One method for setting a stop loss level is to determine a dollar value that represents the maximum amount of money the trader is willing to lose on a trade. For example, the trader may be in a long position and be willing to risk $200 on the trade; the stop loss would be set $200 below the entry price.
“T-note stop loss” (below) shows a June 2012 daily 10-year U.S. Treasury note futures. A long trade was entered on Feb. 22 at 130-15, with a defined $375 risk for the trade, setting the stop loss below the entry price at 130-02 (each full tick is valued at $31.25). The trade could have been closed for a profit; however, if the trade had remained open as prices dropped, it would have incurred only a small loss.
While this technique is straightforward and easy to implement, it is not necessarily the most effective means of establishing stop loss levels because it may not reflect anything more than the trader’s current risk tolerance. It may not account for the current state of the market — trending or sideways; the current activity in the market — quiet or volatile; or fundamental considerations — upcoming earnings announcements or economic reports. For these reasons, a dollar value stop can keep losses at a consistent level, but may not be logical for the trading instrument or market conditions.
That said, dollar value stops can be tailored to suit a particular trading instrument rather than simply the trader’s risk tolerance. One approach is to use a modern trading platform that supports backtesting or historical modeling to discover an optimal dollar value stop loss level that both remains consistent with the trader’s risk tolerance and reflects the unique price movements of the specific market.
As a starting point, traders can begin testing with the dollar value with which they are most comfortable — for example, $200 — and then test a range of values above and below that amount to find the most favorable results.
However, it’s important to note that stop levels determined using historical testing should be used only as a guideline. Often, historical testing will produce spectacular hypothetical performance figures that are the result of extreme curve-fitting to the historical price data. If the profit/loss metrics seem too good to be true, and the stop loss values are extremely large or tight, then curve-fitting likely occurred. Any levels should be checked independently on additional historical data that wasn’t used in the optimization process.
In addition, regardless of the historical optimized levels, an important consideration when selecting any stop is the position’s risk-to-reward ratio — the size of the possible loss with respect to the expected profit. Too much risk can create disastrous results; not enough risk prevents trading at a level that can generate significant profits.
The ideal risk-to-reward ratio varies with trading style, risk tolerance and the type of strategy employed. For example, a trading strategy that buys into strength may be able to employ a tighter initial stop, while one that attempts to exploit weakness may require a wider margin for error in the stop placement.