Wanted to do this at the end of month, but time is a sparse commodity and I’ve got some now.
Pros know that neither $ or % profits mean much. There are just numbers to impress gullible or uneducated on this subject. They are the shiny object that distracts.
One of the things that actually matters is
Risk to Return.
While it is debatable to what is a good measure of such, I’ll use Return to DD here to start with something. Btw, it is “debatable" because there could be “
not materialized” risk. I’m not sure what’s the fancy way of calling this, but one example would be selling options and cashing premiums for a year without much of DD and then blowing up in one day. With stocks, over the large number of trades without averaging down and using fixed positions sizes - big part of risk will eventually materialize in DD. That’s why I thought is reasonable to start with it.
As mentioned in my previous post, I do believe that the longer one trades the less that Return to DD ratio is gonna be. So this year’s result doesn’t mean I have some sort of holy grail, but it looks damn good to me and I will take a moment to enjoy it In fact it is so good that I myself, would be very skeptical of another individual trader achieving it without substantial proof. But again, I don’t think it will be this way over let’s say 5-10 years.
More possible reasons why my results should be somewhat discounted:
- This is year has exceptional volatility
- There is always some element of luck when results are exceptional
Important note: my reconstructed equity from trades doesn’t include certain commissions such as borrowing rates, which start being visible on a 6+ months periods. So when I do analysis of trades/equity/DD - % numbers might be off by around 10% of their value. For most practical purposes - it is not a big deal. But it will create some discrepancy between my end of month PL (based on broker statements) and long term graphs generated by my software.
Net profit YTD: +93.4% (+83% calculated by IB)
Max DD: -13.02%
Return/DD: 7.17
Return(year adjusted)/DD: 11.09
Sortino: 4.08
# of trades: 1204
Average capital use (overnight): 37.32%
This is for combined equity=whole account, which consist of results of multiple systems.
Some work better is some conditions, others in other.
Achieving those kind of high Return to Risk number is exactly why one should use multiple non-correlated systems. That doesn’t guarantee but statistically increases our changes to have higher return to risk.
Comparison with SPY looks just ridiculous this year but I’ll indulge and include it
To give you an idea on density of trades here are open positions daily:
The next one is probably gonna be most controversial. As it is what most people would consider a good example of a system that should not be traded. Because visually, there are much more negative outliers than positive ones. But ultimately it doesn’t matter.
Density of PL matters.
A human eye can’t size it up correctly if any statistically valid sample size is used.
Talking about this might take another long post, for now I’ll just use it to remind that common wisdom is very contextual and doesn’t come with a manual on when to apply it / limitations.
Ultimately - beyond density, understanding implications of such PL distribution matters the most.
MonteCarlo outcomes on fixed position size of 7%. My actual size varies by strategy but this is somewhat useful.
The whole MonteCarlo thing is not something I normally look at. Maybe once in 6 months. There are stronger rules that govern my risk management and I believe they are more practical. Again, there could be a separate post on that. But it is always nice to see MonteCarlo simulation results looking reasonable on a large number or trades.
Val
