Imagine how horrible it would be if Spain sorted its banking industry, and Greece generally got its act together. Wouldn’t it be awful if European stocks rebounded?
“If your total portfolio is lined up for only one outcome, you may be wrong-footed,” Arthur Van Slooten, a strategist with Société Générale, told Reuters. So traders are trying to manage their event risk via options and variance swaps. Other strategies for hedging event risk include trading around values of commodities.
But these can be difficult to implement with real-time sensitivities, especially as news breaks. And these strategies do not take into account technological advantages available for event-risk hedging.
This Just In
Enter the Yale Center for Analytical Sciences’ Casey King and Michael Kane — and their use case of news analytics for automated trading. Inspired by the Chernobyl nuclear disaster of 1989, King and Kane saw that hedging (against interest rates for fixed-income assets, in this case) was not enough.
Their solution is mixed-asset hedging, using a combination of treasuries and equity instruments to manage corporate bond risk. Treasuries serve as an interest rate hedge, while equitites are an event risk hedge.
King and Kane backtested their model with Dow Jones newsfeeds about the BP oil spill of 2010 and subsequent changes in share price, similar to the way they used data related to the Flash Crash (also of 2010) to backtest SEC circuit breakers.
“Our approach essentially was to develop a sector-by-sector lexicon,” Kane said during a recent Sybase-sponsored webcast. “It is essentially a set of words that encode some kind of disaster for a given sector or a given company.”
Almost six in 10 (59 percent) of market participants who invest in fixed income use mixed assets to hedge their positions, according to a survey of the webcast’s audience. The key to mixed asset hedging is to do it better than the competition.
Head of the Analytical Pack
In an age in which everyone receives the same market data, the advantage goes to the trader who processes fastest. Everyone gets the same unstructured data too, but the advantage here is in finding the best way to analyze text data.
“You must correlate it with other text data to create actionable information,” my fellow Trading & Risk Technology blogger Domenic Iannaccone told me after hosting last month’s webcast. “This is more of an analytic advantage than a speed advantage.”
Using unstructured data to gague market sentiment is gaining traction. This includes newsfeeds, blogs, electronic documents and, as I’ve mentioned before, Twitter. And social media’s growing influence on the market is increasingly well documented.
Nevetheless, sentiment is a small subset of text analysis. And more than half of the respondents (52 percent) to a poll during Sybase’s webcast were “interensted but unsure how to implement” news analytics in finance.
Complex Event Processiong (CEP) technology is a good place to start because it helps users separate the valuable information you want from the torrent of data that everyone else is getting, too. And CEP is well suited for mixed-asset hedging, according to YCAS’ King.
Everything Bad is Good Again
Even good news can be bad for traders, depending on their position. So whether or not Spain averts its banking crisis and Greece remains in the eurozone, some will win, and others will lose.
How much they lose will depend on how they’ve hedged.
“When you’ve come down this far,” European trader Justin Haque told Reuters, “few people are brave enough to put more shorts on.”