Comment by stult
20 hours ago
There is no model of the market that can remain stably accurate because the market will inevitably incorporate the insights of any model that is accurate until those insights are no longer accurate
20 hours ago
There is no model of the market that can remain stably accurate because the market will inevitably incorporate the insights of any model that is accurate until those insights are no longer accurate
Also known as the trading model's shelf-life. Based on what I have heard and learned, the average active trading model has a useful life of around 18 months. After that the rest of the market has adjusted and its edge is gone.
If rumours are to be believed, several "slow" hedge funds have models that remain useful and profitable for 5 years or more. Then again, those models are not used to conduct exchange trades but rely more on aspects of fundamental analysis.
Rather curiously some of the largest banks and tech-heavy asset managers tend to sponsor meetups and events like PyData - every now and then doing a slot on some of their open-sourced stuff. You might see a talk on 5-year-old trading model internals with large chunks of it opened up, or they could present some of the internal UI or visualisation libraries. The latter tend to be things that they no longer actively develop (they're "ready") but maintain for their ongoing persistent needs.
Of course anything that actually brings them money and/or gives an edge is not even discussed.
I would imagine a fundamental analysis model should remain fairly consistent over the years. It should be immune to a red queen situation.
Yes, actually there are.
Honestly: People think that "trading models" (whatever this should be) needs to be somewhat "supersophisticated" and "extreme driven by whatever complex math" - the brutal truth, esp. for smaller trading shops is much more simpler:
- Standard approaches like trend following or mean reversion are working very well since decades. (I can speak only for the last ~25 years)
Complexity in trading is not about "building that one specific niche-super-strategy", but more about putting all the ideas in a reproduceable approach/process to repeat it over and over again to grow the money.
This assumes that any accurate model will inevitably get big enough to be noticable by the rest of the actors.
in order for your model to accomplish that, you would get very rich.
there will also likely always be more. in the limit in order to get an edge your model would start to infer insider information. for example, it's common knowledge by now that satellite imagery is used to measure car numbers in parking lots, that's a proxy for insider information.
so it's not even so much the model as it is the data.
even being able to forecast weather better than publicly available methods can be leveraged to gain a significant edge.
> that's a proxy for insider information
Niche information pieces like this are only relevant to a veeeery small subset of all market participants, nearly invisible.
Just having a model that's predictably biased the wrong way when other models have already priced in the same things is pretty good. I mean, you have to look at where your model has no edge and figure out if it does have edges that the other ones are missing.
Coming at this from baseball, where the art is really knowing when not to take a game based on the line; usually if what you predict lines up too closely with Vegas, your edge is gone. (Hand-written A-life/evolutionary algorithm model of competing baseball equations that I've been refining for years, picks lately filtered through AI to isolate which ones fall into bands that are worth risking money on).
AKA the efficient markets hypotheses.
Or, thankfully, for Jane Street: the (eventually) efficient market hypothesis
There's definitely alpha out there, but I wouldn't want to make it my job to look for it
Damn, imagine you're the tribe's only successful hunter. You're the only person that's ever brought a deer back to the fire. You're even really good at it.
But the deer...sometimes they just don't exist. And you checked very carefully. No prints, no rubbings, no hair, no trail. Nothing whatsoever. You even left a bit of hair under a rock one time and the next time you checked it was gone. The only evidence of the existence of deer is the pelt you wear and the memory of last night's dinner. Something happens to the deer in the woods.
Some weeks, you bring back a deer a day. The tribe sings song in your honor. But every time this happens, there are those who grow quite suspicious when you all of a sudden "haven't seen a deer in weeks" because what do you mean you haven't seen a deer you said there were hundreds of them yesterday.
You can try to bring them with you to see, but most aren't interested. The few you bring happen to come when the deer are plenty. You can't convince them to come when the deer have gone because they just went yesterday and saw the foot-print highways and scarred trees; they know trees don't heal overnight.