Anyone trading small and mid caps quickly discovers that unless you have an almost infinite trade time horizon, low touch algorithms on their own just don't work. Low touch algos may be fine for large liquid names, but for small/mid caps the key to efficient execution is also having a flexible high touch strategy in the toolbox.
High touch strategy
A crucial element of this flexibility is how such a strategy can
be adjusted to respond automatically to the appearance of a
desired size of stock in the order book. Assume a trader has a
20,000 share buy order to fill and only wants to sweep the book
if a minimum of 300 shares are actually displayed. If that
trigger quantity of stock appears, the response to the
opportunity obviously needs to be tailored to the trader's
requirements in terms of time and price sensitivity.
At the more passive end of the spectrum, the strategy needs to be able to "under fire" and sweep less than the full displayed amount, thereby nibbling discreetly at the visible volume. By not taking out all the visible stock there is the potential to attract in more liquidity at the same price, as the initial undersized sweep may be interpreted by other participants as being a small retail order. At the aggressive end of the spectrum, the trader in a hurry could set the strategy to "over fire". This would take more than the displayed amount and probe the reserve on exchanges/ECNs, as well as accessing dark pools. Finally, in the middle, lies a neutral setting where just the trigger amount is taken. In all cases, to avoid detection and the risk of being gamed, the facility to randomly vary the percentage of over/under firing within user-defined ranges is essential.
An algo alone is not enough
To somebody accustomed to trading large caps, this might seem
over-complicated - why not just turn on an algo and leave it? But
that approach ignores the fact that opportunities to execute in
many mid/small cap names are typically transient. This makes the
sole use of a conventional algorithm impractical. The sporadic
nature of the data for these names makes it almost impossible for
an algorithm alone to automatically detect whether a stock should
be over or under fired, which is key to successful execution in
small/mid caps. Any attempt to hard code that logic would result
in an algorithm that would be almost immediately obsolete and/or
would require continual retuning.
Another obvious element in the execution process is price/liquidity sensitivity. Any tool for executing mid/small caps has to allow the user to select (and switch between) price, where only a desired price level is swept so as to seek to minimise impact, and liquidity, where multiple price levels (up/down to the limit) are swept to maximise liquidity extraction.
Mid touch workflow
One of the main challenges of executing small/mid caps is
workflow management. Position sizes are likely to be smaller but
more numerous, which creates all sorts of issues around
prioritisation. Therefore any EMS TCA tools have to be able to
quickly prioritise the initial trade list, which will allow the
high touch strategy to be deployed to best advantage. While an
algorithm alone is unsuitable for mid/low cap trades, there is no
reason why the high touch strategy cannot be combined with a low
touch algorithm to produce a 'mid touch' execution strategy that
delivers the best of both worlds.
For example, the trader could set up a participation algo at a low percentage participation rate and leave that ticking along in the background. Then overlay this with the high touch strategy already outlined. When liquidity opportunities appear in a particular name, the trader can activate the high touch strategy, adjusting the settings as desired on the fly.
However, there are two critical caveats to this mid touch strategy - interaction and ergonomics. Unless there is a smart link between the volume in the algo and the executions from the high touch strategy, the algorithm will not recalculate intelligently in response to the completed high touch trades - to say nothing of the risk of over-trading. In addition, the overhead of having to monitor two systems negates any workflow benefit. It is therefore vital that the technology is capable of decrementing any volume traded in the high touch strategy from the volume left in the low touch algo.
With a flexible high touch strategy, flexibility without sound ergonomics equals poor execution workflow and increased error risk. On the one hand, the high touch strategy needs a screen configuration and controls that require the absolute minimum number of clicks/keystrokes to adjust strategy settings as fast as possible. On the other, there needs to be an alert mechanism that allows the trader to fire up the high touch strategy quickly if a possible opportunity is flagged (e.g. a spike in a stock's option volume).
While the sporadic nature of mid/small cap liquidity makes it difficult to tune conventional algos in a stable manner, the human trader can still learn a lot from how and where their strategy executes. Therefore any EMS used to implement a mid touch strategy needs to be able to provide a detailed historical narrative of the trading process - what was sent where and when, what filled, what didn't - and so on. This feedback loop assists in future trade prioritisation and also in setting appropriate alerts on particular stocks that will trigger the high touch strategy.
A mid touch strategy offers the trader several opportunities. Workflow can be streamlined to increase productivity and reduce the risk of errors. The combination of two diverse strategies allows gradual background stock accumulation/disposal to be boosted by a more flexible and opportunistic trading strategy. The net result is a trading process that may provide a combination of price improvement and faster trade completion.