time with a corresponding FX trade, or is there more benefit to waiting until a significant volume of equity trades have been completed before putting up the FX trade? Does the trader fair better in smaller size FX trades throughout the day, or a larger FX transaction at the end of the day?
The electronification of equity and FX trading combined with a series of FIX time-stamps will help us build better audit trails and collect more data to drive this analysis over time, tracing trades from PM idea generation and order creation all the way through to execution.
Better benchmark data in turn will enable traders to defend or re-evaluate their FX trading strategy to institutional investors, similar to how they do for equities today.
The driving forces
We are beginning to see a switch in mindset relating to market structure and the move from passive to more active FX trading. To the extent that the emerging best execution responsibility falls to the institutional equity trader, we expect to see a natural push of the FX markets towards an equity-like market structure.
At the same time, advances in technology are enabling this transformation to happen more organically; the electronification of FX transactions from OMS through EMS to liquidity providers, all the way through allocation and settlement processing, is happening.
Traditionally, each part of the buy-side trading desk has had a different view of the foreign exchange markets. The equity trader spent so much time on their equity transactions that the foreign exchange transaction was either given to a custodian or handed to the back office. This mindset is changing – equity traders are getting accustomed to the idea that they need to give more thought to how the foreign exchange transaction occurs because significant alpha can be lost on the subsequent foreign exchange transaction if not handled properly. FX TCA tools, as mentioned earlier, have been helping the buy-side quantify this loss and provide guidance on steps that can be taken to improve alpha preservation on the FX component.
Last but not least, one of the main drivers behind the focus on FX best execution is now regulation. The FX market is being more tightly controlled by the regulators and the industry is demanding and shaping more defined benchmarks to be held accountable to. This has led to greater pressure on the buy-side from their clients to ensure that best execution tactics are being put into practice.
As the markets, electronic trading tools and venues continue to evolve, we expect to see more FX flow shift to a direct access model by the customer without as much bank intermediation, especially for smaller block trades executed in conjunction with corresponding equity transactions. This should also lead to increased adoption of algorithmic trading and ECN usage for spot trading, as well as the use of FX prime brokers and aggregators. For larger block transactions, we expect to see an increase in multi-bank Request-For-Stream (RFS) trading in order to keep traditional bank liquidity providers in check.
Just as the industry witnessed with the evolution of the equity markets, as the buy-side takes on a more proactive approach to managing FX transactions, they will demand increased transparency with their liquidity providers, and referenceable prices.
Good data will ultimately drive analytics and lead to better trading. This will enable firms to act as their own watchdog, monitoring performance, alpha preservation or slippage, and keeping liquidity providers in check.
It’s an interesting dynamic that should evolve over time, driven by increased regulatory scrutiny, better referenceable benchmarks, pricing and execution data, and a convergence of equity and FX trading on the buy-side desk. These trends, coupled with improved market transparency and analytics, will help the buy-side develop a cohesive structure for calculating the true cost of their FX transactions, and ultimately driving down the total cost of execution.
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