If I have three trading systems with the following Pwin/PLoss, I would assume that the Prob Ruin for the higher expectancy systems would be lower (when the Loss Amount is normalized but when I run the calculations on Pruin (I do an equation and a Monte Carlo) I see that the higher expectancy ones are seeing slightly higher Pruin. What am I missing here:
#1
Pwin: 0.371, Win: 973 pips
Ploss: 0.629, Loss: -317 pips
Expectancy: 161.7 pips
#2 (After normalizing to #1's Loss amount)
Pwin: 0.326, Win: 1221 pips
Ploss: 0.674, Loss: -316.8 pips
Expectancy: 185.38 pips
#3 (After normalizing to #1's Loss amount)
Pwin: 0.306, Win: 1350 pips
Ploss: 0.694, Loss: -316.7 pips
Expectancy: 193.77 pips
The monte carlo results for a 5,000 pip account (assuming 5k account with 10k lot size) shows the following Pruin values:
#1: 2.8%
#2: 3.7%
#3: 5.0%
I guess the bottom line is that I would expect that the higher the expectancy, the lower the Pruin. This assumes that your account is big enough to let the expectancy ride its course each time.
I have the same loss amount. The Ploss is different and I can see someone saying that is the reason why but intuitively it doesnt make sense since the expectancies increase while the Pruins increases. That doesnt make sense to me.
What do you think?
Well, generally what I think is that as traders, when we start researching these stats, we quite simply forget to work on ways of using the very quantitative mathematical methods we are calculating to improve our trading, in ways that are actionable so as to assist in actually turning a profit.
with that said... i think the reason you are seeing the increase in expectancy increase synchronously with your probability of ruin calculation is because you are calculating your figures on back dated data without taking into account how you would actually trade each system... i think, just a theory.
for example, you mentioned something about "holding out" for the expectancy to come through, and in doing so, this would also increase your Pruin.
I think what you have to remember, well what we all have to remember, is that these statistical and mathematical tools, no matter how you calculate them or what you actually calculate to measure your performance, must ALSO be measured against your actual performance in a way in which you can incorporate Risk Control metrics that work within the parameters of the system you are testing.
what I am getting at is that when looking for a "holy grail" system and in attempting to curve fit your results to find the optimum system that achieves the absolute highest Expectancy, you risk forgetting about the minimization of RISK that we must all employ, which if built into the metrics calculated within your system, would help in finding a balanced system where your Pruin is also minimized.
When you find this happy medium, however, i think you will find that the expectancy will be much lower. but, the Pruin will also be stabilized too.
What does all this mean though? How can it be turned into some thing actionable??? :?:
That I believe is the tougher part of the question. I think the answer lies not just in the expectancy, as the real measurement you should concern yourself with at the beginning of every trade should not be how much you are going to win, but rather how much you are going to lose.
The answer lies in measuring you actual Risk per trade and how you actually performed against the stated risk you said you were going to take on by executing the trade, FROM THE BEGINNING OF THE TRADE.
A guy by the name of Van K Tharp did some research on what he calls an R-Multiple.
What is an R-Multiple???
If Risk is defined as how much you'll lose per unit of your investment (i.e. # of forex contracts) and you are wrong about the 'given' position, then the 'initial' Risk associated with the 'given' position is called 'R'. Or, 1R.
Example: If you buy a stock for $10 per share and it drops to $5 per share, your initial Risk for that particular trade is $5 per share. So in this example, 1R is equal to $5. If you buy 100 shares, then your total risk is $500...
R Represents a method in which to compare the initial risk of different trades equally and objectively against all other trades, and it therefore represents your initial risk per unit. the reason you want to objectively quantify this info is because all of your profits & losses should be related to your PREDETERMINED initial risk. you want your losses to be 1R or less. that means if you say (before you get in the trade) that you will get out of the stock when it drops from $10 to $5, then you actually get out when it gets to $5. If you get out when it drops to $0, than your loss is much bigger than 1R. its twice what you planned to lose or a 2R loss. you want to avoid that situation at all cost. as a matter of fact you want to keep all losses as close to 1R as possible or less...
the opposite holds true as well. the few times when the trade DOES go in your favor you want to hold those trades as much beyond a 1R Gain as possible. that means that when the market decides to reward you, you must close the position in the given example at $25, therefore giving you a 3R Profit or 3 times the initial risk...
This is the mathematical procedure of ensuring that you cut your losses short & hold your winners longer...
but its difficult to get that info out there, i know.... The R-Mulitple is simply the Division of the Total Profit or Loss (including commissions & Fees) by the Initial Risk. You want to keep this as close to 1 or greater than 1 as possible.
ill tell you though, most of my winners are 1 to 1 with a few 1 to 3 Risk/Reward Ratios, so it is difficult to achieve trades with higher R Multiples but it is possible... hope that helps... you should check my site and follow me on FB & Twitter, I publish all my trades for free: @TakeYourProfits Goodluck let me know if that helps...
that's my take anyways; you're not getting a decrease in your Pruin because you havent established an actionable way to actually control your Pruin.... measuring and applying the R-Multiple is what your missing....
