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Anatomy of an Algo: Beer Necessities

Published in Automated Trader Magazine Issue 27 Q4 2012

When an unexpected news event lands right in the middle of a high ADV trade, most execution algorithms struggle to adapt strategy to the sudden change of circumstances. But as Brian Schwieger, head of EMEA Execution Services Sales and James Wardle, Vice President, Execution Services at Bank of America Merrill Lynch explain in this example trade from the brewing industry, there are exceptions to every rule.

Brian Schwieger

Brian Schwieger

James Wardle

James Wardle

The Scenario: It is August 7, 2012, a day that will resonate with shareholders of Heineken NV for some time to come, as the takeover of Asia Pacific Breweries (APB) takes a new twist. Heineken has enjoyed premium success in recent years; it now stands as the third largest global brewer with a strong geographically diversified franchise, a rare gem in many portfolios.

A portfolio manager of a large conventional asset manager in London took the view in early October 2011 that Heineken's diversified franchise could be a significant factor in driving market outperformance. While developed markets were likely to prove flat, those in Africa and Eastern Europe could still support overall sales growth. Over the period of several days, she therefore acquired a holding of 1 million shares at an average price of EUR 33.12.

Since then the company has seen a steady flow of good news; mid December 2011 saw the company's purchase of the Galaxy Pub Estate from RBS. This was followed by further upbeat news, with annual results announced in mid February 2012 beating forecasts with a 9 percent increase in annual profits to EUR 1.58 billion.

Finally, the recently approved APB acquisition would help cement Heineken's emerging market presence and has helped contribute to the stock's price approaching a five-year-high. After this strong run, the portfolio manager feels the time is right to take some profits. She therefore instructs her firm's trading desk to sell 320,000 shares with a limit of 44 EUR.

The Asset: Heineken NV ("Heineken")

The Challenge: To sell 320,000 shares of Heineken over the next trading session with a limit of 44 EUR minimising implementation-shortfall cost. The order is large at approximately 20 percent ADV and with the backdrop of recent activity in this name, excessive volatility is likely to be present. The key to execution success here will revolve around spotting the right signals at the right time.

The Algo: A liquidity-seeking implementation-shortfall driven algorithm which employs a variety of opportunistic and protective signals to source favourably priced liquidity intelligently from all sources in the market-place (exchanges, dark pools, MTFs and internal crossing), whilst dynamically balancing trading-speed with market-impact and alpha-decay.

Signals used are selected based upon trade difficulty and market conditions and look to exploit the autoregressive/autocorrelation relationships across time-series components to anticipate future volume/volatility movements, as well as using intra/cross-asset class correlations for trend and fair-price prediction, in addition to looking at the impact of news sentiment and arrival rates. An important differentiator is that the algorithm focuses on opportunity rather than a fixed trade schedule.

Upon receipt of an order, the algorithm checks volume and stock statistics (intra day and historical data including liquidity, spreads, market activity and volume information). Then - based upon a combination of the urgency level specified (see below), order data and stock data - it calculates a unique trading solution specific to the order and time of day. It then reviews this constantly throughout the trading session, adjusting according to market conditions.

Key Parameters:

• Urgency: A value from 1 to 5 offering a range of execution speeds and styles, spanning from (1) high discretion with very passive lit market activity (typically 5-10 percent of volume) and full dark exposure, through to (5) aggressive liquidity seeking order-type (50-70 percent of volume in lit markets) leveraging advanced order-book tactics

• Get done price: A price beyond which the algo should aggressively sweep available liquidity until order completion or price condition expires

The Trader: The trader heads the asset manager's London trading desk and in view of the relatively large percentage of ADV that the order represents, opts to handle the order himself. While the asset management firm deals with several brokers, the trader feels that the characteristics of the order are best suited to this particular execution algorithm.

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