A reader of this blog (hey – I’m as surprised as you are!) sent me an email recently detailing a strategy they’d developed. While the details of that strategy aren’t relevant here, they sounded good and they got me to thinking about the process of selling a trading strategy. This is an activity that I’ve spent some time on and have decided just isn’t for me.
There are a lot of difficulties with selling a trading strategy. One of them is a consequence of the foundational problem of back-testing about which I first started posting on this blog. For any given period of time (that has already elapsed!), it’s not difficult to generate a good number of pretty impressive strategies. All you have to do is try a good enough number of random strategies and some of them will prove to be too good to be true.
Presumably, any credible person who might be listening to your pitch will be at least intuitively aware of this fact and will thus be highly suspicious of any back-tested results you might present. For this reason, it’s impossible to sell a strategy on the basis of back-tested results. Only auditable, real-world returns will be considered valid by any serious person. Of course, you might find someone who’s less particular, but then you’re flirting with fraud rather than a legitimate sale.
So let’s say you have impressive, verifiable results. You still have to answer the question:
If this strategy is so good, why are you selling it? Why not just trade it yourself?
Read more…
rebranding opportunity?
A friend of mine pointed out an article he came across on his bloomberg terminal today which reminded him of a strategy I’d described to him sometime back and which we’ve been trading over the past year or so with good results.
To the great chagrin of some of my partners, I even wrote a few posts about the phenomenon underlying our strategy and its evolution as we capitalized on it. Eventually, they persuaded me to shut up already, but the outline was there for all – including Goldman! – to see.
My first post on the topic, “unsung virtues of a dynamic hedge” published June 4th of last year, was pretty coy and didn’t mention the source of alpha itself but talked about enhancing it with a dynamic hedge.
My next post on the topic, “to dream” was published July 14th of last year and laid out the exploitable discrepancy of the market’s behavior. Interestingly, the data I provided in that posting went back the same amount of time as in Goldman’s piece.
I explicitly wrote one last time about the strategy in “evolution of a strategy” wherein I detailed the process by which we’d been evolving the strategy.
Now, one of the more entertaining things about having a blog is that you get to see who is viewing your content. I’m happy to note that all of the major IBs are represented including a variety of distinct IPs within Goldman.
Now, I’m not accusing them of stealing my ideas or anything untoward like that… but I’ll admit that I am wondering how long it’s going to take them to make similar observations across markets beyond US Equities…
Read on for the Bloomberg article…
Read more…
During some recent travels, I read William Poundstone’s ramblingly entertaining Fortune’s Formula. It had been sitting on my shelf after I’d originally gotten it, perused it and offhandedly discarded it as yet another of these science-is-fun-and-full-of-wacky-characters books for the butch humanities student. My initial impression was a bit harsh as the book proved entertaining and covered a lot of ground including significant coverage of Ed Thorp and his stat arb alchemy (see here for his own papers on the topic).
One of the more compelling segments of the book relates Claude Shannon‘s demon which is a nice thought-experiment / trading-strategy which illustrates the tractability of the problem of trading on a random walk market with fixed properties. I wrote the above applet to explore the impacts of applying friction and otherwise modifying the behaviors of the market and the demon.
The original demon posited a world with no friction in which the market contains one instrument which doubled or halved in value each day. Shannon’s demon looks to take advantage of this volatility by maintaining a portfolio which was rebalanced each day to ensure a 50/50 split between cash and the market. The applet implements a very simple monte-carlo test-bed for Shannon’s Demon. You can configure the demon and the marketplace along a variety of parameters, and then run many instances of the demon, each on its own self-contained random-walk market.
Although Shannon’s demon is a highly “stylized” case in the sense that it operates on a very synthetic, unrealistic and favorable formulation of a random-walk marketplace, it has spawned a great deal of interest and serious research.
Most of all, it’s a revealing illustration of the kind of reasoning one must embrace in order to address stat arb strategy development. Enjoy.
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Updated: March 4th – made price axis logarithmic to better reveal mc paths.
