SRRI Study Part I - How Does Market volatility Impact Risk Measures?

By: Dr Paul Kaplan, Ph.D, CFA, Director of Quantitative Research at Morningstar. PART I: The aim of the SRRI, to provide investors with a standardised measure of risk, is a noble ambition but are there improvements to be had? In this, the first of a series of articles from Morningstar Director of Quantitative Research Dr …

April 7, 2011 | Morningstar

By: Dr Paul Kaplan, Ph.D, CFA, Director of Quantitative Research at Morningstar.

PART I: The aim of the SRRI, to provide investors with a standardised measure of risk, is a noble ambition but are there improvements to be had?

In this, the first of a series of articles from Morningstar Director of Quantitative Research Dr Paul Kaplan the author discusses the options for creating a universal risk ‘metre’ that will act as a useful guide for individual investors without misrepresenting the complexity of risk as a concept. Read PART II: Risk By Any Other Name, by clicking here.
The European Securities and Markets Authority’s (ESMA) proposed Synthetic Risk Reward Indicator or SRRI for the Key Investor Information Document (KIID) has the noble ambition of providing the ordinary investor with a simple measure of risk. There can be no doubt that this is a laudable goal, as theory and practice have proven that the risk of an investment can be difficult to grasp for even sophisticated investors.

Ultimately, explaining complex and technical concepts like risk in a straight-forward manner requires some compromise to “keep it simple” both in calculation and presentation. This is especially true when considering the impact various investment strategies and product structures have on the final investor experience. To the point, this is not easy to do in a formulaic manner–something has to give.

The current specification for calculating the SRRI is a great start. But we’ve asked ourselves at Morningstar, based on our experience and skill at devising just such intuitive presentations of difficult concepts: are there ways to improve the result of the SRRI methodology for investors without adding undue complexity?

As you might have guessed by now, we came up with some possible answers to this question. Over the course of the next several months, through research led by our best quantitative minds we hope to open a discussion on the merits of some possible improvements.

To start, we recommend that “Reward” be dropped from the SRRI name. While taking risk might be a necessary condition for reaping the long-term rewards of investing, it is far from a sufficient one. In fact, most risk goes unrewarded. This is why modern portfolio theory teaches us to diversify our portfolios to avoid taking risks that will not be rewarded.

We start our analysis by considering the fixed boundaries specified by ESMA for the risk scores. Fixing these cut-off points at once makes both the calculation easier to perform and provides some consistency–consistency in process that could help investors understand the outcome better. However, having static boundaries creates its own issues when overall market volatility shifts dramatically.

See Chart 1 below for an illustration of this point. We took generally accepted representative market indices for equity, fixed income, and money market asset classes and plotted their weekly rolling 5-year volatility according to the ESMA specification. The fixed horizontal bands represent the fixed breakpoints for translating volatility into the risk score, which is an integer between 1 and 7. As you can see from Chart 1, the major market disruption at the end of 2008 caused by the financial crisis altered the landscape, especially with the equity indices representing European shares.

Chart 1

Volatility spiked in a very significant way, which is not news to anyone. What is interesting is both the dramatic immediate shift and the enduring impact this shift has had on the risk scores for these equity asset classes.

Our concern with fixed boundaries is that without a link to the underlying market volatility, investors might be alarmed to learn that within a few short weeks many of their funds shifted from a risk score of 5 to a risk score 6, one step away from the most risky investments available in the market by this measure. Even at the low end of the risk spectrum, LIBOR is close to moving from a score of 1 to a score of 2. This means that under certain market conditions it might be difficult for investors to find an investment with a risk score of 1.

A possible solution to the problem of dramatic shifts in risk scores is to use boundaries between the risk scores that adjust based on the underlying market volatility. Chart 2 shows the effects of doing this. Granted this adds some additional complexity in performing the calculation, but we feel it is worth it to ask the experts–the fund companies–to do a little extra work so that investors don’t have to. As you can see, by adjusting the cut-offs these same equity indices remain much more consistent in their risk score. Trading the consistency in the cut-offs for consistency in ratings, yet still providing a useful measure for investors in a way that is easier to understand.

An additional advantage of tying the risk score breakpoints to market indices is that the way the breakpoints vary can be linked to a specific currency. In fact, this is what we did to create Chart 2 below. The reason that we only show the indices that are denominated in Euros in the chart is that breakpoints are tied to a Euro-denominated index. Investments with returns denominated in, say, Pound Sterling would have breakpoints that are tied to an index that is denominated in Pound Sterling. This will be the topic of the next article in this series–a more detailed look at how currencies can impact SRRI score.

Chart 2

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