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Trader Mind Tricks
By Boris Schlossberg | Published  12/4/2011 | Currency , Futures , Options , Stocks | Unrated
Trader Mind Tricks

Let’s say I told you that you could make 25,000 dollars by risking 25,000 dollars. Would you take the bet? Probably not. Like most people you would want to be able to make at least 50,000 dollars on 25,000 dollars worth of risk. And therein lies the problem.

Psychological studies have shown that human beings feel the pain of loss twice as intensely as the joy of winning. In short you would be much more upset about losing 10,000 dollars than be happy about earning the same 10,000 dollars. Out of that quirk of human nature traders developed the classic 2-1 risk to reward rule looking to make $2 of profit for every $1 of risk exposed to the market.

On the surface the 2-1 risk reward system sounds so attractive. Just be right 50% of the time and you make money! Heck you can even be wrong 6 out 10 times and still be profitable! How hard can that be? After all, flipping a coin will give you a 50% chance of success.

This is precisely the type of thinking that gets novice traders in trouble. First of all, disabuse yourself of the notion that on any given trade you have 50-50 chance of success. It that were true we would all be billionaires by now. As my friend Tom Sossnoff used to say when he ran ThinkorSwim brokerage business, the actual odds on any trade are more like 25% - 75% against the trader. The reason is because you are not trading against some predictable number generating machine but against many wily human beings whose primary function is to trick you into making the wrong move. Speculative trading is the art of separating suckerx from their money and as some wise old man once said if you are sitting at a table and don’t know who the sucker is, you are it.

Let me explain in detail why 2:1 risk reward strategy is so difficult to implement successfully, especially on a day trading basis. Let’s say you are trading a strategy that risks 10 pips of loss to gain 20 pips of profit. Since prices very rarely move in straight lines here is what’s going to open. You enter the trade and get stopped out. You enter again and get stopped again. On the third time the trade may go 10 points in the money but will then pause, retrace and stop you out again. On the fourth time you may finally get that clean 20 point run but even if the trade goes to profit you will be net negative 10 points for the day because of all the back and fourth slippage. The tighter the stop the greater the chance of stop out. That’s just the nature of the game and that’s why 2:1 risk reward strategies rarely make it in speculative day trading markets like FX. They may work on longer term horizons, but since I’ve never held a trade for more than 72 hours in my life I wouldn’t know.

What I do know is that there is no “perfect” risk reward strategy for short term trading, but over the years I’ve come up with some guidelines that seem to work relatively well. First and foremost I never make my stops less than 50 points. This is by no means a definitive rule, but after tens of thousands of trades I’ve found that 50 points is the just the right balance between avoiding the repetitive stop-losses and getting out when you are clearly wrong.

As to my limits I find that setting your take profits at 70% of amount risked is a reasonable compromise between fear and greed. This approach requires that your strategy be right 65% of the time but by flipping the risk reward ratio to a slightly negative skew it becomes a lot easier to achieve that goal.

Trading is a wonderful activity, but on the the short term horizon where we ply our craft everyday it can be a little like quantum physics where the normal laws of Newton do not apply. What seems logical is actually foolhardy and what is foolhardy is actually effective. So beware of these mind tricks next time you do a day trade and remember that taking less and risking more may not be psychologically palatable but could be financially rewarding.

Boris Schlossberg serves as director of currency research at GFT, and runs bktraderfx.com.