Week 3: Devising investment strategies – principles and practice

Introduction

Welcome to Week 3 of Managing my investments – a week that explores the theories behind good investment management practices. Begin by watching the video to hear Martin Upton introduce this topic.

Download this video clip.Video player: ou_futurelearn_mmi_vid_1078.mp4

Show transcript|Hide transcript

Transcript

MARTIN UPTON

Hello again everyone, I’m Martin Upton and I work at The Open University’s True Potential Centre.

In Week 3 of Managing My Investments you will start to examine strategies for compiling an investment portfolio. To do this involves some of the more complex concepts that you will come across in this course – but don’t worry, you’ll be guided through these carefully.

We start by reminding ourselves of the basic rules for investment management we learnt in Week 1 particularly the notions of linking your personal objectives in life and the time horizon which relates to them, to the structure of your investments.

We then examine the different types of risk that may apply to your investments – understanding these will help ensure that your portfolio mix aligns with your appetite for risk. We move on to look at two key concepts which need to underpin the management of your investments – portfolio theory and the capital asset pricing model (or CAPM as it is commonly abbreviated).

Understanding these two concepts will help to ensure that your investment portfolio has the right mix of risk versus expected return. To demonstrate that this is not just academic, we look at how fund managers apply portfolio theory and CAPM in practice.

We then examine a number of key ideas about how markets operate and the opportunities these may provide for making timely investment decisions in effect, assessing our capabilities to predict market movements.

Some market analysts who adhere to what is called ‘Efficient Market Hypothesis’ maintain that this is not normally possible – whilst others, called chartists or technical analysts, maintain that there is some scope to do so. And we’ll also take the opportunity here to provide some useful tips about investment management – like ‘pound cost averaging’.

It’s a very full week and the most demanding one so far – but do persevere and you’ll be prepared to take on the rest of the course with great confidence. Enjoy Week 3!

End transcript

Download

 

This week, you’ll start by building on the work on investment management planning that you started in the later stages of Week 1. Armed with the knowledge gained in Week 2 about the range of personal investments available, you are now in a position to build and refine your approach to investment management.

To help understand the key principles of investment management, you will explore key underlying concepts like portfolio theory, the efficient markets hypothesis and the capital assets pricing model. You’ll look at how these theories are applied in the real world of investment management and what they tell us about how we should manage our investments and the decisions we should make.

You will also discuss tactics that we can use to manage our portfolios – like pound cost averaging.

There’s plenty to get through – but once you’ve completed the week you will have a robust understanding of the key theories about investment management and how to apply them in practice.

3.1 Time horizons and goals

Figure 1 What’s your time horizon when investing?

Show description|Hide description

The image is a pile of calendars for the years 2015, 2016, 2020 and 2030.

Figure 1 What’s your time horizon when investing?

Last week you spent time familiarising yourself with the assets you can invest in and the investment products (including funds) you can use to build up your portfolio.

Now you need to turn your knowledge of what you can invest in, to what you want to invest in. To do this requires a plan to be devised and more information to be gathered about the alternative strategies you may want to employ, including the mixture of assets you aim to hold in your portfolio. Devising strategies for the timing of investment activity – whether you’re buying or selling – is also important.

The first stage is to re-visit the core building blocks of investment management introduced in Week 1. This involves asking the questions of what you are investing for and over what time horizon? This analysis provides information about how much you need to accumulate and by when.

One item which all of us should be investing for is a pension. So, a key part of the exercise is to determine what retirement income, other than that provided by the state, you need.

The next stage is to work out when you want to retire, since this will set the time horizon for the compilation of the fund required to provide the income in retirement needed to support your desired lifestyle. Help in doing this analysis is provided by the pension planning tools provided by Age UK.

Why not access this now and work out how much you need to save to meet your pension objectives?

Once you have completed this ‘what’ and ‘when’ exercise for your pension planning then apply it to all the other things you invest money for – perhaps education costs, a new car or a wedding. In stages, you are building up a picture of how big an investment fund you need and the time horizons by which you need the funds to achieve defined volumes.

You also need to consider your risk appetite. This is crucial as, given the trade-off between risk and return, the greater risks you take the more quickly your fund might accumulate. Yet the higher risks associated with the (potentially) higher returns mean that such investments are not suited to building funds over the short-term: an adverse movement in the value of such investments during this period could leave you well short of the size of the fund you need. Rather higher-risk investments are more suited to a long-term investment horizon, over which adverse short-term moves in the value of such assets tend to be more than compensated for by the long-term trend to outperform safer investments.

Even with this maxim in mind, you do need to reflect on how comfortable you are with higher-risk investments. Ask yourself:

• are you sure that if you invest in higher risk investments, you won’t need to cash them in over the short-term?
• have you the capacity to bear financial losses if you do have to cash them in earlier than anticipated?
• is holding investments which may fall in value – sometimes sharply and perhaps only in the short-term – going to upset your life (for example, by keeping you awake at night)?
• finally, and critically, are you sufficiently knowledgeable about all the risks your investments are exposed too? Have you checked your investments off against the full range of risks that could apply to them?

Answering this last question requires you to know what this full range of risks is and see which apply to the assets you could invest in. So in the next section, you’ll look at the risk spectrum to make sure you know what to check for when investing.

3.1.1 Knowing the risks

You now turn to investment risks. Let’s start by hearing Anthony Nutt’s views on investment planning and managing the risks involved. Investment risk is the likelihood that the actual return from an investment will not turn out as expected. There are two dimensions to risk: amount and timing.

Download this video clip.Video player: ou_futurelearn_mmi_vid_1080.mp4

Show transcript|Hide transcript

Transcript

MARTIN UPTON

Anthony, in your experience, do investors really understand the risks they are taking with their investments?

ANTHONY NUTT (Retired investment director and fund manager)

No I don’t think they do Martin, but I wouldn’t be too alarmed about that. First of all I would try and define what we mean by risk. The word itself is quite concerning for investors, but if you try and understand what your aims and objectives are then you can try and understand the consequences or the likelihood of not achieving those aims and objectives. And that I what I think as an investor you should be thinking about in terms of risk. So less about the untoward fear of investing in something which might go horrible wrong and much more about predictability. It really is an important point to understand, what you mean by risk, because risk is almost the very parameters by which you will invest; invest successfully or unsuccessfully, if you go outside those risk parameters that you have set for yourself.

MARTIN UPTON

By risk when it comes to investments, we look at capital risk, the risk that the value of your investment goes down, we look at income risk, that the income from your investments isn’t as high as you would want. There are other risks as well, like foreign currency risks, take the decision to place money in foreign currency denominated investments. When it comes to the investor community though, which are the risks that people commonly misunderstand or perhaps don’t think about at all?

ANTHONY NUTT

Well they’re all risks that one should consider but let me say to you if you are an investor in fixed interest and equity markets; they are that the people you provide capital to will be thinking about very hard indeed. They will be hedging currency; there will be many large companies have enormous risk departments, just dealing with all these issues. You know for me I think as the private investor you should be more concerned about you yourself misunderstanding risk, and making investments that are less about discernible, predictable, reliable returns and more about speculating. So, you may invest in the equity market for instance, with the intention of making a more significant return that is really reliable, that is really realistic. And that I think is where we go wrong in misunderstanding risk.

MARTIN UPTON

Whose reasonability is it to get the personal investor up the learning curve when it comes to understanding risk? Is it down to the personal investor, should it be financial firms and advisors who they can approach about investments or is it the duty of the regulator to protect the investor from an adverse risk appetite?

ANTHONY NUTT

Well that’s a really good question because I feel at the moment that the onus is put by the government, by the regulator, on the advisor, if ones using an advisor, to quantify the risk. And it has become a box ticking exercise, which is really very inadequate. So your advisor will ask you are you a low risk investor or a medium risk investor or a high risk investor? And he will tick the box. But you know what he’s doing Martin he’s considering his business risk, and less of your investment risk. So you have to decide, you have to do your utmost I would argue to try and understand the risks you are undertaking.

MARTIN UPTON

So it does come back to the personal investor?

ANTHONY NUTT

Ultimately, I would argue that if you, me, everyone, the government, can educate ourselves in trying to understand what it is we want from our investments, less about speculation, less about gambling in the stock market, more about discernable returns, more about good corporate governance, reducing risk and things going wrong at board level for instance, and therefore our earnings. So I think we all have a role to play here and at the moment really the emphasis is less...is left with the advisor to quantify the risk having asked some terribly basic questions to an individual what their risk appetite is. And they may not even know they may not, as you alluded to, understand what their risk requirements are.

MARTIN UPTON

So if I’m a personal investor and I say yes I want medium risk it’s really down to me to make an effort to understand what medium risk really means and what I’m exposing myself to.

ANTHONY NUTT

It is, and more so to make sure that your advisor, if you use an advisor, understands what you mean by medium risk because he then may be able to help you out in identifying whether you are genuinely a medium risk investor, because you might actually be a low risk investor.

MARTIN UPTON

Anthony one big decision that investors have to make is “do I take financial advice before making my investments or do I, so to speak, fly solo and make my own decisions?” What’s your advice on this?

ANTHONY NUTT

Well my advice would be that depends on how sophisticated you are on understanding financial matters. If you are coming to the investment arena for the very first time and know little about financial matters then I would seek advice. And sadly the quality of advice you are going to get depends on how much you are going to pay for it. If you are an accountant yourself, if you understand financial matters on a much more significant understanding of these financial matters then by all means fly solo, by all means go it alone, do your own homework, understand the risks, look at your aims and objectives.

MARTIN UPTON

You talked about fees there and the investor having to pay for advice and you know there has been a lot of debate, a lot of discussion about the fees that are paid to fund managers. What are your views are those fees generally in order or are they excessive?

ANTHONY NUTT

Well I think Martin it really does depend upon the product that you are choosing to invest in. There is no doubt in my mind that some products are heavily overpriced, they are weighted too much in terms of the fee towards the underlying fund manager. We think of performance fees within the hedge fund community for instance. And at the other end of the spectrum, maybe index tracking, there are products that are very lowly priced and can retain the same sort of returns as an index by their very nature. So it does vary enormously and it is important to understand what level of fee you’ll be paying. Now I do think the regulator, the government and the regulator has had a very useful role to play in this in recent years in forcing the investment community, the investment professionals, fund managers, independent financial advisors to make more explicit what their fee charges are. So you can make a much more educated guess now than was the case in the past in terms of what your fee levels are likely to be. I should say at this point that the initiatives we’ve seen from government in the past to make very simple investment products very lowly priced hasn’t really worked. The investment community hasn’t been very keen on taking up some of those very lowly priced products because it can be quite an expensive process to provide a product to the retail community in particular at a very, very low price.

MARTIN UPTON

So by the sounds of it you think the regulator is doing a pretty good job then in terms of regulating fees?

ANTHONY NUTT

He’s doing a much better job I would say than has been the case in the past. The city understands, the investment community now generally understands what’s required of them in terms of an appropriate level of fee charging.

MARTIN UPTON

But it’s also important that the personal investor doesn’t turn a blind eye to that percentage which they are paying in terms of fees. It’s typically a small percentage and people are maybe inclined to just ignore it and not think about how it impacts upon their investment return over the longer term. Is that a fair observation?

ANTHONY NUTT

You know my observation over the years would be that actually the retail investor does look at the level of fees he’s paying.

MARTIN UPTON

Right.

ANTHONY NUTT

He looks at what the return has been and he does make a judgement about the level of fees that he has been paying. And too often I think the level of fees have discouraged him from investing perhaps when he should have been investing. So I do think people do look at fee charges, they are concerned, they have been concerned about fee charges and the press has done a relatively good job of taking up some of the more extreme examples of too high fees.

MARTIN UPTON

A fund manager that underperforms, particularly year after year after year, should they be repaying their fees to the investor?

ANTHONY NUTT

Well I don’t know how a fund manager would repay those fees quite frankly if the fund has underperformed significantly investors tend to take their money out over a prolonged period of time. And these funds dwindle and his business risk rises and he goes out of business in theory.

MARTIN UPTON

OK.

ANTHONY NUTT

But I don’t think we’ll ever see underperformers reimbursing fees because fees go to provide a lot more than simply buying and selling investments. There’s a good deal of admin that takes place behind that.

MARTIN UPTON

Yeah I mean a certain amount of the fees which you do pay go towards such things as research undertaken by the financial firms.

ANTHONY NUTT

Yes I think that’s true there is a good deal depending on the size of the firm there is a good deal of resource applied to researching companies and the underlying investments that they offer the retail investor.

MARTIN UPTON

Thank you.

ANTHONY NUTT

Thank you.

End transcript

Download

 

In summary, risk is the chance that the actual return from an investment will:

• be more or less than expected. This is known as capital risk and, if part or all of the return is in the form of income, income risk.
• not be available when expected. This is an aspect of liquidity risk.

Capital risk, income risk and liquidity risk can therefore be viewed as the key ‘high-level’ risks affecting investments.

Note the assumption that risk is symmetrical: the probability of a gain is equal to the probability of a loss. Although investors typically want to avoid the downside risks of a lower return, they do want exposure to the chance (risk) of a higher return. You will follow the normal convention of describing different types of risk in terms of the bad outcomes that may result, but you should bear in mind that the risk–return trade-off means that the reward for running the risk of bad outcomes is the chance of superior returns.

Table 3.1 presents a summary of the ‘high-level’ and the ‘underlying’ investment risks that sit underneath these key risks.

These risks are, of course, interrelated. Can you identify some of these interrelationships?

3.1.2 Risk interrelationships

Figure 2 Risks can have knock-on consequences.

Show description|Hide description

The image is of a row of dominoes falling from right to left.

Figure 2 Risks can have knock-on consequences.

Arguably liquidity risk, counterparty risk, currency risk, default risk, inflation risk, interest-rate risk and shortfall risk are all examples of risks that underlie the capital risk and income risk.

Each of the underlying risks, if they materialise, can reduce the capital value of an investment, perhaps with extreme consequences in respect of default risk, and/or reduce the real value of the income stream from the investment.

Note that risks can be managed. The presence of risk is not an excuse for not investing in the future, as you then expose yourself to the biggest risk: that you have insufficient funds for later life.

Having examined your investment objectives and their time horizons; and ascertained the risks to which your investments are exposed, you now turn to the management strategies you can apply when investing.

3.1.3 Do we really understand our appetite for risk?

To complete your analysis of understanding risks, watch this video of Sharon Collard’s presentation on the extent to which personal investors really understand the subject when making investment decisions. The worrying evidence about a lack of true perception about risk supports the need for improved consumer education on the subject.

Download this video clip.Video player: ou_futurelearn_mmi_vid_1082.mp4

Show transcript|Hide transcript

Transcript

SHARON COLLARD

What are the risks related to saving and investing, and how do consumers understand them, or what do they understand?

I think the first thing that struck me, very forcibly, from the research is that risk has different meanings, as Sue alluded to in her introduction, to different people. In the financial advice and investment industry, it’s really about the mathematical calculation of probabilities. For the rest of the world, for the general public, it generally means uncertainty. So as John Lanchester said in his recent book, it’s ‘the more profound unknowabilities of life and history’. I think the financial sector brings together those two, very different, understandings in an effort to help people make investment decisions.

In terms of what people understand, I think what the research showed, quite clearly, is that there are two different components in terms of people’s understanding of risk. There is a general understanding about the risk of saving and investing. What I’ve come to think about as environmental factors - things like interest or inflation. Then there is actually how do people think about their own attitude to risk.

Let’s turn first to general understanding. What we found in the research was from the literature and from other research that has been carried out, we know that the population has a very limited understanding of risk. It’s kind of limited in terms of investing; to knowing that they go up and down. In our population of consumers that we interviewed, it was a bit more sophisticated than that. It was that investments go up and down, but we do understand that our capital is at risk. What also came through really strikingly was, we know that if we don’t invest, actually there is a risk as well because of our savings being eroded by inflation. The bottom bubble is really things that stakeholders and the financial advice industry felt that people should know but probably didn’t, or, they probably didn’t know enough about these things, so, basic concepts, inflation, interest rates, how the markets work, the impact of charges on your investment returns? What actually does a good return look like? And what might your investment journey look like? The industry and the stakeholders that we spoke to thought that people didn’t have a good enough handle on that third set of things.

What about people’s attitude to risk? Let me remind us that the consumers we spoke to had some experience. They had either bought or considered an investment in the recent past. New investors are going to have much less of an idea than the people we spoke to. We broke it down into the four kind of components of attitude to risk as we understand it. Firstly, in terms of people’s willingness to take risk. Respondents the consumers that we spoke to generally had some sense of the risk they were prepared to take. They used this as a benchmark. People said, ‘I’m kind of middle risk,’ or, ‘I’m medium risk’, ‘I’m cautious’, so they had some understanding because they had been through a process. The sort of thing that influenced their attitude wont’ come as any surprise. It was life stage; having a young family, you take less risks. It was also their past experience. In terms of risk need, I think the striking thing, for me, from the consumer research was that people who were kind of made an active choice or were more active in their investment choices had a sharper sense of their risk need then people whose investment decisions had kind of fallen in their laps because of circumstances, so because of a bereavement or because of a redundancy, for example.

Risk capacity, for me, is one of the most interesting part of this because I think across the interview data, the stakeholders, the industry data, the consumer data, what we actually see is three dimensions to capacity to risk. The first is very present focussed. It’s consumers thinking have I got enough money to actually be able to afford to invest any money at all. The second thing came through much more strongly, from stakeholders in the industry, which is, consumers working out whether or not they have the building blocks in place in order to be able to afford to take some risk with the money they have got. That’s saying, ‘have I got enough savings to cover an emergency’? or, ‘do I have protection for myself and my family’? Once you have answered that second question, then it’s a question of saying, ‘what is my capacity for loss’? ‘What is the amount of money that I could afford to lose, if things don’t work out how I want them to’?

I think it’s true to say that the regulator would prefer investors to understand capacity for loss in a kind of quantitative way, in a pounds and pence way. Certainly, from the interviews that we did, capacity for loss was something people had in their minds although they might not express it, like that, but it was a qualitative sense. It wasn’t a quantifiable thing they thought about. They didn’t, really, think about it in pounds and pence.

Experience and expertise is the final aspect of attitude to risk and the interviews highlighted just the different ways people could gain experience and expertise which we might not always think about. Things like belonging to share clubs, peer influences, and actually things like being involved in running a business. I think the other thing the research shows us is that as well as attitude to risk, there is a question that’s worth asking, and investors worth asking of themselves which is, what kind of investor am I? From the research, I think, we see a continuum and this, I don’t think, will come as a surprise. From one end we’ve got people that are delegators so they delegate the research, they delegate the selection of the investment, they delegate the choice, the final choice of what they take out and usually, they’re going to delegate it to a professional advisor.

Moving along the continuum, we have affirmation seekers as we’ve called them. These are people who might do some of their own research they’re generally more engaged and pro-active but even so, they will seek affirmation or they will seek validation at the point of making the decision. They want to know, from someone else, that they’re doing the right thing; they want some reassurance. They might do some research but they might also seek some validation. That might be in the form of regulated advice, or, it might be on a non-advice basis, or it might be from a friend or relative, that they trust, who has some financial experience.

Then, we have the DIY investors. These are people who are more motivated to invest I think, because they are interested, or because they enjoy it. They are intrinsically motivated, as we would say, and it’s a very, intrinsic motivation is a very powerful determinant of action, so they do tend to do their own research; they will be making their own decisions and they feel confident that they’re making the right decisions, for them.

End transcript

Download

 

Clearly, getting a sound understanding of risk and our true appetite for it is vital to ensure we have control of the second stage of the investment planning model. Only then can we move to third stage of investment decision-making.

Figure 3 The four-stage investment management model

Show description|Hide description

This diagram is a loop of the four ‘golden rules’ – ‘time horizon’ to ‘risk appetite’ to ‘formulate strategy and invest’ to ‘review portfolio’ and back to ‘time horizon’. There are arrows outside this loop labelled to indicate investment opportunities which may become available or unavailable.

Figure 3 The four-stage investment management model

3.2 Diversifying investments dilutes risk

In this and the next few sections, you will explore how the trade-off between risk and return can be improved by holding a mixture of shares or other investments in a portfolio. This can be viewed as part of the third stage of the investment planning model – the process of deciding on investment strategies that fit with our time horizons and risk appetites. Let’s look first at the subject of diversification.

The analysis you need to undertake here and in the next two sections is a little complex, so there will be animations to guide you.

Download this video clip.Video player: ou_futurelearn_mmi_vid_1083.mp4

Show transcript|Hide transcript

Transcript

MARTIN UPTON:

This animation shows why diversifying your investments is a good idea.

Company shares that trade on the stock market are often closely associated with each other. Imagine there was one company selling sun hats and another company selling ice cream. Putting both these shares in a portfolio may not be a good idea, since they are both exposed to a similar risk, the risk of bad weather.

If the weather is cold and wet, both companies might suffer from lower than expected sales and, therefore, lower than expected profits. As a result the price of shares in both companies will be likely to fall.

But what if an investor also bought some shares in a company selling hot chocolate? Here, as a result of the same spell of bad weather, high sales and higher than expected profits can lead to an increase in the share price of the company.

The risk of loss from cold weather has been reduced through diversification. By holding a combination of shares, ones that are unlikely to all move in the same direction at the same time, investors can reduce the risk of loss. So our imaginary portfolio is in better shape for including the hot chocolate company.

Investors use statistics to help establish which combinations of shares are most suitable for diversification. The type of statistics used can be illustrated by considering the example of three companies, Gelato, Solcap and Hotchoc. Gelato makes ice cream, Solcap makes sun caps and Hotchoc makes hot chocolate.

As you can see the share prices for Gelato and Solcap tend to move together over time. When one rises, the other rises, And when one falls, the other falls.

In statistics, this type of close association is described as a strong correlation between variables. Here the variables are the share prices. When the variables are not very well associated with each other, this is described as weak correlation.

In addition to the strength or weakness of correlation we also look at the direction of the association, is it positive or negative? The association between Gelato and Solcap share prices is positive, this means that the share prices move in the same direction.

As you can see, in cold spring weather, Solcap is priced at £160 and Gelato at £150 per share. But when a particularly warm summer comes they both have much higher prices with Solcap at £227 and Gelato at £313 per share as a result of higher than expected profits.

When Gelato’s share price is low the share price of Solcap is low; when Gelato’s share price is high, Solcap’s is high. This type of association between Solcap and Gelato is called a positive correlation.

Perhaps in that spring the weather was worse than expected, so both shares were low in price, while in summer the sequence of good weather led to better results than expected for both ice cream and sun hats.

While positive correlation offers the possibility for diversification, it is not to the same extent as negative correlation.

Now let’s consider an example of negative correlation, the share prices of Gelato and Hotchoc. These shares tend to move in opposite directions to each other, with higher share values of Gelato tending to be associated with lower values of Hotchoc. When Hotchoc is £66 per share, the share price of Gelato is £150; but when Hotchoc goes down to £46, we see that Gelato is up to £313. When there is negative correlation between the price changes, this provides more of an opportunity to reduce risk through diversification.

In our example, the investor might combine Hotchoc shares with shares in Gelato, in order to spread the risk associated with future weather conditions. With this first investment management principle in mind, that diversification reduces risk, we turn in the next section to the next question: how do we determine our desired combinations of different shares within a portfolio?

End transcript

Download

 

3.2.1 Understanding portfolio theory

The last section sets out the benefit of diversification when investing. You’ll now take this analysis further forward, by looking at how a portfolio can be constructed. This is called portfolio theory.

The animation introduces a key statistical concept which is important in investment management: ‘standard deviation’. This is a measure of the dispersion, or spread, of data around an average or mean number. The greater the standard deviation, the more varied or dispersed are the data around the average. The risk/return positions C & D shown at the end of this section’s animation will be explored further in the next section.

Download this video clip.Video player: ou_futurelearn_mmi_vid_1085.mp4

Show transcript|Hide transcript

Transcript

MARTIN UPTON

This simple illustration demonstrates how portfolio theory works. Imagine you have an investment portfolio that contains two shares. Gelato makes ice cream, and Hotchoc, makes hot chocolate.

Suppose that there are four different types of weather Cold but sunny, Hot but rainy, Cold and rainy and finally Hot and sunny. Now suppose that over the last five years each type of weather period occurred 25% of the time. From this we can assume that each will have a 25% chance of occurring in the next five years. These 25% probabilities are shown in the table, next to the average monthly returns over the last five years for Gelato and Hotchoc.

Take a look at the hot and sunny period. The return for Gelato is expected to be 17.21% (obviously there were great ice cream sales), but a loss of 9.07% is expected for Hotchoc (so clearly not much call for hot chocolate). You can calculate the monthly expected return by multiplying each month’s outcome by its probability.

For Gelato this is 1 per cent. Here 0.25, the chance of that type of weather occurring in a particular period, is multiplied by -11.38%, which is the expected return in that period, and so on. Then, the annual (or yearly) equivalent return, is just the compound value of the monthly return.

For Gelato, each £1 invested earns a monthly return of 1 per cent. In the first month this would grow to £1 times 1.01. In the second month to £1 times 1.01 times 1.01, and so on for 12 months. Using this method, the annual equivalent return for Gelato is 12.7%. The annual expected return is the usual way to express returns on shares. Risk is measured by looking at the standard deviation (or dispersion) of returns. The more highly dispersed, or spread out, or volatile, the returns are, then the higher the risk involved in holding the share. These risk measures are also shown in the table: 13. % for Gelato and 8.2% for Hotchoc.

These measures can be displayed in a risk-return diagram. The vertical axis represents the expected return, and the horizontal axis represents risk. Point A shows what happens if the investor chooses to invest 100% of their portfolio in Hotchoc. You can see the risk the horizontal axis of the diagram. This measures at 8.2% the expected return can be read off the vertical axis, in Hotchoc’s case it is 4.4%. However, at point B, if the portfolio only holds Gelato shares, both risk and expected return are higher. The example of Gelato and Hotchoc provides a very good illustration of the risk-return trade-off. Hotchoc is safe, but has a low return, Gelato is riskier but has a higher return. If an investor wants to get higher returns then they have to take on higher risk. That’s where portfolio theory comes in. Using portfolio theory you can identify the best balance of shares in your investment portfolio to either reduce risk or maximise returns.

End transcript

Download

 

Standard deviation can be calculated by following the steps below:

1. Obtain the average (or mean) of all the (daily) share prices over the period in question. To do this, add up all the daily recordings of the share price and divide by the number of those daily recordings.
2. For each share price, work out its difference from this mean and then square this difference. So if the difference is 4 pence, the square would be 16 and so on.
3. Once you have done the second step for all the share prices, add up all these ‘squares’.
4. Divide the total you get in the third step by the total number of share prices. So if the total of the ‘squares’ is 10000 and the number of share price recordings is 100, you end up with 10000/100 = 100.
5. Find the square root of the outcome from the fourth step. So if the outcome from the fourth step is 100, then the square root of this is 10 pence. This is the Standard deviation and it can either be expressed as an absolute number (i.e. 10 pence) or as a % of the mean share price.

The statistical meaning of a (that is, one) standard deviation is that it captures 68% of the individual recorded prices. So if the standard deviation in the example above is 10 pence, then 68% of the share prices are within 10 pence of the average (or mean) share price (either higher or lower).

Thsi information can also be downloaded in the supporting document How to calculate standard deviation and what does it mean?

3.2.2 Applying portfolio theory

In the previous section, you looked at the risk–return trade-off between Gelato and Hotchoc. However, by combining the two shares in a portfolio, it is possible for the investor to reach a better outcome. Watch this short animation about portfolio theory.

Download this video clip.Video player: ou_futurelearn_mmi_vid_1086.mp4

Show transcript|Hide transcript

Transcript

MARTIN UPTON

We all know not to put all of our eggs in the one basket. The problem is how many eggs do you need to put in how many baskets to be safe? That’s where portfolio theory comes in and this example shows how to apply it.

At point A the investor holds 100% of their investment in Hotchoc shares.

Now here is point C. In this portfolio we have 62% Gelato shares and 38% Hotchoc shares. This portfolio bears the same risk as at point A, but the expected return is now 9.5%, significantly higher than the 4.4% expected at point A. So by combining the two shares in a portfolio it is possible to increase expected return without increasing risk. This shows how powerful diversification can be in tackling risk and return.

All possible combinations of Gelato and Hotchoc shares are shown by the curve that links together all the possible portfolios. For an investor seeking the least amount of risk, point D might be chosen, where the risk is 6.0%. Of course, in the real world, the investor can choose between thousands of shares, in any number of combinations.

To illustrate how diversification works for three shares, consider this. Let’s add a company making ice lollies: Icepop. At point E, 100% of the portfolio is allocated to Icepop shares. Various combinations of Icepop and Hotchoc are available along the curve drawn between A and E. As are combinations of Hotchoc and Gelato already shown in the curve joining A and B. The key to this new scenario is that the investor can now choose to combine all three shares in a portfolio.

A third curve can be drawn. This draws together all combinations that are possible from the three shares, Hotchoc, Gelato and Icepop. This curve is called the efficient frontier. It represents points at which the investor can get the highest expected return for a given risk, and the lowest level of risk for a given expected return. Economists refer to these as “optimal” combinations of risk and return. By reaching the efficient frontier the investor is unable to improve their risk-return trade-off. But basically, this use of statistical tools to achieve efficient diversification is just another way to put into practice the well-known adage “don’t put all your eggs in one basket”.

End transcript

Download

 

The conclusion of the animation is that by reaching the so-called ‘efficient frontier’, the investor is unable to improve their risk-return trade-off. The portfolios on the efficient frontier are said to be Markowitz efficient, named after Harry Markowitz (1959), who was the first person to work out the implications for the mathematics of combining shares into portfolios. By following a strategy to reach the efficient frontier, investors are said to employ Markowitz diversification.

This section concludes the analysis of portfolio theory and the rationale of investment diversification.

Further supporting information the topics below is provided in the document Understanding risk versus return in portfolio theory.

3.2.3 The relevance of the size of the portfolio

The previous section looked at diversification of a portfolio through investing in three shares. In practice, many more than three shares could be chosen: let’s call the number n. What should n be? The investor should diversify to improve the balance between risk and return, but to what extent?

Suppose that we adopt a simple investment strategy to find out. We invest equal amounts in randomly chosen portfolios that consist of two, three, four, five and more shares. This type of diversification is less efficient than choosing portfolios on the efficient frontier. Indeed, it is an example of naïve diversification: simply choosing to expand the number of shares in the portfolio without examining their risk–return characteristics. The portfolio will not necessarily be Markowitz efficient (see the previous section), but there are still benefits to naïve diversification.

The benefits of naïve diversification can be seen in Figure 4, which plots the typical risk for holding portfolios of one, two, ten, or even up to hundreds of shares, in equal proportions. For example, portfolios consisting of, say, ten shares have less risk than portfolios consisting of one share. Portfolios consisting of thirty shares have less risk than portfolios consisting of ten shares but, beyond that, the benefits to diversification taper off. Why is that? This is because there are common factors affecting all shares that cannot be diversified away: interest rates, economic conditions, tax rates, inflation and so on. Indeed, the benefits of diversification come from diversifying away what is known as specific risk (risk specific to individual companies). A limit is then reached beyond which risk cannot be reduced further. This undiversifiable risk is called systematic risk – risk that is endemic to the stock market and cannot be diversified away, no matter how many shares are included in a portfolio.

Figure 4 Example of typical risk for holding portfolios

Show description|Hide description

This graph shows the risk in a portfolio plotted against the number of shares contained therein. Systematic risk remains constant, while Specific risk decreases as number of shares increases.

Figure 4 Example of typical risk for holding portfolios

The figure has two major implications for investors. First, small investors need only diversify by holding 10 to 15 shares to have substantially reduced the risk from holding just one share. Second, institutional investors do not need to hold vast numbers of shares to be diversified. The extra reduction in risk gained by holding 100 rather than 30 different shares is very small, and may well be more than outweighed by the additional transaction and monitoring costs involved in holding the extra 70 shares.

3.2.4 Share diversification in practice

Figure 5 ‘Going international’ helps diversification.

Show description|Hide description

The image is of different countries flags outside the general UN building.

Figure 5 ‘Going international’ helps diversification.

Investment trusts and unit trusts were designed to allow small investors the benefits of diversification, when the amounts that they had to invest did not allow them to buy, for example, ten different shares in reasonable quantities.

The earliest British investment trust, the Foreign & Colonial Government Trust (F&C), was founded in 1868 with the declared investment strategy of buying 18 foreign government bonds, from Brazil to Turkey, Egypt to New South Wales, in amounts ranging from 3% to 20% of the value of the overall portfolio. The prospectus read:

It was such a success that it soon had many imitators, primarily investing in fixed-interest securities. Unit trusts, first launched in the UK in the early 1930s, based on a US idea, concentrated on shares rather than bonds, and overtook investment trusts in popularity during the 1960s.

Investment trusts are companies whose shares are traded on the stock market and can be bought and sold by investors. Investment trusts invest in shares whose total market value is called the net asset value of the trust. Interestingly, the market value of an investment trust company’s shares does not have to be the same as the net asset value of the underlying portfolio. The investment trust share price can be at a discount or premium to the net asset value per share.

Consider, for example, an investment trust with a market value of £100 million divided into 10 million shares priced at £10 each. It may, in fact, hold a portfolio worth £120 million, which represents £12 per share. In this case the shares would be trading at a discount of £2 to the net asset value of £12. The size of the discount or premium is what balances demand with supply. Although popular investment trusts may trade at a premium, typically investment trusts trade at a discount. This discount can vary, adding an additional risk to investment. Investment trusts, being companies, can also borrow, which also adds to investment risk.

Unit trusts are structures that hold shares in trust for the beneficiaries, the unit trust holders. Open-ended investment companies (OEICs – pronounced ‘oiks’) are similar but use a corporate rather than trust structure. The value of the underlying investment portfolio of a unit fund is also called the net asset value; but in this case the market price at which the units are bought or sold is the same as the net asset value (with a spread between the bid and the ask price). There is no discount or premium. The balance of supply and demand determines the number of units, so that popular unit trusts grow in size, and unpopular ones shrink. This is why unit trusts are sometimes called ‘open-ended’. In contrast, investment trusts are called ‘closed-end’ because they cannot create additional shares as can unit trusts – unless they make a new share issue in the stock market. Demand for investment trusts is reflected in the premium or discount to net asset value, whereas demand for unit trusts is reflected in the number of units. Unit trust managers have to keep a certain amount of the portfolio in very liquid assets to allow for possible redemptions. Unit trusts do not borrow money.

Life insurance company investment funds are run along the lines of unit trusts and are funds in which investors invest through the wrapper of a life insurance company policy.

Looking at the correlation between returns shows that there are different levels of portfolio diversification. The first is to spread the portfolio across a number of shares, say UK shares listed on the London Stock Exchange, typically spread across a number of different sectors. The next stage is to widen the portfolio to include overseas investments. The idea is that the US stock market is less correlated with the UK stock market than, for example, BP and Vodafone are in the UK. The final stage is to include emerging stock markets, which are even less likely to be highly correlated, for example, the Chinese and Indian stock markets can be argued to have ‘decoupled’ or disconnected from developed economy markets. In building portfolios of shares, fund managers work through these levels of portfolio diversification on behalf of their investors.

As of November 2014, F&C stated that it held shares in more than 500 companies across the globe. It also stated that it invested in another asset class, private equity funds – that is, funds that buy whole companies rather than just shares. International diversification will reduce risk by more than just diversifying across companies in the same country. However, 500-plus companies is a large number when it comes to management costs and monitoring, and it may be that these costs outweigh the diversification benefits of holding such a large number of shares.

3.3 Introducing the Capital Asset Pricing Model (CAPM)

So far you have looked at diversification across shares, and how this can be achieved by collecting shares in funds. But compared to other assets, shares can involve high levels of both risk and return. In this section, you will consider how a less risky portfolio can be put together by combining shares with a risk-free asset.

A key model in investment analysis is the Capital Asset Pricing Model (Sharpe, 1964), also called the CAPM. It makes three additional assumptions to those assumed thus far in our development of portfolio theory, and leads to some pretty startling conclusions for fund management. The additional assumptions are that:

1. All investors are looking at the same risk–return diagram.
2. There is a risk-free asset that is risk-free for us all. The closest we can get to a risk-free asset is a government bond (in the UK, gilts).
3. Investors can borrow and lend at the same risk-free rate. We know that this has to be unrealistic, but allowance for differences in borrowing and lending rates makes the model that much more complicated.

These assumptions are captured in Figure 6. As before, this is a diagram showing combinations of risk and return associated with different portfolios. The risk-free rate of return is represented by R _F. This could, for example, be a yield of 3% on a government bond. Note that there is no risk attached to this investment, hence its location on the vertical axis. An investor could choose to put their entire portfolio into the risk-free asset, yielding the return R _F at no risk. Notice also that a straight line has been drawn on the figure above that starts at R _F. This is called the capital market line. As we move along the line, risk-bearing shares (in proportions to be explained shortly) are added to the portfolio.

Figure 6 Example combinations of risk and return associated with different portfolios.

Show description|Hide description

This graph shows expected return plotted against risk. The risk-free rate of return is marked on the y axis, extending from this is the capital market line. The efficient frontier curve intersects with the capital market line at points G, M and F.

Figure 6 Example combinations of risk and return associated with different portfolios.

Assume that the investor has £100 to invest at the outset. At R _F, the investor puts all of the £100 into a portfolio made up of only the risk-free asset. But at G, the investor holds only £20 in risk-free government bonds, and the other £80 in shares. This increases both the expected return and risk associated with the portfolio.

The investor could alternatively put all of the £100 into shares at M, which is a point on the efficient frontier that touches the capital market line in the figure above. Now, it has been assumed that all investors are looking at the same diagram, which leads them to reach the same conclusion: that the most efficient combination of shares is to hold M since it is a point on the efficient frontier.

Since all investors will hold M in some proportion in their portfolios and, for the economy as a whole, investors hold all shares in the stock market, the portfolio M must include all shares in the stock market in proportion to their market value. This is called the market portfolio. By choosing this efficient outcome the investor diversifies away all specific risk associated with the individual shares held in the portfolio. Only systematic (market) risk is incurred.

At M the investor does not hold any of the risk-free asset: all of the £100 is invested in a market portfolio of shares. Hence the line between R _F and M represents combinations of the risk-free asset and the market portfolio of shares. Under the CAPM, investors choose the combination between these assets that most suits their appetite for risk and return. The choice is between zero risk at R _F or full exposure to market risk at M.

It is important to emphasise that even at G, where only £80 is invested in shares, these shares will consist of the market portfolio (based on the stock market as a whole), in which there is only systematic risk. All that varies, at this stage in our analysis, is the amount of money invested in this market portfolio, and hence the amount of systematic risk.

The CAPM also allows for the investor to borrow. Assume that the investor could borrow £10 and use this to buy more shares: an expanded market portfolio of £110. Moving further along the capital market line to point F in the figure above, the investor has further increased expected return and risk. By borrowing money to invest in shares, the investor has taken on more systematic risk.

What the CAPM essentially says, is that investors get rewarded only for taking on systematic risk. So, provided that all the assumptions underlying the model hold, investors can only expect a return for bearing systematic risk. There is no point in taking on specific risk, as there is no expectation of any additional return for this. According to the CAPM, investors should hold efficient portfolios made up of M and the risk-free asset. Unlike the Markowitz approach, which leaves it open to each investor to hold their own tailor-made portfolio, the CAPM says that we should all hold different proportions of the risk-free asset and of the same risky portfolio of shares (that is, the market portfolio, M).

3.3.1 How fund managers apply CAPM

For fund managers there is a shorthand way of applying the principles of the CAPM. They can compare the risk of any share or portfolio to that of a benchmark that is represented by the market portfolio. This is achieved using a measure called beta.

Beta measures the sensitivity of returns on a share or portfolio to those of the market (or any other benchmark).

Figure 7 shows how beta is used in a simple example. At the market portfolio M, the value of beta is set equal to 1 by definition. But consider point F, in which beta is equal to 1.1. This portfolio will be more sensitive to market fluctuations than M. It will rise by 11% if the market rises by 10%, and fall by 11% if the market falls by 10%. When its beta is more than 1, a portfolio tends to outperform the market in both directions.

Figure 7 Example of using betas.

Show description|Hide description

This is the same risk–return graph seen previously. The risk free rate is labelled with a beta of 0. Points G, M and F on the efficient frontier curve are labelled as having betas of 0.8, 1 and 1.1 respectively.

Figure 7 Example of using betas.

In the risk–return diagram in Figure 7, beta can be adjusted by varying the amount invested in the market portfolio. Consider again what happens if, instead of investing £100 in M, an investor borrows £100 and invests £200: an extra £100 worth of shares added in the same proportion to the portfolio. This will make their portfolio twice as sensitive to the market and so they will have a beta of 2 – taking on twice as much market risk but with twice the expected return. So if the market does well, then they will do very well. Alternatively if, for example, the market falls by 20%, their portfolio is likely to fall by 40%. These are the extreme highs and lows that are associated with leverage (borrowing).

Let’s examine in more detail how borrowing to invest can change your expected return and risk from investing, by considering four different scenarios:

Scenario A: You invest £100 of your money in the market portfolio and the market rises by 5%. You make £5 and your portfolio is now valued at £105.

Scenario B: You invest £200, but only £100 is yours and the other £100 borrowed. The market rises by 5%. You make £10. You repay the £100. So you’re left with £110. A 10% return.

Scenario C: Same as scenario as B but the market falls by 10%. You lose £20 and after repaying the money you are left with £80 – a 20% hit. Without borrowing and investing that extra £100 you would only have taken a hit of £10 (10%).

In Scenario D you borrow £1900 to add to your £100. The market falls by 10% (a hit of £200 on the total portfolio of £2000). So ahead of repaying the lender £1900 you are holding assets worth £1800. Not a good idea!

So gearing-up, by investing with borrowed money, increases the exposure you have to the risk on your portfolio.

Investors who believe in the CAPM and whose portfolios consist only of the market portfolio M and the risk-free asset, are called passive investors. Later this week, you will also be introduced to the Efficient Markets Hypothesis (EMH) that makes the same recommendation. Such investors do not believe that it is possible to consistently outperform the market and so do not try. Next week, you will consider how performance benchmarks can be established that may be tracked by passive investment.

3.3.2 What do we mean by ‘the market’?

Figure 8 Finalising a share deal.

Show description|Hide description

The image is of a trader at his desk viewing trading screens.

Figure 8 Finalising a share deal.

The Capital Asset Pricing Model assumes that the market portfolio M includes all investible assets. This would include stocks, shares, works of art, commodities, property, and even our future earnings if these could be traded. This would be impossible to value in practice, so investment managers choose to represent the market by a stock-market index. Of course, different investors of different nationalities will look at different indices: the CAC40 for France, the S&P500 for the USA, for example. But even within countries there are a number of indices to choose from.

For example, in the UK, the index most cited on the news is the FTSE 100, which tracks the change in value of the top 100 shares listed on the London Stock Exchange weighted by market value. Every quarter, those companies that have fallen out of the top 100 are thrown out of the index and new large companies are included. In the USA, the most popular indices are the S&P500, a market-value-weighted index of 500 large US shares, and the NASDAQ Composite Index, a market-value-weighted index of all shares listed on the National Association of Securities Dealers Automated Quotation system, which consists primarily of shares in technology companies.

But the object of the CAPM is to represent the market as a whole and not the top 100 shares only. So, for our purposes, a more appropriate UK index would be the FTSE All Share Index, which in 2009 included 619 shares, weighted by market value, and these shares represented in value terms around 98 per cent of the value of all the shares listed on the market.

For a more global perspective, there is the MSCI World Index, but even this is designed to measure the equity market performance of only developed and not emerging markets. As of 2020, it consisted of the following 23 developed market indices, also weighted by market value: Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Hong Kong, Ireland, Israel, Italy, Japan, The Netherlands, New Zealand, Norway, Portugal, Singapore, Spain, Sweden, Switzerland, the UK and the USA. You can see how difficult it is to define ‘the market’.

3.3.3 To track or not to track?

Figure 9 The New York Stock Exchange.

Show description|Hide description

The image is of the New York Stock Exchange with a large U.S. flag posted on the building and the George Washington statue in the foreground on the right.

Figure 9 The New York Stock Exchange.

You’ll now turn to the question of how to invest in the market portfolio.

In practice, investors tend to buy investment products linked to a stock market index, which represents an underlying market, through the medium of index funds. These have become widely used by investors partly due to the implications of the CAPM. Economic and financial theories do matter! These index funds are investment trusts or unit trusts designed to track an index as it moves from day to day. Index fund managers do so either by ‘full replication’, buying shares in proportion to their importance in an index, or by sampling, buying the larger shares and a sample of the smaller ones, to reduce transaction costs while still getting a close replication of the movements of the index. Exchange-traded funds (ETFs) are index funds that are listed on the stock exchange as shares but are essentially funds (note that the word ‘exchange’ here has nothing to do with currency exchange). ETFs allow low-cost investment in market portfolios.

Investing in index funds is a passive investment strategy aiming to track an index rather than outperform it, but what this has meant for traditional fund managers is that they now have a benchmark strategy against which they can be judged. They have to try to outperform the index by following an active investment strategy.

Investors who do not believe the assumptions underlying the CAPM and think that they have superior investment skills can take on specific risk in the hope of achieving positive returns that beat the market. This is called an alpha investment strategy. It is the holy grail for investors seeking to earn superior returns. And this type of investor is called an active investor.

Fund managers who are active investors can try to outperform the market portfolio, or an index, by one of two strategies. One is to take on more specific risk by selecting companies in different proportions to their weighting in the index, so that the portfolio will be overweight in those companies that are expected to do well and underweight in those that have poor prospects. This strategy is called stock selection. You will look at the second strategy in the next section.

3.3.4 Market timing: can you outperform the market?

Figure 10 Good timing is important when dealing.

Show description|Hide description

The image is of a stopwatch over a graph of share price over time of two hypothetical companies.

Figure 10 Good timing is important when dealing.

The other way to try to outperform an index is to try to forecast the movement of the market by adjusting the beta of the portfolio. This can involve increasing the amount of shares in the portfolio when the market is expected to rise, and reverting to cash just before the market goes down. By varying beta, fund managers are trying to time their entry into the market, and their exit out of the market. They are indulging in market timing.

In fact, there are two ways in which active fund managers can attempt to time the market. The first is by varying the amount of leverage in a passive portfolio, moving up and down the capital market line and varying the beta of the portfolio according to whether they think the market will rise or fall. The second way is to alter the composition of the portfolio by increasing the proportion of shares that have high beta when the market is expected to rise, and increasing the proportion of low-beta shares when the market is expected to go down.

Figure 11 Choosing a market-related portfolio

Show description|Hide description

This is the same risk–return graph seen previously. The risk free rate is labelled with a beta of 0. Points G, M and F on the efficient frontier curve are labelled as having betas of 0.8, 1 and 1.1 respectively.

Figure 11 Choosing a market-related portfolio

The investor can choose between different types of shares. An example of a cyclical, or aggressive, share is an airline – which does particularly well in a boom and particularly badly in a recession – giving it a beta of more than 1 (high beta). An example of a non-cyclical (defensive) share is a utility or food manufacturer – people use electricity, eat food and drink water regardless of the state of the economy – and these typically have a beta of less than 1 (low beta). Typically, low-beta shares do relatively well in a recession, and high-beta shares do relatively well in boom times. So shares can have high or low betas as well as portfolios, but, if the active fund manager buys a portfolio of shares selected for their high or low betas and not the market portfolio, M, they will no longer have a fully efficient portfolio, and will bear specific as well as systematic risk.

So, whether adopting a stock selection strategy or a market timing strategy, the active fund manager is taking on more risk than the passive fund manager, by varying share beta risk (market timing) and/or through taking on specific risk (stock selection). Active fund managers also reduce the net expected return by charging higher fees than do passive fund managers; the latter run index funds in a competitive market and charge low fees for the replication of indices (essentially because less work is required to seek information about future price changes). Proponents of the CAPM, which assumes no particular investment skill, believe that the active approach is doomed to failure. Active managers argue that since some of them make a good living, some of them must be successful some of the time.

There is little evidence of market timing skills. A few people have become famous for timing the market correctly – George Soros for selling sterling before sterling left the Exchange Rate Mechanism in 1992, and Jon Moulton of Alchemy Partners for selling securities linked to sub-prime mortgages before that market collapsed, but these are individual occurrences for two particular investors and do not reflect general market timing ability. Indeed, retail investors are often sellers in a bear market when prices have already fallen and buyers in a bull market, the exact opposite of ‘buying low and selling high’, which is effectively what a market timing strategy attempts to do.

A way to reduce mistakes of market timing is to invest on a regular basis, such as monthly, quarterly or yearly. This is called pound cost averaging, and reduces the risk of buying at the high and selling at the low. It also reduces the chance of getting market timing right – buying at the low and selling at the high. If someone invested, for example, £50 a month in a unit trust that invested in shares, then if the market fell they would buy more units and if the market rose they would buy fewer units, since they would be spending an equal amount each month on units that varied in price over time. It is also worth adopting a similar approach for selling. If someone wants to sell, it makes sense to sell holdings in regular amounts, since it is difficult to tell when the market has reached a peak. Using this technique may be preferable in order to receive a reasonable average return, rather than to hold on, possibly miss the height of the boom, and have to sell when prices have already fallen.

3.4 Understanding the efficient markets hypothesis

Figure 12 EMH means no ‘freebies’!

Show description|Hide description

This cartoon shows a couple walking past some money on the ground. Behind them a man leans to pick it up and says 'Why didn't they pick it up? They must believe in the efficient markets hypothesis.

Figure 12 EMH means no ‘freebies’!

As financial markets have grown, and as regulatory and information barriers to arbitrage and short-selling have fallen away, economists have been more confident about the efficiency of markets. This greater informational efficiency has led some theorists to go as far as supporting the efficient markets hypothesis (EMH).

The EMH states that market outcomes (the prices set and the volumes traded) are efficient in the sense of immediately and accurately incorporating all relevant information. There are different versions of the EMH, each with striking implications for the behaviour of market prices and for appropriate investment strategy.

A weak form of the EMH acknowledges that traders may not be able to obtain or process all publicly available information, and that current prices only contain all the information conveyed by prices in the past. This form denies the effectiveness of technical analysis, by which some investors study past patterns of price movement and look for signs of their repetition that will indicate the next price movement. If all information from past prices is already priced-in, any apparent patterns will have arisen by chance and cannot be expected to recur.

The semi-strong form of the EMH holds that prices contain all relevant publicly available information, but leaves open the possibility of some traders gaining an advantage through inside information. This form denies the effectiveness of fundamental analysis, by which some investors study published information on the issuers of shares and bonds, and on commodities, to identify those that are underpriced and can be expected to rise in price. If the market price already reflects this publicly available information, there will not be undervalued or overvalued instruments as the fundamental analysts assume.

The strong form of the EMH holds that market prices contain all relevant information. This includes inside information held by a small number of market players, as well as information publicly available to all, such as business and economic news and published company accounts. It is assumed that people holding privileged information will, through their trading behaviour, cause it quickly to be captured in the price, which then transmits the information to everyone.

The type of information that is relevant to the EMH depends on what model of asset price determination is being used. For example, if this is the dividend valuation model, as used in fundamental analysis (see Shares – more on when they are good value ), the model will incorporate all relevant information regarding the expected earnings of a company. So prices will only move on the arrival of genuinely new information that changes the assessment of these earnings. The impact of this news and the direction of price movement will not be predictable, otherwise those who predicted it would already have carried out trades that incorporate the information into the price.

3.4.1 The random walk prediction

Figure 13 Heads or tails?

Show description|Hide description

The image is of a hand tossing a coin.

Figure 13 Heads or tails?

The EMH makes the powerful prediction that prices of shares and other financial assets will follow a random walk. The next price movement, up or down, will be unrelated to any of its previous movements. If the hypothesis is correct, there is little scope for investment experts to achieve better returns than others through stock picking and market timing.

Malkiel (2007) carried out an experiment with his students in which they were asked to toss a coin. The experiment started with a share price of $50. If the coin came out as a head, they were told to add half a point to the share price; a tail would result in a half point cut in the price. Figure 14 is a chart of the stock price for one of these experiments. You can see that it looks like the type of cycle in share prices that we see all the time for companies and stock market indices. Yet this pattern is derived from a purely random event, the tossing of a coin. This argues against the use of technical analysis to look for patterns in stock-market data.

The EMH suggests that there is no reason for such expert investment strategies to work any better than buying stocks in proportion to their weighting in the market index, or even buying a random selection of stocks.

Figure 14 The ‘random walk’ from tossing a coin. Source: Malkiel (2007, p.130).

Show description|Hide description

This graph shows the results of an experiment in which a hypothetical share price moves up or down dependent on the toss of a coin. It looks like a very typical cycle of share prices that is regularly seen for companies and stock market indices.

Figure 14 The ‘random walk’ from tossing a coin. Source: Malkiel (2007, p.130).

3.4.2 Technical analysis: reliable sat-nav or bogus science?

The EMH does not rule out the possibility of different traders working with different models, or inputting different data (especially on expected variables) into the same model. However, it does implicitly require traders to believe that assets have a value set by factors that are independent of other traders’ behaviour and beliefs.

Problems arise for market efficiency if there is momentum trading, with the expectation of asset prices based on recent movements in the price. Such traders use technical analysis of stock market charts to treat previous price movements as containing relevant information, which the EMH denies.

An example of how charts are analysed in technical analysis is provided in Figure 15. A trader might look at the cycle in share prices as taking place in a price channel, as shown by the two horizontal dashed lines. If enough traders believe that there is a support level for the share price, as represented by the price level P _s, their belief in the support level price ensures that this price is supported in the market. Similarly, when the share price threatens to break through the resistance level P _r, this will also lead to a reaction that pushes the price back into the price channel. Technical traders monitor the pattern of prices using this type of charting analysis.

Figure 15 Example of how charts are analysed in technical analysis

Show description|Hide description

This graph shows the cyclical movement of a share price operating between two 'price channels'.

Figure 15 Example of how charts are analysed in technical analysis

Technical traders are anticipating that others will make the same trade later, and ‘because their speculation in the stock market is based on what they think other people wish to do, they are working from a slightly different set of information than those who buy or sell based on a firm’s long-term earnings prospects’ (Peters, 1999, p. 81). This potentially undermines the EMH assumption that everyone works from the same information. Although technical traders typically work on very short time-horizons, their behaviour can amplify price movements, causing these to overshoot beyond fundamental values even if they began with arbitrage correcting misalignment – sometimes contributing to ‘bubble’ episodes, which are examined in Week 4.

3.4.3 Technical analysis: some key features

While you can form your own views as to whether there is any substance to the predictive powers of technical analysis, this section looks at some of the key tenets of chartism.

The first involves moving averages and an example is provided in Figure 16. Here chartists impose on top of the graph of the share price movement a series of moving averages – typically 5-day, 30-day and 90-day averages. If the share price moves upwards through these moving average lines then this is taken as a ‘buy’ signal for the share – the more so if the longer term (for example, 90-day) moving average is breached. The reverse applies if the share price moves downwards through the moving average lines: such moves are taken as ‘sell’ signals.

Figure 16 Moving averages

Show description|Hide description

This graph shows the price of the FTSE 100 over time, plotted as a daily value, a 20 day moving average and a 200 day moving average.

Figure 16 Moving averages

The notions of ‘support’ and ‘resistance’ lines are central to technical analysis. A support line is a straight line that links the low points of the series of movements in the share price over a period of time. A resistance line is a straight line that links the high points of the share price movements. Here, the rule is that a downward breach of the support line presages a further downward movement in the share price. An upward breach of the resistance line points to a further upward move in the share price in the near term.

Figure 17 Support and resistance lines

Show description|Hide description

This image shows a share price fluctuating between a resistance and a support line. The price then rises past the resistance line at a point labelled 'breakout'. The share price now moves between a new upper boundary resistance line and the previous resistance line has now become a supporting line.

Figure 17 Support and resistance lines

Two of the many special chart features which hint at the future share price movements are ‘head-and-shoulders’ and ‘islands’. These are identified in the image above. A ‘head-and-shoulders’ is where you have a series of three up and down movements in the share price over a reasonably short time frame. The first of these three forms the left shoulder, the second the head (which must be higher than the left shoulder) and the third forms the right shoulder (and it must be lower than the head). This patter, particularly if the right shoulder is lower than the left shoulder, presages a fall in the share price in the near term.

Figure 18 The head and shoulders pattern

Show description|Hide description

This graph shows the share price of a company moving over time. A head and shoulders pattern is highlighted, as is an island.

Figure 18 The head and shoulders pattern

Islands (or island reversals) are where a high or low point of a share price cycle is detached from the rest of the chart movements. A clear gap exists between the previous day’s price range and the following day’s price range. In such circumstances, the island points to a reversal of the recent share price trend, for example, an island below the rest of the chart line presages a period of upswing in the share price. The reverse applies when the island is detached above the chart line.

Many technical analysts swear by the predictive powers of charts. But how can they be really predictive? A number of reasons can be postulated to support their predictive powers:

• Those trading shares have predictable behaviour which leads to repeated, and hence, predictable, trading patterns and price movements (we look at behaviour and investment management in Week 6).
• The traders themselves look at the charts, or are advised by those that do, with the result that the predictions made by the charts are fulfilled by subsequent trading decisions. In short, trading behaviour follows the predictions made by the charts!
• The charts are just a summary of market sentiment as reflected in trades undertaken – and sentiment goes through cycles that are sustained for periods, sometimes long periods.

Sophisticated technical analysis uses very detailed charts that incorporate intra-day price movements (as opposed to just end of day prices) and the volumes of trading business done each day (since what happens on a high volume day is usually more telling about market sentiment than what happens on low volume days).

The debate about the predictive powers of charts will go on. There are clear examples where the charts have been ‘right’, but others where a major future price movement has failed to be predicted. Whatever the case, though, many analysts majoring on fundamental analysis to assess the likely future movements in share prices also use technical analysis to provide a ‘second opinion’.

3.4.4 Can investors really beat the market?

To conclude the debate about whether we have the capability to predict future movements in shares and other assets, hear what some financial experts have to say on the matter.

Download this video clip.Video player: ou_futurelearn_mmi_vid_1102.mp4

Show transcript|Hide transcript

Transcript

COMMENTARY

The thought that we can out-guess others or even the market - hubris - plays a part in the creation of all bubbles.

JAMES MONTIER

We have these delusions of our own abilities and those really do feed bubbles, because bubbles at heart are all about over-optimism.

LARRY ELLIOT

People just do assume that they have discovered the one little secret that will actually make what went wrong last time, right this time. It’s a bit like a golfer who goes out there and shoots 90 but thinks actually, there’s one little thing I do to my swing will turn me into Tiger Woods.

And all I really need to do is just tweak a few things and we’ll get things absolutely right. And that’s what people think in the markets.

HOWARD DAVIES

Don’t think that you can regulate away optimism and animal spirits, if you like, and that I think is almost bound to mean that there will be, from time to time, some overshooting on the upside and some overshooting on the downside.

JAMES MONTIER

The four most dangerous words in investing are “This time it’s different” and it never is.

LARRY ELLIOT

People forget. They know that there has been massive boom bust. They know there have been gigantic speculative bubbles. People forget.

MARTIN UPTON

Can fund managers consistently beat the market?

ANTHONY NUTT

Well the record would suggest not, but depending on your time horizons, if the question is, can they beat the market year after year after year after year, it’s unlikely because the market goes through phases of sentiment. Which a long term investor will tend to ignore, and a wise investor would tend to ignore quite frankly, but over the long period of time there are some very significant and many of them, examples of fund managers that have beaten the market.

End transcript

Download

 

3.5 Week 3 quiz

Check what you’ve learned this week by taking the end-of-week quiz.

Start quiz

Open the quiz in a new window or tab then come back here when you’re done.

3.5.1 Monitoring shares, gilts and Bank Rate

You will recall that last week (in the section ‘Shares to follow’) you started to monitor the share prices of some selected companies listed on the London Stock Exchange and also the yields on UK Government bonds (gilts).

Let’s catch up with their movements over the past week.

Remember, you can follow these shares using the BBC Market Data tool, or by picking up a newspaper which focuses on financial markets.

What has happened to the prices of the shares and to the UK gilt yield curve?

Looking at the charts of the share prices, do you detect any features that a technical analyst (or ‘chartist’) would point to as providing a guide about the likely future direction movement of the price?

Share your findings and your thoughts about the factors that have driven these changes over the past week.

Week 3 round-up

It has been a very full week again and we’ve covered some difficult concepts, but these concepts are key to effective investment management.

Understanding portfolio theory, CAPM and the Efficient Markets Hypothesis, as well as concepts like Random Walk theory, pound cost averaging and chartism are all important component parts of a rounded knowledge about how investment markets work.

You’ll have seen as well how these theories apply in the practical world of investment management. All this helps to establish your own strategy for managing your investments.

Don’t forget to continue with Activity 2.4 and check the prices for the selected companies once a week and enter their level in the Market shares tracking worksheet. Remember, you can follow these shares using the BBC Market Data tool, or by picking up a newspaper which focuses on financial markets.

Next week, you’ll turn to the subjects of investment strategies in practice and how to judge the performance of investments – in particular, the performance of those managing investment funds. In moving to these subjects, we arrive at the fourth stage of our investment management model – the ‘review’ stage.

You can now go to Week 4.

Further reading

Senanedsch, J. (2012) ‘A General Methodology for Testing the Performance of Technical Analysis on Financial Markets’ Journal of Computations & Modelling, vol.2, no.2, pp. 79-94 The article examines the performance of technical analysis. The introduction to this article also explains efficient market hypothesis.

References

Acknowledgements

This free course was written by Martin Upton.

Except for third party materials and otherwise stated in the acknowledgements section, this content is made available under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 Licence.

The material acknowledged below is Proprietary and used under licence (not subject to Creative Commons Licence). Grateful acknowledgement is made to the following sources for permission to reproduce material in this unit:

Images

Figure 5 Yerpo via Wikimedia Commons (Creative Commons Attribution-Share Alike 3.0 license https://creativecommons.org/licenses/by-sa/3.0/deed.en)

Figure 9 © wdstock via iStockphoto.com

Figure 12 © Chris Ratcliffe/Bloomberg via Getty Images

Audio/Video

3.2.1 © The Open University

3.2.3 PUFin www.open.ac.uk/ pufin © The Open University

3.5.4: © The Open University

Every effort has been made to contact copyright owners. If any have been inadvertently overlooked, the publishers will be pleased to make the necessary arrangements at the first opportunity.

Don’t miss out:

1. Join over 200,000 students, currently studying with The Open University – http://www.open.ac.uk/ choose/ ou/ open-content

2. Enjoyed this? Find out more about this topic or browse all our free course materials on OpenLearn – http://www.open.edu/ openlearn/

3. Outside the UK? We have students in over a hundred countries studying online qualifications – http://www.openuniversity.edu/ – including an MBA at our triple accredited Business School.