N-Bar win rate

Thanks for the link. didnt know that the author has a blog. some interesting reads there like his definition of price action trading.
 
Quote from goodgoing:

Do you agree that the sooner the exits occur the better the trading system? or that trades should have about the same lifetime?

This is what is argued in this blog post:

http://www.priceactionlab.com/Blog/2010/11/n-bar-win-rate-of-trading-systems/
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Net profit is equal to expectancy x number of trades. The less the trades last the more of them you can have, otherwise you have to increase size, capital and run into other problems. So, I agree with the author. the defition of win rate based on trade duration is a very interesting concept.
 
The bigger your size, the more liquidity is an issue. You should measure the available liquidity at the prices you buy and sell to determine if those signals are still valid as your size increases.
 
I just calculated my N-bar win rate for N 1,2,3 for my real trading results (not simulated) and it is as follows:

w = 74.12%
w(1) = 39.1% day trades
w(2) = 10.4%
w(3) = 16.7%

About 40% of my trades are winner day trades and the remaining 34% are winning position trades. This is an outcome of my R:R and I need to reduce the position trades without adversely affecting w(1).
 
Quote from goodgoing:

I just calculated my N-bar win rate for N 1,2,3 for my real trading results (not simulated) and it is as follows:

w = 74.12%
w(1) = 39.1% day trades
w(2) = 10.4%
w(3) = 16.7%

About 40% of my trades are winner day trades and the remaining 34% are winning position trades. This is an outcome of my R:R and I need to reduce the position trades without adversely affecting w(1).
More...

Is this system based on something like hourly or 4H data? or it just happens that 40% of trades of a daily EOD system exit on first bar?
 
I monitor both duration and time as the trading session progresses. This is particularly important from the opening. I keep comprehensive logs of each day in the form of numbers. This is leagues on from logs kept in words.

Logs kept in numbers cannot help but be statistics and through the parameters (or filters) that you apply to your store of statistics you are able to get an accurate general read not only of the day ahead but also of the day as it progresses. The metrics of the market you trade accordingly become familiar territory. The day to play has already got derived statistical numbers before the opening and this enables you to place it in the correct subset for reading the day ahead.
:)
 
Quote from intradaybill:

Is this system based on something like hourly or 4H data? or it just happens that 40% of trades of a daily EOD system exit on first bar?
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Daily and 60min bars. It rocks!
 
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