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Keeping the Edge in U.S. Options Strategies: Expanding from a Pair to N-Legs

Published in Automated Trader Magazine Issue 24 Q1 2012

Pair trading is one area of the market that has changed significantly over the past year. Traders are increasingly aware that their long-established methods of trade execution are now less accessible and that more complex trading strategies deliver more alpha per unit of risk. Gary Stone, Chief Strategy Officer at Bloomberg Tradebook, examines one way in which pair traders can overcome these issues to keep and enhance their edge.

Assuming that today and tomorrow will be like yesterday is not a sound survival strategy for any market, but for pair traders it currently looks even less viable. A combination of market structure, regulatory change and competition for alpha opportunities means that pair traders are re-evaluating both their methods of order execution and their strategies in order to remain competitive.

Market Structure and Regulatory change

In two short years, the complexion of options market liquidity has dramatically changed. Liquidity is now basically spread evenly over more exchanges and most exchanges have developed a "spread" book to facilitate complex strategy trading without leg risk. The common convention for many pair traders has been to execute their trades manually or use voice brokers, typically looking to those brokers for capital commitment. With liquidity fragmentation, manual trading has become less efficient. Not only are there obvious legging risks but it is even harder to manually get size without the benefit of an algorithm managing the execution.

Passing orders to intermediaries now has two challenges. First, it is more difficult to avoid information leakage and preserve anonymity - especially with large trades - which can adversely impact P&L. Second, the nature of capital commitment is now coming under scrutiny. With complex options strategies, traders would often rely on capital commitment from a bank market maker to get the investment strategy implemented. Although the Dodd-Frank Wall Street Reform and Consumer Protection Act is in varying stages of being implemented, some market participants are questioning if it may impact some of the traditional bank market makers thus potentially decreasing the availability of capital commitment.

The concern is the way that some brokers may apply the Volcker rule within Dodd-Frank. While the Volcker rule states that customer facilitation trades are permitted, the current iteration of the rule suggests that the executing party has to be able to demonstrate that they are hedging the trade. This is relatively easy to accomplish with an outright directional trade, but for pair and complex strategy trades such as an option risk reversal, a market or delta neutral equity/option pair the task is maybe more difficult to demonstrate since the trade being executed is inherently hedged in its own right. In order to comply with the proposed rule, can firms adequately demonstrate that they are hedging a risk-reversal strategy package of an option spread with stock? With this uncertainty, some firms are looking at algorithmic trading methods to implement complex trading strategies. As firms examine their businesses in preparation for the implementation of Dodd-Frank and the Volcker rule, some may feel compelled to withdraw from some of these capital commitment activities.

Risk Reversal

Risk Reversal trades attempt to exploit opportunities inherent in the flexing of the "smile" in the implied volatility curve across out, at and in the money option strikes. Let's assume that we are looking at a company called XYZ. XYZ is a stock that has dropped significantly amid a loss of confidence in the company - its products are old and have lost their edge.

Figure 1

Figure 1

In view of its various difficulties the market was initially predicting the demise of XYZ so at that time its skew was positive, with the implied volatility on out of the money puts trading way above the out of the money calls. Then rumours started that the several competitors were considering buying the company, which caused the skew to turn negative as the implied vol of the out of the money calls (which would obviously appreciate on any takeover) rose. A trader taking the view that the takeover talk was unlikely might wish to express this by placing a risk reversal trade based upon the assumption that the skew would revert to positive (or at least become less negative). At the time of the takeover talk, the XYZ October 90% puts were trading 6 volatility points lower than the 110% calls (see Figure 1). The trader might therefore sell an out-of-the-money (OTM) call, buy the OTM put and buy stock. Liquidity in these options might not be consistently distributed across the strikes, which if handled manually would make the trade a major headache to execute - especially if the trade was to be placed in significant size. However, using Tradebook's N-Leg algo, all three legs could be input to a single ticket. Tradebook's advanced execution tools working in the background sourcing liquidity across nine U.S. options and 13 U.S. equity exchanges keep the trade in balance as it tries to complete at the best possible prices.

Furthermore, traders can leverage Tradebook's Execution Consultants to create a mathematical formula for the strategy and create a synthetic "security" on the Bloomberg Professional service that represents it. This custom index expression can then be used in Bloomberg's analytics, such as technical analysis. Traders can apply advanced quantitative tools such as Bloomberg's ATM studies (see Automated Trader Q4 2012 page 32 or www.automatedtrader.net/articles/sponsored-articles/92088/getting-the-execution-edge . ) for market timing the investment and seek even better prices. The ticket can be staged, or pre-populated in the PAIR platform and be activated in the N-Leg algorithm as soon as the ATM criteria are satisfied.

Alpha change

Market structure complexity and the apparent decline in capital commitment are contributing factors toward execution automation. Another major driver in the automation of pair trading strategies is due to the competitive pressure to capture alpha. The easy days of the mid and late 80s when pair trading could return exceptional P&L by trading off the daily prices of pretty much any two large cap stocks in the same sector are long gone. The explosion in statistical arbitrage trading since then means that obvious simplistic opportunities are few, far between and quickly disappear.

While modelling techniques have become far more sophisticated, from a practical perspective the changes have come about in three key areas - trade complexity (more legs), trade timeframes (shorter and with a higher trade count) and stock capitalisation (lower cap stocks with less liquidity). All three have major implications for trade execution.

Trade complexity: As opportunities in well known stock pairs are increasingly arbed away to the point where the risk/reward metric becomes unattractive, an increasing number of traders and managers have started to look for less obvious opportunities such as basket versus single stock or pair versus pair trades. While these may represent a better chance of capturing alpha, their higher leg count obviously makes them more complex to execute.

Trade timeframes: This change has gone hand in hand with a re-evaluation of the timeframes in which pair trades are executed. Rather than
trades that might last days, weeks or months, pair traders are increasingly looking at opportunities in terms of hours, minutes, seconds - or in some cases even shorter timeframes. In part, this has been due to increasing competition for "traditional" pair opportunities, but risk and capital allocation have also been factors. Some firms have been quick to embrace intraday pair trading as it reduces the risk of being hit by a stock-specific event, such as an unexpected news item outside market hours. At the same time, one week expiry listed U.S. options strategies have started to gain popularity with traders seeking to trade specific events.

Market cap: Competition for alpha opportunities has also compelled traders to cast their nets wider when looking for suitable instruments with which to pair trade. With established large cap pairs such as KO/PEP no longer yielding the P&L of their glory days, traders have started looking for opportunities among lower cap stocks where liquidity is far thinner.

Putting it all together

Any one of these market structure, regulatory or alpha changes has a major effect on the process of trade execution; combine them and things get even tougher. Then expand the investment strategy to include options where traders may be using long calls/puts with stock - an N-Leg trade. For example, 90/110% risk reversals with stock. The execution in two options legs simultaneously with stock is difficult in its own right but then add dynamic weightings and the execution complexity moves to an even higher level.

Bottom line: manual trading is simply too inefficient; putting such a strategy on an option exchange's complex book will not optimize liquidity opportunities because of liquidity fragmentation both at the stock and option level - the option exchange has to be in contact with the stock at the right price in addition to the requisite options. If you want to stay competitive you have to automate; have all of the information from the strategy on the same ticket so it can be delivered to an algorithm that manages the fragmented liquidity in both the options and equity markets.

Which is where Bloomberg Tradebook's new "N-leg" algorithm kicks in. The new algo supports trades with up to four legs in stock or option markets, or a combination of both. It also has access to all Tradebook's advanced order management technology, including execution algos, smart order routing and its short term price predictor model (PPM) - across all major U.S. stock and option markets. Additionally, algorithms can be integrated into third party order management and execution management systems.

This range of functionality effectively helps to ensure that these complex trading strategies will rarely be constrained by your execution environment. For the first time, certain specific pair/arb strategies can now be automated by using Tradebook's "N-leg" PAIR algorithm. Automated butterflies, reverse conversion and 90/110 risk reversal (see sidebar) trades are all possible, as are 3:1 and 2:2 trades.

With many of the factors outlined above driving an increase in trade volumes, there is now an imperative to get more trades done - in shorter timeframes, in more instruments, in thinner pools of liquidity. With this extension to the PAIR functionality you now can. No more scrambling to find thin liquidity to complete a final leg, no more fretting about slippage destroying your trade's alpha, no more having to pass on profitable opportunities because you don't have the bandwidth to take them.

End result? New opportunities, better productivity, less hassle, less leg risk, more alpha.

Bloomberg Tradebook is a global agency broker offering advanced trading algorithms and direct market access to over 60 global equity, futures, and options markets and 41 currency pairs in our Foreign Exchange marketplace. Many traders have created valuation, investment and trading strategy models in various applications and nourish them via the Bloomberg Professional® service data API. Now, using the same connectivity as Bloomberg's data API, traders can integrate their strategies with Bloomberg Tradebook's high performance Order API and connect their strategies to the electronic execution highway.

Nothing in this document constitutes an offer or a solicitation of an offer to buy or sell any security or other financial instrument or constitutes any investment advice or recommendation of any security or other financial

instrument. BLOOMBERG TRADEBOOK believes that the information herein was obtained from reliable sources but does not guarantee its accuracy.

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