Originally Posted by Cantabrigian
Yea - I didn't write that third point correctly at all. Paper trades are obviously useful to you for testing / further R&D but investors won't put much (any) stock in that. If you're looking to move beyond friends and family money, just to give you an idea of how hard it is to get institutional money, you've had hardly any big bank prop traders spin off successfully in the past four years with the exception of Phibro / Andrew Hall. Because investors discount unaudited results completely.
There are several reasons - from the naturally conservative nature of those investors to the fact that you're very levered and simulators don't do a good job of accounting for cash management which post Bear Stearns is absolutely essential. Nobody gets term funding now or if they do, it's at a price.
I actually agree with all of this. I don't expect that we'll be able to receive any institutional money for at least our first three years. However, that still leaves open individuals, family offices, FoFs, and Seeders. I think between those options we can scrape together enough to start the business and sustain it long enough to have a true track record that would make institutions comfortable.
On the model, there are a few obvious red flags - like obvious and complete deal killers for institutional allocators / investors
- If you're up 12pct MTD, you're levered and the some. I'm assuming at least 4x and finger in the air, I'd say more like 10x. You can barely get away with that for some relative value / fixed income strategy but that's too much on equities.
I think you may have misread my post on our performance. We're up 12% (although currently 15% -- it's been a good week) on YTD, not month-to-date. We are levered, but nowhere near those levels. 1.75x. I see what you're saying with running the numbers unlevered and I think that's actually a good idea. It wouldn't be so terribly hard to incorporate that into our backtesting, so I think that's doable for us. However, with the live fund, we've been running it at 1.75 thus far and I'm hesitant of reducing that halfway through the year. It would make our returns look more inconsistent than they actually are, I feel.
- Related to that, look at what you make 1x or better .75x levered. Anyone can borrow money, what people care about is beating the relevant benchmark on an unlevered net return basis and/or on a vol-adjusted basis.
- Assume no one will tolerate more than a 10% capital loss rolling YTD - i.e. being down no more than 10% YTD in any calendar year. What do returns look like with a stop like that?
This is one of our biggest flaws. We have drawdowns larger than 10%. They recover quickly and fully, but they do happen. Some kind of stop would crush us because we need to keep trading aggressively to recover quickly.
- You performed best in 2000 and 2008. Two exceptional years for the market. That immediately looks like overfitting.
Actually I said our best years were 2008 and 2009 -- which can easily be explained as a function of the super high volatility of those two years. 09 is better for us than 08. It's not just crash years that we do well in.
- You need some story about what your edge is. A lot of people with a lot better resources have failed to match that performance. What are the odds that the proverbial two guys in a garage (even if one knows stats) stumbled upon the winning secret. These are deep markets, how did you find what so many people missed?
First I disagree that there is "the" winning secret. I think in the quant world there are many winning secrets, and many yet to be discovered. But with regards to your question, I think we didn't stumble upon it -- we had the advantage of being from the world of analytics and attacked the problem in that way. We knew predicting price movement directly would be too difficult, and it's too computationally complex, so we decided to track the performance of different-but-related trading strategies instead, and dynamically switch between them. That's the key concept that underpins what we do: it's a much simpler task, computationally, to gauge the current performance of a trading strategy, than it is to predict price movement. I can't speak to the extent that others have or haven't come up with the same concept, but I think we attacked the problem in a very straightforward analytic way -- take the thing you can't do, or that's flat-out-impossible, and find a workaround to reduce the number of variables and the overall complexity.