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It is my hope you will find this info valuable and can use it to further explore some better trade management, risk management and overall money management systems.
"Let us be thankful for the fools. But for them the rest of us could not succeed." - Mark Twain
I mentioned this in the NT forum thread concerning this, but it might be worth repeating here. In my opinion, expectancy is a useful bit of data to know about your trading system and evaluate risk/reward, but it is not a very good way to optimize a trading system. The reason is that the expectancy number ignores the number of trades. Expectancy will be higher for a system that averages $100 per trade but only trades once a week compared to a system that earns $50 per trade and trades every hour. For this reason, I'd definitely recommend SQN over expectancy for optimizing. An exception to this might be if you are optimizing a strategy that you only want to trade occasionally, and you are willing to invest your money in alternative strategies when this one isn't issuing signals. In that case, having a system with limited signals (but high expectancy) may not be a problem.
i wrote a custom formula that weighs the net profit, expectancy, and number of trades per day. it throws out (return double.NegativeInfinity) values that also have fewer than a certain number of trades per set/job.
i am really finding it quite useful. i like SQN as well but like expectancy better with my custom weighted formula.
still what you've said is absolutely true.
"Let us be thankful for the fools. But for them the rest of us could not succeed." - Mark Twain
I think that I like 'expectancy score' better because it also takes into account time. I found it at URC Trading - [AUTOLINK]Expectancy[/AUTOLINK] Score vs Sharpe Ratio and is expectancy * opportunity where expectancy = (aw*pw+al*pl)/|al| and opportunity = # trades * 365/studydays. A good explanation is provided at the link I gave.
Since Trade Your Way to Financial Freedom, Tharp has expanded on the concept of system quality by creating a variation of the Student's T-Test called System Quality Number (SQN).
This formula takes frequency (N), reliability (Standard Deviation of avg trade), and expectancy (Avg Trade) and produces an objective score of any system.
Tharp goes into more detail in his book, The Definitive Guide to Position Sizing.
I find SQN to be a much better measure of a system's overall performance than expectancy alone.
I understand about SQN, but I think it is lacking because it does not take time into account. An investment that returns 10% in 2 days is better than an investment that returns 10% in more than 2 days.
Expectancy score is NOT the same as expectancy. It uses expectancy and then multiplies by opportunity, which is where time is factored in.
To my way of thinking, time is a critical element in any trading or investing strategy.
He mentions early in the thread that he only got the "expectancy score" version working.
I now had a look in the Expectancy optimizer type. The following formula is used:
expectancyTemp = (aveWin * percentWin + aveLose * percentLose)/ Math.Abs(aveLose)
Note the devision by the absolute value of the losing trades - which may not be what everyone thinks it should be.