Many treasurers are aware of the importance of quantification of risk exposures and optimising their risk management strategies and policies. The first step is to define the unit of measuring risk. Many companies use "volatility" synonymously with risk. Is there a better metric.

    The problem of volatility

    Consider the following three risk profiles. Distribution A is normally distributed but B and C are not. All three have a mean of zero and volatility1 of 20.

    As a treasurer, which risk profile would you prefer for your company?

    Risk profiles

    Intuitively, C may seem the most appealing, as it offers the comfort of a known worst-case loss of no more than 10 with some potential gain of 50. B, on the other hand, has a high probability of gain of 10 but with some probability of a large loss of 50.

    In the above example, we see that had we based our judgment on volatility alone, without considering the actual shape of the distribution of outcomes, we would not have been able to tell these risk profiles apart.

    The heart of the matter is that volatility, by definition, ignores the direction of market fluctuations. It is only a scalar number reflecting the average magnitude of change, without any regard to the sign or direction of change, i.e. whether it is a positive or negative change.

    Said another way, one could be unfairly penalising "good" volatility by treating it as the same as "bad". Therefore, companies operating on a volatility minimising strategy could often find themselves eliminating both good and bad volatilities altogether, usually by overly deploying linear hedging strategies.

    The fact that "good" volatilities have been given up can potentially lead to a feeling of regret. In our second Rethinking Treasury article, we learnt that the emotion of regret can be a powerful behavioural driver. The feeling of regret may cause treasurers to lose discipline in their hedging decision processes, potentially leaving risks unhedged for fear of missing out on possible advantageous movements.

    The problem of at-Risk measures (VaR)

    "At-Risk" measures such as Value at Risk (VaR) or Cash Flow at Risk (CFaR) offer a step improvement over volatility in terms of quantifying downside risks.

    At-Risk measures focus on tail-end risks. For example, if we measure VaR as the magnitude of loss at the 5th percentile worst outcome (or the worst outcome with 95 per cent confidence) for A, B and C, we get 33, 50 and 10 respectively. C gives the lowest Value at Risk and is therefore most favourable.

    However, a major weakness still remains with at-Risk measures. By focusing entirely on the worst outcomes, one can lose sight of the opposite side of the distribution which are the possible upside scenarios. Because of their focus on just one particular outcome in a distribution, at-Risk measures can be less useful when underlying risk distributions have non-normal shapes, which often happens when options (real or derivative) are involved.

    Is there a better way to measure risk?

    Both volatility and at-Risk measures have their own merits. At-Risk measures focus on tail risks but ignore other outcomes, especially the upside. Volatility incorporates the whole distribution, but penalises both upside and downside volatilities equally.

    The following seeks to strike a better balance.

    An alternative way of looking at risk: "HSBC Risk Aversion Adjusted Volatility"

    HSBC Thought Leadership has used the HSBC Risk Aversion Adjusted Volatility (HSBC RAAV) methodology to help clients evaluate various risk profiles.

    One key difference in our approach is the recognition that upside volatility should receive a positive scoring and downside volatility should receive a negative scoring.

    This intuitive approach helps clarify the goals of treasury risk management. This is because when it comes to risk management decision making, we naturally ask the following three questions.

    • Can I increase the upside volatility of my portfolio?
    • Can I decrease the downside volatility of my portfolio?
    • What is my risk appetite?

    Via this lens, one could view treasury risk management as a balancing act between upside volatility retention and downside volatility reduction, taking into account the risk appetite of the company.

    Companies can determine their own risk aversion factors bespoke to their company situations. For example, a company with lower operating margins can be more susceptible to large negative shocks, and may want to adjust its risk aversion factor upward.

    On risk appetite, we refer back to our inaugural Rethinking Treasury article, "Three scientific reasons why companies hedge". We saw from a simple experiment that people are naturally hardwired to be more loss averse than we are gain loving. In fact, scientists have quantified this asymmetry and found that losses are psychologically twice as strong as gains.

    In other words, cognitive science suggests a number on the asymmetry claiming that eliminating 2 units of downside is just as good as improving 1 unit of upside. Therefore, in our formula, downside volatility is given more weight. The downside weight multiplier is also known as the "risk aversion factor" (e.g. 2 times).

    Companies can determine their own risk aversion factors bespoke to their company situations. For example, a company with lower operating margins can be more susceptible to large negative shocks, and may want to adjust its risk aversion factor upward.

    The HSBC RAAV methodology is also helpful in various risk optimization exercises, such as the efficient frontier analysis and historical simulations.

    Going back to our original example, we can now apply the HSBC RAAV methodology. We use a risk aversion factor of 2 as an illustrative example.

    Distribution

    Volatility

    Upside volatility

    Downside volatility

    HSBC RAAV score
    (Upside vol minus Downside vol x 2)

    Remarks

    A

    20

    14.1

    14.1

    14.1 – (14.1 x 2) = -14.1

     

    B

    20

    8.2

    17.7

    8.2 – (17.7 x 2) = -27.2

    Least favourable

    C

    20

    17.7

    8.2

    17.7 – (8.2 x 2) = +1.3

    Most favourable

     

    Here, C emerges as the clear favourite as it has the best scoring under HSBC RAAV methodology.

    Key Takeaways for Treasurers and CFOs

    We acknowledge that not all companies' views on risks are equal. Some companies may prefer a more conservative risk aversion factor. Other companies may also have their own preferences as to how they define and calculate volatilities.

    The bottom line remains that risk quantification can help stimulate discussions internally and hopefully lead to discoveries that will reveal the company's true underlying risks and risk appetite. Understanding the process and the concepts can help move the company closer to its ideal position.

    HSBC's Thought Leadership has dedicated expertise to help companies optimise their portfolio risks via analytical models such as value-at-risk and efficient frontier analysis.

    Next month, we will look how optimal strategies are arrived at with a simple example of counting words in a book and what they mean for hedge optimizations.

    Note

    1 In this article, we define volatility as the square root of variance. Variance is calculated as the frequency weighted squared deviations from mean.

    For more information, contact us:
    thought.leadership.global@hsbc.com

    Find out more markets insights in our New Future series.

     

     

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