Analysing The Cost Of FX Trades
With Daniel Chambers, Head of Trading, Sequoia Capital Fund Management
Sequoia Capital Fund Management (SCFM) is an alternative investment management company specialising in investing via quantitative strategies and returned 13% in 2015 net of fees. Since going live in June 2011, SCFM has managed to provide an average monthly net return of 0.71%.
The decision to execute entirely through electronic trading was a natural one to make as it is in keeping with SCFM’s ethos of implementing technology to increase productivity. SCFM has always traded electronically, with varying degrees of sophistication. Two of the main drivers for this decision were the reduced risk of errors during execution and increased efficiency. SCFM executes all orders in the market electronically throughout the European liquid trading hours. Although FX is a 24-hour market, liquidity is not equally distributed throughout. A look at the daily profile of spreads in the vast majority of pairs highlights how much more one can expect to pay to execute overnight relative to in the middle of the European trading day. This is certainly a consideration that needs to be made with volume constraints measured against a trading day that is not 24 hours long.
Trades are executed by sending orders via FIX to an aggregator and receiving the information for each clip also via FIX. The trades are sent to the prime broker and matched immediately. As well as matching with the PB, the trades are also matched against the initial ticket to ensure execution took place as expected. All of the processes are automated. Once the trades have been matched, it is possible to view information related to the trading session such as execution costs and share of flow per liquidity provider. This systematic, straight through process is essential when executing multiple times per day in a large number of crosses. The FIX protocol makes the whole process easier and enables us to execute in this fashion and to retrieve all relevant information for analysis conveniently. The orders are placed in the market with the intention of creating as little market impact as possible. A conscious decision was made to execute only with banks, and specifically the large institutions, as opposed to ECNs and other third-party vendors. This provides a level of anonymity when executing. There are undoubtedly other participants with whom we could trade on an ECN, but a direct relationship with the LPs supports communication and assists in reducing market impact. In our opinion, executing with enough liquidity providers directly enables the client to receive the best of both worlds; greater anonymity and diverse flow with extremely tight spreads and great depth.
Improving the steps needed for execution is an ongoing process to ensure all measures are being taken to ensure the most secure and efficient methods are being implemented. The back office/operations systems were prototyped by people with relevant business knowledge. This facilitated us being able to create something effective in a short period of time.
A significant amount of work has been carried out to quantify, analyse and understand the various components of our execution costs and how they might be reduced. Costs are measured against various benchmarks, including arrival and risk transfer price. Over the last few years there appears to have been less liquidity available in the G10 space. Particularly difficult have been the Scandinavian pairs, which have been noted to be behaving like emerging market currencies. Building our capability to drill down into each cross and its various cost components has revealed the most useful information. Deep examination highlights information not available through superficial analysis. Although a lot of what has been revealed is in line with what one might expect, such as EURUSD and USDJPY being cheap to trade, there are other very interesting observations to be made such as discovering if trading EURNOK, EURSEK is more cost efficient than going for the NOKSEK directly. Much of the knowledge gleaned leads to enhancements in execution algorithms. We approach it as a four-part process including:
- Collect – What data can be collected and stored?
- Calculate – What information can be derived from the data?
- Input – How can that then be used in any part of your execution strategy?
- Monitor – How to monitor and quantify the changes made?
This segregation of the different components involved, each with their own elements, allows clear and precise planning for how to implement change.
Trade Cost Analysis is a concept that has been around for a while and we have seen a shift from post-trade cost analysis to pre-trade cost calculation or estimation. The ability to determine the optimal time to take executing an order is a progression from simply measuring incurred costs. Typically used for these estimates are factors such as current volume relative to averages and volatility. The nature of financial markets would suggest that on any individual execution, you’re not guaranteed to be right in your estimation, but over time and with enough observations the estimates should be correct within a margin for error. Being able to store and compare estimated versus incurred is vital to improving confidence in estimates.
With China’s circuit breakers active twice in the first four days of trading this year and crude close to $30 per barrel, the theme this year appears to be uncertainty. In a period where the Federal Reserve have recently raised rates for the first time in seven years, more and more emphasis is put on what comes out of the central bank’s meetings in terms of pace of subsequent actions going forward. Other central banks have proved in the last year that they are willing to shock the market with unexpected decisions if seen as being in their best interest and we’d expect this to be the case going forward. The increased volatility impacts all participants executing in the markets and their execution methodology needs to be able to adapt to the environment.