In the last episode of Trading the Shortstack, we identified two of the most important tasks a trader must accomplish in order to be successful in his battles against the large hedge funds and investment banks that lurk behind the level II screen or in dark pools waiting to fleece him; extreme patience when selecting a trade and risk management when entering it. In this and the following episode, we will examine a risk management model that incorporates those two ideals into a system that can be adopted by any trader to suit their needs.
If you have ever walked across a casino floor, you have witnessed the siren's call of the roulette scoreboard as gamblers swarmed to it whenever they saw an improbable streak of results such as 15 blacks in a row. They crowd around the table to bet on red under the flawed assumption that it is “due”. This flawed assumption is known as the gambler's fallacy. The gambler assumes that a random event is more likely to occur because of the amount of times it has or has not occurred in the recent past. A classic example of this mistaken logic is that if a coin lands as tails four times in a row, it is more likely to land as heads on the next flip. Most people will figure that the odds of tails hitting five times in a row is so low (1 in 32) that the next flip must be a heads without fully understanding that for any set of five flips, the chances are exactly the same that four tails will be followed by a head on the last flip (also 1 in 32). So what on earth does all this talk of gamblers and math have to do with trading anyways? I'm glad you asked.
The fact that incredible streaks that defy statistical odds occur all the time should reinforce the idea that a trader must always limit the amount of money they are willing to lose in a trade in order to protect themselves from such an occurrence. After all, the odds of the ball landing on a black space on a roulette wheel are about 47%, a number that is probably very close to the success rate of an average trader and I personally have seen bizarre roulette streaks that reach the mid-twenties. A better than average trader maybe makes money on 60-70% of their trades, and they can still at any given time hit a rut and lose perhaps 10 trades in a row. Even if a trader was disciplined and always stopped out on his trades, if he risked 5% of his account per trade, he would see his account halved by such a slump. Because of this, I am of the belief that a trader should never risk more than 1-2% of their account. Risking 1% of their account on each trade, a trader would have to lose 50 trades in a row in order to lose half of his account. As a matter of fact, if a trader just focused on following this one rule, he could probably break any number of other rules and still find it nearly impossible to blow up his account.
One thing to keep in mind is that this is the amount of money he will risk on a stop out, not the amount of money he will deploy. For instance, let’s say Joe Twitter just opened up a trading account and funded it with $10,000. Knowing that protecting his capital during the infancy of his account is priority number one, he decides to risk 1% ($100) per trade. If he buys XYZ stock which is trading at $10.00 per share and feels that he should stop out if it drops below $9.50, then he would purchase 200 shares. While the total amount of money he is deploying in the trade is $2,000 which is 20% of his account, he is realistically only risking the $100 it would take to stop out barring any unforeseen circumstances in which the stock gapped below his stop out point. Managing the risk involved in these “black swan” events is a topic that will be discussed in the future.
Once a trader figures out the amount he will risk in this manner, it should become the primary focus of all potential trades he will examine. In fact, the point at which he will stop out should be the first thing a trader looks for anytime he analyzes a chart. If a trader can adopt this mindset, he will have overcome the biggest threat to blowing out his account which is the bad habit of letting losses grow well past acceptable levels. Controlling losses in this manner will automatically improve a trader’s consistency by eliminating wild swings in the loss column due to erratic sizing. Sticking to this plan also prevents a trader from attempting make up for previous losses by trading in a bigger size than would be prudent for his account. Once a trader can perfect the management of his risks, he is ready to focus on the fun part of trading, his rewards.
So now that Joe Twitter knows that he will risk $100 on each trade he takes, he must figure out the amount he hopes to make on each trade. Assuming he wins on about half of his trades, he will have to plan on making more than $100 on each of his wins, as that will get him nowhere fast once he accounts for commissions. This is where patience becomes key, as a trader should ignore all setups that do not offer at least 2 times the rewards as the amount they should risk. Many traders in fact would not enter a trade unless it offered a reward to risk ratio much higher than that but it is up to the trader to figure a multiple that works with the type of trading they do as some styles lend themselves to much higher risk/reward ratios than others. The important thing to remember is that the trader never enter a trade in which he doesn't plan on making at least twice as much as he loses as that will allow him to stay profitable as long as he can hit on one third of his trades. Survival should always be the first thing a trader thinks about. Much like a great hitter in baseball, he should focus on hitting singles not homeruns…if he takes the right approach, the homeruns will follow.
Stay tuned for the next episode in which we will examine the importance of waiting for a setup that offers the requisite rewards to justify the risk we are willing to assume in a trade and illustrate this concept with some sample trades.
If you have any questions or comments, feel free to contact me on twitter @stockdarts or in our great chat room if you are a stockguy22 member.