One of the biggest "grey areas" in trading is knowing when to sell a position that is at a gain. It's certainly much easier to develop rules for when to buy a stock (i.e. buy fundamentally-strong stocks breaking out of sound technical bases on powerful volume) and when to sell a stock at a loss (i.e. never let a stock fall 5% below your buy point). Once a position shows you a gain, however, the correct course of action becomes less clear and is often susceptible to emotionally-driven decisions. For example, greed could cause a trader to overstay his welcome in a winning stock in hopes it will continue to ratchet higher, while fear of losing your current gain could result in a premature sale in a potential big winner. Selling a position and locking in a profit too early in a stock's move can certainly be frustrating as you watch the stock vault higher without you. On the other end of the spectrum, it's equally disappointing to see unrealized gains evaporate on a stock that you once had a sizable gain on, as it falls back to or even undercuts your entry point. On Friday, 10/18, with many leading stocks extending gains after breaking out of basing patterns, I posted the tweet below, which sums up the predicament described above:
In reviewing many of my past trades, I've noticed that one of the best ways to strive for consistent trading results is to view every trade within a risk/reward framework. To clarify, I define risk as the amount of potential loss on a trade, which is determined by the placement of a stop-loss (ie. I'm willing to lose $2/share on this trade). This amount of risk serves as the benchmark for calculating potential reward within this framework (ie. 2x risk would be a $4/share gain, 3x would be $6/share gain, etc.). What I found in studying my results was that stocks will often move up a certain multiple of my risk (often 3x or 4x), and then either correct or settle into another basing pattern. To illustrate this point of how to view trades through a risk/reward lens, let's examine one of my past trades in Facebook, which I began to trade starting in the winter of 2012:
I bought FB on 11/21/12 at $24.30, as the stock broke out of a bottoming basing pattern on the daily chart. Facebook had knocked out a trading range between roughly 19 and 24, and I entered the position on a break of the upper resistance area, which was accompanied by above-average volume. I set my stop below that day's low, giving me a risk/share of $1.30, which still allowed for slightly over 5% wiggle room should the stock pull back. Based on these parameters, it's simple to calculate the various multiples of my risk by adding multiples of my risk/share to my cost basis (ie. 3x equals my cost basis [24.30] plus 3 times my risk [1.30], or 28.20). When I exited the position on 12/3, I wasn't aware that I had sold FB at 3x, as I had yet to integrate this framework into my trading. Instead, my sale was based on the negative reversal, as FB tried to punch higher but got firmly rejected by sellers. Based on similar reviews of my past trades, I've developed a strategy for selling winners that combines multiples of risk (looking to sell at 3-4x) with price action (a move extended and "stretched" from its moving averages, a reversal, or a break of prior support). Although this approach makes it unlikely I'd hold a stock for years and rack up a 200-300% gain on an individual position, I've found this framework promotes consistency and, as shown below, can lead to outsized gains. In the exercise below, let's assume a starting portfolio of $100,000 adopts the technique of selling once a stock has reached 3x, cuts all loses at 5% (meaning 3x will equate to a 15% gain), and the trader is only correct on one-third of his trades, to be conservative.
| Number of Trades | Account Size | Win/Loss |
| 1 | 115,000 | Win |
| 2 | 109,250 | Loss |
| 3 | 103,788 | Loss |
| 4 | 119,356 | Win |
| 5 | 113,388 | Loss |
| 6 | 130,396 | Win |
| 7 | 123,876 | Loss |
| 8 | 117,682 | Loss |
| 9 | 111,798 | Loss |
| 10 | 128,568 | Win |
| 11 | 122,140 | Loss |
| 12 | 116,033 | Loss |
We find that after only 12 trades, the account is up over 16%, and this is assuming a win rate of only 33%. Now, let's look at the results if the win rate is bumped up slightly, to 41%:
| Number of Trades | Account Size | Win/Loss |
| 1 | 115,000 | Win |
| 2 | 109,250 | Loss |
| 3 | 103,788 | Loss |
| 4 | 119,356 | Win |
| 5 | 113,388 | Loss |
| 6 | 130,396 | Win |
| 7 | 123,876 | Loss |
| 8 | 117,682 | Loss |
| 9 | 111,798 | Loss |
| 10 | 128,568 | Win |
| 11 | 122,140 | Loss |
| 12 | 140,461 | Win |
These are obviously simple exercises, but they illustrate multiple points:
First, it's clearly necessary to have your average win exceed your average loss in terms of percentage return. In the examples above, the portfolio was able to accumulate significant profits by cutting all losses at 5%, while taking gains at 15%. This highlights the benefits of taking a "multiple of risk" approach, which we examined with the Facebook trade above.
Second, you can lose money on the majority of your trades in this framework and still deliver hefty returns. In the second example, the portfolio returned over 40% after 12 trades with only a 41% win rate. By focusing on top-quality setups of stocks with explosive earnings and sales growth breaking out of sound bases, traders should certainly aim for an even higher win percentage than 41%, which would obviously result in even greater returns.
Feel free to leave my any comments on StockTwits or Twitter (@CommAveTrader).
