atr Archives - Algorithmic and Mechanical Forex Strategies

Fade Range Reversals For Rich Rewards

September 5, 2014 by Eddie Flower 16 Comments

Fading range reversals is a powerful forex trading strategy. This “fading” strategy capitalizes on markets’ tendency to revert back toward their mean values in time. It relies on simple rules, and there’s plenty of room for adjusting it to fit any market.

Range reversal signals rely on input from earlier-opening markets, which can provide the set-ups for successful trades later during the global business day.

Forex traders often watch the range of a currency pair’s price for clues as to expected price movements during a later-opening marketplace, and the possibility of tradable price reversals.

Two of the most effective reversal indicators are the average daily range (ADR) and the average true range (ATR). They can be used together or separately to signal trading opportunities from range reversals.

Range reversal opportunities

Many experienced traders have noted a tendency for the major currency pairs to reach their intra-session maximums during the New York session. This session is pivotal for the sizes of ranges to be achieved in other sessions.

As well, all markets on opening at least acknowledge the last prices of earlier markets

So, it makes sense to develop mechanical trading systems to harvest gains from these fairly predictable phenomena. Expert advisors (EA) and mechanical trading systems can often find price levels where a currency pair is likely to reach the extent of its range, before moving back inside that range.

The best-designed systems focus on finding high-probability set-ups where the price is likely to complete its range move after the markets open in New York.

Below, I’ve outlined my fading range-reversal forex strategy, which lets me harness the power of probability and the law of reversion-to-mean for profitable trading.

“Reversion to mean” means predictable gains

The range reversal strategy is based on the concept of reversion to mean, which is also sometimes called regression toward the mean.

In financial markets, this concept refers to the mathematical law which says that if a price is extreme during one or a few measurements, that price will tend to be found closer to the average price once subsequent additional measurements are made.

In other words, anytime you see a price outside its normal nearby range it will usually quickly return to a level within that range. Over time, prices tend to return to the average over the entire set of data.

So, with regard to the range reversal strategy, the forex trading system assumes that during each individual trading session or shorter time-frame, a currency pair’s price move will become exhausted at a certain “average” point. At that point, the price will probably reverse and return back within the limits of its average daily range.

My range reversal trading strategy is focused on fading the daily momentum in anticipation that the price is expected to regress toward its mean, that is, move back toward its average range.

Average daily range & average true range

Even in spite of volatility, currency pair prices generally move with a fairly predictable range each session. Under typical market conditions, a price moves around a range calculation called the average daily range (ADR).

The average daily range (ADR) is simply the average of the daily price range calculated for a given number of days.

The average true range (ATR) is a bit more discriminatory of price range during gap-ups or gap-downs. The ATR is calculated as the greatest value of the following:

• Current high minus current low
• Absolute value of current high minus the previous close
• Absolute value of current low minus previous close

The ATR represents a moving average (usually a 14-day MA) of the individual true ranges.

The benefits of using ATR & ADR

The value of these daily range indicators is that they show the volatility of the currency price and also indicate likely reversal points. When the range increases, it shows the price is volatile.

The range reversal strategy works well when both indicators are employed, since the ADR provides a baseline and the ATR accounts for gap-price volatility.

ADR and ATR are easily determined by mechanical trading systems; the most popular time periods are 5, 10, or 20 days. After determining the typical ranges for the targeted currency pairs, the system looks at the day’s open for a given time frame, say from midnight, and then calculates the target price area for trading signals.

For example, let’s use EUR-USD with an ADR indicator, and assume an opening at 12 a.m. ET at a price of 1.2300. The strategy allows the price to make its primary move from 12 a.m. to 5 a.m. ET. During this time period, the price typically sets up or forms the “high” and “low” for the day.

The session opened at midnight ET at 1.2880. Next, as the London session opened, the price dropped to a low 1.2788 before again moving back upward to 1.2811 just before the opening of the New York session.

First, determine support and resistance

During the New York session the trading system automatically looks for support if the price keeps moving downward, or for resistance if price moves strongly upward. Let’s assume that the ADR is calculated as 120 pips.

So, the EUR-USD pair should find support near 1.2760. In this case, the ADR is calculated by subtracting the daily session high minus the daily session low.

On the other hand, if the low price at 1.2788 is sustained and the euro enjoys plenty of buying during the New York session and moves still higher, then the probable next resistance will be around the 1.2910 level.

The system calculates this number by taking the day’s low and adding the Average Daily Range (120 pips in this example) onto it. In either case, the trading system signals support and resistance levels during the New York session.

Find support and resistance levels for the next-highest time-frames

After the trading system determines where the price is located in relation to the ADR, the next step is to find the support/resistance levels calculated for each of the next-highest time-frames, which are typically 1-hour or 4-hour time-frames.

Often, there is plenty of support/resistance in targeted areas, and trading signals should be confirmed by using multiple indicators. Many different technical tools could be used, but Fibonacci retracements and extensions, pivot points, and retracements are some of the best.

Above is a 4-hour chart. You’ll see there’s significant resistance around 1.2910. From a technical viewpoint, this shows the previous high swing on the 4-hour chart, and in the left area you’ll see there’s been strong support during a period of several days. The green boxes show a number of faltered attempts by price to move outside the target area.

For the downside, in this case the 1.2760 price level is at or near the trading system’s calculated value for a 50% Fibonacci retracement of the last swing from the 4-hour time-frame. This move is significant. This level may act as support, or the price may break through this level.

Once the price breaks through that level, it should then act as support if the EUR-USD continues to move downward during the remainder of the New York session. In fact, it can be seen that the 1.2760 level has been an area of price support before.

The trading plan

The trading system has confirmed support around 1.2760 as well as resistance around the 1.2910 level.

When the price begins its move toward one of these two levels during the New York session, the system is standing by, ready to “fade” the session’s momentum and ride the currency pair’s price back into its average daily range or average true range.

The overall goal is to find situations in which momentum has built up, then capitalize on the residual momentum to ride the price back toward its range for a fair profit.

As mentioned earlier, the range reversal is a mean-reversion strategy. In the chart below are some examples of where to apply this strategy, and what to avoid.

The range reversal strategy takes advantage of the probability that, as the price exhausts the movement of its daily range, it will reverse and return back into or toward the ADR in a show of reversion to the mean price.

Even while expanding its range intra-session, the price tends to reverse itself at some point and move back toward one end of the range before resuming its move toward the other extreme.

The trading system relies on a variety of tools to determine support-resistance, including Fibonacci indicators. The system identifies the reversal point, usually at a recent strong resistance or support level.

Fading the range reversal

When the currency pair’s price reaches that reversal point, the system enters a trade which “fades” the price move. It’s expected that the price will return back inside the daily range, or perhaps expand to fill it.

Fading means trading against the current trend, with the expectation that the price will return to its normal daily range. This is a contrarian strategy, since the trading system sells when the price is rising and buys when the price is dropping.

The chart above illustrates three scenarios: The first situation shows a high-likelihood set-up, then the next two situations represent trading signals that should be screened to improve the trading system’s performance.

It’s been said that a range expansion is a very clear signal the market will soon move in the direction of the expansion

In the first situation shown in the chart above, the Euro first became stronger during the Asian session, then the price reversed from support levels of the previous, all just prior to the opening of the London session. At that point the ADR indicator began rising, which signals a range expansion.

During the London session, the price added 55 pips, which is far short of its average daily range of 120, which lays out the scenario for the upcoming opening of the New York session. By adjusting these values, the trading system improves its success rate through better set-ups.

The successful range reversal trade features these elements – A reversal from a support or resistance level, a range expansion, the trend wave is pointing upward, and there’s a tradable opportunity in the remaining average daily range.

The range reversal strategy doesn’t always work, as shown by the last two example set-ups in the chart. In the second scenario, the Euro’s price continued upward, but then reversed strongly during the London session, when it over-ran its ATR by 60 pips. The trading in New York was flat.

In the third set-up shown, the advantage of a mechanical trading system is that it should screen this signal and avoid the trade based on the fact that the force of the move has already been spent. There’s not enough trading activity to repeat the previous performance.

Screening range reversal signals

As seen on the chart, when the minimum and maximum values of the ATR (ADR) are very close together, it indicates that volatility has been exhausted, and trading activity needs time to rest.

Because of the risks from holding “fade” positions during reversing markets, the range reversal strategy favors quick-in, quick-out trading methods. Since the trading system has already pre-calculated the average true range, the rate of momentum, and the amount left for potential gains, the profit expectations must be tailored to fit the marketplace.

Also, it’s important that the trading system screen and reject any trades that are signaled if (1) the price’s average daily range has already been surpassed during the London session, or (2) the signal was generated when volatility reached exceptionally high and low levels during a very short period of time.

Entries

The entry points are determined based on the key resistance and support levels, plus Fibonacci levels. And, the ADR or ATR indicators are assessed in view of the range for the London session.

Returning now to dissect the trading opportunity in the first scenario shown on the above chart, it helps to take a look at the price under a microscope, by using a 15-minute chart, as shown below.

Again, the focus is to adjust the trading system according to what may happen during the New York trading session. In this example, the price momentum began in London, and all indicators suggested that the price move would continue once the New York market opened.

The trading system chooses an entry point just after the typical profit-taking on any positive run-up, which usually happens just before New York opens.

The system can calculate a stop-loss order to meet precise needs for risk management. The typical stop-loss amount is usually 25 or 30 pips.

Range reversal profit-taking

Using a 2 x 1 reward-to-risk ratio calculated based on the stop-loss, the profit targets should be set at a minimum twice the stop-loss amount. It’s best when the stop-loss amount is near the projected upper limit of the ADR or ATR.

It’s important not to become greedy when using the range reversal strategy. Patience is also necessary, since it may take some time to fine-tune the trading system for shorter time-frames.

Keep in mind that there are other trading systems using similar strategies, so it’s always best to get in and out of the trade quickly, before the market sentiment changes. Be happy with a fifty- or sixty-pip gain.

Find range reversals and fade them for profits

You’ll be surprised at how often range reversal trading set-ups occur, yet you’ll need to use the appropriate complementary indicators to screen the signals and confirm your likelihood of success before entering a trade.

Also make sure to apply the principles carefully so your trading system is programmed to reject any trades signaled by the two exceptions to the rules mentioned again here:

Avoid the trade if the price’s average daily range has already been exceeded in the London session, and also reject any signal generated when volatility has reached high and low levels within a very short time.

With tight risk management and fine-tuning, your trading system can profitably trade range reversals on a regular basis, even under fairly volatile market conditions.

A Home On The Range

August 21, 2014 by Eddie Flower Leave a Comment

Trading ranges and range breakouts offer some of the most common and potentially most-profitable marketplace scenarios encountered by forex traders. Yet, many traders are unable to build a winning strategy to profit from trading price ranges and breakouts.

The secret to successful range trading lies in identifying trading ranges and breakouts as early as possible, and then trading them proactively before the herd comes in and drives the price too far in either direction.

By using the right tools, ranges and breakouts are fairly easy to spot and take advantage of. Ranges offer something for everyone: Range traders work to trade currencies while prices remain within the range, and breakout traders focus on entering positions when the currency pair’s price leaves the range.

Properly traded ranges can be very profitable – When breakouts occur, they can yield huge returns. Meanwhile, range-bound forex trading strategies offer a slow, steady way to accumulate gains.

Still, it’s critically important to trade carefully: The keys to success are to avoid trading false breakouts and corrections, manage risks appropriately, and keep the expectations realistic.

In this article, I’ll describe some ways to identify and confirm stable trading ranges, which can then be successfully exploited by mechanical trading systems using a wide variety of strategies.

What’s a trading range?

The term “range” refers to the difference between the high and low prices for a given currency pair during a given time-frame. Range is the price spread during the time-frame, and it also represents the volatility of the currency.

The more volatile a currency price is, the wider its range. Obviously, the longer the time-frame, the wider the observed price range. For mechanical trading systems, ranges are useful for determining technical support and resistance levels as well as setting entry and exit orders.

Likewise, range is a measure of risk – The wider the range, especially during short time-frames, the riskier the currency play. By choosing the right trading strategy and employing appropriate risk-management measures, a forex trader can harness the power of the range to achieve excellent gains.

A trading range or channel occurs when a forex price trades at or near the same price over a period of time. When the price eventually moves outside this range, it’s called a breakout.

Breakouts from a range

Breakouts indicate momentum, whether positive or negative, in the sense that the balance of power of “long” and “short” currency holders has shifted to the opposite side.

After a breakout, the price may either continue to move away from the range, usually very sharply up or down, or else the price may return back inside the range, signaling a false or failed breakout.

Breakout trading strategies work to capture the gains from pent-up buying or selling pressure that can explode when prices move outside their typical ranges.

It’s easy to see a breakout after it has already happened, yet the challenge for traders and mechanical systems is to identify and act on the true breakouts while avoiding the false or failed ones.

Trading systems must effectively manage entries into false breakouts, since they’re so common. After entering a trade, the price may rise quickly before suddenly retreating back toward or into the range. Successful systems choose only the most likely winning trades.

It’s important to keep in mind that about fifty percent of all breakouts from ranges will retrace all the way back to the breakout point before once again resuming their desired moves.

A well-built system should be prepared to re-enter a new trade immediately after a loser, if the price overcomes its correction before again moving in the desired direction. And, during a correction toward the breakout point, the ideal trading system should at least harvest a small gain even after giving back most of the paper profits.

The solution for these issues is to use a winning combination of signal filters and confirming indicators to screen prospective trades before entering positions. In particular, tools and indicators based on the angle of the moving-average line, MACD, Average True Range (ATR) and Standard Deviation (SD) are very helpful for these tasks.

Breakout trading

As mentioned above, the most important concept to understand when trading range breakouts is that half of all forex breakouts fail. So, the most successful strategies are based on avoiding entering trades immediately. Instead, the system checks for confirmation before entering any trade.

The trading system should be programmed to wait until the price first retraces to the breakout point, then begins to move in the favorable direction again. This confirmation helps the trader reduce losses which inevitably occur during frequent retracements.

Psychologically, these retracements are even harder for the trader to tolerate when he or she is first stopped out, then the correction ends and the favorable move resumes without him or her aboard. So, it’s important that the trading system should only enter a trade once the price re-crosses the breakout point.

Of course, a retracement to the breakout level only happens about half the time. Still, the gains from confirmed breakouts can be spectacular and the confidence of success after waiting for confirmation is much higher.

Regardless of the individual strategy used to trade the breakout, one of the most common ways to set profit-targets is by using a target price that is equal to the width of the range either added or subtracted from the breakout price.

Range-bound trading

During trends, small traders can often trade profitably simply by following the trend and riding along with the herd of major institutional players. However, in a trendless, range-bound market, traders need a different group of strategies. Under such conditions, trend-following systems may generate many false signals for trades which ultimately lose.

Trading breakouts and trends can be profitable, yet major breakouts are relatively rare. A given currency price typically spends about half its time moving in a trend, and the other half in a range. Traders who ignore range-bound plays are missing half the fun and profits.

Forex traders who seek more opportunities often develop strategies for trading currencies while their prices are stuck in ranges or channels, where they may remain for long periods of time.

Range-bound trading strategies work by identifying the price ranges or channels in which currency prices are confined. These strategies are based on the prediction that prices will stay within the range.

In the most basic scenario, a mechanical trading system determines the nearby support and resistance levels, then it buys when the price touches the bottom (support) of the range, and sells when the price reaches the top (resistance) of the channel.

“Pure” range traders don’t care whether a currency price is going up or down, as long as it develops and stays within a trading range.

The range-trader’s underlying assumption is that prices will repeatedly return back to recent levels. The goal of mechanical range-trading systems is to harvest the gains from this repetitive cycle, while fine-tuning gains and losses by analyzing and responding to the latest market data.

Instead of merely finding the best entry points, range-trading systems should also be programmed to be “wrong as early as possible” and with carefully-adjusted position sizes so that the trading capital is preserved for subsequent trades that arise during the repetitive up-and-down price cycles that characterize forex ranges.

Detecting range-bound markets

Ideally, the trading system should be configured to spot the earliest stages of range-bound markets. Of course, it’s impossible to precisely predict winning trades every time, but the earliest recognition of a range allows the most flexible trading response.

Here’s the main rule for assessing a given market:

If the market isn’t obviously trending, it should be treated as a ranging market

With regard to technical indicators, when the chosen indicators stop showing clear signs of a distinct price trend, the trading system should assume the market is entering into a new range-bound period.

One of the easiest ways to spot a range-bound market is by checking the angle of a Moving Average (MA), generally by using a Simple Moving Average (SMA). For example, if the SMA is rising quickly, then the angle of its price line compared with the time axis will become steeper.

Likewise, if the angle is becoming lower, the trend is becoming weaker. If the angle is flat or near-zero, then the market is range-bound, or very sleepy.

Trading systems can be programmed with indicators built to compare the steepness of the angle of the current SMA against its “normal” steepness during different market periods. These indicators can be set to respond with various degrees of sensitivity to changes in the moving-average angles.

Another easy way to detect ranging markets is a Moving Average Convergence/Divergence (MACD) indicator. This type of tool works well in real time, especially when markets are volatile.

By adding two levels to the indicator – lower and upper horizontal lines below and above “0” on the MACD, trading systems can spot levels at which prices are most likely to consolidate.

In the chart below, the principal ranging zone is shown inside the green box. And, inside the box I’ve highlighted the ranging areas between the 0.05 and -0.05 levels. These are the tradable areas where the trading system detects a ranging market in real time.

As well, the MACD-based range-bound zone can be adjusted to values such as 0.03 and -0.03 or another value that the trading system determines to be appropriate for a given market. An expert advisor (EA) can help define the appropriate levels by examining historical levels in particular markets.

In any case, the MACD histogram hanging around the zero level indicates a ranging, tradable market.

Although naysayers may claim that this method doesn’t show the entire range until after the sideways movement has ended, your trading system doesn’t need to wait that long. When the MACD first enters the ranging zone, you’ll have plenty of warning that a range-bound market is about to occur.

Once the MACD enters the zone, the trading system can monitor the price and use additional confirmation tools to confirm that the range is still intact before trading. This MACD-based method can be very helpful in combination with other indicators.

Using Average True Range and Standard Deviation to spot trading ranges

As indicated earlier in this article, ATR and SD are helpful in highlighting trading ranges which can be exploited.

Shown in the EUR-USD chart below are two indicators, the 14-period Average True Range and the 14-period Standard Deviation, which can be used as tools to discover potential trading range areas.

In one indicator scenario, for example, when the 14 ATR is greater than the 14 SD, it indicates a ranging market. And, when the 14 ATR is less than the 14 SD, the market is trending.

From one perspective, the apparent logic behind this indicator is that the ATR shows the shorter-term daily volatility while the SD represents volatility over a longer period of time; although the market stops trending, the intraday volatility may stay the same, or slow down even more.

In another simple strategy, the trading system can simply monitor whether both ATR and SD are pointing upward. If so, the market is trending.

Also, savvy traders can build trend-strength indicators based on calculating a rate-of-change ratio between the current ATR and SD values using the desired time-frame. These indicators are useful for showing ranges as well as breakouts.

The usual default number of periods is 14, and Fibonacci-lovers often use 21. Still, as a rule, the shorter the trading system’s time-frame, the greater the number of periods should be.

If the ratio is increasing, it means the trend is becoming stronger. Or, if it’s dropping, it means the trend is weakening and will soon become either a range or a reversal. If the ratio is at the bottom, it indicates a ranging market.

In summary, there are a variety of ways for forex traders to determine whether a market is in a range, breaking out or trending.

Regardless of the strategy employed, traders can feel right “at home on the range” once they’re able to identify ranges and thus have more opportunities to trade them.

What’s your own trading style? Are you a range trader, breakout specialist, or trend-follower?

Forex Volatility Trading Playbook

July 25, 2014 by Eddie Flower 17 Comments

The forex marketplace supports a diverse community of successful independent traders who have developed winning strategies that work during changing market conditions. Trend-following strategies are popular among newbies, but veteran traders truly earn their keep during times of volatility.

This article gathers and summarizes some longtime traders’ forex volatility trading strategies that can win even when markets are volatile. In fact, the strategies in the volatility trading playbook work best during times when the gains from trend-following systems lag far behind.

Forex volatility trading

By definition, volatility means that prices rise and fall quickly, and do not show clear direction or trend. Successful volatility-focused trading systems usually feature these characteristics:

• Based on volatility or breakouts from channels or ranges

• Trades are short-term

• Trading systems are very choosy with trades, and are usually out of the market

• Win a high percentage of trades

• Earn only a small-to-modest profit per trade

• Take advantage of small moves instead of big moves

Well-designed mechanical trading systems can anticipate and take advantage of changes in volatility, then exit the trades without giving back the open profits.

Parabolic stop-and-reverse trading strategy

Some forex traders harness the power of volatility by trading parabolic time-price systems. First introduced by the legendary trader J. Welles Wilder, Jr., the parabolic stop-and-reverse trading strategies capitalize on price reversals.

Parabolic indicators help determine the direction of a currency pair’s price movement as well as indicating when the trend is likely to change and a price reversal is imminent.

These indicators work well for determining both entry and exit points in volatile currency markets, since prices tend to stay within parabolic curves during trends. When prices move wildly, parabolic indicators can help show the direction or change in trend.

Successful parabolic stop-and-reverse strategies are also time-focused: The mechanical trading system weighs the potential gains against the amount of time the position must be held in order to have the best chance of achieving those gains.

If using a “pure” parabolic trading system, the forex trader would always be in a given market, either long or short. For example, when the parabolic indicator generates a buy signal, the trade is entered. Then, when the trend begins to reverse, the “long” position is closed and a new “short” is opened at the same time.

Still, order to reduce the number of quick shake-outs from volatility whipsaws, most parabolic traders filter their trading signals by using a trading volume screen as well as a variety of other indicators.

Parabolic trading rules

The basic parabolic trading rules are simple – For long signals, the mechanical trading system buys when the currency pair’s price reaches a parabolic point above the current market price, and the trading volume is higher than the five-bar simple moving average trading volume.

In order for a trading signal to be confirmed for this parabolic trading strategy, both parameters must be true during the same time-bar. Here are the general parabolic setup, entry and exit rules used by several successful forex traders:

• Calculate the parabolic points

• Calculate the 5-bar simple moving average (5 SMA) of trading volume

• For long entries, the system buys when the price reaches a parabolic point higher than the current market price, as long as the volume is higher than the 5-bar moving average

• For short entries, the system sells short when a price touches the low parabolic point below current market prices, as long as the trading volume is greater than the 5-bar moving average

• To exit from a long trade, the system liquidates the position when the parabolic points decline

• To exit from a short trade, the system covers the position when the parabolic points rise

• To set the trailing stop for a long position, the system uses the parabolic points below the current market price

• To set a trailing stop for a short trade, the system uses parabolic points above current market price

• Savvy traders often set profit targets like this, for example: 70 pips for GBP/USD or 60 pips for EUR/USD when trading a 4-hour time frame; or, 200 pips for EUR/USD or 250 pips for GBP/USD when trading a daily time frame

Volatility channel breakout strategy

Many successful forex traders use channel-breakout strategies fueled by volatility. Here are the basic indicators and trading rules for a simple channel-breakout strategy that works for especially-volatile currency pairs on time frames of 15 minutes or higher:

• 30 ATR (the Average True Range over 30 time periods) with 5 EMA (the Exponential Moving Average over 5 periods)

• 15 ATR with 5 EMA

• 30 EMA (Exponential Moving Average over 30 periods) High

• 30 EMA Low

• For long entries, the system buys when the price closes above the upper EMA band and the 30 ATR is greater than the 5 EMA

• For short entries, the system sells short when the price closes below the lower EMA band and the 30 ATR is greater than the 5 EMA

• The trading system sets the stop-loss on the lower EMA band for long positions, and on the upper EMA band for short positions

• With fine-tuning, the strategy may achieve fairly aggressive profit targets

Volatility double channel breakout strategy

Other forex traders who specialize in harvesting gains from especially-volatile currency prices use a similar, yet “double” channel breakout strategy. Below are the basic trading indicators and rules for a double channel-breakout strategy that works well for volatile currency pairs:

• 11 Relative Strength Index (RSI) at levels 35 and 65

• 20 EMA High

• 20 EMA Low

• 5 EMA High

• 5 EMA Low

• The mechanical trading system buys when the 5 EMA High is greater than the 20 EMA High and the 11 RSI is greater than 65

• The system sells short when the 5 EMA High is less than the 20 EMA High and the 11 RSI is less than 35

• If the initial setup bar’s trading range is more than double the value of the previous bar, the trading system declines the trade

• The trading system sets the stop-loss at the lower band of the 5 EMA for long trades, and at the upper band of the 5 EMA for short positions

• Aggressive profit targets can be set

Forex trading strategy for extreme volatility

Forex traders who thrive on volatility, there are many profitable trading opportunities. Below is a simple forex volatility trading strategy.

When a long candle appears during a trading session, that is, when an intraday time-bar has a greater range than the previous time-bar, it may be the setup for a trade. Long candles are a sign that volatility has increased, and that a change in trend may be imminent.

Often, after a big candle a new trend may develop, or the previous trend may become stronger. And, the trend will usually be moving in the same direction as the price movement of the time-bar when the long candle happened.

When a long candle occurs, if that candle breaks the high or low of the trading session then the price will probably continue to move in the same direction.

Trading rules for extreme volatility strategy

• A candle or intraday time-bar which is much bigger than any previous candles during the session, but has not yet reached 100 pips in total range

• That same long candle is also now setting a new intraday high

• For long entries, the trading system buys at 1 pip over the high of the previous candle’s price

• For short entries, the system sells short at 1 pip under the low of the previous candle’s price

• For longs, the stop-loss is set at 1 pip below the low of the entry candle

• For shorts, the stop-loss is set 1 pip above the high of the entry candle

• Profit targets are set according to nearby support and resistance levels

• It’s important to note that any entry order should be placed only after the time-bar containing the long candle is completed, and the trader should use at least one other indicator to confirm the signal before entering a trade

ATR channel breakout strategy

Some forex traders who specialize in volatility-focused strategies rely on indicators which use Average True Range (ATR).

The trading system determines the midpoint of the ATR channel by calculating the Exponential Moving Average (EMA) of the time-bars’ closing prices, using a number of time-periods as defined by the “close average periods” parameter. When volatility pushes the currency price out of this channel, the breakouts are easy to trade.

This volatility trading strategy is similar to a Bollinger band breakout strategy, except that it relies on ATR instead of standard deviation as a measure of volatility to define the width of the bands or channels. The trading rules for this type of volatility strategy are simple.

• ATR for 20 time-bars

• EMA of the closing prices of each time-bar

• For long entries, when the last price of a time-bar crosses over the mid-band of the ATR channel the trading system buys on the open of the next time-bar

• For short entries, when the last price of a time period crosses the mid-band of the ATR channel the system sells short on the open of the next time-bar

• Stop-loss orders are set 2 pips below or above the first band of the ATR channel

• The trading system sets profit targets according to nearby support-resistance levels

ATR channel breakout strategy using fractals

Forex traders also use fractal indicators with volatility trading. Below is a simple strategy relying on ATR channels to signal breakouts, and using fractals to determine optimal entry and exit points.

• 130 ATR

• 9 EMA

• When ATR is greater than the 130-period average and the EMA is greater than the 9-period average, trading signals can be confirmed

• When ATR is less than 130 and/or EMA is less than the 9-period average, no trade

• Fractal indicators to show the likely breakout range

• Entry orders are set 1 pip above or below the breakout range

• Enter long when ATR is greater than 130 and greater than the 9 EMA, and fractals confirm the upward breakout

• Enter short when the ATR is greater than 130 and greater than the 9 EMA, and fractal indicators confirm the downward breakout

• Stop-loss orders are set to be triggered if/when the currency pair’s price touches the opposite side of the range

• The trading system closes the position automatically when the volatility decreases, for example, if the ATR goes below 14 EMA

• Set profit targets at a ratio of about 1:3 according to the stop-loss levels; so, for example, if the stop-losses are 30 pips, then the profit target is set at 40 pips

Volatility meters

Forex traders sometimes use “volatility meters” such as the Volameter indicator for intraday trading signals. These volatility indicators spotlight overbought and oversold zones. The trading rules vary depending upon the indicator. Below are the basic setup and rules that some traders use with the Volameter, a popular volatility meter.

• Overbought/oversold indicator

• Volameter

• Pivot-point indicators

Trading rules

• A long trade is signaled when the value of the overbought/oversold zone indicator touches or breaks through a level of -8

• Enter the long trade when the overbought/oversold indicator reaches a level of -4 by placing an order to buy-on-open at the next time-bar

• A short trade is signaled when the overbought/oversold indicator reaches a level of 8

• Enter the short trade when the overbought/oversold indicator touches or breaks through the level of 4 by placing an order to sell-on-open at the next time-bar

• Set stop-loss orders to be triggered at 1 pip above or below the price indicated when the overbought/oversold indicator reaches a level of -8 or 8, depending on whether the trade is long or short

• Set profit targets according to nearby support/resistance levels and pivot points

Volatility creates plenty of forex trading opportunities

There are plenty of good volatility trading strategies in the forex playbook. Traders should welcome volatility because of the profitable opportunities available during trading sessions which feature big price ranges. With appropriate risk management, volatility is a forex trader’s best friend.

Is volatility a friend or enemy of your current trading system?

Using an ATR Filter to Gauge Market Conditons

February 19, 2014 by Andrew Selby Leave a Comment

Average True Range (ATR) is primarily used as a mechanism to determine stop-loss levels. Another way to use ATR that is not quite as popular is as a filter to isolate market environments that have the potential to make significant moves.

By gauging the volatility of a given market, ATR can provide us with insight to the possible magnitude of a move. If a market has been experiencing greater volatility, it is probably more capable of producing a significant move than a market that has been experiencing lower volatility.

This interesting example demonstrates how we can use an ATR Filter to evaluate market conditions.

Nat Stewart from NAS Trading wrote an interesting post about this topic where he compared the state of a market to weather conditions. He explains how market conditions can be evaluated just as weather conditions and then breaks down an example using ATR to evaluate market conditions.

Market Conditions and the Weather

Nat starts his post by comparing the similarities between wanting to know about weather conditions and market conditions. His concept that underlying conditions can impact the potential of a buy or sell decision is not revolutionary, but it provides us with an interesting visual when coupled with the weather analogy.

Being aware of your environment is essential to success in life and trading. You would probably be far less likely to leave the house during a hurricane. At the same time, you would have a hard time buying breakouts in a sideways trending market. As quantitative traders, we have the ability to build filters for our strategies that check for weather conditions.

The ATR Filter

Nat explained how this concept could be applied by providing us with backtesting results for a simple S&P 500 futures breakout strategy. For these backtests, he used ATR as a filter, requiring a certain level of volatility before his strategy would participate.

As the volatility required by the strategy increased, so did the win rate and average profit per trade. When an ATR of 10 was required, the strategy posted a win rate of 53.3% and an average trade of $82. When the required ATR was boosted to 40, the win rate increased to 76.5% and the average profit per trade jumped to $761.

Key Takeaways

Nat points out that these results are opposite of what we would expect based on the common practice of setting position sizes based on ATR. Many trend followers will reduce position sizes when ATR expands when those trades appear to actually be more profitable.

One thing that he doesn’t provide us is how many trades were eliminated when the ATR filter was raised from 10 to 40. It is possible that the bigger filter eliminated most of the trades, which would result in a lower annual return and total profit. It could also expose the backtesting results to small sample size bias.

Regardless of whether Nat’s backtesting results are statistically significant, his greater point remains effective. Every trader should be concerned with determining what type of market weather his strategy performs best in and look for ways to isolate those situations.

Do Your Stops Give Their Positions Room To Breath?

January 24, 2014 by Andrew Selby Leave a Comment

The perfect stop-loss does not exist. No matter what method you use to calculate your stops, they will never be perfect. In almost every case you will either set your stop too close and force an early exit, or you will set your stop too loose and give back too much of your profit. Setting stops is a no-win situation.

Despite the fact that you will never be able to completely optimize your stops, there is always room for improvement. Even a fractional improvement in the effectiveness of your stop-loss strategy could add up significantly over the course of a couple hundred trades. That is why many traders are constantly attempting to develop a better stop-loss strategy.

Are you limiting your system by using stops that trap your trades in a box and don’t give them room to breath?

Michael Bryant from Adaptrade Software wrote a guest post for System Trader Success where he made his own attempt at creating a unique stop-loss strategy back in 2012. In his post, he explained the problems that traders encounter with the three most popular types of stops. Then, he attempted to create his own stop-loss strategy that would account for the volatility of the market being traded without having to be optimized for that market.

The Problem with Common Stops

The first common stop strategy that Michael discussed was using a fixed dollar amount for a stop. This is when a trader acknowledges that they are willing to lose a certain amount of money on a trade and sets a stop in a place that equates to that amount of loss. The problem with fixed stops is that they aren’t able to adjust for the volatility of a market. If your fixed stop is set inside a market’s normal daily trading range, it is almost certain to be triggered.

The next common stop strategy that Michael addresses is setting stops at key support and resistance levels. He explains that these levels are commonly associated with recent highs or lows. While this option can better account for volatility, these areas of support and resistance are known for pulling prices towards them. It is also likely that many other traders have stops set in these areas.

The third common stop strategy that Michael discusses is using a multiple of Average True Range (ATR) to calculate the stop location. He explains that this is a great way to account for a market’s volatility, but it also leaves us with another parameter for the system that will need to be optimized. This will make the system more complicated.

Michael’s Noise Tolerant Money Management Stop

The stop-loss strategy that Michael developed has two components:

It’s based on the idea that market movement consists of two components: trend and noise.

In order to calculate the noise in a given market, Michael’s first step is to draw a trendline from the earliest close to the most recent close in a given data set. Then, for each data point, he calculates the difference between the closing price and the trend line.

This gives him values that oscillate above and below a zero line that represents price relative to the current trend. The largest absolute value in this newly derived data set represents the greatest amount the price has strayed from the trend during that period. Michael uses this value to size his stop.

With all of the calculations coded into his strategy, there is no thinking or calculating to be done once the stop is set up. Michael points out that the only parameter that needs to be defined is the lookback period that is used to determine the data set. He suggests that because the goal is to properly size winning trades, the only good option for this value is to make it equal the length of an average winning trade according to backtesting.

In order to demonstrate this approach, Michael compares his stop strategy to a system that uses an optimized fixed stop. The results show that Michael’s stop improved the winning percentage a bit, but hurt the strategy in terms of total return and maximum drawdown. While his strategy doesn’t appear to be a significant improvement in this specific instance, it is still an interesting example of the development process.

Setting Initial Stops Using Average True Range (ATR)

April 18, 2013 by Andrew Selby 1 Comment

Getting stopped out of positions is a common occurrence for all traders. There is a sense of relief involved when a positions gets worse after your stop is triggered, but it can be incredibly frustrating to get whipsawed out of a position only to watch it rocket higher.

Accounting for volatility in your stop placements helps reduce the chance of a whipsaw trade. Fixed distance stop losses don’t bring the same advantage.

Using Average True Range (ATR) To Set Initial Stops

Average True Range (ATR) represents the average range that a market moves over a given time period. Using a multiple of ATR allows a trader to give highly volatile positions enough room to run, while at the same time making sure that low volatility positions are held tightly in check.

I typically set my initial stop 3ATRs below a new position. If that’s new lingo to you, it means that I take the ATR and multiply it by 3. If you bought LNKD at 178.66 and its ATR was 6.22, then you would set your initial stop 18.66 below you entry point, which would be 160.00 if there was no slippage. Based on your own personal risk preferences, you can use any multiple of ATR in order to take into account that market’s historical volatility.

The LinkedIn (LKND) daily chart with its average true range (ATR)

What Is Average True Range (ATR)?

The concept of Average True Range (ATR) was originally introduced by J. Welles Wilder in his 1978 book New Concepts in Technical Trading Systems. Wilder was looking for a way to describe the historic volatility he was encountering in commodities markets.

Wilder took the True Range indicator and smoothed it out using an exponential moving average. The most common time frame for ATR is 14 days.

True Range is calculated using the following formula:

true range = max[(high-low), abs(high-prevclose), abs(low-closeprev)]

By adding the second two components of this formula, Wilder was able to account for gap up and gap down situations that True Range struggled with. True Range only measures the change within a bar and not the change between two bars.

My Evolution To Using Average True Range (ATR)

When I began my trading career over a decade ago, I didn’t think I needed to bother with setting an initial stop loss. I was only going to be buying stocks that went up, so I had no reason to worry about downside risk. That was for suckers who couldn’t identify growth stocks.

Experience humbled me. I was likely to be wrong on as much as 50% of my trades. As I began to come to terms with the fact that I was not a perfect stock picker, I started to see the need to set a stop-loss order when I established a position.

My reading informed me that Livermore and Loeb recommended no more than a 10% stop. O’Neil recommended a 7-8% stop.

Since I still viewed myself as quite gifted, I figured that a 7% stop would work for me because I was only dealing with the very best stocks, and it was very uncommon for them to lose 7% from a breakout…..or so I thought.

As I continued to lose money, a very intelligent trader pointed out to me that I was not even considering the volatility of each of the stocks I was buying. Some of the stocks on my watch list would move 2-3% up or down everyday, but some of them rarely moved more than 0.5%. This explained why it felt like some of my positions had too much room and others felt way too tight. Experience taught me that looking at volatility just makes sense.

Example ATR Comparison

The chart of LNKD above showed a stock with a 6.22 ATR. As a point of comparison, here is a chart of MSFT, which has an ATR of 0.504.

Microsoft (MSFT) daily chart

Even a novice trader can see that there is a huge difference in volatility between these two stocks. Since LNKD moves with much more dollar volatility than MSFT, it will need more room to work with if you establish a position. Conversely, MSFT doesn’t need much room at all because of its low volatility history.

Using ATR For Trailing Stops

ATR extends beyond setting the initial stop loss. The indicator also works for setting trailing stops as a position becomes more profitable, such as in the RSI Trend strategy. A simple application of this is to keep the stop updated to be a mutliple of the market’s ATR below the high of the position.

Using ATR as a trailing stop can help to protect your profits, while at the same time give your position enough room to move.

3 Forex System Tips

April 23, 2012 by Shaun Overton Leave a Comment

Many systems nowadays promise profits without effort and easy pips right to your account. You probably know by now that real life doesn’t work that way. A genuinely profitable system is hard to come by. In this article I will describe three simple tips that help you enhance your existing trading systems. The goal is to make them more powerful and accurate.

Stop and Limit Entries to Catch Trends

Many trading systems use market orders to enter and exit the market. Market orders frequently exhibit low entry efficiencies. They get you in the market at a price that is not optimal. Placing a buy or sell order 10 pips from the price you wish to enter, in the direction of the trend for trending systems can make a big difference. For long trades put a buy order 10 pips higher than price, and for short trades put a sell order 10 pips lower than price. Range trading systems might consider limit entries, which would place the orders in the opposite direction of the example above.

Using ATR to Account for Volatility

Many novice system designers use constant pip distances in their forex trading system, i.e. 15 pips for stop loss, 10 pips for take profit, etc. This is a mistake as it doesn’t take into account changes in volatility. If the pair you trade exhibits changes in volatility, the system faces an increased likelihood of failure.

The Average True Range indicator (a.k.a. ATR) gives the average range of a forex pair or stock, and accounts for gaps as well. Instead of using constant numbers, use a percentage of ATR such as 50% ATR or 30% ATR. Once you do this change your system will automatically take into account volatility and will become much more flexible. Such systems will work better and will maintain profitability even in changing market environments.

Avoid Overoptimization

This is a tip especially for the programmers of you: over-optimization is the kiss of death of a trading system. Over-optimization, a.k.a. curve fitting, means that you add many Forex indicators and filters and use them all to confirm your signals, and optimize them all for maximum profits. In the backtest it will seem that your system is becoming better when in fact it will become good only for the past and will fail in any forward-test on real, live data. Therefore, it is crucial to only include the most important parts of your system and do not add indicators that don’t make sense at the price-action level. Remember the principle of Occam’s razor: “The simplest solution is usually the most efficient one”.

Michael Wells is an FX programmer and trader. His site contains his insights about Forex trading systems.

Random Trailing Limit

March 12, 2012 by Shaun Overton 14 Comments

I got the idea for a trailing limit from Van Tharpe’s market classic Trade Your Way to Financial Freedom. I made Jon Rackley read through the book as part of his training when I first hired him. He brought my attention to an unusual claim made on page 267. Van Tharpe says that it’s often possible to make money even with random numbers.

Random numbers are a pet theory of mine. I’ve long put effort into figuring out whether I could develop a strategy that trades totally at random and still makes money. As the owner of a programming company for traders, and as part of Jon’s initial training for NinjaTrader in December, I assigned him the task of programming the strategy into code.

The book states that trading with totally random entries and a 3 ATR trailing stop generally leads to making money. Flip a coin. You go long if it lands on heads. Go short if it lands on tails. One important note is that we elected to use pure random numbers in our programming instead of the pseudo-random numbers that computers generate. Doing so allows us to avoid time biases in the seeding process that generally pop up when the seeds used are close together in time.

The first working version that I reviewed displayed everything contrary to Van Tharpe’s claims. Using a trailing stop, regardless of the instrument and time frame tested, inevitably led to devastating losses. The profit factors consistently came in near 0.7, a truly awful number.

We did what most of our clients do when they find abysmal strategies. We flipped the strategy on its head. The new strategy uses only a 3 ATR (50 period) trailing limit.

Trailing Limit Analysis

The early conclusion is that trailing limits seem to offer a great deal of potential. Although Jon sent me the code several months ago, it’s only this evening that I had a chance to properly review and test everything.

The profit factors are very encouraging. It depends on the chart that I tested. The worst that I found was a 1.0 profit factor. Everything else came out with profit factors greater than 1. The small table below contains the initial test results. Before you go off salivating that this is the next hot winner, there are a few considerations to keep in mind:

The results depend entirely on the sequence of random numbers used. Using different sets of random numbers will cause different outcomes.
The better results on the higher time frames likely result from sampling error. The number of trades involved was only ~160, which is not enough to make definitive conclusions on the nature of the performance. I prefer to see 400 or more trades before drawing definitive conclusions.
These results do not include spread costs or commissions.

Currency	Period	Profit Factor	Dates Tested
EURUSD	M1	1.12	9/12/2011-3/12/2012
GBPUSD	M1	1.16	9/12/2011-3/12/2012
USDJPY	M1	1.25	9/12/2011-3/12/2012
EURUSD	M5	1.11	2011
GBPUSD	M5	1.0	2011
USDJPY	M5	1.06	2011
EURUSD	H1	1.26	2011
GBPUSD	H1	1.25	2011
USDJPY	H1	1.48	2011

Random trades sometimes produce solid looking equity curves. Remember that this was generated with purely random numbers and a trailing limit

What made me feel better about the results was reviewing the entry and exit efficiencies of each strategy. The number of trades involved really cluttered the graphic. I ran a backtest on a much shorter time period so that the horizontal, blue line would appear clearly on each graph.

The entry efficiency of a random entry is… random (45.45% entry efficiency)

The exit efficiencies of random entries with traililng limits are outstanding

The exit efficiencies of random entries with trailing limits is off the charts. (77.73% exit efficiency)

The entry efficiency tells us exactly what we would expect to find. Trades which enter at random do not perform better than random (obviously). What’s interesting is how the trailing limit exit strategy actually skews the entry efficiencies to read slightly worse than random. This is a good example of why it’s dangerous to rely purely on statistics. Keeping the big picture in mind reduces the likelihood of making an erroneous conclusion, in this case that there might be something “wrong” with our perfectly random entries.

The exit strategy, which is what we’re truly testing, looks absolutely stellar. It shows that acting as a conditional probability allows for a great deal of adverse movement while capturing extreme points of the move.

Adding Money Management

The percentage of winners for the tested charts ranges from 60-67% accuracy. High percentages of winners often lead to winning streaks. My cursory glance through the chart led to my easily finding a suitable example to cherry pick. Here, 5 trades in a row reach their near maximum take profits.

Picking trades at random occasionally leads to streaks of lucky winners

Testing that I’ve done in the past tells me that it’s often advantageous to increase the position size based on consecutive winners when a strategy is more than 50% accurate. My first idea after reviewing the initial results was to modify the forex money management strategy to pursue the consecutive winners. We unfortunately do not have time to pursue those changes in the code right now. Let me know if you’re interested in seeing this and we’ll make it a priority if enough readers respond.

While increasing the risk after consecutive winners works out statistically in your favor, it does add to the risk. It’s entirely possible for a “winning” set of trades to start losing based solely on the money management strategy. There’s no way to know whether your set of trades will be the luck beneficiary of the extra risk or whether it will be the unlikely loser.

Conclusion

Everyone talks about stops. You always have to have a stop. Blah blah blah. I know it’s going to be the first question that everyone asks.

My research shows that trading with a stop is for suckers. Larry Connors’ book Short Term Trading Strategies That Work was the first trading book where I actually felt like I read valuable information. One of my favorite sections is on stop losses. His research shows that using a stop loss (even a 50% stop loss) always reduces the performance of a strategy. My own independent analysis bears this out.

Not using stops does not mean never taking losses. On the contrary, refusing to exit the market at a loss makes for a 100% odds of blowing up one day. The point of using a stop or limit is to empirically define, and to never waver from, a specific point or points in the market at which you will exit. A trailing limit accomplishes that goal admirably.

Interestingly, the trailing limit is one feature which FAP Turbo incorporates that I have yet to find in any other expert advisors. Although I’m not a fan of FAP Turbo type of strategies, it certainly does interest me that one of its main features aligns with this research. Also notable is the fact that the trailing limit continues down even to the point where it accepts losses.

Volatility & Divergence Commentary

February 17, 2012 by Shaun Overton 2 Comments

This week has been an ideas week. An unusual number of clients are asking for my opinion on the ideas that they want to program into an expert advisor. Divergence and volatility keep popping up as themes for the week.

Simple Volatility Filter

Volatility is one of those factors that you cannot ignore in trading. It highlights the overall risk context of the market and says something about the likelihood for a trade to get some wheels.

The number of tools that we have to study volatility is unfortunately very limited. Almost everyone uses ATR, which is the average true range. The calculation for it is very basic. The true range is simply the high minus the low. The ATR is simply the average of all the true ranges over a certain period. Most traders use a 14 period ATR by convention.

I sent the chart below to a client in Australia yesterday who asked if I had any ideas for a volatility filter. It compares a fast and slow volatility window using ATR. The red line represents the 14 period ATR, which I call the fast line. The blue line represents the 300 period ATR, which I call the slow line. I suggested that period he could use the fast line appearing above the slow line as an indicator of high volatility. The opposite indication would indicate low volatility.

Two ATR lines may signal a trend, although they would not indicate the direction.

I created the above chart by dragging and dropping the ATR custom indicator onto a chart. I then dragged and second ATR indicator onto the first ATR indicator. Doing that way overlaps the lines. 0therwise, you would see two lines in separate windows.

When I opened MetaTrader again this morning, the same chart was left open. I immediately noticed that the line crossings appeared to match up with some of the longer term trends. Although it would not indicate the direction of a trend, the ATR crossings might prove useful as a trend detection indicator. If you decide to research this idea, please leave your comments and observation on the blog page below. I enjoy hearing from my readers.

Divergence

I buy into the idea that the market contains price points that are more relevant than others. A lot of the math that I work with involves autocorrelation, which many refer to as the long term memory function. It’s a mathematical tool that allows nerds like myself to find hidden statistical patterns among a bunch of noise in a signal.

Divergence takes a similar idea and applies it to indicators, the most common of which are the MACD, RSI and stochastics. When the price rises above a previous critical point and the indicator does not exceed its previous critical point, then divergence exists. Most traders claim that divergence signals the potential end of a trend.

My biggest gripe with divergence is that the length of trends exhibit random periods. I’ve done plenty of independent research on this topic. Regardless of the method that you use to pick market tops and bottoms or how you define a trend, the time period of the measured trend is always random. It has a probability density, but it definitely does not have a set number.

Divergence completely fails to address this concern. There’s no reason why you can’t have 2 divergences or even 5 divergences in a trend. Divergence does not help the trader distinguish between the end of a trend or a continuing trend. You could use divergence as a trend detection tool, but by that point some traders are already calling for it to end. My personal opinion is that it’s not very useful.

My other complaint with divergence is that the method for picking critical points is totally arbitrary. If you put 10 traders in a room and ask them to draw a trend line, you will get 10 different answers. The absence of consensus on such a basic concept ought to say a great deal about the value of subjective interpretation.

Traders also attempt to draw the points between swing highs and lows. That task should be obvious, but it’s not. I always recommend using the zig zag indicator when customers want to go down the swing trading route. They quickly discover the same problem – how sensitive should the settings be. Again, we circle back to the issue of period length. The swing high that Bob’s Zig Zag settings draw looks like market noise to the swing highs that Alex draws.

My opinion is to stay away from divergence and look for other techniques.