"Should you find yourself in a chronically leaking boat, energy devoted to changing vessels is likely to be more productive than energy devoted to patching leaks."
What actually is signalling risk and is it something I should be worried about? This article will seek to answer both of these questions. As a topic, signalling risk has become more widely talked about in the FX markets following the move to a more order driven market, and the increased adoption of the use of algos. As discussed in a previous article, there are benefits to using execution methods such as algos , although there are also associated potential drawbacks. Signalling risk is one of these drawbacks.
In essence, signalling risk is effectively telling the market what you are about to do, perhaps inadvertently, and is also referred to as information leakage. For example, in a penalty shoot-out, there are occasions when the penalty taker effectively informs the goalkeeper of the direction of his intended penalty, as witnessed in the recent Italy v Germany quarter-final at the European Championships. Providing this signal in advance clearly gave the goalkeeper an advantage, and greatly increased the potential for a negative result for the penalty taker.
Information leakage is already a major concern in equity markets, with some studies indicating that an institutional equity order in the US now needs to run at a participation rate of less than 3% in order to prevent detection, whereas this rate was as high as 33% in 2007. This is supported by a separate study by Credit Suisse, which showed that VWAP performance starts to deteriorate when the participation rate starts to exceed 5%. As with a number of market structure issues, the equity markets can be a leading indicator of future developments within the FX markets, and signalling risk is no exception.
When executing an order over a period of time, such as via an algo, there is always the chance that signals to other market participants are provided before the algo is fully completed. Within FX, a good example of this risk is through the use of some algo types during the expanded 5-minute window for the WMR Fix. A paper published in April this year by Pragma highlighted this behaviour, where the authors found that ‘the rate change during the first minute of the window predicts a continuing rate change in the same direction over the subsequent minutes of the window’. Furthermore, they found that this behaviour was exacerbated at month and quarter ends. Such a pattern is potentially easy to detect and therefore allow other market participants to benefit from this knowledge.
Information leakage is not just a concern for those using algos over the WMR window. As liquidity has become more fragmented, and the depth of order books have become generally thinner, it has become easier for patterns in orders to be identified throughout the trading day. The increasing use of direct market access (DMA) via the use of smart order routers provided by liquidity providers and agency brokers contributes to the concerns as placing any order, especially if done naïvely or simplistically, can result in information leakage. How does this leakage contribute to a negative result to the original client order? Well, it is manifested within higher implicit costs through increased slippage. In order to demonstrate best execution, it is becoming increasingly important to take such factors into account when deciding how to execute.
Regulators are becoming increasingly concerned about the compliance risks posed by signalling, since signalling in effect invites front running and may lead to poor client outcomes and even market disruptions including liquidity air pockets and flash crashes. Such events impact market integrity and harm the reputation of our financial markets. Accordingly, where firms ignore the signalling risk posed by their algorithmic offerings or other execution methodologies, they may face claims for failure to pay due regard to interests of customers and/or failure to meet best execution requirements, especially where such signalling impacts client outcomes. (See, e.g., FCA Principles for Business 6: ‘a firm must pay due regard to the interests of its customers and treat them fairly’). In cases where signalling leads to market disruption, more fundamental claims such as failure to maintain orderly markets may be levelled.
So what can be done about it? Simply deciding not to use order based execution is probably not the answer as such execution methods can contribute to significant cost savings as previously discussed, and therefore should form part of menu within a best execution policy. However, it is a risk that should be considered in such a policy and process, and the first stage in any form of risk management is measurement. Measuring actual signalling risk is obviously extremely difficult as it is not possible to isolate exactly what the response of the market is to any specific execution. In physics this is referred to as the ‘observer effect’, in which measurements of certain systems cannot be made without affecting the systems (exemplified by Heisenberg’s Uncertainty Principle). In the same way, it is difficult to know with precision exactly what the market would have done without your trade participating in it.
However, it is possible to produce metrics which indicate the potential signalling risk that an order may have created, and hence, how easy or not it would have been to read by potentially predatory market participants. The key here is to compare apples and apples and use the same metrics, computed in exactly the same way, to allow fair comparisons across order types and providers. BestX have developed unique measures for this purpose, which allow users to compare the relative signalling risk across different order types. These metrics form part of the best execution suite within the BestX Post-Trade application, and use of such measures over time will allow users to mitigate the risk of information leakage. If a particular venue, or algo, consistently produces relatively high signalling risk in a given currency pair when analysed over a statistically large sample size, then informed decisions can be made, and justified, to alter execution choices and decisions.
As Warren notes at the beginning of the article, it is probably best to change vessel once you discover you are in a chronically leaking boat.
For further information on Signalling Risk and the available metrics, please contact BestX at firstname.lastname@example.org