In all those stops he specialized in quantitative short-term trading with a bit of a discretionary overlay. In fact, Lavin points out that he was one of the very few people trading off of intraday data back in the 1980s when it wasn’t so easy to get.
He took those skills to Fort and when he decided to launch Vallen it was based on intraday data trading with a one-day time horizon. The program earned 9.5% in the last nine months of 2009 but dropped 4.5% in 2010. He decided to shut it down and take on a consulting offer, but he continued to trade and optimize the program with proprietary money.
He really liked the improvements to the program and decided to offer it to customers again earlier this year. “I hadn’t really thought of coming back and trading for institutional money until late 2012 after I did all the stress testing and was pretty certain this thing was for real,” Lavin says. “First I thought it was too good to be true.”
The changes included lengthening the time horizon from one to three days, eliminating intraday data from his models, changing the entry time from the open to late in the day and, perhaps most importantly, adding an intermarket overlay to his entry model.
“Vallen 1 had some good ideas but then I took everything and reworked it; changed some of the time horizons, changed some of the ways I calculated formulas, changed the time of execution,” Lavin says. “One thing that I found that was very favorable was using more than one market to [trigger] a trade. I call it a combination; we take markets that are positively correlated and trade the more volatile one. For example, in metals the most liquid markets are silver and gold; silver is more volatile. The only instrument I trade is silver but [run my] analytics on both.”
He uses five predictors that together create a score that indicates whether to go long, short or stay neutral. A neutral position can be pushed to a long if the companion market has a buy signal based on his analytics.
Lavin calls this his most significant upgrade and has a companion market for all of the eight markets he trades. In the stock indexes he will run his analytics on the Dax, which can trigger a signal in the S&P 500. For the Nasdaq 100, he looks at the FTSE and for the 30-year bond he will look at the TLT exchange-traded-fund (iShares Barlcay 20-year+ bond).
“It was kind of a big breakthrough. I also look at index ETFs. I use them as analysis instruments and then trade the comparable futures contract,” Lavin says.
His strategy is a combination of momentum, countertrend and pattern recognition with a volume overlay. The risk is equally divided into four asset classes: Equities, fixed income, commodities and forex. Each sector has one quarter of the risk.
The changes seem to be working well. His proprietary trading since the initial 2009 launch has produced a compound annual return of 14.32% with a worst drawdown of 6.34%. And the program is up (based on proprietary and customer returns) 15% through July. Seems like the second time is the charm for Lavin.