Learning Objective
5.1.3 Be able to apply an understanding of market risk to simple, practical situations
As discussed above, three key drivers of market risk are currency, interest rate and liquidity risks. Some concrete examples will help to apply the concepts to the real world.
1.3.1 Currency Risk
A UK investor purchases an equity portfolio in the US. The investment itself, in dollars, provides a positive return of 10% but because the dollar loses 8% of its value against the pound, the investor’s return is only 2%.
1.3.2 Interest Rate Risk
An investor purchases a long-term bond in the UK hoping to sell it at a profit in the future. Bond prices move inversely to interest rate moves, so if interest rates increase, the price of bonds will fall. For short- term bonds (less than three years) the change in prices will be relatively minor compared to the change in price for a long-term bond (more than ten years). This is because longer-term bonds are generally more volatile because the distant future is unknown and therefore riskier.
1.3.3 Liquidity Risk
An investor purchases a commercial property to rent out. Because of liquidity issues in the property market, it takes much longer to sell again – even reducing the price may not help if no-one else wants to own the property, or if it becomes difficult to obtain credit for a mortgage.
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The main financial instruments used in hedging are derivatives, in particular futures and options. For instance, an investor who has bought an equity is at risk of losing money if the market declines. This risk could be hedged by buying a put option, costing a fraction of the price of the equity investment. This option gives the investor the right, but not the obligation, to sell the stock at a set price (the strike price) within a particular time in the future. The investor is now protected against adverse market movements.
The decision to hedge is a trade-off between the risk of adverse market movements and the cost of the hedge – in this case the purchase price of the option. However, it is difficult to achieve perfect offsetting of the risk and the use of hedging introduces, or exacerbates, other risks such as basis risk (described earlier), credit risk and operational risk.
2.1.2 Market Risk Limits
Market risk limits are used as a tool for managing market risk in the same way that credit limits are applied to protect firms from credit risk (see Chapter 4). When an organisation takes a risk, it will often specify the maximum loss that it is prepared to make on a portfolio or transaction. This is called the
market risk limit or stop-loss limit and may be expressed in terms of VaR (see Section 2.7).
The effectiveness of risk limits to manage market risk is dependent upon the accuracy of the risk measurement used to set the limits. The potential problems of using over-simplified risk measurement are:
• risk limits usually have to be inflated in order to accommodate the errors and uncertainty in the measurement. This adversely affects the potential profit of the firm
• traders or other investment professionals may exploit the inaccuracy of risk measurement and take risks that they know the measurement does not account for.
Provided that high quality risk data is used, risk limits can be very effective. While investment professionals sometimes see them as restrictive, they can also be viewed as empowering because they set the risk appetite of the firm and represent explicit authority to take specified levels of risk.
2.1.3 Diversification
The market risk of holding two securities in isolation is given by their respective standard deviation of returns (see below). However, by combining these assets in varying proportions to create a two stock portfolio, the portfolio’s standard deviation of return will, in almost all cases, be lower than the weighted average of the standard deviations of these two individual securities.
The weightings are given by the proportion of the portfolio held in each security. This reduction in risk for a given level of expected return is due to the effects of diversification. A very simple example of diversification would be to combine shares in a sun cream factory with shares in an umbrella business. The sun cream factory does well when the summers are hot, while the umbrella business does well on rainy days. Although the earnings of each individual business can be volatile, the combined earnings will be less so because of the inverse relationship, or negative correlation between their earnings.
Of course, most portfolios hold many more than two stocks, so to quantify the diversification potential of various multi-stock combinations, a concept called correlation is used, which is explained in Section 2.6. Diversification is achieved by combining securities whose returns ideally move in the opposite direction to one another or, if in the same direction, at least not to the same degree.
2.2
The Market Risk Management Function
Learning Objective
5.2.2 Understand the role and sound practice features of an effective market risk management function
In the same way that institutions use a credit risk management function to manage credit risk, it is also essential that they develop and implement an independent market risk management function to manage market risk in a company-wide context.
An effective market risk function will include the following features:
• ownership of the firm’s market risk management policy • proactive management involvement in market risk issues
• defined escalation procedures to deal with rising levels of trading loss, and market risk limit breaches • independent validation of market pricing and adequacy of VaR models
• ensuring that VaR is not used alone, but is combined with stress testing and scenario analysis • independent daily monitoring within banks of risk utilisation through the daily production of profit
and loss (P&L) accounts and review of front-office closing prices (independent means a separately accountable function reporting directly to senior management).
The role of the market risk function varies according to the type of firm because market risk management requires a different approach in a bank than in an investment manager. For example, a bank trading on its own account has limits applied ‘across the board’, whereas each fund in an investment management firm could have a different risk appetite for market, credit and other risk types.
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In addition, unlike operational risk, market risk analysis is able to draw on large amounts of data. However, having a large amount of available data is a mixed blessing because the larger the dataset, the harder it can be to distinguish which data items represent ‘expected’ behaviours (which will be replicated in the future with a high level of certainty), from those data items that are outliers (and therefore may or may not recur from time to time).
Often market datasets become so large and cumbersome that using and making inferences from samples is the only viable and cost-effective means of analysing the whole population.
We need to know three things about the sample:
1. What is its ‘typical’ value? It would be useful to derive a single number that captures the ‘essence’ of the distribution. This is referred to as the central tendency.
2. Do the other values stray very far on either side of this ‘typical’ value? This is referred to as the
dispersion.
3. How closely do the characteristics of our sample mirror that of the whole population? This is factored into the formulae for standard deviation shown below.
To illustrate these concepts, the following diagram shows a typical ‘distribution’ of values from naturally occurring datasets, such as people’s IQ or the age of staff in a company.
On the horizontal X axis are the different values which the data item could have. On the vertical Y axis are the number of times each value of the data item appears in our sample. The curve is this shape because there are lots of similar values in the dataset, with fewer small values and fewer large values. The concepts of central tendency and dispersion are illustrated on the graph.