R-Multiple™ Distribution Graph

R-Multiple™ Distribution Graph

The concept of an R-Multiple™ was pioneered in 1993 by trader Chuck Branscomb, who explains that this technique is "The most important way to look at systems." The idea came about as a way to equate all markets and get away from looking at expectation in currency terms." R-Multiple™s were popularized by Dr. Van Tharp in his book, "Trade Your Way to Financial Freedom".


An R-Multiple™ is simply the profit or loss for a given trade divided by the entry risk. The entry risk is defined as the difference between the entry price and the stop price at the time of the entry.

Click to Enlarge; Click to Reduce.

R-Multiple Distributions Graph

The R-Multiple™ Distribution graph accounts for every closed trade in the simulation, both winning (green) and losing (red) trades. For the test reflected in the graph above, there were a total of 807 trades. Of 292 winning trades, 105 fell in the range between 0R < 1R. Continuing to the right, 47 winning trades had R-Multiple™s between 1R < 2R, and 38 trades fell in the bin of trades in the range 2R < 3R, etc. Note that 14 winning trades had R-Multiple™s of 15R or greater.


The histogram of Losing Trades (above, left) shows that the vast majority of losers were of a magnitude of -1.5R or less, with 393 trades (out of a total of 515 losing trades) less than -1.5R.


The thin lines above the bars of the histogram are cumulative plots. Note that two scales apply to the vertical axes: on the outside is the Number of Trades, and on the inside is the Cumulative Percentage. For Winning Trades, the starting point of the cumulative plot (<1R on the horizontal axis) contains 105 trades. But the next data point (the 1R < 2R bin on the horizontal axis) grows to 152 trades (105+47) on the right vertical axis, and encompasses slightly more than 50% of all winning trades, according to the left vertical axis.


As can be clearly seen, the Losing Trades were relatively well contained: The cumulative plot line shows at a glance that roughly 90% of losers were of a magnitude of -1.5R or less.


Edit Time: 6/25/2017 9:43:30 AM

Topic ID#: 4006


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