###### Forex for a trader

How to Measure Volatility. Volatility is something that we can use when looking for good breakout trade opportunities. Volatility measures the overall price fluctuations over a certain time and this information can be used to detect potential breakouts. There are a few indicators that can help you gauge a pair’s current volatility. Moving averages are probably the most common indicator used by forex traders and although it is a simple tool, it provides invaluable data. Simply put, moving averages measures the average movement of the market for an X amount of time, where X is whatever you want it to be. There are other types of moving averages such as exponential and weighted, but for the purpose of this lesson we won’t go too much in detail on them. For more information on moving averages or if you just need to refresh yourself on them, check out our lesson on moving averages. Bollinger bands are excellent tools for measuring volatility because that is exactly what it was designed to do. Bollinger bands are basically 2 lines that are plotted 2 standard deviations above and below a moving average for an X amount of time, where X is whatever you want it to be. One line would be plotted +2 standard deviations above it and the other line would be plotted -2 standard deviations below. When the bands c ontract , it tells us that volatility is LOW. When the bands widen , it tells us that volatility is HIGH. For a more thorough explanation, check out our Bollinger bands lesson. 3. Average True Range (ATR) Last on the list is the Average True Range , also known as ATR. The ATR is an excellent tool for measuring volatility because it tells us the average trading range of the market for X amount of time, where X is whatever you want it to be. So if you set ATR to 20 on a daily chart, it would show you the average trading range for the past 20 days.

When ATR is falling , it is an indication that volatility is decreasing. When ATR is rising, it is an indication that volatility has been on the rise. Currency Volatility Chart. See the currency pairs with the most significant price fluctuations. The following graphs provide a simplified overview of recent price activity for different currency pairs and commodities. The Price Movement graph shows the extent and direction of price movement since the beginning of selected time period until current time. The High-Low Movement graph shows the extent of price fluctuation between the high and low prices during the same time period. This value is always positive and can be used as a simple measure of market volatility for the selected currency pair or commodity. Note: Not all instruments (metals and CFDs in particular) are available in all regions. How to use this graph. Contracts for Difference (CFDs) or Precious Metals are NOT available to residents of the United States. This is for general information purposes only - Examples shown are for illustrative purposes and may not reflect current prices from OANDA. It is not investment advice or an inducement to trade.

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Forex Volatility Calculator. Volatility is a term used to refer to the variation in a trading price over time. The broader the scope of the price variation, the higher the volatility is considered to be. For example, a security with sequential closing prices of 5, 20, 13, 7, and 17, is much more volatile than a similar security with sequential closing prices of 7, 9, 6, 8, and 10. Securities with higher volatility are deemed riskier, as the price movement--whether up or down--is expected to be larger when compared to similar, but less volatile, securities. The volatility of a pair is measured by calculating the standard deviation of its returns. The standard deviation is a measure of how widely values are dispersed from the average value (the mean). The importance of volatility for traders. Being aware of a security's volatility is important for every trader, as different levels of volatility are better suited to certain strategies and psychologies. For example, a Forex trader looking to steadily grow his capital without taking on a lot of risk would be advised to choose a currency pair with lower volatility. On the other hand, a risk-seeking trader would look for a currency pair with higher volatility in order to cash in on the bigger price differentials that volatile pair offers. With the data from our tool, you will be able to determine which pairs are the most volatile; you can also see which are the most - and least - volatile days and hours of the week for specific pairs, thus allowing you to optimize your trading strategy.

What affects the volatility of currency pairs? Economic andor markets related events, such as a change in the interest rate of a country or a drop in commodity prices, often are the source of FX volatility. The degree of volatility is generated by different aspects of the paired currencies and their economies. A pair of currencies - one from an economy that’s primarily commodity-dependent, the other a services-based economy - will tend to be more volatile because of the inherent differences in each country’s economic drivers. Additionally, different interest rate levels will cause a currency pair to be more volatile than pairs from economies with similar interest rates. Finally, crosses (pairs which do not include the US dollar) and ‘exotic’ crosses (pairs that include a non-major currency), also tend to be more volatile and to have bigger askbid spreads. Additional drivers of volatility include inflation, government debt, and current account deficits; the political and economic stability of the country whose currency is in play will also influence FX volatility. As well, currencies not regulated by a central bank - such as Bitcoin and other cryptocurrencies - will be more volatile since they are inherently speculative. How to use the Forex Volatility Calculator? At the top of the page, choose the number of weeks over which you wish to calculate pairs volatility. Notice that the longer the timeframe chosen, the lower the volatility compared to shorter more volatile periods. After the data is displayed, click on a pair to see its average daily volatility, its average hourly volatility, and a breakdown of the pair’s volatility by day of the week. Forex Training Group. Volatility is the change in the returns of a currency pair over a specific period, annualized and reported in percentage terms. The larger the number, the greater the price movement over a period of time.

There are a number of ways to measure volatility, as well as different types of volatility. Volatility can be used to measure the fluctuations of a portfolio, or help to determine the price of options on currency pairs. Understanding and learning how to measure volatility in the foreign exchange markets is a must for every serious trader. Different Types of Volatility. There are two specific types of volatility. What has already happened is known as historical volatility, whereas what market participants think is going to happen is referred to as implied volatility. The former, can be used to predict the latter, but the latter is a market input, determined by the people that are participating in the forex options market. The market’s estimate of how much a currency pair will fluctuate over a certain period in the future is known as implied volatility. Option traders can use a currency volatility index to price options on currency pairs. Implied volatility is generally considered a measure of sentiment. When the currency markets are complacent, implied volatility is relatively low, but when fear infiltrates the market environment, implied volatility rises. Implied Volatility is used to Value Currency Options.

Implied volatility is a critical component of option valuations. There are two main style of options on currency pairs – a call option and a put option. A call option is the right but not the obligation to purchase a currency pair at a specific exchange rate on or before a certain date. A put option is the right but not the obligation to sell a currency pair at a specific exchange rate on or before a certain date. The exchange rate where the currency pair will be transacted is referred to as the strike price while the date wherein the option matures is called the expiration date. Forex options are quoted by dealers in the currency markets in two different ways. Dealers at times will quote a number that describes the volatility expected for a specific option that expires on a certain date. At times they will quote the price of the option. Options on currency futures are always quoted as a price.

Options on currency exchange traded funds are also quoted as a price. The price of a currency option incorporates the market volatility of a currency pair; which is how much market participants believe a market will move on an annualized basis. If you are an active currency options trader you will likely be aware of the implied volatility of each major currency pair. For those that are not actively trading options, there are some tools you can use to find current options implied volatility. Determining implied volatility for a financial instrument requires certain inputs. The equation is an options pricing model. The most widely used and famous options pricing model is the Black Scholes options pricing model. Currency Options Pricing. An options pricing model uses several inputs which include the strike price of the option (which is an exchange rate), the expiration date of the option, the current exchange rate, the interest rate of each currency, as well as the implied volatility of the forex option. The calculation determines the probability that the underlying exchange rate will be above or below a strike price, depending on whether you are generating a price for a call or a put option.

All the inputs for the Black Scholes Pricing model are related to one another and therefore if you know the price of the option, you can back out the implied volatility of the forex option. So, if you see the price of an option (or the bid offer spread of an option), you can use an options pricing model to find the implied volatility of the currency pair. A simple options calculator will allow you to input a price and find the fx option volatility of a specific currency instrument. Another simple way to get the volatility of a Currency ETF is to use Yahoo Finance. The options chain example above shows a one-month option price that is closest to the money ($106), has implied volatility of 7.73%. This is a way of estimating what options traders believe will be the movement of the FXE (Currencyshares Euro Trust) over the course of the coming year. Once you know where current implied volatility is, it is helpful to understand where it was in the past. There are some free versions of software that will show you historical volatility. Ivolatility. com, offers a forex volatility chart which can help you determine the relative level of implied volatility. The free version shows currency ETF implied fx volatility index for 52-weeks, and is helpful in determining the relatively strength of present implied volatility. There are a few software packages available that will allow you to view long term historical volatility on currency futures as well as currency ETFs. This type of software will allow you to perform many different types of technical analysis studies on historical volatility. Since implied volatility is generally a mean reverting process, you can use different technical studies that measure this – such as the Bollinger bands indicator.

Technical Methods for Measuring Volatility. The Bollinger bands indicator show a 2-standard deviation band above and below the 20-day moving average. These defaults can be changed, depending on how wide you believe the distribution should be. So you can use a 3-standard deviation on a 50-day moving average if you prefer. When the implied volatility index hits the Bollinger band high which is 2-standard deviations above the 20-day moving average, implied volatility could be considered rich, and when the implied volatility hits the Bollinger band low (2-standard deviations below the 20-day moving average), the level is considered cheap. This type of analysis helps the forex trader implement volatility based strategies. Additionally, you can use Bollinger bands to evaluate the volatility of any security. The difference of the change in the Bollinger bands (change in standard deviations) is a measure of historical volatility. The Bollinger band width is a measure of the difference between the Bollinger band high minus the Bollinger band low. As the Bollinger band width expands, historical volatility is rising and when the Bollinger band width contracts historical volatility is falling. Understanding Historical Volatility. In addition to evaluating implied volatility to determine how volatile the market could be, you can also evaluate what has happened in the past to determine future volatility. This is known as historical volatility. Historical volatility tells us how much the market has moved on an annualized basis. The historical volatility is calculated by defining several parameters.

First, you need to decide on the period which for you are calculating the change in price. Historical volatility is calculated by analyzing the returns; which is the change in the value of a currency pair. The basic period can be a one-day change, which is often used, or a 1- week or 1-month change. You will also need to determine how many periods you plan on using in the calculation. This process can be easily accomplished with excel or by using a calculator. What you are actually trying to calculate is the standard deviation, which is the average squared deviation from the mean. The last thing you need to do is annualize the number by multiplying the volatility by the square root of time which is the days in a year. The output number is a percent value which tells you the annualized movement of the returns of a currency pair. You can use different technical analysis tools to help you gauge historical volatility. There are many times that current implied volatility is higher or lower than historical volatility. Remember that historical volatility represents the past, and implied volatility represents what traders believe will be the future. Another statistical indicator that is widely used to measure historical volatility is the Average True Range (ATR) indicator developed by J. Welles Wilder. This indicator was developed to measure the actual movements of a security for implementing trading strategies around volatility. The average true range differs from a standard range formula as it incorporates gaps in price action.

The technique used by Wilder was to incorporate absolute values which guarantees positive numbers. The key is to measure the distance between two points regardless of the direction. So why would you want to know the historical volatility of a currency pair? One important reason is it can help you manage your risk. Most traders do not sufficiently consider the risks of trading. However, the serious trader understands and incorporates volatility into their trading plan. Whether you are managing one currency pair or a basket of currency pairs it is helpful to understand the overall risks of your portfolio. Value at Risk (VAR), is a way of describing the risk within a portfolio of currency pairs. The process of analyzing the returns of multiple currency pairs is essential in determining the capital you have at risk. If you have ever had a situation wherein you have multiple currency positions open at any one time, your risk is very different than having a position open in just one currency pair. What you are attempting to define with VAR is the amount of funds you would lose or gain with a specific movement of your portfolio.

Measuring Risk with Value at Risk (VAR) Value at Risk can be determined using a few basic methodologies. You can use an analytic solution which uses historical volatility to determine the variances in a portfolio. A second measure is to use simulations. This means that you look at all the historical paths that were taken over time and simulate the most probable scenario. The more data you have the more likely you will be able to find a solution that is pertinent. Monte Carlo simulation is a popular method for sampling of values in a data series. Of course there are drawbacks to using VAR as the only strategy to measure market risk. First, there are many assumptions that one can use to define a VAR, which means there is no standard measure. Liquidity plays a role in defining your ability to use VAR as a risk management tool. If you are running a portfolio of currency majors, your liquidity will be different compared to running an emerging market portfolio. One of the assumptions with VAR is that you will be able to exit with specific parameters. VAR works well with assets that are normally distributed and will not see outside movements caused by political unrest or currency manipulation. VAR also has a relatively narrow definition and does not incorporate other types of risk management challenges such a credit risk, and liquidity risk. The calculation is purely focused on market risk and could provide a false sense of security if used as a standalone measure.

Additionally, VAR shows a trader the greatest adverse effect of a market move on a portfolio. With currency pairs, there are up and down moves which need to be taken into account when measuring the risk of a portfolio. There are a number of reasons you would want to know the most volatile currency pairs. The first is to determine the risk you are assuming. It is important to know whether an asset has moved 100% in the last year or 10%. Understanding the risk of a currency pair or a basket of currency pairs is imperative to a successful trading strategy. Having a robust entry signal is only helpful if you have a sound risk management strategy. Closing Thoughts and Some Additional Considerations. Implied volatility will provide you with the markets estimate of how much the market will move. Historical volatility is the actual volatility that occurred in the past. Generally, implied volatility is higher than historical volatility.

The volatility for the majors in the currency market are relatively subdued relatively to individual stocks or commodities. Rarely does implied volatility for major currencies move above 15%, but this is quite common for individual stocks. The volatility on the S&P 500 index averages around 14%, and has seen spikes as high at 48%. And individual stocks can experience much higher volatility than the Index. Implied volatility for currency crosses will generally be higher than the implied volatility of the majors. The most volatile forex pairs are exotic currency pairs which can have volatility numbers that are as extreme as some individual stocks. Implied volatility can also help you measure sentiment. Traders will associate high level of implied volatility with fear and low levels of implied volatility with complacency. Market extremes usually occur when sentiment is at its highest or lowest levels. With this knowledge you can measure the markets pulse by gauging sentiment using implied volatility levels. By graphing implied and historical volatility, you have a way of measuring perceived future sentiment as well as actual historical sentiment. This can allow you to see how the markets reacted after an event or before an event occurred. You can use a number of technical indicators to help gauge where volatility might be going in the future. By incorporating volatility into your trading plan, you can enhance your return and fine tune your risk management techniques.

The volatility calculated on this page is called Average true range (ATR). It is calculated by taking the average of the difference between the highest and the lowest of each day over a given period. For example, with this method, let's calculate the volatility of the Euro dollar over three days with the following data. First day: The Euro Dollar marks a low point at 1.3050 and a high point at 1.3300 Second day: EURUSD varies between 1.3100 and 1.3300 Third day: the low point is 1.3200 and the high point is 1.3350. The Highest - Lowest difference over the three days is 250pips, 200pips and 150pips, or an average of 200pips. We will say that the volatility over the period is 200 pips on average. The volatility is used to evaluate the potential for variation of a currency pair. For example, for intraday trading, it may appear more interesting to choose a pair which offers high volatility. Another use may be as an aid to fix the levels of objective or stop-loss, to place an intraday objective at 2 or 3 times the volatility may be a risky strategy; conversely, one may estimate that an objective of at least one times the volatility has more chance of being achieved. I wish to buy the Euro Dollar for an intraday trade at 1.3200. My objective is 100 pips. At the time when I want to open my trade, the low point for the day was 1.3100 and the average volatility is 150 pips, which means that on average one can estimate that the high point could be close to 1.3100+150 pips = 1.3250. Now my objective is 1.3300, or 50 pips above. In this case, my analysis shows that the EURUSD seems likely to have a stronger variation than on the previous days; I can open my position and maintain as my intraday objective 1.3300.

However, if the rate shows no exceptional variation one may estimate that the objective will probably not be achieved during the day, which does not invalidate my analysis but defers my timing. How to Measure Volatility. by James Stanley , Currency Strategist. Price action and Macro. Your Forecast Is Headed to Your Inbox. But don't just read our analysis - put it to the rest. Your forecast comes with a free demo account from our provider, IG, so you can try out trading with zero risk. Your demo is preloaded with ?10,000 virtual funds , which you can use to trade over 10,000 live global markets. We'll email you login details shortly. You are subscribed to James Stanley.

You can manage you subscriptions by following the link in the footer of each email you will receive. An error occurred submitting your form. Please try again later. Volatility is the measurement of price variations over a specified period of time. Traders can approach low-volatility markets with two different approaches. We discuss the Average True Range indicator as a measurement of volatility. Technical Analysis can bring a significant amount of value to a trader. While no indicator or set of indicators will perfectly predict the future, traders can use historical price movements to get an idea for what may happen in the future. A key component of this type of probabilistic approach is the ability to see the ‘big picture,’ or the general condition of the market being traded. We discussed market conditions in the article The Guiding Hand of Price Action; and in the piece we enclosed a few tips for traders to qualify the observed condition in an effort to more properly select the strategy and approach for trading that specific condition. In this article, we’re going to take the discussion a step further by focusing on one of the primary factors of importance in determining market conditions: Volatility. Volatility is the measurement of price variations: Large price movementschanges are indicative of high volatility while smaller price movements are low volatility.

As traders, price movements are what allow for profit. Larger price variations mean more potential for profit as there is simply more opportunity available with these bigger movements. But is this necessarily a good thing? The Dangers of Volatility. The allure of high-volatility conditions can be obvious: Just as we said above, higher levels of volatility mean larger price movements; and larger price movements mean more opportunity. But traders need to see the other side of this coin: Higher levels of volatility also mean that price movements are even less predictable. Reversals can be more aggressive, and if a trader finds themselves on the wrong side of the move, the potential loss can be even higher in a high-volatility environment as the increased activity can entail larger price movements against the trader as well as in their favor. For many traders, especially new ones, higher levels of volatility can present significantly more risk than benefit. The reason for this is The Number One Mistake that Forex Traders Make; and the fact that higher levels of volatility expose these traders to these risks even more than low-volatility. So before we go into measuring or trading volatility, please know that risk management is a necessity when trading in these higher-volatility environments.

Failure to observe the risks of such environments can be a quick way to face a dreaded margin call. Average True Range. The Average True Range indicator stands above most others when it comes to the measurement of volatility. ATR was created by J. Welles Wilder (the same gentlemen that created RSI, Parabolic SAR, and the ADX indicator), and is designed to measure the True Range over a specified period of time. True Range is specified as the greater of: High of the current period less the low of the current period The high of the current period less the previous period’s closing value The low of the current period less the previous period’s closing value. Because we’re just trying to measure volatility, absolute values are used in the above computations to determine the ‘true range.’ So the largest of the above three numbers is the ‘true range,’ regardless of whether the value was negative or not. Once these values are computed, they can be averaged over a period of time to smooth out the near-term fluctuations (14 periods is common). The result is Average True Range. In the chart below, we’ve added ATR to illustrate how the indicator will register larger values as the range of price movements increases: Created with MarketscopeTrading Station II; prepared by James Stanley. After traders have learned to measure volatility, they can then look to integrate the ATR indicator into their approaches in one of two ways. As a volatility filter to determine which strategy or approach to employ To measure risk (stop distance) when initiating trading positions. Using ATR as a Volatility Filter. Just as we had seen in our range-trading article, traders can approach low-volatility environments with two different approaches.

Simply, traders can look for the low-volatility environment to continue, or they can look for it to change. Meaning, traders can approach low-volatility by trading the range (continuation of low-volatility), or they can look to trade the breakout (increase in volatility). The difference between the two conditions is huge; as range-traders are looking to sell resistance and buy support while breakout traders are looking to do the exact opposite. Further, range-traders have the luxury of well-defined support and resistance for stop placement; while breakout traders do not. And while breakouts can potentially lead to huge moves, the probability of success is significantly lower. This means that false breakouts can be abundant, and trading the breakout often requires more aggressive risk-reward ratios (to offset the lower probability of success). Using ATR for Risk Management. One of the primary struggles for new traders is learning where to place the protective stop when initiating new positions. ATR can help with this goal. Because ATR is based on price movements in the market, the indicator will grow along with volatility. This enables the trader to use wider stops in more volatile markets, or tighter stops in lower-volatility environments. The ATR indicator is displayed in the same price format as the currency pair. So, a value of ‘.00458’ on EURUSD would denote 45.8 pips. Alternatively, a reading of ‘.455’ on USDJPY would denote 45.5 pips.

As volatility increases or decreases, these statistics will increase or decrease as well. Traders can use this to their advantage by placing stops based on the value of ATR. If you’d like more information on this method, we discuss the premise at length in the article, Managing Risk wi t h ATR . --- Written by James Stanley. James is available on Twitter @JStanleyFX. Would you like to enhance your FX Education? DailyFX has recently launched DailyFX University ; which is completely free to any and all traders! DailyFX provides forex news and technical analysis on the trends that influence the global currency markets. How to Calculate a Currency's Volatility. Calculating volatility allows individuals to measure the overall turbulence associated with a specific currency pair such as the European euro and U. S. dollar. An increase in the volatility of the exchange rate between currencies is often the result of major changes that are occurring within the global economy. In many instances the changes are the direct result of fiscal and or monetary policy undertaken by the national governments of each country. Anyone interested in participating in the foreign exchange market should have a basic understanding of volatility and the underlying causes that create such economic turbulence. Determine the time period for which you want to measure volatility for a given currency pair such as the U. S., dollar and the British pound. For example, you could pick a month's worth of a data, a quarter's worth of data, half a year's of data, or as much as one entire year of data. If you are interested in understanding the most current situation between two currencies exchange rate you might want to use a shorter time frame such as a month or quarter.

If you are interested in understanding the longer term trend between two currencies you will want to use a longer time frame such as a year. Subtract the highest exchange rate from the lowest exchange rate for each trading day for the entire time period you have chosen to analyze. If you are comparing the dollar to another currency such as the euro you will want to use exchange rate information obtained from the U. S. trading session which occurs from 8 a. m. to 5 p. m. EST Monday through Friday. You can also chose to use the highest and lowest exchange rate achieved over the course of an entire week for your calculation. Whichever way you chose to do the calculation be consistent and do not switch back and forth between using daily and weekly data. To determine the volatility add all of the differences obtained between the highest and lowest exchange rates together and then divide this number by the total number of differences you recorded within your chosen time period. This number represents the volatility or average range in the daily or weekly exchange rate between two different currencies. A higher number suggests the exchange rate is more volatile whereas a lower number suggests less volatility and a more stable economic situation between the nations of the two currencies being analyzed. How to Calculate a Currency's Volatility. Calculating volatility allows individuals to measure the overall turbulence associated with a specific currency pair such as the European euro and U. S. dollar. An increase in the volatility of the exchange rate between currencies is often the result of major changes that are occurring within the global economy. In many instances the changes are the direct result of fiscal and or monetary policy undertaken by the national governments of each country. Anyone interested in participating in the foreign exchange market should have a basic understanding of volatility and the underlying causes that create such economic turbulence.

Determine the time period for which you want to measure volatility for a given currency pair such as the U. S., dollar and the British pound. For example, you could pick a month's worth of a data, a quarter's worth of data, half a year's of data, or as much as one entire year of data. If you are interested in understanding the most current situation between two currencies exchange rate you might want to use a shorter time frame such as a month or quarter. If you are interested in understanding the longer term trend between two currencies you will want to use a longer time frame such as a year. Subtract the highest exchange rate from the lowest exchange rate for each trading day for the entire time period you have chosen to analyze. If you are comparing the dollar to another currency such as the euro you will want to use exchange rate information obtained from the U. S. trading session which occurs from 8 a. m. to 5 p. m. EST Monday through Friday. You can also chose to use the highest and lowest exchange rate achieved over the course of an entire week for your calculation. Whichever way you chose to do the calculation be consistent and do not switch back and forth between using daily and weekly data. To determine the volatility add all of the differences obtained between the highest and lowest exchange rates together and then divide this number by the total number of differences you recorded within your chosen time period. This number represents the volatility or average range in the daily or weekly exchange rate between two different currencies. A higher number suggests the exchange rate is more volatile whereas a lower number suggests less volatility and a more stable economic situation between the nations of the two currencies being analyzed. How to Measure Volatility. Volatility is something that we can use when looking for good breakout trade opportunities. Volatility measures the overall price fluctuations over a certain time and this information can be used to detect potential breakouts. There are a few indicators that can help you gauge a pair’s current volatility.

Moving averages are probably the most common indicator used by forex traders and although it is a simple tool, it provides invaluable data. Simply put, moving averages measures the average movement of the market for an X amount of time, where X is whatever you want it to be. There are other types of moving averages such as exponential and weighted, but for the purpose of this lesson we won’t go too much in detail on them. For more information on moving averages or if you just need to refresh yourself on them, check out our lesson on moving averages. Bollinger bands are excellent tools for measuring volatility because that is exactly what it was designed to do. Bollinger bands are basically 2 lines that are plotted 2 standard deviations above and below a moving average for an X amount of time, where X is whatever you want it to be. One line would be plotted +2 standard deviations above it and the other line would be plotted -2 standard deviations below. When the bands c ontract , it tells us that volatility is LOW. When the bands widen , it tells us that volatility is HIGH. For a more thorough explanation, check out our Bollinger bands lesson. 3. Average True Range (ATR) Last on the list is the Average True Range , also known as ATR. The ATR is an excellent tool for measuring volatility because it tells us the average trading range of the market for X amount of time, where X is whatever you want it to be. So if you set ATR to 20 on a daily chart, it would show you the average trading range for the past 20 days. When ATR is falling , it is an indication that volatility is decreasing. When ATR is rising, it is an indication that volatility has been on the rise. Calculating volatility: A simplified approach.

Many investors have experienced abnormal levels of investment performance volatility during various periods of the market cycle. While volatility may be greater than anticipated at times, a case can also be made that the manner in which volatility is typically measured contributes to the problem of stocks seeming unexpectedly, unaccountably volatile. The purpose of this article is to discuss the issues associated with the traditional measure of volatility, and to explain a more intuitive approach that investors can use in order to help them evaluate the magnitude of risks. Traditional Measure of Volatility. Most investors know that standard deviation is the typical statistic used to measure volatility. Standard deviation is simply defined as the square root of the average variance of the data from its mean. While this statistic is relatively easy to calculate, the assumptions behind its interpretation are more complex, which in turn raises concern about its accuracy. As a result, there is a certain level of skepticism surrounding its validity as an accurate measure of risk. (To learn more, see "The Uses and Limits of Volatility.") In order for standard deviation to be an accurate measure of risk, an assumption has to be made that investment performance data follows a normal distribution. In graphical terms, a normal distribution of data will plot on a chart in a manner that looks like a bell-shaped curve. If this standard holds true, then approximately 68% of the expected outcomes should lie between ±1 standard deviations from the investment's expected return, 95% should lie between ±2 standard deviations, and 99.7% should lie between ±3 standard deviations. For example, during the period of June 1, 1979, through June 1, 2009, the three-year rolling annualized average performance of the S&P 500 Index was 9.5%, and its standard deviation was 10%. Given these baseline parameters of performance, one would expect that 68% of the time the expected performance of the S&P 500 index would fall within a range of -0.5% and 19.5% (9.5% ±10%). Unfortunately, there are three main reasons why investment performance data may not be normally distributed. First, investment performance is typically skewed, which means that return distributions are typically asymmetrical. As a result, investors tend to experience abnormally high and low periods of performance.

Second, investment performance typically exhibits a property known as kurtosis, which means that investment performance exhibits an abnormally large number of positive andor negative periods of performance. Taken together, these problems warp the look of the bell-shaped curve, and distort the accuracy of standard deviation as a measure of risk. In addition to skewness and kurtosis, a problem known as heteroskedasticity is also a cause for concern. Heteroskedasticity simply means that the variance of the sample investment performance data is not constant over time. As a result, standard deviation tends to fluctuate based on the length of the time period used to make the calculation, or the period of time selected to make the calculation. Like skewness and kurtosis, the ramifications of heteroskedasticity will cause standard deviation to be an unreliable measure of risk. Taken collectively, these three problems can cause investors to misunderstand the potential volatility of their investments, and cause them to potentially take much more risk than anticipated. (To learn more, see our "CFA Level 1- Quantitative Methods Exam Guide.") A Simplified Measure of Volatility. Fortunately, there is a much easier and more accurate way to measure and examine risk, through a process known as the historical method. To utilize this method, investors simply need to graph the historical performance of their investments, by generating a chart known as a histogram. A histogram is a chart that plots the proportion of observations that fall within a host of category ranges.

For example, in the chart below, the three-year rolling annualized average performance of the S&P 500 Index for the period of June 1, 1979, through June 1, 2009, has been constructed. The vertical axis represents the magnitude of the performance of the S&P 500 Index, and the horizontal axis represents the frequency in which the S&P 500 Index experienced such performance. As the chart illustrates, the use of a histogram allows investors to determine the percent of time in which the performance of an investment is within, above, or below a given range. For example, 16% of the S&P 500 Index performance observations achieved a return between 9% and 11.7%. In terms of performance below or above a threshold, it can also be determined that the S&P 500 Index experienced a loss greater than or equal to 1.1%, 16% of the time, and performance above 24.8%, 7.7% of the time. Comparing the Methods. The use of the historical method via a histogram has three main advantages over the use of standard deviation. First, the historical method does not require that investment performance be normally distributed. Second, the impact of skewness and kurtosis is explicitly captured in the histogram chart, which provides investors with the necessary information to mitigate unexpected volatility surprise. Third, investors can examine the magnitude of gains and losses experienced. The only drawback to the historical method is that the histogram, like the use of standard deviation, suffers from the potential impact of heteroskedasticity. However, this should not be a surprise, as investors should understand that past performance is not indicative of future returns. In any event, even with this one caveat, the historical method still serves as an excellent baseline measure of investment risk, and should be used by investors for evaluating the magnitude and frequency of their potential gains and losses associated with their investment opportunities.

Application of the Methodology. How do investors generate a histogram in order to help them examine the risk attributes of their investments? One recommendation is to request the investment performance information from the investment management firms. However, the necessary information can also be obtained by gathering the monthly closing price of the investment asset, typically found through various sources, and then manually calculating investment performance. After performance information has been gathered, or manually calculated, a histogram can be constructed by importing the data into a software package, such as Microsoft Excel, and using the software's data analysis add-on feature. By utilizing this methodology, investors should be able to easily generate a histogram, which in turn should help them gauge the true volatility of their investment opportunities. In practical terms, the utilization of a histogram should allow investors to examine the risk of their investments in a manner that will help them gauge the amount of money they stand to make or lose on an annual basis. Given this type of real-world applicability, investors should be less surprised when the markets fluctuate dramatically, and therefore they should feel much more content with their investment exposure during all economic environments. (For more, see "Understanding Volatility Measurements.")

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