The importance of volatility
Studying price changes can bring attractive opportunities to trade on financial market trends. Some strategies taken into consideration are primarily based on the concept of Mean Reversion.
Estimating volatility, i.e. the measure of price changes over a certain period of time, is fundamental to assessing the risk of each financial asset.
High volatility suggests that prices tend to fluctuate widely over the period analysed. This pattern reflects both a source of opportunity as well as a high level of risk.
There are basically two types of volatility:
- historical volatility, used for technical analysis, is calculated by measuring price movements over a specified period. Historical volatility is therefore based on observations of a period prior to the valuation date and assumes that future volatility will be similar to its past behaviour; and
- implied volatility, which is based on expected future price movements for a given underlying financial asset on the options market. The underlying assumption is that the options market is a particularly effective indicator of future volatility.
In practice, implied volatility expresses volatility expected by professional traders in the future.
For example, if traders expect higher variability, the premium that the option buyer will have to pay in order to have the opportunity to buy (call) or sell (put) the underlying asset in the future at a price set today increases. This marks a clear difference between the two methods: historical volatility expresses fluctuations in past returns, while implied volatility reflects expected future price changes. Traders often refer to intraday volatility. Intraday volatility is represented by price highs and lows within a single day. It is determined based on:
- the day’s range, calculated simply as the difference between the high and the low for each session. However, this value can be erratic: that is why traders often use the Average True Range, an indicator that calculates the average range of the last 14 days (reflecting any price gaps);
- standard deviation, a statistical measure of the dispersion of a dataset. This metric is applied for example in determining the widely used Bollinger Bands, an «envelope» around a central moving average. The standard deviation above and below this average is then plotted out and multiplied by two to set the upper and lower band, respectively.
The characteristics of volatility
The characteristics of volatility make it a useful in trading:
- volatility is cyclical: periods of low volatility are followed by periods of high volatility, presuming the trend is cyclical, increasing and decreasing periodically;
- volatility is persistent: this means that volatility can persist from day to day on its values;
- volatility tends to move towards its average: even after reaching extremely high or low peaks, volatility will generally to revert back to its average values (this is referred to as mean reversion).
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