Trading Nuances: Adaptive Stop Losses Based on Volatility
In a previous article, we reviewed the technique of placing orders stop loss. As a continuation of this theme explore other ways to place a protective stop-loss order depending on the characteristics of the market volatility. In doing so, we first need to move away from the fixed stop-loss order and begin to develop Stop order, adaptive to the conditions of current market volatility.
Adaptive stop loss based on volatility
A promising way to develop such a stop loss is to studying the current market volatility. In this case, we can use the Average True Range over a period of time or the Standard Deviation over a period of time and multiply that value by some constant to determine how far a stop loss order level can be located from our entry.
One of our favorite stop loss orders is an order that is placed at some distance from the entry, calculated according to a simple algorithm: you need to take the Average True Range for a certain period, multiply it by the given coefficient and place our order at this distance from the entrance stop loss. To prevent random price movements, it is recommended to place the stop at a distance of more than one Average True Range value from the entry point.
The advantage of using such an adaptive stop loss is that it is tied to current market conditions and your risk tolerance. At the same time, the value of the stop itself in pips will increase during periods of high market volatility and decrease during periods of low market volatility.
In actual trading practice, you may find that problems with ATR stop loss begin to occur when short-term market volatility becomes unusually small, and narrow stops can be knocked out by random movement. To eliminate these false triggers of stop-loss orders, we calculate both short-term market volatility (approximately in the range of 3 bars on the working sweep) and long-term volatility (at least 20 bars on the same time interval) and set the stop-loss value using the larger value of volatility from the resulting two numbers. This allows stop-loss orders to adapt quickly enough to changing market conditions and prevents false triggering of stop-loss orders after an unusually calm phase of market consolidation.
Adaptive stop loss based on standard deviation
Another variant of the adaptive stop loss is associated with the use of Standard Deviation of past prices as a value related to volatility. For example, you can calculate the standard deviation for a certain period, multiply the obtained value by a certain constant, and place a stop from the entry point by the obtained value. The reasoning behind this method of placing a stop is the same as for ATR stop loss. In this case, players are also quite often able to avoid random price fluctuations, but at the same time there is an opportunity to control serious losses in the event that the market has a really serious trend against the open position.
Example of Adaptive Stop Loss
Adaptive Stop LossesThe market volatility based on market volatility plays an important role in money management. Probable loss values can be quickly calculated before opening a position, and we can be sure that the potential loss size is consistent with current market conditions. For example, suppose our system suggests placing a stop loss at one and a half times the 21-day ATR from the entry point. If we take the EUR/USD market in the summer of 2005 as the initial data, the Average True Range at that time was $900, hence, the stop-loss order must be placed at a distance of $1350 from the entry point.
Now let's assume an equity of $50,000 and we want to risk no more than 10% of that deposit on a single position. Based on the volatility of summer2005, we will trade 3 lots of $100,000, thus risking $4,050 of our capital. Now let's assume that we trade with the same tolerances of summer2007. Now the Average True Range of the market is $2,200. Accordingly, the stop loss order is placed at a distance of $3 300 from the entry point. If we still have the same $50,000 deposit with an acceptable risk of 10%, we should only operate with 1 lot.
From this example we can see that working with with an adaptive stop loss order - is an excellent way to manage risk in a changing market environment.