In this second experimental article, our resident programmer Craig & I want to make sure we know what we are talking about, when we talk about volatility (our first article can be found here). However we are not so much interested in the academic definition. There is no particular reason to express or measure volatility in one of several possible ways, so long as you remain consistent in your studies. Instead, we are going to demonstrate in which ways volatility is important to traders, and explore potential ways of exploiting volatility dynamics.
Large changes tend to be followed by large changes, of either sign, and small changes tend to be followed by small changes – Mandelbrot (1963)
Volatility Clusters in Crude Oil as identified by the ATR Volatility Indicator (programmed by Craig Consulting). To download the indicator for MT4, click here
Have you ever noticed the fact that when the market starts to “explode”, it tends to produce oversized moves at relatively small intervals? This tendency is called “volatility clustering” and is evidenced clearly in the above chart. Large range days tend to stick together once the market experiences volatility expansion; small range days tend to cluster together, when the market calms down.
In the chart above, the ATR Volatility indicator answers a very simple question: how large has today’s absolute price move been, relative to the average absolute price move over the lookback period? To show the clusters better, we have used a longer term ATR average (100 Days) and a cutoff value of 1.5 (so there will be a spike only if today’s ATR was larger than 1.5xAvg ATR). In case you were wondering about ATR, we wrote a post about it some time ago.
There are a few important considerations to make, regarding volatility clusters:
- dormant markets tend to be “shocked” when sudden information enters the market. This may be in the form of earnings (for stocks), geopolitical turmoil (all asset classes), Central Bank announcements or NFP or other intense market movers (FX), etc. Basically sudden, non-discounted information hits the market and causes volatility increases.
- It is infrequent that after a sizeable volatility shock, the market goes back to sleep. More often than not, the market will remain volatile for some period of time.
- Volatility does not mean direction. Directional volatility (i.e. momentum) is something else that we may explore in another article. Volatility in itself is non-directional. This means that you can (and will) observe large up days alternated by large down days once the market is shocked.
So when a relatively calm market gets shocked, bet on increased future volatility and don’t consider it a one-off event. However, to exploit this tendency via directional trading, the going gets tough. Options traders might decide to sell volatility when there are large shocks and volatility reaches extreme levels. But in trading, how can we exploit the phenomena of volatility clustering?
The answer lies (once again) in learning how to identify market sentiment (so Coaching members will now be on the edge of their seats). To understand this dynamic, scroll back on your charts and match the market movers or news from the volatile days. You should find a correlation. In the markets, volatility tends to follow new information. That is defined as event volatility risk. So the key, then, is to incorporate this into your own trading. Think about ways to incorporate the knowledge you now know about volatility clustering into your trading plans.
Volatility Clusters in GBPUSD with the ATR Volatility indicator. We notice that periods of high and low volatility alternate much more frequently than in Crude Oil. This could be a direct result of FX Volatility being much more “calendar dependant”.
For those readers that are more technically inclined, we would suggest researching “volatility autocorrelation” and “volatility persistence”. There is a wealth of academic literature on the subject.
The basic premise of the system is that markets move sharply when they move. If there is a sudden range expansion in a market that has been trading narrowly, human nature is to try and fade that price move. When you get a range expansion, the market is sending you a very loud, clear signal that the market is getting ready to move in the direction of that expansion. – Paul Tudor Jones
Volatility Cycles as evidenced by the ATR Oscillator. Volatility rises and falls in a cyclical manner. The ATR Oscillator, programmed by Craig Consulting, is a simple comparison of volatility over two time horizons. Effectively, it compares long vs short term volatility. To download the oscillator, click here.
Beyond volatility clustering, another key feature of volatility is it’s tendency to move in cycles. When volatility starts to contract, traders should be prepared for the subsequent expansion in volatility. Vice versa, when volatility starts to reach relatively high levels, traders should be prepared for a drop in volatility.
The funny thing is that the media, and many retail traders, lose interest in the markets when they start to range-trade. Markets seem “boring” and nobody talks about them. However, it’s exactly at this stage the the market is preparing for it’s next move. Expert traders know this and are monitoring levels & volatility, carefully stalking their prey and getting ready to capitalize on the subsequent volatility expansion which usually results in some kind of directional move out of the range.
What are the practical implications of this?
- breakout trades should have a higher probability of success, when in low volatility states.
- When volatility starts to contract, it generally (but not always) leads to range trading environments.
- When volatility starts to expand, it generally (but not always) leads to trend trading.
Options are priced lowest when recent volatility has been very low. In my experience, however, the single best predictor of future increases of volatility is low historical volatility. When volatility gets very low in a market, we consider that a very interesting time to start looking for ways to get long volatility, both because volatility is very cheap in an absolute sense and because the market certainty and complacency rejected by low volatility often implies and above-average probability of increased future volatility. – James Mai
The ATR Oscillator, programmed by Craig Consulting, and below it a normal 22 Day ATR reading. Whether with these or other tools, volatility cycles are extremely important for traders. To download the oscillator, click here.
The volatility cycles are evident even on lower time-frame charts. Now it may make more sense why London Breakouts tend to have a stronger edge than other time zones: London wakes up within a low volatility environment, and the increase in participation and activity make breakouts or at least trends the higher odds solution.
Volatility vs. Trend Following Profitability
Many studies have attempted to link volatility states with the efficacy of CTA trading models. Most CTA models are trend-following in essence, so the following observations should be relevant for traders adopting trend-following systems.
It appears that Trend Following is profitable in both high volatility and low volatility, but it also depends on the correlation amongst asset classes. Let’s explore the two states which give Trend Following an advantage.
– Low Volatility, Low Correlation. In low Volatility environments, assets do not react violently to information arrival. This increases the likelihood of underreaction to news (and thereby follow-on momentum), which is good for trend followers. In addition, low Correlation implies that related markets are not moving in lock-step. Thus, low Correlation makes it more likely that information diffuses across markets slowly.
– High Volatility, High Correlation. This state indicates crisis. A good example is 2008, and before that the state materialized in (e.g.) 1998, the 2001-2002 recession, and during the pullback in 2004. High Volatility reduces asset-specific drift. These forces are all directionally bad for trend followers. But the big opposing force is that crisis causes persistent deleveraging, driving positively autocorrelated asset class returns. In this state, the large net exposures can actually pay off. So long as deleveraging happens over an extended window, CTAs will benefit as they tactically get long or short in the middle of a cycle of outflows.
Over To You
This article is more about stimulating considerations and thought more than offering concrete solutions. You now know that volatility comes in clusters, and that these clusters alternate in an inconsistent fashion. Periods of low volatility are found generally in range-bound conditions and traders should stalk breakout/continuation trades. Periods of high volatility are found generally within trending markets but traders should be ready for the return to lower volatility states.
As usual, this is experimental work that Craig & I are doing, so any ideas or considerations are quite welcome.
About the Author
Justin Paolini is a Forex trader and member of the team at www.fxrenew.com, a provider of Forex signals from ex-bank and hedge fund traders (get a free trial), or get FREE access to the Advanced Forex Course for Smart Traders. If you like his writing you can subscribe to the newsletter for free.