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analyzes data. Essentially, it was a way to look at any set of data and organize it, and even make predictions based on it. It could find the underlying patterns in the numbers, when a human being would see only a mass of random information. This was something I discovered when I was looking into Sienkiewicz-Moore theorems, a subset of Big Number theory, back when I was still in graduate school.”
    All I get from that is the ice wall again. He sees he’s lost me and tacks quickly back into simple concepts. “So I take a series of facts, translate them into numbers, plug them into the formula, and it makes a series of educated guesses about the future. What made the algorithm so interesting was that the predictions were almost always right. I could take any facts that could be reduced to mathematical inputs—migration patterns of birds, or tide tables, or annual rainfall in the Gobi Desert, for instance—and I would get a very good idea of how those samenumbers would turn out in the future. Then it occurred to me, what if I entered something a little more concrete than rainfall estimates?”
    I’m starting to get it now. “Like, say, stock prices.”
    He smiles again, and I sense genuine pride still lingering there. “Exactly. I quickly found the algorithm was a great deal more valuable to me in practice than as a theory published in an academic paper. That’s how I began trading. I’d use the algorithm to predict the rise and fall of the market, and I’d make bets accordingly.”
    â€œAnd you got very rich.”
    Another small burst of pride. “Yes. Other people noticed. They hired their own computer engineers and math professors. Now there’s a whole industry of traders and programmers analyzing market data using algorithms and computers. Each firm has something they call their ‘secret sauce.’ That’s a proprietary algorithm that’s the heart of their trading. It tells their computers how to interact with the markets. I called mine Spike. To find the spikes in the markets.”
    He looks at me. I smile, to show him I get it. “Your secret sauce is better.”
    â€œMuch, much better. Not to boast, Mr. Smith, but nobody else has come close to understanding what I did when I broke that problem back in graduate school. And we’re constantly refining the process, feeding more data to the algorithms. Spike, like every other piece of trading software, makes millions of decisions every second. Literally billions of dollars every minute, all moved around by computers. That requires incredibly smart people to analyze market trends, to see risks and opportunities and then translate them into the kind of math that machines can understand. Everyone is trying to beat the odds, trying to get their computers to think a little faster, a little smarter. It’s not easy. As I said, most firms are lucky to match the market. The best ones can offer you perhaps a ten percent return over time.”
    â€œWhat’s your return?” I ask.
    â€œEighty to ninety percent,” he says. “Even when the economy collapsed, we managed to make a profit. All with Spike. It’s simply smarter than anything anyone else can come up with. Other people will promise you pennies. We double your money, or close to it.”
    Bullshit. That’s Ponzi scheme territory. Nobody can guarantee that kind of return. I don’t get any active deception off Sloan, but people have a habit of buying into their own hype. After all, it’s not a lie if you really believe it.
    Some of my skepticism must show up on my face, because Sloan smiles and asks, “You don’t believe me?”
    I try to be diplomatic. “That’s quite a return,” I say. “Warren Buffett only manages nineteen percent, and he’s supposed to be the most successful stock picker in history.”
    Sloan smiles again. “Warren’s a friend. But he’s a