Capacity for risk explained

Capacity for risk explained

The section called ‘Check my capacity for risk’ helps you to assess and compare different ways of investing your money. It gives you an idea of the risk of losing some or all of your money if you choose a particular portfolio.

Written by Jonquil Lowe on 17 September 2013


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Why capacity for risk is important

Most experts agree that, when you invest money, how well your investments grow usually depends more on your asset allocation - in other words, the mix of assets you choose - than on the particular equities (shares), bonds and investment funds you select.

There are four main asset classes: cash, bonds, property and equities. Of these, cash is judged to be the lowest risk, because normally you will not lose any of the money you originally invested or any of the interest that has been added. But the return from cash is usually low (and might not be enough even to protect you from the effects of inflation).

You can increase the likelihood of making a bigger return by including other asset classes, especially equities and property, in your portfolio. But the value of these other assets can go down as well as up, so you are exposed to capital risk. This means:

  • Your investment will not follow a steady growth path.
  • Even if your investment grows over the long term (say, 10 years or more), this is not guaranteed.
  • Over shorter periods, your investment may fall so that you experience periods where you lose money.

The capacity for risk test aims to help you think about how likely it is that a portfolio you are looking at could lose money over the short term and how much. You can then consider whether such losses could cause you:

  • financial damage - for example, because you might need your money back when the value of your portfolio is low
  • emotional distress -for example, if you have a cautious attitude towards risk.

What the test tells you

The capacity for risk test starts with the amount you are investing and the portfolio you are looking at. For example, the chart below shows £100,000 invested in a portfolio made up of 20% cash, 40% bonds, 10% property and 30% equities.

Using data about how each of the asset classes has performed in the past, the test gives you information about how this portfolio would have performed if you had invested in the past for a one-year period.

No-one knows what will happen in future and it is very unlikely to be exactly the same as the past. So the capacity for risk test gives you a guess based on past performance that can be no more than a rough guide to the possible riskiness of this portfolio in future.

What do the charts show?

The information the test gives you will look something like the chart below.

 

graph3

 Based on what has happened in the past, the chart suggests:

  • First bar at the top of the chart called 'Any'. This shows, if you invest for a year, the risk of your making a loss of any amount rather than the gain you had hoped for. The amount of the loss could range from losing all your money to losing as little as £1. Unless your whole portfolio is invested in cash, the probability of making any loss at all is likely to be fairly high. In the example shown, the probability of losing any of the £100,000 invested is 1 chance in 2. This is the same as a 50% chance, 50-50 or 'evens' (1-1) in betting terms.
  • Last bar at the bottom of the chart. This shows the probability of losing all the money you invested (in this example, £100,000). This is an extreme event that, in most cases, is very unlikely to happen. The 'amount of loss' test rounds very small probabilities, so very unlikely events will be shown as having a '1 in 1,000 or less' chance of happening.

The bars in between show the chance of losing:

  • Second bar from the top: up to 5% (one-twentieth) of the money you invested. In this example, there is a 1 in 3 chance of losing £5,000 (5% of £100,000)
  • Third bar from the top: up to 10% (one-tenth) of the money you invested. In this example, there is a 1 in 5 chance of losing £10,000 (10% of £100,000)
  • Fourth bar from the top: up to 25% (one-quarter) of the money you invested. In this example, there is a 1 in 51 chance of losing £25,000 (25% of £100,000)
  • Fifth bar from the top: up to 50% (half) of the money you invested. In this example, there is a 1 in 1,000 chance of losing £50,000 (50% of £100,000)
  • Sixth bar from the top: up to 75% (three-quarters of the money you invested. In this example, there is a 1 in 1,000 or less chance of losing £75,000 (75% of £100,000).

The probabilities shown have been rounded to whole numbers - for example a 1 in 2.4 chance will be shown as a 1 in 2 chance. As a result, the probability of making different losses may sometimes appear to be the same - for example, a 1 in 2.4 chance (42%) is less likely than a 1 in 2.1 (47%) chance but both will be shown as 1 in 2.

Bear in mind that these probabilities are just a rough guide to what might happen in future based on the past. They are not a guide to what will definitely happen in future.

What do the probabilities mean?

Most people find it hard to grasp what the risk (in other words, probability or chance) of making a loss really means. Here are the odds of some events happening that may help you get a feel for the investment risks you could be taking on:

  • 1 in 2 chance (50%). The chance of a head if you toss a coin once.
  • 1 in 3 chance (33%). The chance in the UK of developing some form of cancer during your lifetime.
  • 1 in 6 chance (17%). Chance of throwing a six with one dice. Chance of suffering from asthma or an allergy.
  • 1 in 10 (10%). The risk of dying from lung cancer if you smoke a packet of cigarettes a day for 30 years.
  • 1 in 20. Risk of being the victim of a serious crime some time during your life.
  • 1 in 37 (3%). Chance of a particular number winning on the single spin of a (European) roulette wheel.
  • 1 in 54 chance (2%). The chance of winning any prize in the main National Lottery draw if you have bought one ticket.
  • 1 in 89 (1.1%). Chance of naturally having twins.
  • 1 in 1,000 (0.1%) chance. The chance of needing emergency treatment over the next year because you have been injured by a can, bottle or jar. Also the chance of winning the £250,000 jackpot in the TV show, Deal or No Deal.
  • 1 in 5,000 (0.02%). Odds of getting a hole in one playing golf.
  • 1 in 576,000 (0.0002%). Odds of being killed by lightning.

Interpreting the capacity for risk test

You should think twice about investing in a portfolio if, over the span of a year:

  • The amount of money you might lose (even if the chance is small) is greater than you could afford to lose. Nobody likes to lose money, but you probably have a reasonable idea of whether you could afford to lose, say, £50, £100, £1,000 or so on. However, bear in mind that you actually make the loss only if you sell the investment. If you are a long-term investor, you may be able to cope with a short-term 'paper loss'.
  • There is a bigger probability of losing money than you are comfortable with. It is especially important to realise that, although a very small chance, such as 1 in 1,000, means an event is unlikely, but it could still happen. So, if there is a 1 in a 1,000 chance that you might lose £100 but you cannot afford to lose that amount, you should not take that risk.

 How the test works: the technical bit

If you don't like maths, look away now! The capacity for risk test starts by looking at how a portfolio like the one you are considering would have grown over 36 different periods of one year ending in each of the last 36 months.

The next step is to work out the average yearly growth rate for these 36 one-year periods and a figure called 'standard deviation'. Standard deviation is a measure of how much these 36 results vary from the average. A large standard deviation (big risk) means the results are very volatile with big swings in the one-year growth rate from one period to the next. A small standard deviation (low risk) means that the results are similar and consistent from one year to the next.

Assuming that the results fall into a pattern called a 'normal curve' (or 'bell-shaped curve'), it will always be the case that 68% of the results fall within one standard deviation either side of the average, 95% will lie within two standard deviations and 99% within 2.5 standard deviations.

Armed with this knowledge, the test works out the percentage of the results that have recorded losses of the specified amounts. It is these percentages - expressed as chances of 1 in 2, 1 in 3, and so on - that are shown in the chart.

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