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ESG: The metrics jigsaw


Investing in credit - key success factors at Lomba

Corporate introduction
Lombard Odier Darier Hentsch is a Swiss private bank with total assets under management amounting to approximately €80 bn of which some €11 bn have been invested in fixed income securities for institutional accounts. This is managed on a discretionary basis as well as through pooled investment vehicles. The credit team of Lombard Odier Darier Hentsch is located in London, Amsterdam and Zurich.

The case for credits
With government bond yields currently at historic low levels and risk adjusted return outlooks for equities being not too rosy, investors with a long-term view are looking at alternative investment categories. Although the case for credit investments has been made more than once, we will briefly touch upon the reasons why we believe this asset class is currently attractive. More in detail, we will outline our view concerning the factors, which are key to outperformance and how we have fared by applying these factors in practice.

Why invest in credit in the first place?
Assume the starting point is a 100% government bond portfolio, which is open to invest into alternative categories. If the investor would opt for credits, two considerations can advocate investing in this investment category:
(1) Diversification benefits created by negative correlations between government bond yields and credit spreads;
(2) A better risk return profile of the credit asset class itself versus government bonds.

Diversification benefits
Intuitively, one would expect negative correlations and therefore diversification benefits. In the current yield environment, the risk for pure government bond portfolios is rising yields that could be caused by either a resurgence of economic activity, thus triggering central banks to tighter monetary conditions or a decrease of risk aversion. Both factors would cause credit spread compression, which would reduce capital loss if credits were included in the portfolio. This negative correlation can be challenged if we look at the recent period of economic expansion. During the period 1997–2000 the negative correlation between positive excess returns for credits and government bond yields did not always pertain. What we observed during this period was that credit quality deteriorated, caused by ballooning debt financed acquisitions and capital expenditure. So, credit investors should also monitor the credit cycle. Graph 1 shows the yield ratio since 1960 and how it developed over time, especially during periods of recession.
The credit cycle normally lags behind the economic cycle. Towards the end of the growth cycle credit quality deteriorates because of reduced cash flow with increased liabilities. At the deepest point of a recession credit quality starts to improve due to reduction of debt and capital expenditure and eventually through improving cash flows resulting from accelerating economic growth.
Let us look at some figures. As the Euro credit market only started to develop as of 1997, we used numbers available in the US market. Table 1 below shows correlations between total returns of US treasuries and excess returns of US credit. Credits are represented by the Lehman Brothers index.
There is a clear negative correlation between excess returns and total returns of government bonds implying there are diversification benefits to be achieved. These negative correlations tend to become stronger once we move down the credit rating scale. Naturally, the lower quality segments are the more risky ones. It is also noted that the high yield category is closely correlated to equities.

A better risk return profile of credits versus government bonds
If we compare the risk return characteristics of credits versus government bonds over longer periods, the general picture can be drawn that credits decrease risk and raise return and therefore improve the risk return profile. Graph 2 below shows, over the given periods of time, the risk and return profiles of credits versus government bonds. The horizontal axis shows volatility of the respective asset classes, the vertical axis the corresponding annualised total return.
In graph 2, we have compared credits and government bonds in euro, sterling and US dollar markets. Credits are shown by the yellow dots, government bonds by the red dots. In addition, the periods that were measured are shown; in the case of US corporates 1926–2001, 20-year periods were taken into consideration. From the graph it can be concluded that in all cases, except euro/ECU Eurobonds case, credits show a lower volatility and a higher total return.
Within this context, the euro figures look a lot less attractive. There are several reasons that have led to this outcome:
(1) The Euro credit market has started to develop in one of the worst periods ever for credits. Default rates have reached a historic high in 2002.
(2) We have seen the burst of the internet bubble in this period, as well as a variety of accounting scandals.
All of these factors resulted in increased risk aversion amongst investors and therefore a rise of risk premiums (credit spreads) in 2002. The effects of idiosyncratic risk (risk related to one single issuer) have been substantial. To put this into perspective, the cumulative excess return for Euro corporates has been a negative 45 basis points during 2002 (Lehman corporate index). But if we exclude the fallen angels, the index produces a completely different result, ie, a positive 56 basis points!
Timing is obviously important. We believe we are currently at the brink of a major move towards deleveraging of corporate balance sheets. This has already started in the telecom sector. This does not mean the investor can just buy the credit index and wait until the asset class starts performing. Investing in credits should not be taken lightly as pitfalls still abound. Especially the Euro credit market is characterised by specific traits and is dominated by a few very large issuers and many small ones. Having one or two fallen angels in the portfolio is devastating for the performance of the entire portfolio. Hence, resources and skill sets are needed to operate successfully in this market segment over the longer period.
Looking at the numbers, the case for credits looks compelling. However, one must not mix up index returns with portfolio returns. In practice the amount of issuers in a portfolio is smaller than in the index and as such idiosyncratic risk is much larger. Almost any 1% position in a portfolio is a de facto overweight position versus the benchmark. Looking at the experience of the last two years shows us that overall idiosyncratic risk has risen sharply due to the burst in the growth bubble, accounting scandals and the resulting exponential rise in downgrades and defaults. The gains to be made by avoiding so called ‘blow ups’ are large. For example a 1% holding that widens 500 basis points assuming a modified duration of 4 will cost 500*0.04*0.01 = 20 basis points on portfolio level. This year 21 issuers widened more than 500 basis points, which is close to 10% of the corporate universe. If an investment manager had avoided all of these, the portfolio would have made 56 basis points versus the JP Morgan Maggie Corporate index. Looking at these numbers, we believe that the upside potential of credits is limited compared to the downside risks that come from falling angels. In addition, statistics show that risks in credit markets are heavily skewed towards the downside. This is why investment strategies based on some mean reversion principle are risky if they are not combined with proper fundamental analysis. Only fundamental analysis can separate bonds that look cheap by quantitative measures (such as z-scores) from potential fallen angels.

The question remains how can we efficiently manage credit portfolios and outperform the benchmark?
From a quantitative point of view, there are a few considerations to be taken into account that may even be conflicting. Diversification is needed to reduce the potential effects of ‘blow ups’ but too much diversification will tend towards index replication. In terms of efficient portfolio management a portfolio needs around 50 names to achieve a reasonably low ex-ante tracking error. That would mean on average 2% per holding which could potentially lead to a large negative single issuer effect. Reducing it to 1% would mean one hundred different issuers and reducing blow up effects by half. Bear in mind the amount of corporate issuers in the Lehman Corporate index is 238. One hundred names would resemble the index too much. The answer lies in the middle.
Index and historical analysis show us a few things. AA risk is not the same as BBB risk and blow-ups were mostly BBB rated issuers. The euro index has a few large issuers and many small ones, which are rated below average. This requires a tailored approach. The Credit Team of Lombard Odier Darier Hentsch has determined a strategy that is aiming to minimize risk and maximise outperformance. We work along the lines described hereafter.
From a fundamental point of view good credit analysis is key to avoid any serious problems in the portfolio. Avoiding blow ups is strongly related to proper analysis and raising the right issues. There are a number of significant warning signs and questions that should be asked in credit analysis, such as:
q Does the company have a history of debt-financed M&A?
q Is the company suffering from a degree of financial stress, ie, negative cash flow, combined with high leverage?
q Did the company address its problems through dividend cuts, cost cutting, and management resignations?
Negative answers to a combination of the above raised questions are normally a clear sign of a deteriorating credit story. To a varying extent, Ahold raised concerns on all of the above points and so did Enron, Worldcom and TXU. Companies involved in compensatory and punitive legal proceedings are another reason for scrutiny. If potential liabilities would not be quantifiable, why would anyone want to invest in such a company?
In addition, there are a number of risk factors that need to be included when managing credit portfolios:
(1) Weights in higher rated names can be larger than in BBBs;
(2) Diversification pays in lower ratings. This is due to larger dispersion and higher spread volatility;
(3) Use larger weights only on high conviction trades;
(4) Illiquid bonds/issuers should get lower weights as spread volatility is higher and tradability is lower. This argument is also valid with respect to the total size of the asset manager. The weight of one single holding in the portfolio can be low but total size holdings at the asset manager’s level can be large. This makes it more difficult to get out of difficult positions due to total transaction size;
(5) Cut losses quickly, do not wait until the bonds really trade at 70;
(6) Sell when you can, not when you have to.

To summarise, Lombard Odier Darier Hentsch believes there are substantial gains to be made by allocating part of your fixed income portfolio to credits. Benefits can be generated from diversification as well as an improved risk/return profile. Successful credit investing requires tight single issuer risk limits, overall strong risk management and thorough credit analysis. The investor should focus on avoiding the downside risks instead of focusing on upside potential. Since inception in February 2000, the flagship institutional Euro credit fund of Lombard Odier Darier Hentsch has not had one single blow up. With an annualised tracking error of 1.08, the total return over the period reached 25.73%, which corresponds, with 8.42% annualised basis. Versus the benchmark Salomon Smith Barney non-egbi Euro Big, this means a 3-year outperformance of +2.29%.
Rodrigo Araya Arancibia
Vice President and senior credit portfolio manager
If you need further information, please contact at Lombard Odier Darier Hentsch in Amsterdam:
Fernand Schürmann, Senior Vice President
Tel: +31 20 522 0564
Web site:

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