We fire a bunch of questions at Berenberg’s global head of electronic trading and distribution to get a heads up on the lack of European liquidity in European markets, how algos are evolving in response – and why collaboration is key.
What is the state of the liquidity landscape in Europe in 2024?
In short, concerning. There are numerous macroeconomic factors affecting both the attractiveness and competitiveness of capital markets in Europe. At the forefront, a lack of on-exchange liquidity, in part due to increased internalisation and the usage of bilateral liquidity arrangements, is having a significant impact on liquidity discovery and price formation. While these arrangements satisfy approximately 20% of the buy-side’s liquidity needs, the unintended consequences on the remaining 80% is increased trade implementation costs. While it may be naïve to expect altruism, perhaps it’s time for all participants – buy-side, sell-side, and exchanges – to acknowledge that we may very well be the creators of the problems we are trying to solve.
It also begs the question of whether disintermediation, where liquidity providers interact directly with buy-side firms bilaterally, is a net benefit to investors or disproportionally contributes to a decline in accessible liquidity in multilateral venues resulting in increased trading costs. Collaboration on future innovations should aim at providing long term sustainable liquidity channels which can be accessed by all market participants in a manner that promotes the growth of Europe’s capital markets.
Industry standards for algo development – where next?
Algorithmic innovation continues to be contingent on broker and algo selection being meritocratic. Meritocracy incentivises brokers to compete with one another to build cutting edge solutions for the buy-side. An ecosystem whereby commissions get concentrated to a handful of brokers will only reduce the number of participants, and along with it the technology investment.
The next phase of algorithmic development will focus less on providing specific out-of-the -box strategies, and more on a holistic understanding of client objectives and prevailing market dynamics to determine the optimal execution strategy. This will include automating the selection of multiple algorithmic strategies and tactical behaviours during an order’s lifecycle to achieve trading benchmarks. Enhanced signalling frameworks focused on using relativity and correlation to determine optimal price levels, continue to be a key area of differentiation.
Trading benchmarks – single or multi-factor analysis?
Adjusting for market conditions and trade difficulties remains crucial in establishing the effectiveness of algorithms in achieving trading benchmarks.
Whether its measuring VWAP as a % of spread or adjusting implementation shortfall (IS) performance for expected costs and broader market moves, accounting for these factors is critical to achieving consistency of outcomes over time. Separating broader market conditions and exogenous factors is a pre-requisite to accurately evaluate algorithmic and broker performance.
Top tips for traders
The lack of liquidity in European markets is leading to more pronounced signalling and greater market impact. Optimal lit participation rates in Europe have nearly halved over the last 12 months. It is very important that traders optimise their current liquidity seeking and participation-based strategies to account for these changes in the market microstructure.
Understanding timing risk and opportunity cost on low average daily volume (ADV) orders is pivotal to improving trade performance. Stretching smaller orders unnecessarily over the day can lead to wider standard deviations of performance, often resulting in smaller sets of underperforming orders disproportionately increasing benchmark slippage.
©Markets Media Europe 2024
