Managing High Yield public small caps with Robeco s corporate bond selection model COALA For professional investors only

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1 ROCK note December 2010 Managing High Yield public small caps with Robeco s corporate bond selection model COALA For professional investors only By Sander Bus, CFA, portfolio manager Daniël Haesen, CFA, quantitative researcher Patrick Houweling, PhD, quantitative researcher Introduction Generating benchmark-like returns is a difficult job in the High Yield corporate bond market. High index turnover and illiquidity, i.e. high bid-ask spreads, are the main reasons why passively tracking a High Yield index comes at significant costs. In this note we show that Robeco's corporate bond selection model COALA is very well able to keep up with its benchmark, after taking index turnover, transaction costs and illiquidity into account. Besides, by applying the model to a specific segment of the High Yield market - small caps with publicly listed equity - we gain access to a long-term source of smart beta. Robeco's High Yield Bonds fund benefits from this smart beta effect by investing in public small caps using the COALA model. Corporate bond index tracking is costly Buying a portfolio of all index constituents, and adjusting the portfolio in response to index changes, is possible at low costs in liquid markets, such as equity markets and Treasury bond markets. However, due to specific features of the corporate bond market, generating benchmark-like returns is not easily done. The main reasons are index turnover and the illiquidity of corporate bonds 1. Index turnover is caused by events like new issuance, upgrades and downgrades, tenders, calls, or defaults. Also, redemptions and coupons generate cash that needs to be reinvested. In order to keep track with its benchmark, a fund needs to buy and sell bonds, thereby incurring significant trading costs. This puts the fund at a disadvantage to its benchmark that does not incur costs. Tracking costs are higher for High Yield indices than for Investment Grade indices, because transaction costs are larger due to lower liquidity and because turnover is much larger due to more frequent earlier redemptions and defaults and higher coupons. Furthermore, the illiquidity of the High Yield market makes it difficult to trade bonds within reasonable time, leaving a fund underinvested when it receives large inflows. Robeco research 2 has shown that Exchange Traded Funds (ETFs), which are specifically designed to track corporate bond indices, are indeed lagging their benchmarks. Furthermore, the underperformance of High Yield ETFs is more severe than of Investment Grade ETFs. To give more color on the tracking costs in High Yield, we calculated the annual turnover using data of the Barclays Capital U.S. High Yield index over the period from January 1990 to December We found that, on average, 40% of the constituents leave the index for any of the aforementioned reasons. Further, we calculated that the costs of replicating this index, solely caused by index turnover, amounts to about 90 bps per annum. For any High Yield fund this implies it needs to make up for 90 bps of performance only to break even with the benchmark. These costs are varying over time, and are higher when the market is less liquid and transaction costs are higher, as a result of higher bid-ask spreads. For example, in 2009, the tracking costs amounted to 180 bps. 1 These and other reasons are also mentioned in Levine, Drucker and Rosenthal, 2010, The Problems and Challenges of High- Yield Bond Benchmarking, The Journal of Portfolio Management, Summer See High Yield ETFs are not the low-cost, low-tracking error alternatives to the Robeco High Yield Bonds fund, Robeco Rock Note, April 2010 and On the Performance of Investment Grade Credit ETFs, Robeco Rock Note, June Both notes are available from (in the Research section). Page 1 of 5

2 Robeco s High Yield Bonds funds unique investment process The High Yield universe consists of a relatively small number of large names, and a large number of small names. About 50 of the largest names account for approximately 40% of the market capitalization of the High Yield index. The remaining 60% of the index consists of over 800 names. 3 In Robeco s High Yield Bonds Fund, the large names are covered by a team of experienced credit analysts, who conduct thorough fundamental research on a company s ability to meet its obligations. The remaining part of the universe consists of smaller constituents, both private companies and companies with public equity outstanding. Robeco s quantitative corporate bond selection model COALA focuses on the latter group: about 400 small and mid cap High Yield names with publicly listed equity. Smart Beta effect in High Yield: public small caps outperform These public small caps, as we call them, constitute an overlooked market segment. Our research shows that in the long term, public small caps tend to outperform the High Yield index. This outperformance can be attributed to two sources of smart beta: small caps outperform large caps, and companies with publicly listed equity outperform private companies. We find that both effects account for an information ratio of about 0.4. Due to the negative correlation between these effects, the combined effect results in an information ratio of 0.7 and an outperformance of about 75bps per annum. Figure 1 summarizes the performance of public small caps relative to the index. In order to have sufficiently long data series, we use data on US High Yield only. Small (large) caps are identified as the 33% companies with smallest (largest) amount of debt outstanding. We conclude that public small caps are an attractive segment of the High Yield market. However, due to the large number of names, covering this market segment in a fundamental credit selection process would require a prohibitively large number of analysts. However, a quantitative credit selection model does not have capacity constraints. On the contrary, the larger the universe, the more stable a model s selection skills come out. Therefore, by applying Robeco s quantitative corporate bond selection model COALA to the public small cap segment of the High Yield market, we can gain access to these long-term sources of outperformance in a very efficient way. 70% 60% 50% 40% 30% 20% 10% 0% Public Small All Difference Figure 1: Outperformance of public small caps relative to High Yield index 3 These numbers apply to the Barclays Capital US + Pan-European High Yield index excluding Financials. Page 2 of 5

3 Robeco s corporate bond selection model COALA Already since 2001, Robeco uses a proprietary quantitative model as one of the tools in the selection of investment grade corporate bonds 4. In 2003, the COALA model was expanded to the High Yield universe. Two years later, the COALA model started covering the public small caps in the High Yield portfolio a role it currently still fulfills. In credit analysis, avoiding the losers is more important than picking every winner in the corporate bond space. Therefore, the COALA model focuses on selecting high-quality companies, with strong balance sheets, attractive bond valuation and strong equity performance. The model consists of three themes, Equity, Balance Sheet and Valuation, which each receive an equal weight in the model. Each of the themes consists of several equally-weighted underlying variables. We rank companies cross-sectionally on each of these variables. Equity The Equity theme measures the direction and strength of the companies stock prices. We give preference to companies with strong positive equity price trends, as this could be a signal of confidence in the companies operations. Besides, there is academic evidence of a momentum spillover from equities to corporate bonds of the same firm 5. This means that companies that delivered high equity returns in the recent past, earn high bond returns in the nearby future. Balance Sheet The Balance Sheet theme measures the strength of the companies financial condition. For example, this theme considers leverage ratios, to assess the companies ability to meet financial obligations. In general, the theme prefers companies that are carefully managed, without incurring too much debt, or engaging in risky acquisitions. After all, if a company s investments turn out successful, the bond holder does not receive a higher coupon. On the other hand, if the firm does not recoup its investments, the payments to the bond holder may be at stake. Valuation The third theme, Valuation, indicates whether the firm s bonds are attractively priced. Valuation is measured by relating the bond s risk premium, i.e. its credit spread, to the risk it should compensate for. The theme prefers bonds that offer a high spread compared to their risk. To summarize, the COALA model selects companies with a healthy financial position, in which the stock market has confidence, and whose bonds are attractively priced. Testing the model in a realistic context In order to assess whether the COALA model is able to add value in practice, we simulate under realistic assumptions how a portfolio based on the outcomes of the model would have performed historically. We follow a portfolio of 100 US High Yield bonds over the period from January 1994 to December On a monthly basis, the COALA model rankings are used to initiate buy and sell actions. When a bond in portfolio drops to the bottom 20% of the ranking, it is sold from the portfolio. The top of the ranking is used to buy new names. To take the relative illiquidity of the 4 See Hottinga, van Leeuwen, and van IJserloo, 2001, Successful Factors to Select Outperforming Corporate Bonds, The Journal of Portfolio Management, Fall See for example Gebhardt, Hvidkjaer, and Swaminathan, 2005, Stock and bond Market Interaction: Does Momentum Spill Over?, Journal of Financial Econcomics, Volume 75, Issue 3. 6 Due to the limited size of the universe the portfolio consists of 50 names until Page 3 of 5

4 High Yield market into account, we impose the following restrictive assumptions that describe situations that can be encountered in practice: each month we are unable to sell the 2 worst performing names (with 1-month forward-looking knowledge). In other words, we are obliged to keep the worst names in portfolio. each month we are unable to buy the 4 best performing names (again with 1-month forward-looking knowledge). rather than each month buying the very top-ranked names we randomly buy from the top 20% of the ranking. we impose conservative assumptions for transaction costs, making high-spread names more costly to trade 7 We find that a portfolio based on the COALA model, using the realistic backtest methodology as described above, is very well able to keep track with its benchmark 8. Compared to the gross benchmark, which does not take the costs of index turnover into account, the model portfolio even generates a small outperformance over the period from 1994 to 2009, as shown in Figure 2. If we compare the model to its net benchmark, where the costs of index turnover are deducted - and which we think provides a more fair comparison - we observe a decent outperformance of more than 140 bps per annum, with an information ratio of This outperformance can be fully attributed to the selection power of the COALA model, and does not include the public small cap smart beta effect as described above COALA vs gross benchmark Net benchmark COALA vs net benchmark Figure 2: Performance of the COALA model relative to gross and net benchmark Conclusion Robeco's corporate bond selection model has been in use for almost ten years now. The model selects companies with healthy financial statements, in which the stock market has confidence, and of which the bonds are attractively priced. Since 2005, the model has demonstrated its added value in Robeco's High Yield Bonds fund, where the model covers the small caps with publicly listed equity. Using the COALA model for this purpose offers two advantages for investors. First of all, the COALA model is able to keep track of its benchmark of public small caps, even after accounting for index turnover, transaction costs, and illiquidity. Second, by investing in public small caps, a long-term smart beta effect is captured. In other words, the COALA model offers an efficient way to capture the public small cap smart beta in High Yield. 7 This is affirmed by Barclays Capital, 2009, Liquidity Cost Scores for US Credit Bonds. 8 The benchmark is represented by the peer group of US BB and B-rated companies with publicly listed equity. Page 4 of 5

5 Important information This document has been carefully prepared by Robeco Institutional Asset Management B.V. (Robeco). It is intended to provide the reader with information on Robeco s specific capabilities, but does not constitute a recommendation to buy or sell certain securities or investment products. Any investment is always subject to risk. Investment decisions should therefore only be based on the relevant prospectus and on thorough financial, fiscal and legal advice. The content of this document is based upon sources of information believed to be reliable, but no warranty or declaration, either explicit or implicit, is given as to their accuracy or completeness. This document is not intended for distribution to or use by any person or entity in any jurisdiction or country where such distribution or use would be contrary to local law or regulation. The information contained in this document is solely intended for professional investors under the Dutch Act on the Financial Supervision (Wet financieel toezicht) or persons who are authorized to receive such information under any other applicable laws. Robeco High Yield Bonds is a subfund of Robeco Capital Growth Funds SICAV that has a license of the Supervising Authority CSSF in Luxemburg. Historical returns are provided for illustrative purposes only and do not necessarily reflect Robeco s expectations for the future. Past performances may not be representative for future results and actual returns may differ significantly from expectations expressed in this document. The value of your investments may fluctuate. Results obtained in the past are no guarantee for the future. All copyrights, patents and other property in the information contained in this document are held by Robeco Institutional Asset Management B.V. No rights whatsoever are licensed or assigned or shall otherwise pass to persons accessing this information. The information contained in this publication is not intended for users from other countries, such as US citizens and residents, where the offering of foreign financial services is not permitted, or where Robeco's services are not available. Robeco Institutional Asset Management B.V., Rotterdam (Trade Register no ) is registered with the Netherlands Authority for the Financial Markets in Amsterdam. Page 5 of 5

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