Industry viewpoint : Frank D’Erasmo

BETTER EXECUTION.

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Frank D’Erasmo, Head of Algorithmic Trading, Global Futures and North America Cash Equities, Societe Generale Prime Services.

Finding liquidity remains increasingly challenging which is why buyside firms are looking for new tools and strategies to achieve best execution. The growth and sophistication of venue analysis and algorithms are a direct result of the many differing factors influencing liquidity issues prevalent and growing in both cash equity and futures markets.

These views are borne out by a TABB Group study – Institutional Equity Trading: Crossroads of Best Execution – published June 2015. About 74% noted that while trade size was important when evaluating dark pool executions, other components including liquidity, price, fill ratio, slippage and natural flow were also crucial components.

Additionally, more than half of respondents placed greater emphasis on execution quality, stressing sourcing liquidity and routing, as well as highlighting venue analysis. The study noted that buyside firms no longer just wanted to know what happened to an individual order but also whether there were any steps that should have been taken to attain better execution and an optimal alignment with the portfolio manager’s intent. Other areas earmarked in need of further work included information on trading counterparts, algo behaviour and routing logic, and uniform standards and metrics.

With a long established pedigree in developing bespoke and liquidity-seeking algos for both dark and lit venues as well as non-equity, Societe Generale has led industry thinking with the bank’s creation of its Algo Factory. The Algo Factory does detailed analysis on the microstructure of global cash equity and global futures markets to calibrate their algorithmic trading platforms and transaction cost analysis to meet these liquidity nuances.

Following a recent study, Societe Generale has introduced two new quality execution measurements, which aim to enable smarter order handling practices and improved execution quality across its algo suite. The first metric is an “all in trading cost” measurement, which calculates the weighted average cost between realised slippage and opportunity cost. It provides a consistent, correlated comparison of true transaction cost across various dark platforms. The second – “flat fill” – adds greater transparency to dark venue selection instead of the commonly used industry dot measurement. The metric defines good quality executions based on market volatility and momentum adjusted time weighted average midpoint.

Societe Generale put the two metrics through their paces and used them to analyse the liquidity across various US dark pools. Based on client transaction orders of SG America’s algorithms from March to July 2015 they show the need to link the venue selection with the parent order objectives and stock profiles. For passive full day or small orders algos may send to destinations with low all-in-cost while for larger orders, they should either be directed to venues with a high percentage of flat fill, or overweight those with high fill rates based on urgency to complete.

Some of the issues though are not only the domain of the equities world. Liquidity has become a major concern in the fixed income space. Stricter regulations such as Basel III are taking their toll as banks that are in the midst of changing their business models to adapt to legislation that requires them to hold more capital against losses. This has exacerbated price moves in several fixed income markets, even the generally safe and steady areas such as top-rated government bonds.

Take US Treasuries, which are considered the bedrock of global finance with around $12.6tn of debt outstanding, and roughly over $500bn changing hands every day. Figures from the Federal Reserve show that primary dealer holdings of high-grade debt, including treasuries, mortgage-backed securities and corporate bonds has dropped from $524bn at the end of 2007 to $170bn today.

There are similar concerns in the European markets as underscored by a recent, semi-annual joint report on risks and vulnerabilities in the European financial system published by three of the most powerful regulators – the European Securities and Markets Authority, the European Banking Authority and the European Insurance and Occupational Pensions Authority. They noted that liquidity had been “affected by structural changes, potentially including regulatory reforms in the post-crisis period”

For example, earlier in 2015, the yield on benchmark 10-year German Bunds soared a full percentage point in just two months after trading at a record low, close to zero, in mid-April. Not surprisingly, these trends have had an impact on the futures markets. A review undertaken by our Algo Factory shows that US 10 Year Notes, Euro Bunds, E-mini-S&P and Euro Stoxx 50 have all suffered a reduction in order book sizes since last year. This makes it difficult to execute large orders and forces traders to exert more caution when lifting the liquidity aggressively.

The review recommends futures algos that are calibrated to the unique structure of each individual exchange and instrument as an alternative solution to combat increasing transaction cost. These algos determine the optimal time for order placement that will cause the least amount of price impact, thereby delivering highly predictable and superior performance. Societe Generale also provides post trade analysis that explains how the algos performed when handling an order. Performance metrics dissect how the “parent” algo delivered as well as the individual “child” slices entering the market.

Led by the creation of its Algo Factory, Societe Generale has been at the forefront of developing innovative and liquidity-seeking algos for trading equity and non-equity instruments for both dark and lit venues. A global team of quants, engineers and developers across its four main regional trading hubs conducts microstructure research into the underlying trends driving the markets as well as developing algos to meet clients’ specific needs.

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