Published: March 01, 2012
The risk measure Value-at-Risk (VaR) was designed to measure market risk for use in financial institutions. It can be regarded as a market standard for risk measurement. Its popularity in the market is based in part on the fact that risk management regulations for financial institutions have defined this measure to be an appropriate method of risk measurement. However, its success is also based on the fact that it is one single number, is easy to understand and can be implemented with a reasonable effort. Over the years, the approach has been developed further in terms of methodology, application, interpretation, implementation and other dimensions. However, in the corporate world, a discussion about the reference value of risk management and risk measurement and further practical thoughts have led to the development of a modified approach, the Cash Flow-at-Risk (CFaR).
The Value-at-Risk approach is defined as follows: The potential loss of a specific portfolio will not be larger than amount x given a confidentiality level of a and given a holding period of T days.
For example, if we consider a company exporting cars from Europe to the USA and its revenues in Q1 2012 based on today’s expectation of USD 100 Mio for the next quarter, the application of a Value-at-Risk approach could be implemented using the following steps - see chart 1.
The according calculations performed based on the assumptions might lead to the following result:
Figure 1 shows that the company might end up with a loss of EUR 1.75 Mio instead of a profit of EUR 2.25 Mio that it can expect or alternatively lock in directly by using FX-Forwards. The difference between the expected profit of EUR 2.25 Mio and the maximum expected loss of EUR 1.75 Mio implies a Value-at-Risk of EUR 4 Mio.
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The interpretation of the calculated numbers has to consider all assumptions made when setting up the model and the appropriate methodology:
The maximum loss caused by movements in FX-markets for the USD-revenues of Q1 2012 within the next 30 days is expected to be EUR 4 Mio given a confidence level of 95%. This implies that in 5% of the cases the loss might be higher than EUR 4 Mio. And, of course, there is no information about the exact assumptions for the historic simulation that has been used for the calculation (e.g. length of historic time series, extinction of outliers, use of 30 day interval vs. 30 independent days, etc.).
In the academic world, and even in public journals, a significant number of articles have been published since the concept was first introduced. A large number of follow up articles mainly deal with the application, calculation and interpretation of this figure. One development in the discussion is about the techniques used and the necessary methodology adjustments when applying this measure in the corporate world.
Many non-financial companies measure their risk using the planned cash flows from their operating business. While in financial institutions the enhancement of the portfolio value and the company value is the focus of risk management, in industrial and trading companies we find a different approach. This approach is directly linked to the expected or forecast cash flows generated by the company. A good illustration for this is the example of a company loan:
A) a bank has bought a commercial paper with a fixed interest payment
B) a non-financial firm has launched a commercial paper with a fixed interest payment
While both actions are identical regarding the economic effect linked with this derivative instrument, the interpretation of the risk management within the two companies will be quite different. Usually the bank would hold the paper for trading purposes only and would consider a potential change in fair value to be the main risk and calculate a Value-at-Risk for the linked interest rate risk for this paper and the according portfolio. The non-financial company, on the other hand, might have a different view because the risk management in this company aims to stabilize the prospective cash flows. A change in fair value of the commercial paper due to a change in interest rate levels will be recognized by the company, but it will usually not be considered as a risk since the cash flows related with the commercial paper will remain constant over time. In most of the cases, the company will regard this paper as risk free and will not calculate a risk measure, knowing that since the cash flows are fixed, there is no risk.
When looking at a different example, it leads to a similar result:
A) a bank has issued a Nickel commodity swap with a floating payment based on the LME 3M-Seller against a fixed price level of USD 20,000
B) an industrial company has bought a Nickel commodity swap with a physical delivery of LME-quality Nickel for a fixed price level of USD 20,000
While both actions again are similar regarding the economic effect, the interpretation of the risk management within the two companies might be different. The bank will usually hold the derivative for trading purposes and will consider a potential change in fair value as the main risk and calculate a Value-at-Risk for the according commodity portfolio.
When looking at the industrial company, there are two different interpretations. The risk management could come to the conclusion that it has fixed its expected cash flows because the swap can be used for the fix price delivery of the Nickel that is needed for its production. But this could only be half of the full picture. The risk management might also come to the conclusion that there is a risk attached. This is the case if the sales price for the material produced with the Nickel has not been fixed yet. In this situation, the result might be a negative competitive position if Nickel prices drop until the product is sold and the Nickel component is part of the price negotiation. Of course, it might also result in a positive situation, when prices rise after buying the swap.[[[PAGE]]]
These considerations have led to the creation of the risk measure Cash Flow-at-Risk. For this risk measure the reference value is the expected or planned cash flow rather than the value of a portfolio.
The Cash Flow-at-Risk approach derived is defined as follows: The potential monetary decrease of a specific cash flows series will not be larger than amount x given a confidentiality level of a and given a considered period of T days.
In analogy to the VaR the parameter T again represents the time from calculation until the next calculation run rather than the future period of expected cash flows.
Taking a deeper look into the different models for Cash Flow-at-Risk, another way of interpreting this risk measure can be found. This interpretation considers the fact that future cash flows of a company can be matched to an appropriate cash flow map on a time frame. This time frame is the basis for simulation runs that assume the applicable cash flow forecast for the relevant period and implement all relevant risk factors that could affect the cash flows in the model.
This model is used for a number of simulation runs in order to determine the path dependent risk figure. In the illustration below the green path is clearly the best outcome of the simulation runs. Analyzing the red path the main differences between Cash Flow-at-Risk and Value-at-Risk can be seen. While the ending point of the simulation is within the theoretical confidence interval represented by the black parabolic line, and will therefore be regarded as an average run, the path dependent analysis shows a new worst case. This worst case would not have been detected by the Value-at-Risk measure.
The Cash Flow-at-Risk approach derived is defined as follows: The potential monetary decrease of a specific cash flows series will in not on single path, meaning at no point of time, be larger than amount x given a confidentiality level of a and given a considered number of n days until T.
Depending on the nature of a company’s business, all cash flows must be modelled individually. In particular for large companies with a complex business and a number of risk factors this approach results in a very sophisticated model. Even in the simplest of all cases when movements of risk factors are considered to be independently distributed in the model, the effort for setting up a consistent model can be challenging for risk managers. Adding the complexity of conditional probabilities and correlations between risk factors is likely to end up in a large project. The accuracy and thus the complexity of modelling cash flows are theoretically without a limit, but the gain in knowledge and the increase in risk management quality have to justify the costs for obtaining information and the effort for the implementation of the model as well as the information processing.[[[PAGE]]]
In traditional financial planning and in budgeting, which is practiced in most companies, much information is already contained. The task of modelling the appropriate cash flows and the change from looking at the expected values to looking at distributions and random variables is a perspective that includes a large benefit for many companies.
Especially for companies with a business that is influenced by market risk factors to a large extent, the effort for the implementation of a new risk management concept around the ‘At-Risk-Figures’ leads to a significant increase in risk management quality. The reason for this is that it is much easier to create a reliable model when using observable market time series for the risk factors in the model. From our experience with various risk metrics and risk management approaches we have found that the Cash Flow-at-Risk is most valuable forcompanies with a significant exposure to market risk factors. Those companies are most likely to be found in the trading sector, the energy sector and in all commodity intensive industries. But also for other companies, the implementation of ‘At-Risk-Figures’ can be very useful, for example, in separated risk areas in the risk management for FX, interest rate or counterparty risk management.
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