2Bull Forex Blog

If there is one area that is regularly ignored by CFD traders it is that of volatility, which is often confused with risk. Certainly in terms of grading different types of asset classes, the two are connected, and both the risk and volatility of a government stock for instance will usually be much lower than say a dot.com or emerging market smaller company.

But the bottom line is that risk is related to reward, and it simply measures the amount that it is possible to lose within each investment or trade. Volatility however measures how much prices rise or fall over a set time for each investment issue, sector or share, and this is very useful when constructing portfolios, assessing margin requirements and position sizing.

Standard Deviation – the basic measure of volatility

Standard Deviation is the basic statistical measure of the dispersion of a population of data observations around a mean (average), and is widely used in stockmarket trading, forex and commodity analysis. It is simply the square root of the variance, and is calculated as follows:

1. Establish the mean value over the chosen time period.
2. Measure the deviation of each data point from that mean.
3. Square each deviation (this ensures all the deviations are positive).
4. Total up the squared deviations.
5. Divide that figure by the number of data points less one.
6. The Standard deviation is the square root of that figure.

There are some variations on the way the STD can be constructed, but the above is the usual formula supplied with most trading software systems.

Problems with standard deviation

1. If using short term action, the validity of the STD becomes less certain due to the usual short term randomness in the market.

2. It is a retrospective measurement, and is of little use if there is a major change in volatility due to outside news. Having said that, there are certain technical buy and sell indicators which search for changes in volatility to establish potential new trading opportunities, and here it is very useful.

Implied Volatility

Many traders in the options markets will be aware of the use of implied volatility in terms of option pricing, and here the trader can use both the underlying price of the security and the prices of puts (rights to sell) and calls (rights to buy) to establish an expectation of future or implied volatility.

This creates arbitrage possibilities if the stock, or market, is incorrectly priced compared to underlying options available in it, and these disparities often occur after big price moves or panicky action. The formula for implied volatility is much more complex, but it is an interesting area for more sophisticated players to analyse, as it also includes dividend payments and interest rates.

What is beta?

Beta is another measure of volatility, and whilst totally different from standard deviation, it nevertheless provides another angle in portfolio or trade construction.

Standard deviation determines the volatility of a fund, market, sector or stock according to the disparity of its returns over a period of time, whereas beta determines the volatility in comparison to an index or other benchmark.

If an investor has a portfolio of shares with a beta of 1, this means that the list should generally match the underlying movement in that benchmark over time. It doesn’t mean that it will naturally perform better or worse on an individual stock basis, but if the FTSE 100 index was to rally by say 10% over one year, the portfolio with a beta of 1 would in total expect to improve by a similar amount.

On a trading level, each stock has its own beta which is important for CFD traders, and a beta of more than 1 suggests greater volatility than the benchmark, with a beta of less than 1 suggesting lower volatility.

A stock with a beta of 2 for instance would be expected to move 2 times more than the benchmark, or double the underlying index move. Clearly if a CFD trader has a balanced list of positions in terms of longs and shorts, the average beta on each side needs to be assessed in terms of the overall risk of big market moves in one direction.

Normally, but not always, the highest beta stocks are those with the greatest volatility as measured by the standard deviation, but also how much they are affected by the business cycle and interest rates. Fund managers, house builders and insurance companies for instance have much higher betas than supermarkets, pharmaceuticals and utility stocks.

In portfolio analysis, the beta coefficient, or financial elasticity (sensitivity of the asset returns to market returns and relative volatility), is a key parameter in the capital asset pricing model and is a way of separating an investor’s profits related to market action as opposed to the willingness to take risk. In essence this means how much added value there has been as opposed to just the luck from being in rising markets.

If one is highly bullish about the underlying market, it makes it easier to beat the market over the term in question by choosing high beta stocks. Equally, if a big fall is expected imminently, a CFD trader might prefer to take low beta long positions and high beta shorts if a balanced trading list was required.

The average true range indicator

This is an important indicator that can be used for setting stops and is also another way of measuring volatility, and is included in most software systems.

The ATR determines a share’s volatility over a set period that can be defaulted as desired. The daily ATR indicator is very simple to calculate and is the highest of:

The difference between the current high and the current low
The difference between the current high and the previous close
The difference between the current low and the previous close

Basically this is the maximum range in which the share has traded from the previous close to the current high and low. The average is then taken over a set number of days (ten is often used), and the stop is then calculated as a multiple of the ATR.

The reason traders like the ATR is that it captures more intra-day information, while the standard deviation only measures the volatility of closing prices (although it can be refined to include highs, lows, etc).

Reasons for volatility and what to look for

On a short term view, shares that have quotes in more than one market or currency may exhibit high volatility, but not necessarily a high beta. This is simply because of arbitrage possibilities, where traders buy the stock on one market and sell in another to take advantage of price discrepancies.

Changes in technology naturally affect the volatility of individual stocks because it takes a while for this information to become available to the wider investment community, so a period of volatility often ensues. Once the stock becomes more mainstream or loses its super-growth tag, volatility can often die down.

News-led events often lead to big changes in volatility, again as traders and investors begin to adjust expectations for future prices. This can include profit upgrades or warnings, unexpected changes in economic policy, natural disasters or geopolitical events.

If the volatility increases for the same investment amount, so does the potential risk and reward and trade sizes/stop losses should be adjusted accordingly for CFD traders.

Albert Einstein – yes, he of “e equals mc squared”, said that compound interest was the greatest mathematical discovery of all time, and this brief summary might just convince you how right he was.

When one first examines a potential investment, it is natural to look at the headline expected rate of return, but it is the compounding of the interest (or profits) on that principal which creates the biggest returns over time.

The compounding of profits, or dividends, or interest applies in all financial markets, so if you are a short term stock market trader, property investor or other short or long asset holder, you may find the magic of compounding interest very interesting. We will see here though how using CFDs and compound interest can provide potentially astonishing returns.

The rule of 72 and long term returns

You might not have learn this at school, but Einstein’s rule of 72 is one of most magical and simple formulas around. What this says is that to work out how long it takes to double the value of an investment, you simple divide the return into 72.

So, if we say that the stock market has returned around 11% on average over the last one hundred years or so, (and property is not far behind for that matter), then to work out on average how long it would take an investment in the market to have doubled, the calculation is 72 divided by 11, which equals about six and a half years.

A few quick points need to be made clear here. First, this rounded figure assumes all dividends are reinvested, and there are no charges for investment, which clearly is not realistic for most investors. It does not include taxes of any sort, which again would have to be factored into potential returns.

Doubling and doubling again

Once we have the time it takes to double your money, this is where the magic of compounding comes in, because it becomes possible then to extrapolate some very tasty figures over the longer term.

If we return to long term equity investment, and say that the real return on shares (that is adjusted for inflation and charges) is say 5%, then you could work out how much would you need to invest and how long to give you a future investment value of say £1m in today’s money.

A simple spreadsheet model can do this, but let’s say you began with £10000 and each year your investment appreciates by 5% in real terms. To double the initial figure would take (72 divided 5 approximately) just over fourteen years. Another fourteen years is what it takes to double again, and after 42 years of working life, your £10000 becomes £77615 in real terms. Now this doesn’t sound much, but of course this does not include any further contributions you make through your working life.

But going back to nominal returns, the story is dramatically different. Assuming a round 10% per annum returns after costs, it takes just over seven years to double your money. After 42 years, your £10000 is now worth £547637 – a quite amazing figure. Now you can see the linkage with the trend of property prices based on these long term returns from the past, but as mentioned before the figures for total return on the stockmarket (not just how much the indices have gone up) is even higher.

Just to show how this sort of compounding works in the real world, Warren Buffett began with $105,000 fifty six years ago – it was a lot of money admittedly then. His fund’s compound returns have been around 25% per annum, and his fortune is currently over £50bn, making him the second richest man on earth.

Monthly returns and hitting the magic million

How then does all this relate to the short term and in particular to CFD trading? The first thing we have to presume is that a good trading methodology is crucial to all traders, whether it is in equities, indices, forex or commodities. It is then possible to leverage short term investments for spectacular gains within just a few years.

Let’s return to our fictional £10,000 starting investment, but this time we’ll measure performance in months, not years. A very good trading system might return 1.5% per month after costs, which compounds to 19.6% per annum. This is not far off the sort of figure that only the best hedge funds aim to match or beat over the long term.

Without leverage, the £10,000 becomes £24432 over five years, which is a pretty good return on its own.

Using just three times leverage however the return jumps to an astonishing £140274 over just five years.

You would theoretically hit a million in less than nine years, and that’s just from £10,000!

A word on risk/reward

All the above simulations (with the exception of Warren Buffett) are based on average long term returns and take no account of short term movements. CFD traders should of course be aware that by increasing your leverage, the risk of major falls in equity increases accordingly.

It is paramount that all traders have applicable money management systems and stop losses in place to protect against potential pitfalls when trading, but by using CFDs with a profitable trading system and leverage, the sky really is the limit.