For the same reason I would not blot all my personal info on my tax returns then mail it to all my neighbors.

But really it is a waste of time. I could quite easily create a fake statement and make every one oooh and ahhh. Point being any statement posted here by anyone cannot be proven to be real. So there is no reason to make effort to do so or request anyone else to do so.

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).

Correct.


The 20/20 system cannot take the same number of trades over the same time period, but I had already taken it into account! Based on the square root relationship between volatility and time, I had made an estimation that the 20/20 system will be able to enter only one trade, while the 10/10 system enters 4 trades. This assumption is realistic, you can compare the average true range from N-minute bars with the average true range from 4xN-minute bars, and will find that it is approximately the double.

If you read my post attentively you will also understand that I have not directly compared the 6302 trades needed by the 10/10 system with the 218 trades of the 20/20 system, but I have used the above approximation to state that the 10/10 system will be able to take about 872 trades while the 20 /20 system takes 218 trades.

But even after 872 trades (4-times as many as the 20 point system) the 10/10 system is far from reaching the target. I will take about 7 times (!) as long to achieve its target, as it has to generate 28 times as many trades.



The 20/20 system needs 28 times fewer trades (218 versus 6302), and will reach its target about 7 times faster. It is therefore both faster in terms of trades and in terms of time.


Have added the 15 min charts of ES 06-12 from last Friday with the ATR(256) calculated from the primary bars (red) and the ATR(25) calculated from 60 minutes bars (blue)=. The approximation which I have used postulates that the
ATR from the secondary bars should be about twice the size as the ATR from the primary bars, and this is indeed the case, as 3.16 is about the double of 1.64.

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!

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:

Risk of Ruin As @TheTrend ( is busy, I have enhanced the spread sheet. The left part of the spreadsheet is used to adjust Optimal F for the tolerated risk of ruin, when you start off with your trading strategy. The right part of the spreadsheet allows to calculate …

The ratios are calculated as follows:

winning trade = 20 points - 1.8 points slippage and commission = 18.2 points
losing trade = - 20 points - 1.8 points slippage and commission = -21.8 points

Then divide 18.2 (winning trade) by 21.8 (losing trade) and you get 18.2/21.8 = 0.83

Accordingly for the 10/10 system you would obtain 8.2/11.8 = 0.69

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).

20/20 System @ 60% Winning
(0.6)(18.2) - (0.4)(21.8) = 10.92 - 8.72 = 2.2 points

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.

40/40 System (60% Winning)
(0.6)(38.2) - (0.4)(41.8) = 22.92 - 16.72 = 6.2

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?

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).

@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.

Expectancy at 80% : 0.8 * (10 - 1.8) * $ 5 - 0.2 *(20 +1.8) * $5 = $ 32.80 - $ 21.8 = $ 11
Expectancy at 72%: 0.72 * (10-1.8) * $5 - 028 *(20 + 1.8) * $5 = $ 29.52 - $ 28.00 = 0.52 $

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.