What new developments are you seeing in the algo space?
Algos have evolved immensely since program desk’s developed them to handle large volumes of orders and now they are even accessible to retail clients. In the institutional client space, the vanilla strategies have largely become commoditised and the algo suite providers seem to be focussed on improving their smart order routers and tweaking the non-vanilla algos that seek to mimic trader behaviours for the more complex orders – for example, scaling at the close or switching strategy when certain criteria are met. I am also seeing more work being done to avoid adverse selection, indicating that maybe not all block liquidity is good liquidity. Lastly, I think more algo providers are starting to use RFQ systems where they feel it can improve fill rate, while minimising price impact.
Where can algo wheels be used to better tap into alpha generating opportunities?
Algo wheels were originally developed for strategy selection, but uptake soon changed (possibly driven by regulatory concerns) to using them as a tool to absolve traders of broker selection, avoiding broker preferencing/trader bias. I am glad to see the trend is moving back towards strategy selection. They are a useful tool to handle the high volume/low ADV% orders allowing traders to focus on the orders where they can add more value. In order to generate alpha, maybe some portfolio manager profiling would be necessary but a large enough data set to analyse would be required.
What lessons can other asset classes take from equity algo wheels?
Other asset classes are embracing algos, but their market structures are so different from equities that I don’t think they will be using algo wheels to the same extent as in the equity world.
Has algo usage reached its maximum capacity or do you expect it to account for more volumes in the years to come?
Algos allow traders to handle vastly higher volumes than without and as such, I think they will continue to grow. I see traders using them more frequently for complex trades that would traditionally have gone to a high touch desk. For example, you no longer need a sales trader to access central risk book liquidity. They are constantly evolving and improving, which is a factor that you need to bear in mind when going down the customisation route – will your customised algo get upgraded at the same time as the non-customised algos? Also, all users, current and future, really need to know and understand what customisations have been made. I am seeing algo provider lists shrinking and stronger partnerships between users and providers being built.
What are some of the hurdles that algos face?
We are seeing growing retail participation in the markets, and it is very different from institutional flow with regards to the fact that it leads to higher volatility and price impact, together with relatively fast reversion and it is also largely inaccessible flow. It would be great if algo engines could factor this in and act accordingly, but it would be very useful to be alerted when retail participation is particularly high.
Recently we had a bank crisis, and trading styles often change during such events, often toward more risk averse strategies like VWAP. When this happens, liquidity seeking strategies may be less likely to find blocks, so the strategies need to be able to adapt to a fast changing liquidity landscape.