Wednesday, March 11, 2009

Introduction to the volatility

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.

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.

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

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.