A Foundation for Long-term Success

At the end of the day our success as traders is based on the equation below returning greater than 1:

(Average $ Win x Win Rate) – (Average $ Loss x Loss Rate) = >0.

To produce the desired result we need to consider three factors:

  1. The Win/Loss Rate. Elsewhere I have postulated why the Win or Loss Rate is largely outside our control. (see Ebb & Flow in Position Sizing 2).
  2. Our Position Sizing (see Position Sizing and Position Sizing 2)
  3. Our entry and exit. These are two factors totally within our control.

In this blog I want to examine entry and exit strategies that will maximize the probability our losses will be less than our profits i.e. our Avg$Win will be greater than our Avg$Loss. In the process, I’ll use my most recent AUDUSD to illustrate the ideas.

We’ve often heard that the key to our trading success lies in the maxims, ‘cut your losses and let your profits run’ and ‘never let a profit run into a loss’. As stated, the advices are next to meaningless. (!)

Let me ask you this, what would constitute ‘profits’? If I entered, say Gold long, at 970 and the market declines to 969, should I cut the position? Or if Gold runs to 995, should I not take profits? Or if Gold first goes to 971 and then declines to 969, have I let a profit turn into a loss?

The key to all these questions lies in our initial stop loss. This is the benchmark for our risk management positions. We cannot consistently take smaller profits than losses and hope to succeed. Here I am not talking about the times when the market tells us our analysis is incorrect and therefore it’s time to exit. So we exit with a small loss or profit. No, here I am talking about a perspective of a large sample size. If on the whole, we find that we take larger losses than profits, we’ll find we fail as traders.

Yet my experience with traders shows that this tendency to consistently grab profits smaller than our stop loss is the strategy employed by most newbies. Oh, there will always be a good excuse: a change of timeframes; a change in the condition of the market etc. But the fact remains that if we examine their data, we’ll see consistently larger losses than profits.

Let’s have a look at the AUDUSD. I sold the AUDUSD at an average price of .9600. My stops was .9768, a risk of 168 points. Figure 1 shows the target to be around .9100 to .8955.



Figure 2 shows the support zones on an 18d basis.



Notice too that there is intra-day support at 9493 to 9515. (See Figure 3)



Armed with support zones, let’s see an application of the risk management approach I favour.

My stop is 168 points. As long as I see no evidence that my original analysis is incorrect, I’ll risk the bounce from the intra-day Primary Buy Zone. Of course I’d love for the market to break that support zone at its first attempt but there is nothing in my analysis that says it must; indeed I rate a bounce as a 40% probability.

If the market bounces back up to the .9600 area, I’ll be feeling some heat; so should I exit at the .9500 zone? If I KNEW that the market would bounce, the answer is of course. BUT I DON’T KNOW if it will; it may and then again it may not. If I take an .80 profit and the market proceeds to my target, I’d have risked 168 points for an 80 point when there was much more to gain.

If I do this over a large sample size, I’ll need a Win Rate of around 70% to be profitable and for my trading style that would neigh be impossible. So, I would have to forgo taking profits at this level and run the possibility of being stopped out. I’d have to treat the move to the .9500 as noise.

Note that if I were trading a different timeframe with a different stop structure, I may come to a different conclusion.

The next support level is the Primary Buy Zone at .9365 to .9325. If I took profits at .9370, I’d make 230 for a risk of 168. At this point, I can start thinking of protecting my position.

The stop in this case was a little wider than normal, so I’d amend the normal Rule of Three process (see Risk Management 5). I’d take profits for 1/3 of my position and bring my stop down to 67% retracement area of the zone .9667 to .9327 (Top of Value). I’d bring the stop on the remaining position down to breakeven.

If all goes well, I’d liquidate the rest of the position at my target zone around the .9100 area.

By employing our initial stop as a benchmark we’ll go a long way against mathematically taking premature profits, a step that guarantees long-term failure.

Tomorrow I’ll look at the S&P. The market generated a buy signal today.

11 thoughts on “A Foundation for Long-term Success”

  1. Ray, could you explain a little bit why “(Average $ Win x Win Rate) – (Average $ Loss x Loss Rate) = >1” NOT “(Average $ Win x Win Rate) – (Average $ Loss x Loss Rate) = >0”. Thanks.

  2. Hi

    My error. You are correct, the formula should be greater than 0 not greater than 1.

    Thanks for pointing that out. I’ll amend my post.

  3. another great post from you, as usual,seems like the bionic hip man is back in action! wish you a speedy recovery..

  4. PPS

    While multi-tasking, I was listening to Martin Pring on his video and what caught my attention was his admission: I hate mathematics but I love indicators!

    Same applies to me, although I was quite good with Additional Maths in school; after passing the exams, I just want to forget about formulae.

    More right-brained, I like to look at the big picture ie a positive result eg rather than to think in terms of digits!

    So when vetting articles for Ray, I tend to skip over formulae, leading to the errors as spotted by a sharp-eyed reader.

    Now I need to overcome this aversion.

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