Vegasoul isn’t Vincent Wong’s favorite German band. “They’re pretty obscure,” the Hong Kong native laughs. “I found them on compilation.”
He doesn’t own any of their CDs, and isn’t even sure he remembers which songs on that compilation were theirs. But he liked the name so much that he adopted it for the asset management business he launched in 2004 — an operation that’s a lot more successful than the band for which it’s named. Wong has $132 million under management, an average annual return of 58% and a sharpe ratio of 2.73 for the last three years.
The program combines long-term trend following, short-term reversal and pattern recognition strategies. The majority of his positions are short-term positions that try to identify inefficiencies in the market caused by illiquidity or asset allocation.
Like many undergraduates during the dot-com years, Wong had planned on a career in information technology, which he’d studied in college, along with economics.
“I got out of college in 2001, and started trading stocks, but just as a retail guy,” he recalls, adding that he found them illiquid and too closely correlated with each other to really trade aggressively. Then he discovered futures.
“I was like, ‘You only have to put up one dollar to buy $10 dollars of investment? Great!’” he recalls. “Of course, at that point, I didn’t understand that leverage is a double-edge sword, then you look at transaction costs — the spread and the commission — and I was really attracted by it.”
He started buying books like “Trade Your Way to Financial Freedom” (“A cheesy title,” he concedes, “but worth reading”), then began experimenting with TradeStation, and was soon putting his programming skills to work on his own strategies. Within two months, he had the core of the systems that he uses today.
“You find out pretty quickly that there are no secrets,” he says. “Everyone uses the same ideas. You experiment with trend-following and with mean-reversion systems, and you either learn through self-experimentation, or you don’t.”
Once he got his confidence up, he borrowed money from friends and relatives, and opened trading accounts with brokers in different Asian nations. “I started with Hang Seng stock index futures, but really wanted to be as diversified as possible,” he says. “One thing you learn when you study economics is that diversification is the only free lunch in investments.”
At the time, diversification meant stock index futures in as many countries as he could access, but eventually he began to look into different markets in different time zones.
“Because of the 13-hour time zone difference, I didn’t trade U.S. markets at first,” he says. “I would follow them, of course, but didn’t start trading them until 2003.”
And as he began to diversify, he found that the systems he developed for Asian stock indexes worked on Chicago corn and New York coffee as well, with a few tweaks to the parameters.
“You don’t want to capture every nuance of every different market into a single system – which is known as ‘curve-fitting,’” he says. “What you want to do is to capture a phenomenon, and we’re trying to capture the tendency of markets to trend and to revert to the mean — basically, the tendency of markets to go through bubbles and crashes, which is nothing special; it’s what most CTAs do. It’s what basically every system trading book describes and I believe these phenomena won’t change 100 years from now, because the way our brain is wired hasn’t changed.” For traders, the challenge is identifying this phenomenon in current markets. “These tendencies will morph and manifest themselves in different ways as people arbitrage out these expectations,” he says.
That doesn’t, however, stop him from putting in 13-hour days “researching” his system, much like a professional athlete who drills basics over and over again.
“I’m a great fan of evolution, and that means looking for incremental improvements and new ideas to test,” he says. “These ideas might be about developing new systems or capturing new phenomena, but maybe it’s about how you execute or how you reduce transaction costs.”
On the new development front, he’s been exploring the “Turtle Soup” concept of trading, which was named by Linda Raschke and Larry Connors in their book “Street Smarts” to describe a method of trading against the famous Turtles mentored by Richard Dennis.
“In general, breakout systems like the turtle system have a percentage of winning trades below 50%, so the intuition is that by taking the other side of the trade and managing your risk, you have the basis of a mean-reversion system,” he says. “You can extend this concept to other trading styles and prey on their failings.”
In other words, he uses his own systems to identify longer-term trends, but will then try to identify data entry points by determining where popular trading strategies will create entries.