Transparency around dark pool trading has been low: the terminology has been indecipherable, profits have surged and corruption has been the main stage headliner. Coming to grips with how a wide range of securities are traded is already a complex process, without having to comprehend the activity in the financial shadows.
Dark pools are nothing new, neither are the incentives for the public to recognise how they work or what purpose they serve. A pension that delivers its payments (ones made over time) after retirement on time and on value, leaves little drive to understand its journey. Yet pensions are being put at unnecessary risk because of the growth of dark pools.
There are many questions that surround their existence, but few answers are ever heard. A good way of understanding them is to imagine a bread market as an open pool. The bread market pools buyers and sellers together in the open market for everyone to see and participate in. However, say a bread merchant is overloaded with stock and needs to offload it into the market. The stockpile is too large to sell it in the market at one time, so it has to be sold in blocks. Yet every time these blocks are sold in the open market, the price of bread consequently decreases due to the increased supply in the market.
Enter the Dark Pools
Creating a private market place where specific buyers and sellers can trade without the eye of the open market eliminates the price volatility of big orders. The practice is perfectly legal and contrary to belief, well regulated. Furthermore, it can be argued that dark pools promote better trading practices, due to participants not needing to bend rules to hide orders. However, dark pools could become too canny for their own good.
Fintech has shown it is the way forward in creating a fast, profitable and efficient trading environment. Though what it has also done is widen the gap of trust between the financial sector and its onlookers. An already fractured relationship is cracking at the same rate of increased algorithm speeds. As the system gets faster, education of how it works gets slower.
The dilemma with Dark pools is that they are putting pensions funds at greater risk than they should. With any effective system comes a mischievous opportunity. Commanding algorithms present this chance by setting coded orders charged with completing a specific task. Funds are therefore vulnerable to a wide range of techniques used by HFT (High-frequency trading) firms to sabotage a pension fund’s trading activity.
There is a misconception that the trading of financial securities is recognised by many as a place where risk thrives. But in reality, the sector has a distaste for risk.
The Rise of Latency Arbitrage and Front Running
Using the bread market example can illustrate how this works. Firstly one needs to envision five bread markets in different locations with different prices. Say a buyer wanted to make a bulk order, and in line with making it attainable, they would need to buy from different locations at the same time. Yet it takes time to get to these locations. This leaves a favourable circumstance for an opportunist, who has heard of their intentions. If the spectator were to get to the locations before the buyer and buy up the resources, they would then be able to sell it to the buyer when he/she arrives, at a higher price.
This risk-free manoeuvre is using latency arbitrage to ‘Front Run’. In reality, this is all achieved by computerised algorithms racing each other. Firms and brokers eventually realised that it paid to be closer to exchanges.
Pension funds are effectively getting caught up in a game of cat and mouse. It is unclear the amount of pension funds targeted by latency arbitrage, but a Reuters report in 2016 showed the potential profits from LA trading are close to $3.3bn. There are also ways for predatory traders to be informed of activity in a dark pool by simply using ‘Pings’.
Latency Arbitrage and Pinging
Pinging involves creating small 100-share block trades that are sent out to learn about hidden trades in the pool. Once a firm gets a ‘ping’, it alerts them there is a large trade out there, which they can then use to their advantage. These trading methods are creating a dangerous precedent for what is to come.
The infamous flash crash of 2010 was a warning of how millions of algorithms can get tangled in one another, causing a devastating outcome. In just 20 minutes, 2bn shares worth $56bn had changed hands. Fortunately the market rapidly regained its composure. Nevertheless, a second shock to the market might not be so easy to recover from. Furthermore, one of the remarkable stories to come out of the crash was the lack of stories. There was an emphasis in the industry, to lay the event to bed.
A brisk investigation led to a few explanations. Outside the spectacle, there was suspicion and a disorientated feeling. If the scholars on the 35th floors where bemused by the events unfolding, there was likely little hope of observers knowing what materialised. It would be evident to blame dark pools for a crash that was a mix of big orders and badly timed algorithms, yet some argue that the uncertainty goes past them.
Algorithmic trading wont be leaving the financial industry anytime soon, but slowing the growth of dark pools could limit it. Earlier this year the (Investment instruments) EU regulator MIFID introduced strict new rules that firms in dark pools would have to adhere to, if they wanted to carry on befitting from the pools.
The MIFID plans to cap a stock from trading in a dark pool, once it accounts for more than 8% of the trading volume in the company. If this threshold were to be breach, there would be a minimum 6 month ban from dark pool trading.
Examining the current figures and trading volumes (from Rosenblatt Securities Inc) in dark pools, shows that more than 90% of the UK’s FTSE 100 companies would be unable to trade in dark pools if the cap were implemented tomorrow.
Regulating the pools, will help push more trading volume onto public exchange markets, which will benefit the fight for transparency within the industry. Yet, there is still an immense lack of informative data on what financial intermediates do in dark pools and where pension funds are traded.
What we are potentially seeing is how innovation has moved faster than our understanding of it. This has put pension funds at risk of becoming victims to this financial structure. It is also making it challenging to inform and educate on the industry’s proceedings. Without a new solution, an already cracking relationship will eventually meet its end.