“Quick and dirty” portfolio risk management

In my January performance review, I made the following comment:

Overall, if you don’t have an active opinion on interest rates (which in my opinion you shouldn’t), one should make sure that the overall exposure of the portfolio is as neutral as possible with regard to interest rates. This sounds easier than it actually is. For some companies (insurers) it is relatively easy to see how their exposure is to interest rates. For others, it is much harder. But in my opinion, just checking business models against the influence of interest rates is a very worthwhile and value creating exercise.

Checking a portfolio against interest exposure (or any other exposure) involves 2 basic steps:

1) You have to make a judgement how businesses are effected by the exposure (positive, negative, neutral)
2) You have to aggregate those exposures over your portfolio

Complex or keep it simple ?

In institutional environments, risk management departments are usually staffed by legions of math or physics Phd’s which employ very complex modelling tools in order to both, come up with exposures and aggregate them. There are a myriad sophisticated risk management techniques available. Monte Carlo analysis, correlation modelling etc. etc. can be combined to come up with great looking distribution charts showing portfolio exposures against a multitude of factors.

The problem with such sophisticated models is that the outcomes are often not stable and outcomes change a lot if some inputs are changed only slightly. In many cases those models develop into your typical “black box” where people do not understand any more of what is going on and how the results are actually creates and no one dares to ask.

This is the reason why I personally think that one should prefer simple and easy to understand models even if they lack most sophisticated tools. Maybe the results are not 100% accurate but at least one can understand them.

A very simple way to analyze and aggregate interest rate exposure

For step 1), I use a very simple heuristic based on capital intensity and sector:

– banks and insurance companies a clearly negatively effected, the more traditional the business model, the more negative the impact
– capital-intensive business or real estate related stuff usually profits most from low-interest rates
– capital light businesses are relatively neutral
– any longer term fixed income investments will do very well

For step 2), I then attach a score ranging from +1 (low-interest rates are very positive) to -1 (very negative) to each position and multiply it with the percentage of the portfolio.

This is how this would look for my current portfolio:

Name Weight Impact low interest rates Weigt
Hornbach Baumarkt 4.3% 0.5 0.02
Miko 4.3% 0 0.00
Tonnellerie Frere Paris 6.1% 0.5 0.03
Installux 3.6% 0 0.00
Cranswick 3.0% 0 0.00
Gronlandsbanken 2.5% -0.75 -0.02
G. Perrier 4.5% 0 0.00
IGE & XAO 2.1% 0 0.00
Thermador 2.6% 0 0.00
Trilogiq 1.5% 0 0.00
Van Lanschot 2.4% -1 -0.02
TGS Nopec 4.7% 0 0.00
Admiral 4.6% -0.5 -0.02
Bouvet 2.4% 0 0.00
KAS Bank NV 4.5% -0.75 -0.03
Emerging Market     0.00
Koc Holding 1.2% 0.5 0.01
Ashmore 4.2% -0.25 -0.01
Depfa 0% 2022 TRY 3.0% 1 0.03
Romgaz 2.5% 0.5 0.01
Electrica 2.6% 0.5 0.01
Drägerwerk Genüsse D 4.9% 0.5 0.02
DEPFA LT2 2015 5.1% 0 0.00
HT1 Funding 4.2% 0.5 0.02
MAN AG 2.4% 0.5 0.01
NN Group 2.8% -1 -0.03
Citizen Financial 2.8% -0.75 -0.02
Cash 11.3% 0 0.00
Overall IR exposure     1.2%

The resulting score will be between -1 (totally negative) to +1 (in aggregate positive).

Overall, based on my initial judgements, my portfolio looks pretty neutral vs. low interest rates. Clearly this is no scientific approach and I would not get any academic grades for this, but still, just doing the exercise in my opinion makes a lot of sense and makes you think about your overall portfolio exposures.

Once you have created this spreadsheet, it can be used with additional columns also to look at exposures like Oil prices or EUR crisis scenarios.

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