Understanding and Applying Standard Deviation in Market Analysis
Standard Deviation — value of the market volatility measurement. This indicator describes the range of price fluctuations relative to Moving Average.
Moving Standard Deviation (MSD), or moving average standard deviation (MASD), is the statistically measured quantity that expresses the extent of volatility in the market. MSD does not tell about the direction of market trends. You can get it by estimating in a time period by the simple moving average of the data. Then, the sum of the squares of the difference between the moving average and the current item brings you the required average.
The moving average is a way to get an overall picture of the trends in a collection of data. It is more precisely known as the moving average deviation indicator. It implies the magnitude of volatility in the market. We’ll discuss here the standard deviation (SD) from MetaTrader 4. It applies the concept in forex trade and in estimating other financial prices to show the details about volatility in the market and it’s implications for professional traders.
The term standard deviation (SD) originates in statistics. SD is the term that finds the quantity of dispersion or variability with respect to an average. Further, SD is an amount of volatility. You may be aware of dispersion. Dispersion implies the variation between the average and the actual values. When the dispersion is higher, the SD is going to be higher. Likewise, when the variability or dispersion is low, the SD is going to be lower. Chartists use the notion of SD to measure the probable risk and estimate the important movement at certain prices.
How to calculate the SD?
While determining the SD for a data population that takes the periods to be representative of the whole set of data. It does not represent a sample extrapolated from a value set.
The SD can be calculated thus:
- 1. Determine the average price (the mean) for the given number of observations or periods
- 2. Estimate the deviation for each period.
- 3. Find the square of the deviation for each period.
- 4. Find the sum of s squared deviations.
- 5. Divide the sum obtained in step 5 by the total number of values.
- 6. Now the SD equals the square root of the number obtained in Step 5.
Note that the average is estimated after the tenth period applies to all the periods. Determining a moving standard deviation (MSD) is a major challenge. To render it easily, you can use MSExel where you can get the formula.
There are various steps in estimating the SD for a price set. You need to follow these steps:
Take a specific observation window (say, 20 periods).Estimate the mean average for the price set for the window.Find the difference between price and mean in each case.Square the value of deviation obtained in the last step.Find the sum of values obtained the last stepDivide the sum by a number as many as periods to obtain the variance.
Find the square root of deviation to obtain the standard deviation.
Mathematically it can be put as (for N periods)
In this mathematical expression, = standard deviation,
Xi = price
X = mean of the prices
Thus, the standard deviation is exactly the variance square root driving you home to the unit of measure it was initially expressed.
This formula for SD is used by indicator used in MT4.
Thus, the standard deviation takes into account the price over a period and plots the histogram representing the SD for the set of observations.
The window of observations is on the move with time and the old data are replaced by new data each time a new bar showing prices is shown. This helps you get a view of the extent of volatility and its changes. It also helps build your future expectations.
Values of standard deviation
The SD values depend on the security price. High price securities, for example, Google, do not reflect a higher volatility. SD values are such that they come directly into a relationship with the security price.
Historical SD values as well are influenced if security undergoes a change in price in a given span of time. As a thumb rule, a security moving from 10 t 5o is likely to experience a higher SD at 50 as compared to what it does at 10.
In the chart given, the scale on the left is related to SD. Google’s SD goes up from 2.5 to reach 35. On the other hand, Intel’s security rose from 10 to reach 75. The average change in price (deviation) in Intel varies between 10 cents and 75 cents.
There is a difference in ranges; charts can determine the volatility change in security by just taking a cursory glance at the data. The volatility in the security of Intel increased during April-June. Google showed up a volatility spurt in the month of October as standard deviation beyond 30. You need to divide the SD by the price at the close to make a comparison of volatility for two given securities.
Simplifying the concept of standard deviation
The SD is an indicator that quantifies the extent of recent fluctuation in the price of an asset to bring forth the trend in the future (how volatile the price is going to be). Simply put, the standard deviation is a measure of the average gap between the data values in the set the mean.
The SD is a concept from statistics to describe the distribution of a data set value.
The standard deviation has a value to indicate how deviated the distribution values from the average value for the given set of data. When the SD is higher, it has more broadly spread values in the set of data. Likewise, when the SD is less, the values are narrowed distributed. We’ll elaborate it here a little:
High standard deviation
In high standard deviation, the price moves up considerably from the values they were at before. A high SD is indicative of the data points being spread over a large value range.
Low standard deviation
Contrariwise, when the standard deviation is low, it indicates the price is stable showing that was low fluctuation in price. If the reading is fairly low it indicates that volatility is going to be high shortly.
Standard deviation is amonh the most common methods of finding the magnitude of risk involved in an investment. If the SD is high, it happens when there are wild price fluctuations. Therefore, under the circumstances, it’s not advisable to invest. and low standard deviation indication low risk in investment.
Using of standard deviation in finance and forex
The SD is used particularly in financial markets to measure the extent of volatility. Thus, it’s a measure of risk.
Note that volatility in this context has diverse connotations. We’ll discuss here the notion of market volatility and the ways it is described.
How to measure expectations
You can use the present value of SD to determine the importance of a change and set expectations. Under the circumstances, you assume that the price variations are distributed normally. Chartists can use guidelines on normal distribution to estimate price movement significance.
When it comes to the normal distribution, of all, 68% of the values are within one SD. 95% of values are within 2 to 99.7 of the values are within three.
Taking the help of these guidelines, trades determine the importance of a movement of the price. A move more than one SD will indicate more than average weakness or strength as per the direction the move happens.
The chart depicts Microsoft’s 21-day SD in the window indicator. Usually, a month will have 21 business days and month SD was 88 at the close of the day. A normal distribution will have 68% of observations, a change of 88 cents, and values to the extent of 95% show change price below 1.76 cents. 99.7% values would reflect a price deviation of below 2.64, which is equivalent to three SDs price deviations with 3, 2 or 1 as SDs are significant.
The SD for 21 days is very unstable as it deviated between 0.32 to 0.88 during the middle of August to the middle of December. A moving average of 250 days is worth considering to smoothen the indx and estimate the average. It approximates at 68 cents. Variations in price over 68 cents were over the 250-day standard moving average of 21-day SD. These variations greater than the average price imply there is increased interest could trigger a change in trend or indicate a breakout.
How to rule out high volatility
The SD indicator is frequently used in scan to rule out volatility in securities. The scan is simple an looks for S&P stocks (600). These select stocks are in an upward movement. The final stage scan clause removes stocks that experience high volatility from the results. Under the circumstances, the SD is changed into a percentage point. This will help make the comparison easy and simple because all the values are on the same scale.
SD and Sharp charts
The SD can be used with SharpCharts along with a parameter 10. The parameter could be modified as per the needs of the analysis. One month has 21 business days, therefore, 63 days make a quarter, 250 business days make a year. The SD can be applied on monthly or weekly charts. You can apply the indicators to SD by just clicking the advanced options. The add an overlay and you’re done.
Why is studying volatility so important?
Fund managers have the great pleasure to observe the trends in volatility in the market. Thus, they will be interested in SD as a yardstick to make a comparison of diverse groups of funds and their continuously compounded returns over time.
In comparing managed funds, the most widely used measure is Sharpe ratio, developed by William F. Sharpe. The Sharpe ratio is the difference between the returns on investments divided by the standard deviation being considered. This version of the indidcator in investing enables pension funds to make a comparison of diverse mutual funds by suitably taking into account the risk. Even long term investors take volatility into account as it is a helpful indicator to help determine expectations of the way losses may go against you over the life time of an investment.
In forex trading
As for forex trading, how broadly prices vary from the average price over time is beneficial for various reasons.
The Sharpe ratio can apprise traders on how far or near to place a stop-loss or it can provide clues on if prices are going away from the range or going to move in the direction as that of a recent mean. If the SD for a pair of currency is high, values corresponding to price are scattered and the range of price is wide. Thus, the SD is an indicator that shows how volatile the market is.
How forex traders use volatility
For forex traders, volatility brings dual scenarios. This is because when volatility is high it brings the potential for profit. However, there is an equally higher risk: prices moving to a level, not in your favor. The amount of volatility you wish to experience is according to your trading style. Thus, a swing trader looks for more volatility in markets because when the price fluctuation is steeper, it leads to more profits within a shorter period.
Traders who use long-term-follow strategy would like to accept a less volatile instrument as the noise of fluctuation of in price, which may make it difficult to recognize the trend. It can also make the ride less smooth in a holding a position.
Now the question is how to calculate the standards deviation.
If you’re on the lookout for an indicator that is simple, easy to understand and use, moving average deviation indicator commonly known as standard deviation, discussed so far is the best option as a quantifier of volatility. It is used in MT5 and MT4. It uses proven theory in estimation of the values and enables you to check easily the volatility trend.
As a measure of volatility standard deviation/ moving standard deviation is an important concept. The values of SD offer to help chartists to bring out insights into the market trends in terms of price variation. When the price moves are higher than SD it shows more than average weakness or strength. Further, the SD is also used with indicators like Bollinger Bands. These bands comprise two standard deviations more and less than a moving average. Moves that are greater than the bands are considered important worth attention. Note that just like the other averages, the SD has to be used with other tools such as chart patterns or momentum oscillators.