I was listening to a podcast featuring John Bollinger and he mentioned that “volatility is the most important, least analysed and worst understood”. The importance of volatility in trading is indeed under emphasized as the limelight typically shines on entry and exit rules. I first came across usage of volatility in position sizing used by the Turtles and Richard Dennis and that definitely gave me one of those “Light bulb” moments.
In this article I will share a common way to position size your trades using volatility.
Firstly we need to decide how to measure volatility. For much of the investment community volatility is standard deviation. Another way to measure volatility is to measure the Average True Range of the time series.
True Range is the maximum of either:
Average True Range of past 100 periods is the average of True Range of the last 100 periods. The same method goes for any periods (e.g. 20 or 50 periods) of Average True Range.
When we trade different markets and instruments, the volatility profile of each would be different. For example, bonds would have very different volatility profile compared to stocks. Different stocks would also have different volatility profiles. We would like to take larger positions with less volatile instruments and smaller positions with more volatile instrument with the aim that the profit and loss generated per trade has roughly the same impact to the overall strategy regardless of the instrument traded.
We will illustrate using a simple example below:
We would like to risk 50 basis points per trade with a portfolio of $1 million in value. Thus the impact per trade would be 50 basis points * $1 million = $5000
We calculate the Average True Range of past 100 periods of 1 unit of stock to be $10.
No. of units of stock to be traded = $5000 / $10 = 500 units
We calculate the Average True Range of past 100 period of 1 unit of bond to be $1.
No. of units of bond to be traded = $5000 / $1 = 5000 units
While the example above is overly simplified, I’m sure you see the idea behind position sizing using volatility.
Next, if you have a stop-loss level based upon volatility, you would be able to size the trade such that the maximum amount that you lose is the risk percent you have chosen. For example, the stop loss can be 3 units of ATR above or below your entry price.
Again we will illustrate using a simple example below:
We would like to risk 50 basis points of capital per trade with a portfolio of $1 million in value. Thus we would like to calculate the size of the trade such that we will lose $5000 when stop loss level is triggered.
Suppose a stock is trading at $80 and our stop loss is at $70. Hence we would make a loss of $10 per unit of stock when stop loss level is triggered.
No. of units of stock to be traded = $5000 / $10 = 500 units
Suppose a stock is trading at $80 and our stop loss is at $75. Hence we would make a loss of $5 per unit of stock when stop loss level is triggered.
No. of units of stock to be traded = $5000 / $5 = 1000 units
Hence we can see that when stop loss is wide, the size is smaller and when stop loss is narrow, the size can be larger.
Position sizing is important in trading and it is important to place emphasis on it.
In this article I will share a common way to position size your trades using volatility.
Firstly we need to decide how to measure volatility. For much of the investment community volatility is standard deviation. Another way to measure volatility is to measure the Average True Range of the time series.
True Range is the maximum of either:
- Distance from today’s high to today’s low
- Distance from yesterday’s close to today’s high
- Distance from yesterday’s close to today’s low
Average True Range of past 100 periods is the average of True Range of the last 100 periods. The same method goes for any periods (e.g. 20 or 50 periods) of Average True Range.
When we trade different markets and instruments, the volatility profile of each would be different. For example, bonds would have very different volatility profile compared to stocks. Different stocks would also have different volatility profiles. We would like to take larger positions with less volatile instruments and smaller positions with more volatile instrument with the aim that the profit and loss generated per trade has roughly the same impact to the overall strategy regardless of the instrument traded.
We will illustrate using a simple example below:
We would like to risk 50 basis points per trade with a portfolio of $1 million in value. Thus the impact per trade would be 50 basis points * $1 million = $5000
We calculate the Average True Range of past 100 periods of 1 unit of stock to be $10.
No. of units of stock to be traded = $5000 / $10 = 500 units
We calculate the Average True Range of past 100 period of 1 unit of bond to be $1.
No. of units of bond to be traded = $5000 / $1 = 5000 units
While the example above is overly simplified, I’m sure you see the idea behind position sizing using volatility.
Next, if you have a stop-loss level based upon volatility, you would be able to size the trade such that the maximum amount that you lose is the risk percent you have chosen. For example, the stop loss can be 3 units of ATR above or below your entry price.
Again we will illustrate using a simple example below:
We would like to risk 50 basis points of capital per trade with a portfolio of $1 million in value. Thus we would like to calculate the size of the trade such that we will lose $5000 when stop loss level is triggered.
Suppose a stock is trading at $80 and our stop loss is at $70. Hence we would make a loss of $10 per unit of stock when stop loss level is triggered.
No. of units of stock to be traded = $5000 / $10 = 500 units
Suppose a stock is trading at $80 and our stop loss is at $75. Hence we would make a loss of $5 per unit of stock when stop loss level is triggered.
No. of units of stock to be traded = $5000 / $5 = 1000 units
Hence we can see that when stop loss is wide, the size is smaller and when stop loss is narrow, the size can be larger.
Position sizing is important in trading and it is important to place emphasis on it.
Editors’ Picks
EUR/USD hits two-day highs near 1.1820
EUR/USD picks up pace and reaches two-day tops around 1.1820 at the end of the week. The pair’s move higher comes on the back of renewed weakness in the US Dollar amid growing talk that the Fed could deliver an interest rate cut as early as March. On the docket, the flash US Consumer Sentiment improves to 57.3 in February.
GBP/USD reclaims 1.3600 and above
GBP/USD reverses two straight days of losses, surpassing the key 1.3600 yardstick on Friday. Cable’s rebound comes as the Greenback slips away from two-week highs in response to some profit-taking mood and speculation of Fed rate cuts. In addition, hawkish comments from the BoE’s Pill are also collaborating with the quid’s improvement.
USD/JPY drops back below 157.00, as focus shifts to Japan snap election
USD/JPY is back in the red below 157.00 in the Asian session on Friday. The Japanese Yen recovers ground against the US Dollar amid some profit-taking ahead of Japan's snap general election on Sunday. The preliminary reading of the Michigan Consumer Sentiment Index report for February will be released later on Friday.
Editors’ Picks
EUR/USD: US Dollar to remain pressured until uncertainty fog dissipates Premium
The EUR/USD pair lost additional ground in the first week of February, settling at around 1.1820. The reversal lost momentum after the pair peaked at 1.2082 in January, its highest since mid-2021.
Gold: Volatility persists in commodity space Premium
After losing more than 8% to end the previous week, Gold (XAU/USD) remained under heavy selling pressure on Monday and dropped toward $4,400. Although XAU/USD staged a decisive rebound afterward, it failed to stabilize above $5,000.
GBP/USD: Pound Sterling tests key support ahead of a big week Premium
The Pound Sterling (GBP) changed course against the US Dollar (USD), with GBP/USD giving up nearly 200 pips in a dramatic correction.
Bitcoin: The worst may be behind us
Bitcoin (BTC) price recovers slightly, trading at $65,000 at the time of writing on Friday, after reaching a low of $60,000 during the early Asian trading session. The Crypto King remained under pressure so far this week, posting three consecutive weeks of losses exceeding 30%.
Three scenarios for Japanese Yen ahead of snap election Premium
The latest polls point to a dominant win for the ruling bloc at the upcoming Japanese snap election. The larger Sanae Takaichi’s mandate, the more investors fear faster implementation of tax cuts and spending plans.
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