Volatility-based currency trading

Market volatility can be a complex subject, but understanding a few basic principles can help you implement strategies to capitalize on volatility extremes.

Volatility-based trading approaches have traditionally been popular among hedge funds, commodity trading advisors, and other professional traders. There are many ways to gauge volatility and incorporate it in a trading strategy. Of the different ways to characterize and trade volatility, the best are based on the tendency of volatility to “revert to the mean.”

The premise behind volatility mean reversion is that periods of extraordinarily high volatility should be followed by periods of lower, more normalized volatility. Similarly, periods of extraordinary low volatility should be followed by periods of higher, more normalized volatility. This tendency is reflected by the familiar progression of a market that meanders in a narrow trading range (a low-volatility condition), only to explode out of the consolidation and embark on a strong price trend (a highvolatility condition). Eventually, the price move exhausts itself, at which point volatility will again fall to a lower level.

We’ll analyze the two simple methods for trading volatility in the forex market: inside days and shortterm/ long-term volatility comparisons.


Consecutive inside bars

An inside bar is a bar whose range is contained within the prior bar’s range — that is, the bar’s high and low do not exceed the previous bar’s high and low (see Figure 1). They are easy to identify visually and should be one of the basic patterns traders should notice immediately.

Inside bars by definition have lower volatility — that is, less price movement — than their preceding bars, and successive inside bars reflect progressively shrinking volatility. Per the mean-reversion theory, the more inside bars, the higher likelihood of a volatility surge or a breakout scenario.

The following volatility trade can be implemented after at least two consecutive inside bars have formed. This type of strategy is best employed on daily charts; the longer the time frame, the more significant the potential breakout.

The strategy works for both longs or shorts. Although entry orders can be placed on both sides of the market, traders should use other tools to determine the bias for a particular trade. For example, if the inside days occur within a bullish chart pattern, such as a developing ascending triangle, this increases the likelihood of an upside breakout. On the other hand, if the inside days are developing within a descending triangle formation, this increases the likelihood of a downside breakout. Here are the rules for a long trade setup:

1. Buy above the high of the most recent inside bar.
2. Place a stop-and-reverse (SAR) order a few pips (approximately 5 to 10 pips, depending on the bid-ask spread) below the low of the most recent inside bar. The purpose of the SAR order is to reverse the position if the initial move turns out to be a false breakout.
3. If the position moves higher by the risk amount (the difference between the entry price and the stop price), sell half the position and replace the SAR order with a trailing stop.
4. If the SAR order is triggered after the entry, place a stop a few pips above the high of the most recent inside bar.
Short trades: For a short trade, the rules are the same except that you enter below the low of the most recent inside day and place an SAR order a few pips above the high of the most recent inside day.

Figure 2 shows two consecutive inside bars in the U.S. dollar/Canadian dollar (USD/CAD) rate. Applying the strategy, a buy order is placed above the high of the most recent inside bar, while a stop is placed below the low of the most recent inside bar. The long order is triggered and a 200-pip rally ensues with virtually no retracement.

Figure 3 shows a more complex trade example in which the SAR order is triggered. Because of the bullish implications of the ascending triangle that was forming when the two inside bars appeared, the long-trade entry rules were executed:

1. We placed an order to go long a few pips above the high (.7660) of the most recent inside day. The order was triggered.
2. We placed an SAR order a few pips below the low of the most recent inside day at .7600 for a risk of approximately 60 pips. The SAR was triggered when the market broke out of the bottom of the triangle, and we sold the original long position and entered into a new short position.
3. When the market moved lower by the risk amount (60 pips), we sold half the position (at .7540). We then used a 30-pip trailing stop on the remaining position.

The low on April 14, 2004 was .7299, and we exited the remaining half of the position at .7329.


Volatility comparison

Currency option volatilities measure the rate and magnitude of the past and potential future changes in a currency’s price, and they can be a useful tool for timing currency movements.

Implied option volatilities, which are reflected in option premiums, are the market’s current estimate of the future fluctuation of a currency’s price. Historical (or statistical) volatility, which reflects past price movement, is typically measured by calculating the annualized standard deviation of price changes over a given period (e.g., 20 days, 100 days).

Figure 4 shows only current option implied volatilities (which are based upon a survey of interbank sources). Traders implementing this strategy would need to keep a journal tracking historical implied volatilities. Onemonth and three-month implied volatilities are two of the most commonly benchmarked time frames.

When option volatilities are low, traders should look for potential breakouts. Current implied volatility should be at least 25 percent lower than historical implied volatility. (It is best to measure against actual historical volatility, but that data is not always readily available.) Conversely, when option volatilities are high, traders should look for range trading opportunities.

Typically, when a currency trades in a range, its option volatility will decline, because by definition range trading means lack of movement.
When option volatilities make a pronounced down move, it is usually a sign of a significant potential price move and upcoming trade opportunity.

This characteristic is very important for both range and breakout traders.
Traders who usually sell at the tops of ranges and buy at the bottoms can use this approach to predict when their strategy could potentially stop working, because if volatility becomes very low, the likelihood of continued range trading decreases.

On the other hand, breakout traders can monitor option volatilities to make sure that they are not buying or selling into false breakouts. If volatility is at average levels, the likelihood of a false breakout increases. Alternatively, if volatility is very low, the probability of a real breakout is higher. However, traders must be careful because volatilities can have long downward trends, as they did between June and October 2002. Therefore, declining volatilities can sometimes be misleading. What traders need to look for is a sharp move in volatility, rather than a gradual one.

Figure 5 shows an example in the U.S. dollar/Swiss franc rate (USD/CHF). The blue line is price, the green line is the one-month (or shortterm) volatility, and the red line is three-month (or longer-term) volatility. For most of December 2003 the onemonth volatility was below the threemonth volatility, which coincided with the development of sharp down moves in USD/CHF. Between Feb. 24, 2004 and March 9, 2004, the one-month volatility spiked above the threemonth volatility, which coincided with a period of range trading.


All shapes and sizes

Volatility is expressed many ways — on different time frames and in term of option prices and past price fluctuations in an underlying market.
Understanding some simple volatility principles, such as mean reversion, can help you time trades when a volatility shift is likely to occur.


BY KATHY LIEN
February 2005 • CURRENCY TRADER

Introduction to the volatility

Advisor to trade on commodity markets Lendri David is the head of the firm to manage money «Sentive Trading», and the head of hedge fund «Harvest Capital Management». David Lendri has a lot of copyright trading systems, including the breakthrough 2 / 20 EMA and the method of explosion variability. His research has links to several books, such as books Connors «Advanced trading strategies» and «Basic Principles of computerized trading techniques for beginners».

Traders are never far from the notion of variability, whether due to technical factors or because of the news. We hear this all the time: intra-day traders report that volatility is their best friend when it provides opportunities for short-term trading, while the long-term investors always keep a cautious and try out the most recent period of volatility until the situation is again not rest. It is not surprising that many traders have trouble understanding what is actually meant variability and how it affects their trade.

To better understand this important aspect of trade, at first look, that is the variability inherent
her features and an easy way to measure it. We also describe the general ways of applying these concepts to market. In the future, we will consider more sophisticated measurement variability and more certain methods of trade.

Simple concept

From a mathematical point of view, variability is one of the most complex market concepts. But this does not imply that it must be difficult to understand in a practical trade. Variability is a simple measure of how price changes in a given period of time. For example, if the Dow Jones rose 10 points in one day and fell to 10 points in the next, you probably would say that volatility is low. However, if it increased by 200 points in one day and fell to 200 points the next, you probably would say that the market is volatile.

In the most general terms, this is really all. A more detailed and complex material belongs to the consistent measurement of variability by monitoring its behavior, and using it in their trade.

The characteristics of variability

Variability has some inherent characteristics: cycles, constancy and return to the mean value. While this may at first sound is unclear and difficult, again, the notion, in fact, very simple.
Variability is cyclic: Variability tends to move in cycles, rising and reaching a peak, then decreasing until it reaches the lower limit and the process begins again and again. Many traders believe that the variability of more predictable than the price (because of the characteristics of pro-cyclical) and are developing models to trade, based on this phenomenon.

Variability is constant: Consistency is the simple ability to follow the variability from one day to the next, suggesting that the variability that exists today will probably be tomorrow. That is, if the market is today varies, then most likely it will be varies and tomorrow, on the contrary, if the market does not currently varies, it is likely that he will not be varies and tomorrow. The same way as if the volatility is increasing today, it is likely that it will continue to rise tomorrow, and if variability is reduced today, it is likely that it will continue to decline tomorrow.

Variability tends to revert to the mean: I was once asked to describe the return to the mean in simple terms as possible. My answer was as follows - if you know someone who usually keeps you cautiously and then within a few days would be too lyubezen with you, there is a high probability that he will return to again be restrained.
If serious, this concept simply means that the volatility tends to revert to a mean value or the normal level when it reaches the upper or lower extreme. As soon as the market reaches the upper extreme in its variability, it is likely to revert back to the mean value, ie, the variability will decline back to more normal or average. On the contrary, as soon as the variability is extremely low, it is likely to rise to more normal or average. This is like a gum: when it is stretched, it tends to go back.

Figure 1. The characteristics of variability

The above concepts shown in Figure 1. Pay attention to the characteristics of cyclic variability. She has a tendency to oscillate back and forth between periods of low volatility and periods of high volatility. She has a tendency to persist. Days of increasing variability (a) tend to be accompanied by increasing variability of days (b). On the contrary, the days of declining variability (c) tend to be accompanied by decreasing variability in days (d). Finally, it has a tendency to return to its average value, ie, periods of extremely high variability (e) have a tendency to be accompanied by moves to a more normal or average (f). On the contrary, periods of extremely low volatility (g) tend to be accompanied by periods of more normal or average volatility (h).

Measurement variability

As this introductory article on the variability, we show a simple way to measure it. One of the easiest ways is to take the middle range (maximum - minimum) for the period. The number of days (or hours, weeks, etc.) that you are using in their calculations, gives you a picture of variability over this period. Calculation of the five-day mid-range gives you an idea on how volatile the market was last week, but it does not tell you about the past six months. Evaluating the 100-day average would reflect the range of variability for a much longer period.

Figure 2. The true range.

As more volatile markets often form GEPy up or down between the opening and closing, then the true range, developed by Vélez Vaylderom provides a more accurate measure of variability because it takes into account the inter-sessional GEPy in its computation. This concept is demonstrated in Figure 2. Since the range for only one day does not give much information, the true range can be averaged over a period of time (say, two weeks). This average true range gives you a better sense of the variability of a time.

The true range is the highest value (in absolute terms) of:
1. So now the maximum minus minimum
2. So the maximum minus yesterday's closing
3. So at least minus yesterday's closing

Figure 3. Global Telesystems (GTSG)

Here, we measured the volatility by taking a 10-day average true range (ATR). Again, pay attention to the cyclical variability. It tends to be cyclical movement from periods of high volatility to periods of low volatility. She has a tendency to continuity, periods of increasing volatility (a) tend to be accompanied by periods of increasing volatility (b). On the contrary, periods of decreasing volatility (c) tend to be accompanied by periods of decreasing variability (d). Also, please note that it has a tendency to go back to its average value. That is, periods of extremely low volatility (e) have a tendency to be accompanied by periods of higher or more normal (average) levels of variability (f). On the contrary, periods of very high variability (g) tend to be accompanied by periods of lower or more than normal (average) levels (h) variability.

The general application to trade
Markets with higher variability suggest a potentially greater returns, accompanied by increased risk. Short-term traders, whose profits are limited by the extent to which market-based instruments can move over time, can seek more volatile markets. Long-term or more, conservative investors can look for markets that are less volatile.

If market volatility is extremely low (compared to the average or normal level), there is a high probability that inevitably followed by a larger movement, as the variability of returns to its average value. On the contrary, if the variability is extremely high (compared to normal levels), whereas a large price movement, which created a jump in volatility, could end up as the variability of returns to more normal levels.

Conclusion

Variability measures the price change in the market for a certain period of time. The average true range of the market provides a simple way to calculate the volatility. Markets that are more variable, suggest a potentially greater profits when trading with an increased risk. Variability has several important characteristics: cycles, constancy and return to the mean value. These concepts can be used to help determine which markets provide the highest potential profit when a large movement is likely to happen when the movement can be completed.

In future articles, we have a more detailed look at these concepts by using historical volatility, more mathematically complex but useful way to measure volatility. We show how this can be used to find (or avoid) a very volatile market, set realistic point for establishing the initial protective stop order and to find markets that are likely to explode or fall within the period of accumulation of low variability.

David Lendri
www.hardrightedge.com