Loss Potential from Credit Derivative Use by Corporate Bond Funds under U.S. and German Regulation – A Cross Country Comparison

Gałkiewicz, Dominika P. Article Loss Potential from Credit Derivative Use by Corporate Bond Funds under U.S. and German Regulation – A Cross Country Comparison Credit and Capital Markets – Kredit und Kapital Provided in Cooperation with: Duncker & Humblot, Berlin Suggested Citation: Gałkiewicz, Dominika P. (2016) : Loss Potential from Credit Derivative Use by Corporate Bond Funds under U.S. and German Regulation – A Cross Country Comparison, Credit and Capital Markets – Kredit und Kapital, ISSN 2199-1235, Duncker & Humblot, Berlin, Vol. 49, Iss. 2, pp. 245-298, https://doi.org/10.3790/ccm.49.2.245 This Version is available at: https://hdl.handle.net/10419/293782 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Credit and Capital Markets 2 / 2016 Loss Potential from Credit Derivative Use by Corporate Bond Funds under U.S. and German Regulation– A Cross Country Comparison By Dominika P. Gałkiewicz*1 Abstract This study analyzes the loss potential arising from investments into CDS and CDS use-induced risk and performance implications for a sample of large U.S. and German mutual funds. For several funds in the U.S., the regulatory potential losses arising from selling CDS protection are almost as high as net assets, while in Germany, this potential can be even higher. As opposed to the U.S. funds, German funds face a higher risk exposure, i. e. standard deviation and idiosyncratic risk, and suffer from worse performance due to the enormous selling of credit protection during the crisis. Furthermore, additional analysis of the CDS trading activity of German funds between two consecutive reporting dates suggests that period-end data overlooks many round-trip CDS trades (purchases followed by sales or the other way around) undertaken by management. Thus, funds are able to circumvent the direct leverage restrictions, which limit bank borrowing to 10 % and 33.3 % of net assets in Germany / the EU and the U.S., respectively, by using derivatives, such as CDS, and inflate overall leverage to levels that lie above the value of net assets. Based on the results, it seems advisable that regulators in both countries monitor rules restricting the speculative use of derivatives. Keywords: Mutual funds, leverage, derivative, credit default swaps, regulation JEL-Classification: G11, G15, G23, G28 * Dr. Dominika P. Gałkiewicz, University of Applied Sciences Kufstein, International Financial Management, Accounting & Controlling, Andreas Hofer-Str. 7, 6330 Kufstein, Austria, Phone: +43 5372 71819 181, E-mail: Dominika.Galkie [email protected], and associated with Humboldt University Berlin, Institute of Corporate Finance via SFB 649 “Economic Risk”, Dorotheenstr. 1, 10117 Berlin, Germany, E-mail: [email protected]. I thank Tim Adam, Tobias Berg, Hermann Elendner, Andre Guettler, Laurenz Klipper, Urska Kosi, Patrick Lehmann, Li Ma, Richard Stehle, an anonymous referee, and the participants of the European Financial Management Association Conference 2014 (Maastricht) for their very helpful suggestions and comments. I further thank Florian Hiss for excellent research assistance. The author gratefully acknowledges financial support from the Deutsche Forschungsgemeinschaft (German Science Foundation) through SFB 649 “Economic Risk” and SFB-TR15 “Governance and the Efficiency Economic Systems”. Credit and Capital Markets, 49. Jahrgang, Heft 2, Seiten 245–298 Abhandlungen OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 246 Dominika P. Gałkiewicz Credit and Capital Markets 2 / 2016 Das Verlustpotential von Rentenfonds aufgrund ihrer Kreditderivatenutzung unter Berücksichtigung der amerikanischen und deutschen Regulierung– Eine Ländervergleichsstudie Zusammenfassung Die Studie analysiert das aus gehaltenen CDS-Positionen resultierende Verlustpotential sowie die Auswirkungen der CDS-Nutzung auf das Risiko-Rendite-Profil der größten amerikanischen und deutschen Fonds. Das regulatorische Verlustpotential aus CDS-Nutzung von U.S Fonds erreicht vereinzelt die Höhe ihres eigenen Nettofondsvermögens, während in Deutschland dieses Potential sogar höher werden kann. Im Gegensatz zu U.S. Fonds, weisen deutsche Fonds in der Finanzkrise ein höheres Risiko auf und generieren Verluste aufgrund des erhöhten Verkaufs von CDS-Absicherungen. Weitere Untersuchungen weisen zudem darauf hin, dass die zum Berichterstattungszeitpunkt ausgewiesene CDS-Nutzung deutscher Fonds einen kleineren Teil der vom Management vorgenommenen CDSTransaktionen ausmacht (insbesondere bleiben im selben Halbjahreszeitraum zwischen zwei Berichterstattungszeitpunkten Käufe von CDS-Absicherungen, die von Verkäufen dieser gefolgt werden und umgekehrt unbemerkt). Folglich können Fonds die Leverage-Regeln, die es vorsehen, dass Kreditaufnahmen in Deutschland / der EU höchsten 10 % und in den U.S.A. 33,3 % des Nettofondsvermögens betragen, umgehen, indem sie Derivate wie beispielsweise CDS nutzen. Auf diese Weise können sie ihr Gesamt-Leverage auf ein Niveau über den eigenen Nettofondswert hieven. Basierend auf den Ergebnissen dieser Studie wäre es aus Investorensicht empfehlenswert, dass die Regulierungsbehörden in beiden Ländern die Regeln betreffend die spekulative Nutzung von Derivaten verstärkt überwachen. I. Introduction Can funds default solely due to their investments in derivatives? In recent years, highly regulated market participants, including mutual funds, were heavily exposed to risk via derivatives. The majority of corporate bond funds in the U.S. that sold more credit default swaps (CDS) protection than they bought suffered severe losses compared to funds that predominantly bought CDS protection during the 2007–2009 financial crisis (Adam / Guettler (2015)). The Oppenheimer Champion Income Fund nearly collapsed in 2008 because of speculative investments into CDS and faced lawsuits concerning inadequate disclosure.1 These developments 1 See “Recovering Oppenheimer Champion Fund Losses” and “Oppenheimer Champion Income Fund Lawsuits” [http: / / www.oppenheimerfundfraud.com / id3. html, http: / / www.youhavealawyer.com / blog / 20 09 / 04 / 16 / oppenheimer-championincome-fund-lawsuits / , respectively, visited on 08.09.2012]. OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 Loss Potential from Credit Derivative Use 247 Credit and Capital Markets 2 / 2016 follow from the fact that CDS are not only used for hedging, but also for implementing risky investment strategies that potentially create either high returns or losses. For instance, whenever a fund sells protection via CDS, it effectively adds leverage to its portfolio, because it is exposed to the notional amount of the swaps beyond its total net assets. This study analyzes the CDS use by U.S. and German funds along with the associated loss potential as defined by U.S. regulation, CDS use-induced risk and performance implications during and around the time period of the 2007–2009 financial crisis. The goal of this study is to determine whether investors in both countries should worry about funds potentially taking extensive risks via derivatives. Although mutual funds are highly regulated in both countries, they can implement speculative strategies by selling CDS, which undermines the effectiveness of investor protection offered by regulation.2 From the European side, this study focuses on mutual funds distributed in Germany as they follow EU-wide regulation3 and have been allowed to use credit derivatives since 2004. In addition, mutual funds originating in Germany are obliged to list the cumulated amounts of individual securities sold within the period in annual and semi-annual reports. These data provide unique insights into fund activities within the period. On the contrary, U.S. funds only report the overall portfolio turnover rate. The purpose of this study is threefold. First, I document the level of CDS use and the regulatory potential for realizing losses via CDS for a sample of U.S. and German corporate bond funds under the regulation existing around the financial crisis. Second, the effect of CDS use on various U.S. and German funds’ risk and performance measures during and around the crisis are analyzed. Third, based on period-end and within-period data, which are only available for German funds, I investigate to which extent end-of-period CDS holdings are indicative of a fund’s investment behavior during the reporting period. 2 Managers, especially those of poorly performing funds (but not exclusively), often face strong incentives to increase the riskiness of their funds as their salary (and position) depends on the development of a fund’s assets. It is well documented that managers succeeding in fund tournaments and fund family tournaments attract more inflows from investors and support from a fund family (e. g., Brown / Harlow / Starks (1996); Chevalier / Ellison (1997); Taylor (2003); Kempf / Ruenzi (2008); Kempf / Ruenzi / Thiele (2009)). 3 German regulation is based on the UCITS Directive 85 / 611 / EEC, which also applies to public investment funds in other EU countries. OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 248 Dominika P. Gałkiewicz Credit and Capital Markets 2 / 2016 Although many rules are related to the use of derivatives, funds have a high level of flexibility when designing their investment strategies under both U.S. and German regulation: According to Galkiewicz (2014), U.S. and German funds might increase their derivative investments up to the point at which it is possible for them to default solely due to derivatives. Thus, losses generated by the Oppenheimer Champion Income Fund in 2008, which reached almost 80 % of its value, were in accordance with the existing regulatory limits on derivative use. Given the high regulatory flexibility, I analyze the CDS holdings of the 30 largest U.S. and German corporate bond funds (as determined by total net asset value (TNA) in 2004) included in the CRSP and BVI databases as they have the widest investor base.4 Annual and semi-annual U.S. filings are obtained from the SEC, while German reports are directly provided by the funds. From these reports, I collect data on the funds’ net assets as well as the direction, notional and market values of CDS. The results show that between 2004 and 2010, the use of long and short CDS positions (buying and selling CDS protection) was extensive and increased over time for funds in both countries. However, German funds, which have been allowed to use CDS only since 2004, had significantly higher and more varying CDS positions (measured by CDS notional amounts as a fraction of a fund’s TNA) than their U.S. counterparts, especially after EU regulation took full effect in Germany in 2007. As indicated by the negative CDS net notional amounts (long– short positions) at period end, both U.S. and German funds often took on more risk via CDS than they hedged. This was especially pronounced during the 2007– 2009 financial crisis where the CDS market peaked (BIS Quarterly Review (2004, 2013)). For example, the highest (unrealized) reported loss due to CDS at reporting date equaled -8.10 % (-1.63 %) of TNA for U.S. (German) funds during the crisis. This is substantial given that corporate bond funds generated returns between -2.82 % and 2.97 % during the same time period (Adam and Guettler (2015)). According to U.S. regulation, which measures the loss potential of selling CDS protection by the sum of notional amounts, potential losses reached up to 93.82 % of TNA for U.S. funds (127.04 % of TNA for German funds) during the crisis. Even if these regulatory potential losses are measured more conservatively by negative CDS net notional amounts, they still reached up to 4 I thank Lehmann / Stehle (2013) for kindly providing me with the TNA and return data for German funds. OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 Loss Potential from Credit Derivative Use 249 Credit and Capital Markets 2 / 2016 58.54 % of TNA for U.S. funds (93.19 % of TNA for German funds) during this time. As opposed to the largest U.S. funds, German funds faced a higher risk exposure and suffered from worse performance due to the enormous selling of credit protection during the crisis. The decrease in returns of German funds during the crisis is accompanied by an increase in standard deviation and idiosyncratic risk. In contrast, U.S. funds staying net short versus long in CDS face lower standard deviation. This differing result might be an outcome of regionally varying investment strategies; however, further research is needed on this topic. As indicated by Jiang / Zhu (2015), the largest U.S. bond funds were able to gain leveraged returns based on selling CDS protection (systematically betting) on institutions perceived as “too big or systemic to fail” in anticipation of the negative effect on returns during the crisis. Nevertheless, these authors also warn that the incremental returns from selling CDS protection come at the cost of a “hidden tail risk”. This is comparable with selling disaster insurance leaving these funds appearing to produce high alphas. Moreover, they show that smaller funds rather herd in taking on more risk via CDS than buying CDS protection which could lead to potential financial system instability. In their reports, German funds are obliged to list the cumulated amounts of individual securities sold within the last period (including derivatives). By analyzing within-period data for German funds, I find that the purchases and sales of CDS observable from one period-end to the other only explained a fraction (37.34 %) of the average (or 32.72 % of the median) of aggregate CDS purchases and sales implied by period-end and within-period data. Overall, the above evidence suggests that management undertakes many undetectable round-trip CDS trades (purchases followed by sales or the other way around) within a period. This is concerning given the fact that almost half of the observed cumulative amounts of CDS traded over the course of a period (either small amounts turned over frequently or large amounts turned over infrequently) were higher than a fund’s average CDS holdings as implied by period-end data. Interestingly, some funds repeatedly traded CDS in the second half of the calendar year between 2007 and 2010. However, definite conclusions about speculation require information about the portfolio holdings of funds and a wider database. My analysis reveals potential risks allowed by mutual fund regulation in the U.S. and Germany / the EU with respect to derivative transactions. OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 250 Dominika P. Gałkiewicz Credit and Capital Markets 2 / 2016 In the U.S., the conservatively measured potential for realizing losses by selling CDS protection might become almost as high as a fund’s TNA, while in Germany / the EU, it is sometimes even higher. Thus, funds face the possibility to inflate overall leverage by using derivatives, such as CDS, to levels above the value of their net assets, while existing strict direct leverage regulation limits bank borrowing to only 10 % and 33.3 % of a fund’s TNA in Germany / the EU and the U.S., respectively. Even if the size of the CDS holdings of the largest U.S. and German funds is in line with regulation, it remains unknown to which extent these holdings are used by funds for speculation. Evidence from this study shows that investors could theoretically lose their entire investment due to a fund’s exposure to CDS, if hidden tail risks suddenly materialize. This is of significant importance to regulators and investors alike. Investment strategies pursued by mutual funds should be intensively monitored by regulators and stronger regulation eventually considered. A large body of literature focuses on the measurement and sources of mutual fund performance, which goes back to Sharpe (1966) and Jensen (1968). In the last two decades, this stream of literature was extended in the U.S. by the studies of Elton / Gruber / Blake (1995), Carhart (1997), Daniel / Grinblatt / Titman / Wermers (1997), Wermers (2000), Chen / Hong / Huang / Kubik (2004), Ingersoll / Spiegel / Goetzmann / Welch (2007), Mamaysky / Spiegel / Zhang (2008), Comer / Boney / Kelly (2009), Gutierrez / Maxwell / Xu (2009), and Chen / Ferson / Peters (2010). Most prominent in Germany are the more recent studies of Kaserer / Pfau (1993), Scherer (1994), Kielkopf (1995), Steiner / Wittrock (1994), Reichling / Trautmann (1997), Griese / Kempf (2003), Stotz (2007), Lehmann / Stehle (2013), and Brückner / Lehmann / Schmidt / Stehle (2015). Most of these studies show that, on average, mutual funds underperform the market. This study adopts a market model approach of Elton / Gruber / Blake (1995) rearranged by Gutierrez / Maxwell / Xu (2009) and adjusted by Cici / Gibson (2012) for German bond funds for the first time. This study mainly relates to the emerging literature on the purpose and the extent of derivative use by mutual and hedge funds (e. g., Koski / Pontiff (1999); Johnson / Yu (2004); Almazan / Brown / Carlson / Chapman (2004); Marin / Rangel (2006); Chen (2011); Aragon / Martin (2012); Cici / Palacios (2015); Adam / Guettler (2015); Jiang / Zhu (2015); Natter / Rohleder / Schulte / Wilkens (2015)). These studies compare the performance and risk characteristics of funds using derivatives with those of nonusers. Most of the mutual fund studies find sporadic evidence that the use OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 Loss Potential from Credit Derivative Use 251 Credit and Capital Markets 2 / 2016 of derivatives affects the performance and / or the risk of the funds using them. For example, lower fund performance of derivative users compared to nonusers is reported for Canadian domestic equity funds (Johnson / Yu (2004)), for several categories of Spanish funds (Marin / Rangel (2006)), and for U.S. equity mutual funds writing put options (Cici / Palacios (2015)). In contrast, Natter / Rohleder / Schulte / Wilkens (2015) give evidence that U.S. equity funds using options mainly hedge based on protective puts and covered calls leading to superior risk-adjusted returns and lower systematic risk. The study of Adam / Guettler (2015) shows that, in general, there are no significant risk and performance differences between CDS using and non-using U.S. bond funds. Focusing on the same sample funds as Adam / Guettler (2015), Jiang / Zhu (2015) document that the largest U.S. bond funds are more likely than the smaller ones to take on “hidden tail risk” by selling CDS protection especially on “too big to fail” companies. They claim that through this channel mutual funds contributed to a higher fragility of the financial system between 2007 and 2009. A few authors ((Mahieu / Xu (2007), Minton / Stulz / Williamson (2009), Hirtle (2009) and Van Ofwegen / Verschoor / Zwinkels (2012)) have studied the use of CDS by banks. Mahieu / Xu (2007) and Minton / Stulz / Williamson (2009) presume that only a small fraction of loans are hedged by banks via CDS, while Van Ofwegen / Verschoor / Zwinkels (2012) find higher insolvency risks at European financial institutions using credit derivatives. Fung, Wen, and Zhang (2012) document that insurance companies using CDS face greater market risk and suffer from deterioration of financial performance and firm value. However, detailed information about the purpose of using derivatives is limited as empirical observations and data are not widely available. This study contributes to the above literature by providing first insights into the investment behavior of the largest German funds with regard to CDS and by documenting diverging levels of potential losses, risks and returns due to CDS use as compared to their U.S. counterparts during and around the crisis. The rest of the paper proceeds as follows. Section 2 discusses CDS related strategies. Section 3 presents the U.S. and German / EU regulation of mutual fund leverage and derivative holdings. Section 4 presents the data and section 5 analyzes the CDS use. Finally, section 6 concludes the paper. OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 252 Dominika P. Gałkiewicz Credit and Capital Markets 2 / 2016 II. CDS Related Strategies CDS are the main form of credit derivatives and can be viewed as default insurance on loans or bonds (Duffie (1999)). For protection, a buyer (seller) pays (receives) a premium until the time of the credit event, or the maturity date of the contract (whichever is first). If a defined credit event occurs, the buyer receives the insured notional amount of a bond from the seller (after subtracting the recovery value of the bond); if a triggering event does not take place, the buyer pays the premium until maturity. Due to the fact that selling CDS protection generates high implicit leverage (at low premiums), it is suitable to implement risky investment strategies, which might lead to significant losses. Funds buy and sell various types of CDS that can be classified as single-name CDS (CDS on individual corporate or sovereign bonds), and multi-name CDS (CDS indices, CDS on bond indices and asset-backed securities). As reported by Mengle (2007) a major driver of credit derivatives growth since 2004 has been the index CDS. This type of index CDS offers protection on all entities in the index in which each entity has an equal share of the notional amount. If a company included in the index defaults, the buyer of CDS protection is compensated for the loss and the CDS notional amount is reduced by the defaulting company’s pro rata share. Depending on the constellation, the following CDS strategies are classified either as hedging or investment strategies predetermined to gain additional exposure to credit risk (e. g. Adam / Guettler (2015)). In the case of bought CDS (protection buyer, long position), one can distinguish between at least four strategies: First, buying CDS on a specific underlying bond without having the underlying bond in the portfolio (naked long CDS) is probably a bet on the deterioration of the creditworthiness of a company. This strategy is speculative in nature and exposes the fund to counterparty risk. Second, buying CDS on an underlying in a portfolio is probably a way to hedge against a value loss of the bond caused by its deteriorating credit quality. Buying CDS on an underlying position that is highly correlated with a bond in the portfolio would be an additional way to hedge against a value loss of the bond, while a high volatility in bought CDS positions could imply speculative strategies. Third, simultaneously buying a bond and CDS on the respective bond can be perceived as a way to exploit temporary spread differences in the CDS market and the bond market, which are due to mispricing or differing counterparty and liquidity risks. Buying CDS at a lower spread than implied by the bond spread (CDS basis = CDS spread– bond spread) OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 Loss Potential from Credit Derivative Use 259 Credit and Capital Markets 2 / 2016 lion. As seen in Table 1 and 2, the 30 largest U.S. and German funds significantly differ in terms of size. All U.S. funds are at least four times larger than their German counterparts. This might have an effect on the size of the derivative holdings, which is expected to be higher for larger funds due to cost saving arguments (e. g. Koski / Pontiff (1999)). 2. Regulatory Loss Potential Definition Two proxies are determined to gain insight into the lowest and highest regulatory potential fund loss due to CDS (i. e., for the case that all short CDS are triggered and the recovery value of the underlying positions is equal to zero12): the notional amount from CDS short positions and the CDS net notional amount. This potential fund loss shows what a fund can lose in addition to the potential 100 % of TNA loss it can suffer from other portfolio investments, and differs from measures reflecting actually realized risk of a fund. According to U.S. regulation, the notional amount from short CDS positions (short CDS positions) reflects the potential future obligations (future undiscounted payments) a fund must cover. In the absence of long CDS, and if short CDS are used for speculation only, the potential future obligations from CDS indicate the highest possible fund losses over and above its potential losses from other portfolio securities. Additionally, CDS net notional as a common measure of potential obligations that assumes a fund’s long and short CDS positions offset each other is used. However, it should be noted that the sample funds seldom hold long and short CDS positions on exactly the same securities in terms of notional amount, coupon, and maturity to cancel existing positions. Regarding leverage regulation, long CDS reflect, in general, negative leverage because using long CDS is equivalent to shorting a bond and investing the notional value of the CDS into Treasury securities. Thus, this proxy also reflects the amount of indirect leverage a fund keeps. The size and direction of the CDS net notional allows an estimation about whether CDS were largely used for hedging (+) or for gaining exposure (-), as suggested by Adam / Guettler (2015). When construing these regulatory measures of potential fund obligations, it is implicitly assumed that all short CDS underlying positions could simultaneously fall under economic pressure 12 In reality, these potential obligations would be partially offset by any recovery values of the referenced debt obligation. However, this assumption is made following U.S. regulation. OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 260 Dominika P. Gałkiewicz Credit and Capital Markets 2 / 2016 even if they comprise CDS written on various singleand multi-name references with differing risk profiles. 3. Risk and Return Measures Additionally, the typical risk and return characteristics of the funds are evaluated for comparison with the regulatory measures. Following Adam / Guettler (2015) the sample period is split up into non-crisis periods and the financial crisis comprising 21 months between July 2007 and March 2009 following Ben-David / Franzoni / Moussawi (2012). Afterwards, risk and performance measures are determined for each fund and period, thus, finally delivering 109 and 116 observations for the German and U.S. sample, respectively. In order to investigate the influence of CDS and the crisis period on funds’ risk and return data the following measures are considered. RETURN is the cumulated monthly raw return in one period. STD is the standard deviation of monthly returns in one period. EXCESS RETURN is a period’s total return minus the return on a risk-free asset. For the U.S. sample I use the three-month T-bill rate, while for the German sample, as recommended by Brückner, Lehmann, Schmidt and Stehle (2015), the European Interbank Offered Rate (EURIBOR) is chosen. In fact, German funds do not exclusively invest in German securities and indices, thus, for generating BETA, IDIO and the ALPHA measures European indices are needed. The market model approach explained below is adopted from a model of Elton / Gruber / Blake (1995) rearranged by Gutierrez / Maxwel / Xu (2009), who excluded the macroeconomic factors. It is widely used in recent literature, e. g. by Cici / Gibson (2012) and Adam / Guettler (2015), who changed the order of the factors slightly. After modification the four factor model has the following form: rt – rf, t = α + β 1 BONDt + β 2 STKt + β 3 ABSt + β 4 DEFt + ε t,. The first part describes a market model regression: rt – rf, t = α + β 1(rm, t – rf, t) + ε t. 1ALPHA is the constant α of a market model where the market return expressed by rm is decreased by the risk-free rate rf. The bond market return rm is represented by the return of the Barclays Capital U.S. Aggregate Bond Index for the U.S. and Barclays Capital Euro Aggregate Bond Index for the German sample, respectively. BETA is the systematic risk a fund exhibits on the market in a particular period and captured by β of the market model regression above. IDIO is the idiosyncratic risk of the OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 Loss Potential from Credit Derivative Use 261 Credit and Capital Markets 2 / 2016 fund in the respective period and calculated as the standard deviation of the residual of the market model regression above. 3ALPHA is calculated by an extension of the market model by two additional risk factors: β 2 STKt + β 3 ABSt. Those factors include an equity index (STK), where the index is represented by S&P 500 for the U.S. and Eurostoxx 50 for the European market, respectively, decreased by the respective risk-free rate. The third factor (ABS) is the yield spread between Barclays US AGG MBS FHLMC 20 YR for the U.S. sample and Barclays EURO AGG Securitized ABS for the German sample and the risk-free rate. 4ALPHA is extended by one more risk factor β 4 DEFt which captures default risk and is calculated as the spread between BARCLAYS US Corp High Yield and Barclays Capital U.S. Intermediate Government / Credit Bond Index for the U.S. and BARCLAYS EURO High Yield B & Above and Barclays Capital Euro Treasury Bond Index for the German sample, respectively. V. Results First, I document the level of CDS use and the regulatory potential for realizing losses via CDS for U.S. and German corporate bond funds. Second, the effect of CDS use on various U.S. and German funds’ risk and performance measures during and around the crisis is analyzed. Third, based on period-end and within-period CDS data, which are only available for German funds, I investigate to which extent the former are representative of a fund’s investment behavior within the period. 1. U.S. and German Bond Funds’ Use of CDS and Their Potential to Realize Losses CDS were held by 19 out of the 30 sample U.S. funds in 192 half-years between the end of 2004 and 2010 and by 19 out of the 30 sample German funds in 106 half-years across the same time period as indicated by period-end data. Additionally, 13 German funds list the amount of cumulated CDS notionals sold within the period in 57 half-years in their reports. In the U.S., the number of CDS users increased from 11 in the second half of 2004 to 17 funds in the second half of 2007, and then decreased to 13 funds in 2010. Likewise, the number of CDS users in Germany increased from 1 in the second half of 2004 to 15 funds in the OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 262 Dominika P. Gałkiewicz Credit and Capital Markets 2 / 2016 second half of 2007 and first half of 2008 before it started to vary between 9 and 13 funds after 2008 (Figure 1). Funds in both countries usually held many CDS contracts, which were partly written on regional single-name corporate (and seldom sovereign) references and partly on multi-name indices such as the European iTraxx or North American CDX and asset-backed securities. As shown in Table 3 and 4, the sum of all CDS positions (long and short CDS) held by U.S. funds over the entire sample period was on average 7.84 % of TNA ($1,181 mio.), compared to 17.33 % of TNA ($175 mio.) in Germany.13 The largest CDS positions within the observation period were held by the U.S. Fidelity Short-Term Bond Fund (129.09 % of TNA or $33,778 mio.) and Deka-CorporateBond Euro (160.89 % of TNA or $592 mio.). Figure 2 shows that the total size of the CDS positions increased from an average of 2.28 % in 2004 to 4.58 % of TNA in 2010 for U.S. funds and from 1.56 % to 9.65 % for German funds during the same time period. At the beginning of 2007, after the new EU-wide regulation was fully implemented by the funds registered in Germany, CDS positions increased significantly. Especially after the initiation of CDS use, the average percentage observable for German funds was higher than for U.S. funds. Given the fact that German funds did not have prior experience using CDS, this trend is surprising. Additionally, while U.S. funds reduced their overall CDS positions after the height of the crisis in the second half of 2008, German funds continued to hold substantial CDS positions until mid-2009. Figure 3 distinguishes between long CDS (protection bought) and short CDS (protection sold) positions as related to a fund’s TNA. German funds maintained significantly larger CDS long and short positions than U.S. funds, except in the second half of 2008 where U.S. funds had larger short CDS positions. While U.S. funds started to successively reduce their CDS positions, German funds began to build significant short positions again in 2010. U.S. funds also reduced long positions after 2007 and 2008 when credit risk premia were the highest, while German funds first in13 I report the mean values of CDS for the sample of funds that used CDS, which changes over the selected time period. The mean and median values as presented in Figures 2 to 4 often differ by a large amount, which is due to outliers. Thus, some average figures overemphasize trends in general CDS use. However, for the purposes of this study, it is more important to estimate what is potentially possible under current regulation, i. e., the results obtained for the extreme cases are of large importance. The analysis of extreme cases shows the shortcomings of mutual fund regulation and a potential lack of protection for bond fund investors. OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 Loss Potential from Credit Derivative Use 263 Credit and Capital Markets 2 / 2016 creased their long CDS positions before reducing them in 2010. Figure 4 graphs the CDS net positions (long – short) over time, measuring the fund’s net exposure to credit risk compared to the credit risk premium (measured by the yield difference between BBB-rated debt and Treasury securities). The CDS net positions for both countries were persistently negative, with the exception of German funds in the second half of 2009. Overall, there were no significant differences between the average net strategies pursued by funds in both countries (Table 5) that stayed net short until the end of 2008 when the credit risk premium rose significantly. Hence, in the worst case scenario, if funds used short CDS as a speculative tool (and not for synthesizing bonds) during the financial crisis, this strategy could have led to substantial losses due to the large increase in credit risk premia during this time (see Figure 4). The above results are in line with those of Adam / Guettler (2015) who find that U.S. bond funds are net sellers of CDS, implying that managers, on average, do not use CDS to hedge credit risk. In fact, one cannot determine the effect changes in CDS use have on a fund’s risk and return profile without taking into account parallel changes in asset allocation or changes in the overall investment strategy of a fund.14 However, the market (fair) value of CDS (unrealized depreciation / appreciation) shows how much a fund’s TNA was negatively / positively affected by CDS contracts at a specific reporting date. This accounting value is more than ten times smaller than the CDS notional amount. As shown in Table 4, the average unrealized value for U.S. funds equaled–0.25 % of TNA with the highest value of–8.10 % of TNA observable in the second half of 2008. The values are lower for German funds: The average unrealized value equaled–0.10 % of TNA with the highest value of–1.63 % of TNA observable in the first half of 2009. Given the average return of 0.54 % for U.S. corporate bond funds between 2004 and 2010 (Adam / Guettler (2015)), the highest and average unrealized losses in fund value due to CDS observable at reporting date were substantial for both countries. 14 Recent research provides evidence that sold CDS are mostly perceived as a risk increasing tool: For example, Van Ofwegen / Verschoor / Zwinkels (2012) give evidence that banks sell CDS to increase their risk exposure, while Fung, Wen, and Zhang (2012) find that these insurance companies which use CDS face greater market risk and suffer from inferior financial performance leading to lower firm value. OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 264 Dominika P. Gałkiewicz Credit and Capital Markets 2 / 2016 Although definite conclusions about speculation require access to the portfolio holdings of funds, the current data on CDS allow the analysis of the regulatory potential for realizing losses via CDS beyond the potential 100 % of TNA loss the fund can suffer from other portfolio investments. As Table 4 shows, the mean (median) short CDS positions of U.S. funds equaled 5.47 % (2.03 %) of TNA for the entire sample period with a peak of 15.14 % observable in the second half of 2008 (Figure 3). As shown in Table 6, the largest short CDS positions of the top30us funds no. 14 and 24 reached 93.82 % and 61.66 % of TNA, respectively, indicating that if CDS were used for speculative purposes only (not for synthesizing bonds in combination with Treasury securities), potential additional losses from short CDS exposure could have been as high as 93.82 % and 61.66 % of TNA for these two funds. However, the majority of U.S. funds held moderate short CDS positions that did not exceed 15 % of their TNA and did not lead to negative net CDS positions higher than 15 % of their TNA. For U.S. funds, the mean (median) CDS net notional equaled –3.10 % (–1.32 %) of TNA for the entire sample period (Table 4). It peaked at –9.89 % in the second half of 2008 and was persistently negative, which indicates that U.S. funds took on more risk than they hedged (see Figure 4). For two funds (top30us no. 14 and 24) the negative net notional (and indirect leverage) reached a value of 58.54 % and 54.46 % (Table 6), respectively, indicating that, if used for speculative purposes only, these CDS could cause losses as high as 58.54 % and 54.46 % of TNA. However, U.S. funds are generally required by law to be diversified with regard to security issuers (SEC Concept Release on Derivatives (2011)). The portfolio holdings of these funds were highly diversified; one of them included “diversified” into its name to attract investors with this feature. Therefore, it might have been beneficial for them to use many short CDS for synthesizing bonds or indices. Indeed, discussions with practitioners confirm that many funds kept higher cash positions in their portfolios during the crisis (especially those facing higher outflows) and used short CDS to increase their exposure to individual names and the broader market. In fact, Oehmke / Zawadowski (2014) predict and Jiang / Zhu (2015) confirm that U.S. bond funds facing higher trading needs due to more volatile fund flows, rather tend to enter into short CDS positions, if the latter are liquid relative to the underlying bonds, than to buy the underlying bonds. As shown in Table 4, the mean (median) short CDS positions of German funds equaled 10.91 % (5.09 %) of TNA for the entire sample period with a peak of 20.95 % observable in the first half of 2008 (Figure 3). As OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 Loss Potential from Credit Derivative Use 265 Credit and Capital Markets 2 / 2016 opposed to U.S. funds, several other German funds presented in Table 7 (top30de no. 1, 8, 12, and 14) sometimes kept a relatively high amount of short CDS, ca. 40 % of TNA, which led to negative net positions in CDS (and indirect leverage) of around 30 % of TNA at reporting date. Again, since these funds are generally required by law to be highly diversified (CESR Guidelines (2010)), it might have been beneficial for them to synthesize bonds or indices via short CDS. However, if CDS were used only for speculative purposes, a German fund’s loss from short CDS exposure in the first half of 2008 could have been up to 127.04 % of TNA (top30de fund no. 30) – 1.35 times higher than for an individual U.S. fund. For German funds, the mean (median) CDS net notional equaled –4.48 % (–1.46 %) of TNA for the entire sample period (Table 4). It ranged from 21.22 % to –93.19 % of TNA with the largest negative net notional (top30de fund no. 30) and loss potential being 1.6 times higher than for an individual U.S. fund (Figure 4). Figure 5 and 6 compare the Deka-CorporateBond Euro Fund’s (top 30de fund no. 30) and the Putnam Diversified Income Trust’s (top30us fund no. 14) CDS long and short positions together with their half-year returns between 2004 and 2010. These funds used large amounts of short CDS (127.04 % and 93.82 % of TNA, respectively) in the middle of the crisis and decreased the amounts shortly afterwards to less than 5 % of TNA once performance recovered. Although the potential levels of indirect leverage of 93.19 % and 58.54 % of TNA, respectively, created this way were in line with existing regulation, one can only speculate why these funds used such high levels of CDS. From a credit market timing perspective, increasing short CDS positions until the middle (Deka-CorporateBond Euro) and the end (Putnam Diversified Income Trust) of the crisis such that they surpassed multiple times the size of long CDS at times when the level of credit risk premia was increasing (Table 4), possibly led to losses (Adam / Guettler (2015)). A large part of the short CDS could have been used to increase the riskiness of the fund and its potential to gain or lose above the usual level as well. Consistent with Rajan (2006), Jiang / Zhu (2015) show that the largest U.S. bond funds are rather prone to take on “hidden tail risk” by selling CDS contracts than their smaller counterparts. Hence, both German and U.S. funds operating in an environment of unpredictable liquidity needs might have sold CDS protection to synthesize regular bonds and to add risk. Overall, funds are able to circumvent direct leverage restrictions, which limit bank borrowing to 10 % and 33.3 % of TNA in Germany / the EU and the U.S., respectively. The above findings show that the potential reOPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 266 Dominika P. Gałkiewicz Credit and Capital Markets 2 / 2016 alizable losses from CDS conservatively measured following U.S. regulation could be higher than a fund’s net assets in Germany, while in the U.S., they might be almost as high as a fund’s TNA. The case of the Oppenheimer Champion Income Fund, which lost 80 % of TNA largely due to derivative use, shows that potential losses from derivatives can materialize. Analyzing the funds’ risk and return beyond regulatory loss potential measures might shed new light on the above issues. 2. CDS Use and Its Effect on the Performance and Risk of U.S. and German Funds Table 8 shows the descriptive statistics of all risk and performance measures of German and U.S. funds between 2004 and 2010. The average return of German funds is positive and higher than that of U.S. funds for the whole observation period. For German funds (U.S. funds), the average 1ALPHA, 3ALPHA and 4ALPHA (1ALPHA and 3ALPHA) measures are negative, indicating that, on average, these funds underperform the market during this time period. In Table 9 the average risk and performance measures are reported separately for the crisis and non-crisis periods. As shown by 1ALPHA (3ALPHA), German funds (U.S. funds) perform slightly better than the market during non-crisis periods, but the result is not robust based on the other performance measures. In general, during the financial crisis the standard deviation increases and return measures turn negative for both sample funds. The average beta decreases significantly during the crisis, i. e. sample funds face less exposure to systematic risk, while the average idiosyncratic risk is higher than in non-crisis periods. However, the economic impact of the crisis on German funds is not as severe as on U.S. funds. The aforementioned trends can be also observed for median risk and return data except that idiosyncratic risk decreases in the crisis period and the return measures remain on a high positive level. This is consistent with median sample funds having been most successful in the past. Panel A and B of Table 10 present OLS regressions of German and U.S. risk and performance measures on CDS use and interaction of CDS use and Crisis period dummies, respectively. CDS use does not seem to influence the performance and riskiness of the 30 largest U.S. funds, while for German funds some negative effect on various return measures can be identified during the crisis. However, U.S. funds’ risk and return measures are negatively affected by the crisis– an effect that is in line with OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 Loss Potential from Credit Derivative Use 267 Credit and Capital Markets 2 / 2016 the former findings of Adam / Guettler (2015). The results further show higher return volatility as well as idiosyncratic risk for both German and U.S. funds during the crisis. As seen in Table 11, staying net short as opposed to net long during the crisis only affects the returns of German funds negatively, i. e. decreases them on average by –19 % (at a 10 % significance level). The decrease in returns during the crisis is accompanied by an increase in standard deviation and idiosyncratic risk. This is in line with funds entering into short CDS to earn the premium on sold insurance in order to, for example, hide their bad performance around the crisis. However, because of rising credit risk premia, the unrealized loss from short CDS at that time would possibly negatively affect the value of a fund’s net assets during the crisis. In contrast, U.S. funds staying net short in CDS versus long face lower standard deviation. As indicated by Jiang / Zhu (2015), the largest U.S. bond funds were able to gain leveraged returns based on selling CDS protection (systematically betting) on institutions perceived as “too big or systemic to fail” in anticipation of the negative effect on returns during the crisis. Nevertheless, these authors also warn that the incremental returns from selling CDS protection come at the cost of a “hidden tail risk”. This is comparable with selling disaster insurance leaving these funds appearing to produce high alphas. Moreover, they show that smaller funds rather herd in taking on more risk via CDS than buying CDS protection which could lead to potential instability of the financial system. Even though both German and U.S. funds stay net short during the crisis, on average, where the risk of default is higher, only German funds suffer from decreased returns due to CDS use during this time. As the pattern identified for German funds is different, the investment strategies and motives for entering into CDS might be regionally diverging as compared to U.S. funds. Based on the above empirical results, one can see that stronger restrictions on the use of CDS would not affect the majority of mutual funds, but could benefit the mutual fund industry as a whole by preventing potentially high losses due to outliers. Further research should shed light on the within-country variations and relate them to cross-country variations. The trends in CDS use by the 30 largest U.S. funds are in line with the findings of Adam / Guettler (2015). I contribute to the derivative literature by providing first evidence for the extent of CDS use by German corporate bond funds and its diverging effects on the regulatory loss potential, various risk and performance measures as compared to their U.S. counterparts. OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 268 Dominika P. Gałkiewicz Credit and Capital Markets 2 / 2016 3. Representativeness of CDS Holdings of German Funds Reported at Period End One of the main disadvantages of using semi-annual CDS holdings data is that round-trip trades occurring within half of a year (i. e., the purchase and sale of CDS– or the other way around– that takes place between two consecutive reporting dates) are missed. However, gains and losses generated by CDS holdings within the reporting period could have already affected the fund’s TNA via the realized gains and losses position. In this case, German data, which specify the level of fund activity within the reporting period, provide additional insights compared to U.S. data. The German reports comprise an initial and second schedule of portfolio holdings; the second schedule shows all transactions closed within the reporting period, including the cumulated CDS sales (reflected by the sum of long and short CDS notional).15 Analyzing how active funds are in trading CDS within a half-year helps gaining insights into the extent end-of-period CDS holdings are indicative of a fund’s investment behavior within the period. In order to approximate CDS turnover by the number of missed trades, the focus lies on a subsample of 13 German funds that report cumulated within-period sales of CDS in 57 periods. The aggregate sales of CDS capture the decrease in CDS holdings between the past and present reporting dates (i. e., sales of CDS) and within-period CDS trades in which purchases are followed by sales. However, one erroneous observation is deleted. Thus, for the final sample consisting of 56 observations, I define a variable showing missing trades, because turnover ratio data are not available for German funds. Figure 1 shows that the number of German funds reporting within-period CDS increased from 1 in 2005 to 8 at the end of 2007 before it started to vary between 5 and 8 funds afterwards. This corresponds to the development of the number of funds reporting the use of CDS at period-end, suggesting that some funds repeatedly used CDS in the second half of the calendar year. The variable missing trades is expressed in percentage of aggregate CDS by subtracting the period-end difference in CDS notional (the absolute value) from either the aggregate sales or purchases (whichever value is higher) and dividing the entire expression by the respective aggregate 15 Funds originating in other EU countries, such as Luxemburg, are not all required by law to list derivatives in this schedule. OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 Loss Potential from Credit Derivative Use 275 Credit and Capital Markets 2 / 2016 – 0,15 –0,1 – 0,05 0 0,05 0,1 Dec 2004 Jun 2005 Dec 2005 Jun 2006 Dec 2006 Jun 2007 Dec 2007 Jun 2008 Dec 2008 Jun 2009 Dec 2009 Jun 2010 Dec 2010 German funds US funds Credit risk premiu m German funds (md) US funds (md) Figure 4: The Development of the Net CDS Positions of U.S. and German Corporate Bond Funds and the Credit Risk Premium This figure presents the development of the average CDS net notional positions (long CDS– short CDS) as a fraction (frac.) of a fund’s TNA for U.S. and German CDS users and the level of the general credit risk premium represented by BBB yield– Treasury yield between 2004 and 2010 at a particular period end. The respective median (md) positions are represented by dotted lines. OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 276 Dominika P. Gałkiewicz Credit and Capital Markets 2 / 2016 –1 ,4 –1 ,2 –1 –0 ,8 –0 ,6 –0 ,4 – 0,2 0 0,2 0,4 0,6 Dec 2004 Jun 2005 Dec 2005 Jun 2006 Dec 2006 Jun 2007 Dec 2007 Jun 2008 Dec 2008 Jun 2009 Dec 2009 Jun 2010 Dec 2010 Long CDS Short CDS Half-year retur n Figure 5: The Development of Long and Short CDS Positions and Half-Year Returns of Deka-CorporateBond Euro (Top30de Fund No. 30) This figure shows the development of the Deka-CorporateBond Euro fund’s CDS long and short positions at a particular period end together with its halfyear returns between 2004 and 2010. CDS notional amounts are normalized by the fund’s total net assets. OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 Loss Potential from Credit Derivative Use 277 Credit and Capital Markets 2 / 2016 –1 ,2 –1 –0 ,8 –0 ,6 –0 ,4 –0 ,2 0 0,2 0,4 0,6 Dec 2004 Jun 2005 Dec 2005 Jun 2006 Dec 2006 Jun 2007 Dec 2007 Jun 2008 Dec 2008 Jun 2009 Dec 2009 Jun 2010 Dec 2010 Long CDS Short CDS Half-year retur n Figure 6: The Development of Long and Short CDS Positions and Half-Year Returns of Putnam Diversified Income Trust (Top30us Fund No. 14) This figure shows the development of the Putnam Diversified Income Trust’s CDS long and short positions at a particular period end together with its halfyear returns between 2004 and 2010. CDS notional amounts are normalized by the fund’s total net assets. OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 278 Dominika P. Gałkiewicz Credit and Capital Markets 2 / 2016 0 0 ,2 0 ,4 0 ,6 0 ,8 1 1,2 Dec 2004 Jun 2005 Dec 2005 Jun 2006 Dec 2006 Jun 2007 Dec 2007 Jun 2008 Dec 2008 Jun 2009 Dec 2009 Jun 2010 Dec 2010 Missing C DS trades (as a fraction of agg. CDS) Figure 7: The Development of the Median Number of Missing CDS Trades of German Funds over Time This figure shows the development of the median number of missing CDS trades as a fraction of aggregate CDS of German funds that report using CDS within period between 2004 and 2010. OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 Loss Potential from Credit Derivative Use 279 Credit and Capital Markets 2 / 2016 Table 1 The Largest U.S. Funds (top30us) as Measured by TNA on June 30, 2004 (CRSP) No. Fund family name: Fund name TNA in mio. $ 1 PIMCO Funds: Pacific Investment Management Series: Total Return Fund 73,202.1 2 Vanguard Fixed Income Securities Funds: Vanguard Short-Term Corporate Fund 17,751.5 3 Bond Fund of America, Inc 17,620.6 4 PIMCO Funds: Pacific Investment Management Series: Low Duration Fund 14,469.9 5 American High-Income Trust 8,895.6 6 Vanguard Fixed Income Securities Funds: Vanguard High-Yield Corporate Fund 8,743.3 7 Lord Abbett Bond-Debenture Fund, Inc 8,211.8 8 Pioneer High Yield Fund, Inc 7,664.5 9 Fidelity Commonwealth Trust: Fidelity Intermediate Bond Fund 6,774.7 10 PIMCO Funds: Pacific Investment Management Series: High Yield Fund 6,759.0 11 Dodge & Cox Income Fund 6,629.0 12 Oppenheimer Strategic Funds Trust: Oppenheimer Strategic Income Fund 6,181.8 13 Fidelity Fixed-Income Trust: Fidelity Investment Grade Bond Fund 5,732.3 14 Putnam Diversified Income Trust 5,533.0 15 Fidelity Fixed-Income Trust: Fidelity Short-Term Bond Fund 5,044.6 16 Intermediate Bond Fund of America 5,039.4 17 Evergreen Select Fixed Income Trust: Evergreen Core Bond Fund 4,517.3 18 Vanguard Fixed Income Securities Funds: Vanguard Long-Term Corporate Fund 4,444.0 19 Vanguard Fixed Income Securities Funds: Vanguard Intermediate-Term Corporate Fund 4,225.9 20 MainStay Funds: MainStay High Yield Corporate Bond Fund 4,225.7 21 Fidelity Summer Street Trust: Fidelity Capital & Income Fund 4,148.9 22 SEI Institutional Managed Trust: Core Fixed Income Portfolio 3,949.2 23 T Rowe Price High Yield Fund, Inc 3,897.0 24 Western Asset Funds, Inc: Western Asset Core Plus Bond Portfolio 3,431.0 25 Putnam High Yield Trust 2,938.0 26 Franklin High Income Trust: AGE High Income Fund 2,849.0 27 AXP Diversified Bond Fund, Inc 2,816.7 28 Fidelity Fixed-Income Trust: High Income Fund 2,785.9 29 Calvert Fund: Calvert Income Fund 2,776.5 30 Sanford C Bernstein Fund, Inc: Intermediate Duration Portfolio 2,691.1 OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 280 Dominika P. Gałkiewicz Credit and Capital Markets 2 / 2016 Table 2 The Largest German Funds (top30de) as Measured by TNA on December 31, 2004 (BVI) No. Fund family name: Fund name TNA in mio. $ 1 Allianz GI Lux: dit-Euro Bond Total Return 6,303.1 2 DEKA: RenditDeka 6,166.6 3 DWS: DWS Vermögensbildungsfonds R 4,521.0 4 ACTIVEST LUXEMBOURG S.A.: Activest TotalReturn 3,521.7 5 DWS: DWS Select-Rent 2,837.4 6 DIT: dit-Allianz Rentenfonds 2,707.2 7 DIT: DIT-EURO RENTENFONDS >>K<< 2,662.3 8 UIL S.A.: UniEuroKapital Corporates A 1,855.3 9 DWS S.A.: DWS Euro-Bonds (Medium) 1,817.1 10 GERLING INVESTMENT: Gerling Rendite Fonds 1,680.1 11 DekaLux-Bond 1,451.4 12 DWS S.A.: DWS Euro-Corp Bonds 1,449.5 13 DIT: dit-Allianz Mobil-Fonds 1,425.4 14 UNION S.A.: UniEuroRenta Corporates 1,263.8 15 UNION S.A.: UniPlusKapital DM (Lux) 1,254.4 16 DEKA: DekaTresor 997.2 17 Ring-Rentenfonds DWS 921.9 18 DIT-EURO RENTENFONDS 919.4 19 MEAG EuroRent 875.6 20 UIP: UniEuroRenta 873.5 21 DWS Inrenta 840.5 22 DWS Invest Euro Bonds (Short) FC 761.1 23 DWS Euro-Bonds (Short) 747.4 24 Union Investment Lux.: UniEuroKapital II 746.7 25 UIP: UniEuroRenta Absolute Return 710.5 26 WestAM: Mundo I Invest 709.7 27 MEAG ProRent 702.5 28 FRANKFURT-TRUST: Basis-Fonds I 664.0 29 DWS Euro-Bonds (Long) 596.4 30 Deka-CorporateBond Euro 591.8 OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 Loss Potential from Credit Derivative Use 281 Credit and Capital Markets 2 / 2016 Table 3: Summary Statistics This table reports summary statistics for the total net asset value (TNA), CDS notional (sum of long and short positions), long CDS notional, short CDS notional, CDS net notional (long– short positions), and the unrealized value change in mio. $ of German and U.S. funds that reported using CDS in a particular half-year between 2004 and 2010. 19 out of the 30 U.S. funds report using CDS 192 times, and 19 out of the 30 German funds report using CDS 106 times. Country Variable N mean sd min p25 p50 p75 max Germany TNA (in mio. $) 106 1,627 1,928 239 673 1,002 1,600 10,383 CDS notional (in mio. $) 106 175 230 1 42 96 230 1,383 Long CDS notional (in mio. $) 106 75 161 0 0 33 99 1,169 Short CDS notional (in mio. $) 106 100 123 0 15 59 141 562 CDS net notional (in mio. $) 106 –25 172 –458 –94 –17 23 1,079 Unrealized value change (in mio. $) 106 0 3 –8 –1 0 0 14 CDS use 106 1 0 USA TNA (in mio. $) 192 16,076 34,457 781 4,515 7,005 10,134 252,184 CDS notional (in mio. $) 192 1,181 3,657 1 62 221 668 33,778 Long CDS notional (in mio. $) 192 289 1,001 0 0 17 163 11,118 Short CDS notional (in mio. $) 192 893 2,937 0 32 156 483 31,059 CDS net notional (in mio. $) 192 –604 2,425 –28,341 –358 –88 –4 393 Unrealized value change (in mio. $) 192 –25 127 –1,172 –8 0 1 252 CDS use 192 1 0 Total TNA (in mio. $) 298 10,936 28,511 239 1,331 4,624 7,760 252,184 CDS notional (in mio. $) 298 823 2,975 1 52 149 405 33,778 Long CDS notional (in mio. $) 298 212 815 0 0 22 125 11,118 Short CDS notional (in mio. $) 298 611 2,387 0 21 102 303 31,059 CDS net notional (in mio. $) 298 –398 1,967 –28,341 –225 –38 1 1,079 Unrealized value change (in mio. $) 298 –16 102 –1,172 –3 0 0 252 CDS use 298 1 0      OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 282 Dominika P. Gałkiewicz Credit and Capital Markets 2 / 2016 Table 4: Summary Statistics This table reports summary statistics for CDS notional (sum of long and short positions), long CDS notional, short CDS notional, CDS net notional (long– short positions), and the unrealized value change as a fraction of a fund’s total net asset value (TNA) (in %) of German and U.S. funds that report using CDS in a particular half-year between 2004 and 2010. 19 out of the 30 U.S. funds report using CDS 192 times, and 19 out of the 30 German funds report using CDS 106 times. Country Variable N mean sd min p25 p50 p75 max Germany CDS notional (in % of TNA) 106 17.33 % 25.05 % 0.05 % 2.96 % 7.86 % 21.75 % 160.89 % Long CDS notional (in % of TNA) 106 6.43 % 9.12 % 0.00 % 0.00 % 1.93 % 10.37 % 41.04 % Short CDS notional (in % of TNA) 106 10.91 % 18.50 % 0.00 % 1.38 % 5.09 % 12.16 % 127.04 % CDS net notional (in % of TNA) 106 –4.48 % 14.94 % –93.19 % –7.49 % –1.46 % 2.18 % 21.22 % Unrealized value change (in % of TNA) 106 –0.10 % 0.28 % –1.63 % –0.11 % –0.03 % 0.00 % 0.50 % USA CDS notional (in % of TNA) 192 7.84 % 15.75 % 0.02 % 0.87 % 2.95 % 7.67 % 129.09 % Long CDS notional (in % of TNA) 192 2.37 % 5.65 % 0.00 % 0.00 % 0.36 % 2.18 % 37.71 % Short CDS notional (in % of TNA) 192 5.47 % 11.12 % 0.00 % 0.48 % 2.03 % 5.96 % 93.82 % CDS net notional (in % of TNA) 192 –3.10 % 7.95 % –58.54 % –3.51 % –1.32 % –0.08 % 11.92 % Unrealized value change (in % of TNA) 192 –0.25 % 0.83 % –8.10 % –0.16 % 0.00 % 0.01 % 0.68 % Total CDS notional (in % of TNA) 298 11.21 % 20.05 % 0.02 % 1.50 % 4.17 % 10.96 % 160.89 % Long CDS notional (in % of TNA) 298 3.81 % 7.33 % 0.00 % 0.00 % 0.50 % 3.60 % 41.04 % Short CDS notional (in % of TNA) 298 7.40 % 14.40 % 0.00 % 0.73 % 2.50 % 7.55 % 127.04 % CDS net notional (in % of TNA) 298 –3.59 % 10.95 % –93.19 % –4.97 % –1.40 % 0.05 % 21.22 % Unrealized value change (in % of TNA) 298 –0.19 % 0.69 % –8.10 % –0.14 % –0.01 % 0.01 % 0.68 %     OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 Loss Potential from Credit Derivative Use 283 Credit and Capital Markets 2 / 2016 Table 5 T-test for Differences in Means of CDS Holdings of U.S. and German Funds This table reports the results of the t-test for differences in means of CDS holdings of U.S. and German bond funds that report using CDS in a particular half-year between 2004 and 2010. Panel A provides results for the following variables: CDS notional (sum of long and short positions), long CDS notional, short CDS notional, CDS net notional (long– short positions), and the unrealized value change expressed in absolute dollar terms, while Panel B reports results for the same variables expressed as a fraction of a fund’s total net asset value (TNA). The last column reports p-values of Levene’s test for the equality of group variances. *, **, and *** indicate statistical significance at the 10 %, 5 %, 1 % level. Standard errors are presented in brackets. Variable German funds U.S. funds Difference (d_se) Levene’s test (p-value) Panel A: Variables in mio. $  TNA (in mio. $) 1,626.6800 16,076.2200 –14,449.5400*** (2493.7600) (0.0000) CDS notional (in mio. $) 174.6153 1,181.0810 –1,006.465*** (246.8322) (0.0000) Long CDS notional (in mio. $) 74.6085 288.5282 –213.9197*** (73.9182) (0.0003) Short CDS notional (in mio. $) 100.0068 892.5524 –792.5456*** (212.2812) (0.0000) CDS net notional (in mio. $) –25.3983 –604.0242 578.6259*** (175.8362) (0.0007) Unrealized value change (in mio. $) –0.4031 –24.5986 24.1955*** (9.1378) (0.0000) Panel B: Variables as a frac. of TNA CDS notional (as a frac. of TNA) 0.1733 0.0784 0.0950*** (0.0269) (0.0000) Long CDS notional (as a frac. of TNA) 0.0643 0.0237 0.0406*** (0.0097) (0.0000) Short CDS notional (as a frac. of TNA) 0.1091 0.0547 0.0544*** (0.0197) (0.0003) CDS net notional (as a frac. of TNA) –0.0448 –0.0310 –0.0138 (0.0156) (0.0000) Unrealized value change (as a frac. of TNA) –0.0010 –0.0024 0.0014** (0.0007) (0.0012) OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 284 Dominika P. Gałkiewicz Credit and Capital Markets 2 / 2016 Table 6 Summary Statistics for Individual Top30us Funds Listed in Table 1 This table reports summary statistics for short CDS notional and CDS net notional (long– short positions) as a fraction of a fund’s total net asset value (in %) of U.S. funds that report using CDS in a particular halfyear between 2004 and 2010. Top30us Variable N mean sd p50 p75 max 1 Short CDS (in % of TNA) 13 4.99 % 3.69 % 4.80 % 7.14 % 12.32 % 2 Short CDS (in % of TNA) 13 1.15 % 0.71 % 1.35 % 1.54 % 2.31 % 4 Short CDS (in % of TNA) 13 5.31 % 3.76 % 3.90 % 7.96 % 13.19 % 7 Short CDS (in % of TNA) 4 0.17 % 0.13 % 0.20 % 0.27 % 0.27 % 9 Short CDS (in % of TNA) 13 1.69 % 1.14 % 1.79 % 2.51 % 3.66 % 10 Short CDS (in % of TNA) 13 8.89 % 4.51 % 9.22 % 11.94 % 15.69 % 12 Short CDS (in % of TNA) 11 4.36 % 4.61 % 2.28 % 10.42 % 11.56 % 13 Short CDS (in % of TNA) 13 2.51 % 1.28 % 2.67 % 2.96 % 5.42 % 14 Short CDS (in % of TNA) 13 21.30 % 29.08 % 9.72 % 22.01 % 93.82 % 15 Short CDS (in % of TNA) 13 1.96 % 2.75 % 1.70 % 2.09 % 10.57 % 17 Short CDS (in % of TNA) 5 3.24 % 2.59 % 3.26 % 5.33 % 6.26 % 18 Short CDS (in % of TNA) 4 5.51 % 0.94 % 5.18 % 6.04 % 6.89 % 19 Short CDS (in % of TNA) 13 0.36 % 0.20 % 0.37 % 0.49 % 0.73 % 22 Short CDS (in % of TNA) 11 1.82 % 1.49 % 1.93 % 2.73 % 4.95 % 23 Short CDS (in % of TNA) 8 0.46 % 0.30 % 0.43 % 0.64 % 0.97 % 24 Short CDS (in % of TNA) 13 22.37 % 16.95 % 16.77 % 30.25 % 61.66 % 25 Short CDS (in % of TNA) 11 1.73 % 1.35 % 1.86 % 2.92 % 3.79 % 27 Short CDS (in % of TNA) 5 0.09 % 0.15 % 0.00 % 0.10 % 0.36 % 30 Short CDS (in % of TNA) 3 0.95 % 1.64 % 0.00 % 2.84 % 2.84 % Total Short CDS (in % of TNA) 192 5.47 % 11.12 % 2.03 % 5.96 % 93.82 % OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 Loss Potential from Credit Derivative Use 291 Credit and Capital Markets 2 / 2016 Table 10: Determinants of Fund Risk and Return: CDS Use This table shows in Panel A and B the OLS regression results with respect to the CDS use decision of the top 30 German and U.S. funds, respectively. Refer to Table 1 and 2 for the U.S. and German sample selection process, respectively. The dependent variables are the risk and performance measures as defined in Table 8 and section 4.2. Crisis equals 1 for the crisis period (2007M07–2009M03) and 0 otherwise. CDS equals 1 if fund i used CDS in halfyear t and 0 otherwise. The control variables include fund size (TNA), total expense ratio (TER), fund age and fund flows (not reported). All regressions contain fund fixed effects (FE). *, **, and *** indicate significance at the 10 %, 5 %, and 1 % level, respectively. Standard errors are clustered at the fund level and are reported in parentheses. Country Variable RETURN EXCESS RET. STD BETA IDIO 1ALPHA 3ALPHA 4ALPHA Panel A crisis –0.0040 –0.0446 0.0017** –0.0942** 0.0024*** –0.0024 –0.0003 0.0002 Germany (0.0329) (0.0312) (0.0007) (0.0406) (0.0007) (0.0015) (0.0016) (0.0012) CDS use 0.0644** 0.0580* –0.0005 0.0485 –0.0012 0.0026** 0.0027* 0.0020 (0.0311) (0.0329) (0.0007) (0.0597) (0.0008) (0.0011) (0.0014) (0.0012) CDS * crisis –0.0925* –0.0840* 0.0010 –0.0923 0.0016 –0.0040* –0.0050** –0.0055*** (0.0456) (0.0434) (0.0010) (0.0855) (0.0012) (0.0022) (0.0022) (0.0017) Control var. Yes Yes Yes Yes Yes Yes Yes Yes Fund FE Yes Yes Yes Yes Yes Yes Yes Yes Adj. R square 0.2000 0.3132 0.6037 0.1630 0.5524 0.3473 0.3041 0.3712 N 109 109 109 109 109 109 109 109 Panel B crisis –0.0817*** –0.0805*** 0.0046*** –0.0666 0.0048*** –0.0032** –0.0015 0.0108*** USA (0.0263) (0.0250) (0.0014) (0.0772) (0.0014) (0.0013) (0.0015) (0.0020) CDS use 0.0841 0.0704 –0.0011 0.0837 –0.0008 0.0027 0.0036 0.0069* (0.0629) (0.0678) (0.0019) (0.1140) (0.0018) (0.0036) (0.0040) (0.0041) CDS * crisis –0.0039 –0.0052 –0.0020 0.0883 –0.0023 –0.0011 –0.0017 –0.0102* (0.0488) (0.0474) (0.0022) (0.1072) (0.0022) (0.0023) (0.0027) (0.0060) Control var. Yes Yes Yes Yes Yes Yes Yes Yes Fund FE Yes Yes Yes Yes Yes Yes Yes Yes Adj. R square 0.6467 0.6317 0.2235 0.0227 0.2218 0.6001 0.5039 0.1423 N 116 116 116 116 116 116 116 116 OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 292 Dominika P. Gałkiewicz Credit and Capital Markets 2 / 2016 Table 11: Determinants of Fund Risk and Return: Net Short CDS Use This table shows in Panel A and B the OLS regression results with respect to the net short CDS use of the top 30 German and U.S. funds, respectively. Refer to Table 1 and 2 for the U.S. and German sample selection process, respectively. The dependent variables are the risk-performance measures as defined in Table 8 and section 4.2. Crisis equals 1 for the crisis period (2007M07–2009M03) and 0 otherwise. For funds which used CDS in a particular period, CDS net short equals 1 if fund i stayed net short in CDS in halfyear t and 0 otherwise. The control variables include fund size (TNA), total expense ratio (TER), fund age and fund flows (not reported). All regressions contain fund fixed effects (FE). *, **, and *** indicate significance at the 10 %, 5 %, and 1 % level, respectively. Standard errors are clustered at the fund level and are reported in parentheses. Country Variable RETURN EXCESS RET. STD BETA IDIO 1ALPHA 3ALPHA 4ALPHA Panel A Germany crisis 0.0707 0.0342 0.0020* 0.1453 0.0022 0.0016 0.0017 –0.0011 (0.0742) (0.0752) (0.0010) (0.1844) (0.0018) (0.0031) (0.0029) (0.0026) net short CDS –0.0812 –0.0827 –0.0018* –0.1049 –0.0011 –0.0023 –0.0025 –0.0021 (0.0679) (0.0716) (0.0009) (0.0713) (0.0013) (0.0022) (0.0030) (0.0020) net short CDS * crisis –0.1907* –0.1846* 0.0022* –0.3488 0.0035* –0.0094* –0.0084** –0.0049 (0.1059) (0.1035) (0.0011) (0.2182) (0.0018) (0.0047) (0.0039) (0.0034) Control var. Yes Yes Yes Yes Yes Yes Yes Yes Fund FE Yes Yes Yes Yes Yes Yes Yes Yes Adj. R square 0.5023 0.6236 0.6451 0.4065 0.6203 0.5570 0.5711 0.6957 N 40 40 40 40 40 40 40 40 Panel B USA crisis –0.1272 –0.1541 0.0005 0.3878 –0.0003 –0.0085*** –0.0083** 0.0035 (0.0987) (0.1097) (0.0017) (0.2666) (0.0018) (0.0026) (0.0031) (0.0063) net short CDS 0.1405 0.1231 –0.0062* 0.0774 –0.0060 0.0059 0.0032 –0.0043 (0.1139) (0.1164) (0.0034) (0.1121) (0.0036) (0.0058) (0.0060) (0.0072) net short CDS * crisis 0.0381 0.0727 0.0030 –0.3590 0.0040* 0.0042 0.0047 –0.0040 (0.1274) (0.1369) (0.0022) (0.3127) (0.0023) (0.0044) (0.0046) (0.0103) Control var. Yes Yes Yes Yes Yes Yes Yes Yes Fund FE Yes Yes Yes Yes Yes Yes Yes Yes Adj. R square 0.7281 0.7196 0.2151 0.1532 0.1974 0.7088 0.6014 0.0721 N 64 64 64 64 64 64 64 64 OPEN ACCESS | Licensed under CC BY 4.0 | https://creativecommons.org/about/cclicenses/ DOI https://doi.org/10.3790/ccm.49.2.245 | Generated on 2023-01-16 13:25:37 Loss Potential from Credit Derivative Use 293 Credit and Capital Markets 2 / 2016 Table 12 Summary Statistics for Aggregate CDS and Missed Trades of German Funds from Period-end and Within-period CDS Data This table reports summary statistics for the differences in CDS notional implied by period-end data, aggregate purchases and sales of CDS, and missed trades implied by period-end and within-period CDS data of German bond funds. The variable period-end difference in CDS notional (in mio. $) shows the difference in CDS holdings between present and past reporting dates. The aggregate sales CDS notional (in mio. $) reflects the aggregate within-period CDS sales reported by funds, while the aggregate purchases CDS notional (in mio. $) presents the aggregate purchases of CDS determined as the sum of the respective period-end difference in CDS notional and aggregate sales CDS notional. The missing trades (as a fraction of aggregate CDS) show the fraction of the higher of aggregate sales or purchases of CDS not explained by the pe riod-end difference in CDS notional. Germany Variable N mean sd min p25 p50 p75 max Period-end difference in CDS notional (in mio. $) 56 23.5408 183.5515 –577.5111 –20.1476 7.7089 91.4164 818.1523 Aggregate purchases CDS notional (in mio. $) 56 705.1489 1,593.5419 0.5392 43.4869 162.6237 519.4897 8,151.6802 Aggregate CDS sales notional (in mio. $) 56 681.6081 1,585.1466 3.9510 26.5422 115.6641 501.2390 8,186.6416 Missed trades (as a frac. of agg. 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