| RESULTS FOR DAY | |
|---|---|
| CL Contracts: | 10 |
| Net $P/L: | 506 |
| Wins: | 7 |
| Losses: | 3 |
| Win%: | 70 |
| Avg$Win: | 96 |
| Avg$Loss: | -54 |
7 hours ago
Friday, May 11, 2012
Fri. 5/11
1:45pm CDT - Another nice day. This latest system (only 2 days of live trading) has 10 tick target, 30 tick stop loss and if price moves 15 ticks against position, target moves to a 5 tick loss. No -$300 trades the past 2 days but they do happen in backtesting. For the week, net gain of $302.
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I see plenty of mention invert risk/reward ratio but not negative target strategy.
ReplyDeleteCory - can you explain "negative target strategy?" I've never heard the term.
ReplyDeleteAs far as 1:3 Reward:Risk ratio, that can work, with high enough winning percentage. As I'm sure MBA and most here know, it all come down to positive expectancy (positive trader's equation).
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ReplyDelete>target moves to a 5 tick loss.
ReplyDeletethat is negative target strategy.
Gotcha, thanks Cory!
ReplyDeleteI think what's most important has already been mentioned above. If MBA's back tested method has win% is high enough, a 1:3 ratio could easily work. A 1:1 ratio may not be realistic if MBA tries for a 30 tick target.
ReplyDeleteAlways a good thing to finish the week on a positive note.
ReplyDeleteI take it the determination of risk/reward as well as where to place the negative target trigger was done via backtesting results?
Thanks for comments.
ReplyDeleteYes, this was backtested and I realize having more risk than reward is against what everyone preaches. But I've never been a conformist. I'm still testing various filters to improve results but don't want to over optimize either. Kevin is right, it all comes down to overall positive expectancy.
1:3 80% win
ReplyDelete1:1 60% win
2:1 40% win
All have the same .2 expectancy. I think a 1:1 strategy is a little better but they should all be similar.
@Anon -
ReplyDeleteActually, 1:3 Reward:Risk with 80% wins yields expectancy of 0.0666. (You need 90% win rate with 1:3 to get 0.2 expectancy).
A 1:2 Reward:Risk with 80% wins yield expectancy of 0.2.
Your other two examples are correct.
(1*.8)+(-3*.2) = 0.8-0.6 = 0.2
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ReplyDeleteAnon -
ReplyDeleteMy apologies. We are talking about 2 different expectancy calculations:
Your method - http://www.tradermike.net/2004/05/trading_101_expectancy/
which is also the average profit per trade.
My method - http://unicorn.us.com/trading/expectancy.html
which is the average net profit divided by the average loss
I think the confusion was created by Dr. Van Tharp. In "Trade Your Way To Financial Freedon" he shows the formula you use. In a later book "Definitive Guide To Position Sizing" he says that method 2 is correct, and method 1 is incorrect.
Dr. Tharp also states that this "error" was corrected in the Second Edition of "TYWTFF." So, the second edition of the book uses method 2.
If anyone wants further info (it is confusing), just drop my an e-mail.
Sorry for the confusion!
I have posted Van Tharp's Expectancy explanation here:
ReplyDeletehttp://www.kjtradingsystems.com/expectancy.jpg
Thanks
ok - I havent read van Tharp. I use expectancy to mean average profit/trade. I also use a calculation similar to what you mention called profit factor or $win per $ risk. So if you risk $300 to make $100 then your PF = (100 * .8) / (300 * .2) = 80 / 60 = 1.33. The 1:1 risk example has a PF of 1.5 which is why I said it was preferable.
ReplyDeleteThanks guys. Everything I've ever wanted to know about expectancy calcs but was afraid to ask! LOL
ReplyDelete