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— By Matt Haines from Throwing Good Money After Bad

A common tactic for some traders is to scale out of successful positions. The logic is this: I’ve already made some money, so I want to hold onto some of that. I’ll cash out a portion of my trade now, and see how the trade continues, but with reduced risk. You see this behavior with day traders, as well as long-term investors.

But it’s a fallacy.

And it’s costing you money.

Let’s devise a thought experiment to isolate the scaling out portion of a successful trade.

Imagine you have a trading system where you can invest $100 each time (no commissions or fees), and are guaranteed to double your money the first day. Pretty cool, huh? But the second day’s trade is a toss-up: you have a 50/50 chance of either doubling your money again, or cutting it in half (bringing your position back to your starting point). You have to exit after that second day, regardless. Here’s a diagram to demonstrate that:

But then you realize you could hold onto some of those winnings by scaling out. So after your guaranteed-win day, where you double your money, you decide to cash out half (your original investment of $100) and let the remaining $100 ride. That remaining $100 has the same 50/50 chance of either doubling or being cut in half. You’d either end up $300 or $150 (i.e. [ $100 + ( $100 * 2) ] or. [ $100 + ($100 / 2) ] ).

Oh sure you don’t make as much profit, but you also don’t suffer as much loss. How would that look over time?

I generated 10 equity curves each for the normal “all in” system and the scaling-out system, with a random 50% chance of winning that second leg of the trade. The red lines are the “all in” system, and the blue lines are the scaling-out system.

“Yeah okay Matt, but my system isn’t just due to chance. I’ve got an EDGE! My second leg is going win 55% of the time!”

So what? You’re still leaving money on the table if you scale out. Here’s what a bias toward winning looks like.

“But Mr. Haines, I’m scared. My system makes money, but that second leg… it’s a sketchy thing. It only works 45% of the time. I want to be conservative and hold onto some of my winnings.”

Here’s what those equity curves look like when the win rate is biased to only 45% of the time. The lines are closer together, but the “all in” system is still superior to the scaling-out system.

At this point you might be thinking to yourself: hey, that’s all very tidy to have things double or half, but that’s not realistic. What if the returns are asymmetrical? What if the losses are higher than the gains?

Let’s devise a crushingly risky system. You invest $100. You’re guaranteed to make $100 that first day. But day 2 can give you a smack in the behind. It still has a 50/50 win/loss likelihood. If it wins, you double your position. But if you lose, your position is reduced to 20% (i.e. x 0.2). No longer can you be guaranteed to hold onto your first day’s winnings.

The all-in system:

• invest $100

• day 1: guaranteed doubling to $200

• day 2: your position is either $40 or $400

The scale-out system:

• invest $100

• day 1: guaranteed doubling to $200. You sell half and keep $100.

• day 2: your remaining position becomes either $20 or $200, for a net of $120 or $300.

Was that what you were expecting? I’ll bet not. Yes the lines for each system wander further afield in this system, but the all-in system still beats the scale-out system. Even with the asymmetrical skew toward bigger losses.

If you’re considering the use of scale-ins or scale-outs in your trading system, it’s imperative that you treat each leg as a separate trade (with the corresponding reduced position/commission ratio, different signal quality etc.). If you think that a system showing momentum is likely to continue showing momentum, then you’re better off staying all-in than reducing your position size. And conversely, if you think it’s going to fail, then get “all out”!

Perhaps there are instances where scaling in and out are in fact more profitable. If you can cite some examples (preferably not just anecdotal, although those can be fun too), please do so in the comments!

— By Matt Haines from Throwing Good Money After Bad

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