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Risk Management

Risk management involves ‘uncertain’ outcomes. In financial analysis, the greater the variability in financial outcomes, the greater the risk.

The Efficient Frontier

One of the most general strategies in financial analysis is determining relative financial value by finding the greatest yield (or rate of return) for a given level of risk (or variability in cash flows). The yield is often referred to as alpha and the variability in return is referred to as beta. For any given level of beta, investors tend to prefer assets with the greatest alpha. The set of assets that provide this maximum alpha for each level of beta is called the ‘Efficient Frontier’ – and these are the candidates from which investors usually select investments.

It is essential that any financial analysis and all risk analyses include both ‘point’ estimates of expected return and ‘distribution’ estimates of return for given scenarios to allow the comparing of variability in outcomes (beta) of assets.


A simplified risk-management matrix that illustrates the four major strategies of risk management.

General Principles of Risk Management

Another general principle of risk management is to assess both the relative ‘impact’ of a risk and the relative ‘likelihood’ of that risk. Some risks are very frequent but have a very small impact. Some risks are relatively rare but are catastrophic. The management of risk requires that a specific strategy be developed for each category of risk.

Some risk managers classify their management strategies as having SARA characteristics – which stands for Share, Avoid, Reduce, Accept. These strategies are illustrated in the accompanying risk matrix.

Model Risk Management

One category of risk that has become increasingly important (as financial markets and instruments have become much more volatile lately) is that of Model Risk Management. This relates to the risk that arises from developing and relying upon quantitative models for estimating other risks.

As financial managers begin to rely upon the output of a financial model, for example, they might become blind to the limitations of those very same financial models. Sometimes the volatility of certain markets far exceeds the ‘normal’ limits within which those models have been developed. The ‘fat tails’ of distributions discovered in the 2008 market disruptions proved that sometimes entire markets are disrupted in ways that are wholly unanticipated… Events and correlations among variables that seemed impossible in ‘normal’ times actually occur. This is like a string of ‘100 year floods’ that occur in multiple back-to-back years. Model risk management is designed to identify the underlying weaknesses of the models that provide us with this false sense of security.

Download a sample chapter from Risk-Based Pricing book by Craig M. Allen.

See other posts on risk management.