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I don't think @Anagami or @Fat Tails wasted time by posting some good studies. It does not have to be a broker's summary. It could be stats on let's say a year of trading or a few hundred trades or some kind of mathematical demonstration. It's usually obvious if the stats are bogus or real. People tend to believe what they see (religion aside).
Otherwise, it's like this guy who is selling his fakebars for $199 a month and has been telling the followers I can't legally give you stats (although he is not licensed in anything), but if you don't believe me go do your own stats (he used to post stats that showed miserable results, then he stopped doing that).
Aligator I never said what Anagami or Fat tails posted was a waste of time. What they posted is very different from someone being asked to post a brokerage statement as proof of results. It is a waste because it cannot be verified as being true. Even if a brokerage statement could be verified to be true it helps no one on board unless the method that goes with it is revealed as well. I am not selling anything here so it is moot.
However, I am going to bow out of this conversation because it is really not the intent of Anagami's thread and this just clutters up the original intent.
"The day I became a winning trader was the day it became boring. Daily losses no longer bother me and daily wins no longer excited me. Took years of pain and busting a few accounts before finally got my mind right. I survived the darkness within and now just chillax and let my black box do the work."
Thank you for your detailed and elucidating post, Harry (@Fat Tails).
Yes, 4 times the # of trades (10/10 system) for every 1 trade (20/20 system) is a reasonable modelling.
As a good empiricist, I plan to write some quick Java code to duplicate your results (not sure what sim you are using? Prop?).
Before that, however, maybe you can help me understand the formula for the Adjusted Win Loss Ratio in your simulation (I think you mean Loss / Win Ratio?). I tried factoring in commission and slippage but was unable to come up with the same ratios (0.83 and 0.69).
Thanks!
You are never in the wrong place... but sometimes you are in the right place looking at things in the wrong way.
The excel model is just from the thread "Risk of Ruin". You can actually read through the stuff and download the excel model from post #65, as per link below:
Thanks again, Harry! (@Fat Tails) Much appreciated. You help me (and I'm sure many others) to correct certain distortions that have been ball and chain in our trading.
Just crunching some numbers with respect to the 20/20 and 10/10 system. Let's calculate trade expectations after factoring in vig (slippage and commission) as well as time (10/10 trades 4 times more often).
10/10 System @ 60% Winning
(0.6)(8.2) - (0.4)(11.8) = 4.92 - 4.72 = 0.2 points.
Because this system trades 4 times more often, for the same time window, we get 0.2 * 4 = 0.8 points
Wow. The 20/20 has almost 3 times higher expectancy (even though 10/10 trades 4 times more often), because the vig is much less of a drag. This ratio is amplified with % position sizing. Essentially, the 20/20 gets ahead, stays ahead, and increases the lead more and more because it is dragged down less on every turn.
Now, does this effect continue? In other words, what happens if we create a 40/40 system (60% Winning)? Will it perform better than 20/20, just as 20/20 performed better than 10/10?
NO! It breaks down somewhere...
Let's take a look at math and then do a simulation.
The expectation for 20/20 system was 2.2. Keeping that same assumption about the number of trades when we double, the system at 20/20 level would be taking 4 times as many trades.
So, for the purposes of comparison, we get 2.2 * 4 = 8.8
20/20 has better theoretical expectancy than 40/40!! Why??
Let's look at the simulation.
Ouch! It doesn't perform better anymore than the previous step up. Why not? 20/20 was better than 10/10.
But 40/40 is not better than 20/20.
It took us less trades at 40/40 (112), BUT by the time we get to 112, the 20/20 system already finished (remember, it takes 4 times as many trades. So by the time 40/40 finished 112 trades, 20/20 would have completed 448 trades... but it finished in only 218).
I think the answer lies in the fact that once vig (commission/slippage) has become sufficiently small (how do we calculate this without going through every case?), what becomes more important is the number of trades taken at 60% winning.
It seems there's a 'saddle' transition point somewhere. Vig becomes relatively small, and leveraged compounding multiple times within a fixed timeframe becomes more paramount.
Any thoughts? Harry?
You are never in the wrong place... but sometimes you are in the right place looking at things in the wrong way.
Now that thanks to Harry I have access to a quick and dirty simulator , I want to go back to the original question. Which is the best:
1) 40% @ 1:2 RR ('trend model')
2) 60% @ 1:1 RR ('low R-multiple model')
or
3) 75% @ 1:0.5 RR ('scalping')
As Harry already posted simulations for the first two, here's a simulation for scalping.
75% @ 1:0.5 RR
UGLY. It took us 991 trades to reach the target.
75% @ 1:0.5RR seems worse than 60% @ 1:1 RR.
What if we improve by 'only' 5%?
80% @ 1:0.5 RR
Surprising!! Improving from 75% to 80%, the time to reach our target was reduced by a factor of 10!!! This confirms my initial thesis, that trading edges are small, and 'small' improvements have very large consequences.
All of a sudden, MUCH better than 60% at 1:1 RR!! It took us only 99 trades instead of 218 (or 450 or 991). And optimal f is significantly higher than any of the other simulations.
So, scalping seems like a great choice at 1:0.5 RR, BUT you must bat 80% (on a reasonable timeframe where your vig is 10% or less of your SL).
You are never in the wrong place... but sometimes you are in the right place looking at things in the wrong way.
@Anagami: First of all, I agree with your findings. The 40/40 system only requires 112 trades as compared with 218 trades of the 20/20 system. Based on volatility expectations, however the 20/20 system should still achieve its target first. This suggests that there is an optmimum size, as
-> commissions and slippage destroy any system that has too narrow stops and targets
-> the trade frequency is low and drawdowns are high for systems which have wide stops and targets
In this case the risk adjusted Optimal F is slightly higher for the 40/40 system (4.22% versus 3.14%), but as your stop is wider, you are only allowed to trade 20 contracts with the 40/40 system, while you may trade 29 contracts with the 20/20 system - a 20 point stop on 29 contracts equals $ 2,900 and is less than a 40 point stop on 20 contracts, which equals $ 4,000.
The narrow stop of the 20/20 system allows you to trade more contracts, but at a lower value for Optimal F with the same risk of ruin.
Your conclusion is correct, there is an optimum size which of course relies on all the dubious assumptions, such as the relationship between time and volatility, slippage and commissions, and the model parameters such as the 1:1 win/los ratio. The model tell us that the optimum size to trade is 18/18, that is a profit target of and a stop loss of 18 points.
But it is only a model based on a Bernoulli Distribution.... so do not take this as the ultimate wisdom.
@Anagami: Very dangerous conclusion: You have a nice system and you hope to make a win rate of 80%. If the win rate drops by 10% to 72%, your expectancy drops to zero.
The problem is that the model calculates the fixed fractional amount based on the assumption that you have a known edge. This would hold true for card games, at least over the period during which the rules of those games are not changed. Trading is a game with ever changing rules, so there is an additional risk that the backtested or assumed edge does not exist.
No model covers the model risk, and here the model risk is huge, as it includes the assumption of a known and stable edge. Also there is an operational risk. Would you feel happy if you ran a position of 64 contracts of YM with an account of $ 100,000? The favorable results with the win rate of 80% heavily rely on leverage. The leverage is suggested by the Optimal F model, because it ignores model and operational risks.
Models simplify, so they should not be applied to reality without care. If I was to trade anything like this, I would rather rely on a Monte Carlo Simulation of a backtest and a forward test then a model. The model should only be used for understanding the basic mechanisms, for example it is certainly interesting if a model postulates that there could be an optimum size for trades.
If the win rate in the 60% 1:1 RR model drops by 10%, then one's expectancy is much worse than zero.
Thinking about it, I have to agree with you. Yes, the results with the 80% scalping do rely heavily on leverage, and no, I would not be comfortable with 64 cars of YM with a 100K account.
There seem to be much greater unstated risks in the 80% 1:0.5 RR model (scalping) than in the 60% 1:1 RR model (low R-multiple).
You make a strong case against scalping, one that I cannot argue with.
You are never in the wrong place... but sometimes you are in the right place looking at things in the wrong way.
The case against scalping is a case based on commissions, slippage and the spread. There is no argument against scalping if
-> you do not pay retail commissions, but have an exchange seat and lower rates
-> you trade a highly liquid instrument, where you do not experience slippage
-> you enter via limit orders in order to avoid to pay the bid-ask spread (market maker strategies)
But being a retail trader and paying the commissions that I have mentioned, I am not in this game for good.