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I've thought about this as well, its part of why i started trading in small cycles of trades so I could track if and how this result "(avg_win * win%) - (avg_loss * loss%)" changes as I modify my technique in an ever changing market. And that's just for one contract with its own unique behavior.
Its an interesting problem and one which I've been coming to the conclusion that I'll have to come up with my own formula eventually unless there is already good stuff out there.
@centaurer you have hit upon a topic which has bothered me, the fact that there is so much cargo-culting of information that is of questionable value. But that's a huge topic. And I think exploiting this condition could be a rich area for developing an edge perhaps.
Note: I didn't mean to imply that anyone in this thread is cargo-culting bad information, I meant in the broader sense that you see throughout trading in general.
I do think I agree (partially), for several reasons. The main one is simply that this formula gives you an "average trade" based on the group of trades you figured it for. While there's nothing at all wrong with knowing what your average has been (in fact I think it's a good idea), by itself it doesn't tell you important things like:
(a) How were the trades distributed? By this I mean essentially how consistently are they close to your average. "All tightly bunched up" means something very different from "all over the place." If the variation is large enough, the average number is semi-worthless, because a really big losing trade can still be in the average, and could also kill you. You'd want to know something like the standard deviation, but you would likely then run into the problem that your trades probably aren't actually distributed in a classic bell curve so the s.d. will mean less. This does not mean "don't use an average and/or a measure of deviation," it means "don't put too much faith in it."
(b) As @centaurer puts it, the actual distribution of trades (or let's say, of potential good trades) will change a lot with market conditions. Not only by day or month, but with anything else that can affect profitability -- are prices ranging, trending, high volatility, low volatility, etc. So your expectancy -- meaning, what you can really expect -- may not depend either on you or your method as much as the market at the time. One thing is certain, and that is that the market will change.
With all this said, I do think you should know your averages, and also how differing conditions affect them, and certainly how consistently you come close to your averages under different conditions.
I also think you should be fairly nuanced in how you look at and apply your past trade statistics. Use them, but recognize the often-changing context they came from and apply to.
(I wish I could be more conclusive about how to do that.... When I have it all figured out, I'll be sure to let people know .)
I agree with @bbilotta's sentiment that there is no one-size-fits-all answer here and it will be highly dependent on your strategy and historical results. I did a bunch of work on this a while back (analysis here) on a subset of randomly generated trades and there was no exit strategy that showed edge over another. Exit strategy is never going to be perfect and all you can do is adopt something that makes sense within the context of your strategy and historical results.
Please correct me if I've taken your quote out of context, and this may be getting off topic, but for a discretionary trader with a non-benchmark-correlated absolute return strategy (which is what I see most short-term intra-day traders here attempting) isn't this the whole point?
haha yea getting way off topic but it is interesting.
I think many people believe that but I am just not sure it is correct. The distribution of trades for entry on ES at 10:06am 3 seconds and 125 milliseconds on 5/13/19 is the same for both of us.
I think it is like trying to argue that the deck of cards is not the generating process in a poker game. Of course the player has strategic options given the deck run out but I do think there is much language used here that is slightly magical thinking. "I didn't stick to the trading plan and so the flush draw didn't hit so I lost."
snax mentioning cargo cult is perfect. I never really think to use that phrase but it is perfect.
There is all kinds of strange historic artifacts IMO. Why does every charting package default to different color up and down bars even though absolutely no one uses that information for anything? Especially red and green that has all these associations with traffic signals to nicely throw some unneeded bias into your brain as you try to make a decision.
Then IMO there is a ton of cargo cult stuff because there is self interest in selling things that don't work but can't be easily shown to not work.
I still don't think I'm following here. I'm a discretionary trader, so the items below are in this context. I think of the expectancy formula as having 2 uses:
As a display of edge
As a metric to compare different sets of trades and whether performance is improving or degrading
On the first point, assuming a large enough sample-set of trades one should expect with random entry to achieve a result that is negative and equal to the spread of the instrument they are trading. If expectancy over a large enough sample of actual results is greater than this, to me that indicates that skill or an edge is present. If it is negative, then no edge or skill is present.
On the second point, assuming the sets of trades being compared are large enough to encompass multiple market regimes and minimize the impact of randomness, then higher expectancy on one set over the other would indicate better performance on that set.
To bring this back to the OP's question then, if moving the initial stop to BE+1 on the set of trades in question increases expectancy over leaving the stop at BE, then it would be the better choice. Obviously there are multiple variables here, size of set in question, stability of market conditions over the set, consistency of execution, etc., that can make this the wrong strategy in the next set of trades, but I don't see the issue with using expectancy as a gauge of which strategy would've performed better.
I'll add a big disclaimer here that I don't believe moving a stop a fixed amount relative to entry makes sense. The market doesn't know or care where your entry was, so saying your market call is "wrong" and you should get out if price retraces to your entry point isn't logical to me, but this will obviously depend on your own strategy.
I do agree with you on your magical thinking comment though. Every gain or positive day is a display of skill and every loss or down day is either a psychology problem or not following a plan when most of them are likely either due to the randomness of the market or simple lack of edge.
Back in the day when I was in MBA night school I learned two very important lessons that are per-tenant to this.
A very large tech firm with a world wide monopoly on a very common office technology was not interested in sophisticated analysis. All the managers were held accountable in a way that made a simple payback calculation the go no go decision rule. So there is always a better way but that does not make it the best.
We also learned by experiencing an emotional disaster involving tinker toys, that the best plan in the world is worthless if you can not implement it in the real world.
To the original question. Many trading systems use a scale out. Price Action Trading System takes profits on half of the entry at 4 ticks and then moves the stop loss to break even at 5 ticks. Mack says this is based on years of observation.
Futures Trader 71 keeps statistical analysis of the average rotation size in the ES so he knows the difference between noise and a move.
So yes the first step is to track rotations and then work backwards to a rule of thumb that usually works. Then double check the rotations as the market changes.