Journal of Fixed Income最新文献

{"title":"Valuation of Callable/Putable Corporate Bonds in a One-Factor Lognormal Interest-Rate Model","authors":"R. Goldberg, Ehud I. Ronn, Liying Xu","doi":"10.2139/ssrn.3647507","DOIUrl":"https://doi.org/10.2139/ssrn.3647507","url":null,"abstract":"Whereas the callable-bond market used to emphasize primarily public debt—government agencies and investment grade and non-investment grade corporate debt—that has changed dramatically over the past 20 years, in part due to the low prevailing rates of interest as well as some systematic changes in the agency sector. While some agency and investment grade corporate bonds are still extant, there are more numerous callable bonds of lower ratings categories. In delivering a theoretically sound practical model, one that does not call for computation or use of an option-adjusted spread, the article seeks to use a one-factor lognormal interest rate model to calibrate the implied vols of callable and putable bonds in the US bond market and to relate those implied volatilities to measures of time to call, time from call to maturity, moneyness, and the credit-yield spread. TOPICS: Fixed income and structured finance, derivatives, options, quantitative methods, statistical methods Key Findings ▪ Valuation of callable and putable bonds in a theoretically sound practical model that does not use “option-adjusted spreads.” ▪ A one-factor lognormal interest-rate model is used to calibrate implied vols of callable and putable bonds in the US corporate and agency bond markets. ▪ Volatility calibration uses observed bonds’ market prices to elicit dependence of priced volatility on time to first call, time from call to maturity, moneyness, and the credit-yield spread.","PeriodicalId":53711,"journal":{"name":"Journal of Fixed Income","volume":"31 1","pages":"80 - 95"},"PeriodicalIF":0.0,"publicationDate":"2020-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49401130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pricing Death Bonds: Fair Value Measurement in the Life Settlement Market","authors":"Alexander Braun, Jiahua Xu","doi":"10.3905/6285","DOIUrl":"https://doi.org/10.3905/6285","url":null,"abstract":"IFRS (International Financial Reporting Standards) 13 and the AIFMD (Alternative Investment Fund Managers Directive) require assets to be held at fair value. Life settlement prices are commonly determined by present value calculus. Yet, the asset class lacks an established approach for the determination of adequate discount rates. We estimate historical yield spreads used for pricing based on 2,863 transactions that occurred between 2011 and 2016. We then explain their cross section through hedonic regression methodology. Out-of-sample results indicate that market-consistent life settlement prices can be conclusively predicted using discount rates from our model.","PeriodicalId":53711,"journal":{"name":"Journal of Fixed Income","volume":"55 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78820835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Student Loan Asset-Backed Securities: The Next Market in Crisis?","authors":"X. Xu, Miki Ortiz-Eggenberg","doi":"10.3905/jfi.2020.1.096","DOIUrl":"https://doi.org/10.3905/jfi.2020.1.096","url":null,"abstract":"Recent media reports highlight the looming student debt crisis, with its link to the student loan asset-backed securities (SLABS) market, as the potential catalyst for the next financial crisis. Contrary to these reports, the authors show that tighter underwriting standards, stronger internal credit enhancement, and stricter credit ratings during the last decade have reduced the credit and liquidity risk exposures of SLABS, and the yield spread has rationally reflected the degree of credit enhancements in private SLABS and the risk of “technical” defaults in public SLABS. However, as public policy debates on student loans come under the spotlight, investors should still be vigilant of the potential impact of any policy actions that could increase the systemic risk of the SLABS market. TOPICS: Asset-backed securities (ABS), financial crises and financial market history Key Findings • Despite the looming student loan crisis, credit and liquidity risks of student loan asset-backed securities (SLABS) have been well contained and rationally reflected in the yield spread. • The SLABS market’s strong credit enhancement, small market size, and low return comovement with stocks and bonds do not justify the fear that the SLABS market will be the catalyst for the next major financial crisis. • Investors should still monitor the ongoing public debate and policy propositions of student loans, which could potentially change the landscape of student loans and indirectly affect the systemic risk of SLABS.","PeriodicalId":53711,"journal":{"name":"Journal of Fixed Income","volume":"30 1","pages":"22 - 43"},"PeriodicalIF":0.0,"publicationDate":"2020-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41401962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Conditional Fixed Income Correlations: Skews and Straddles","authors":"Zava Aydemir","doi":"10.3905/jfi.2020.1.087","DOIUrl":"https://doi.org/10.3905/jfi.2020.1.087","url":null,"abstract":"We apply extreme value and copula theory to estimate conditional correlations of various pairs of US fixed-income assets. This framework is applied to both co-movements of fixed-income assets, and cross-movements of fixed-income assets where one, typically flight-to-quality, asset strongly outperforms and the other, typically a risky spread product, strongly underperforms. Our results show that for co-movements between risky spread products the correlation structure resembles a straddle where conditional correlations monotonically increase both with increased market stress and with increased market rallies. This finding stands in contrast to the correlation patterns found in international equity markets and hedge fund strategies for which the correlation structure has the shape of a skew with increased correlations under extreme market stress and zero correlations during risk-on episodes. We also find this skew shape in the correlations between US fixed-income assets when we estimate conditional correlations for cross-movements with a flight-to-quality asset performing strongly during periods of stress and risky spread products considerably widen. Under these conditions, conditional correlations are very negative, but monotonically fade with market recoveries to eventually become zero during risk-on episodes. TOPICS: Fixed-income portfolio management, tail risks, statistical methods Key Findings • This study presents the first analysis of extreme value and copula theory applied to correlations estimations of various pairs of fixed-income assets conditioned on market sentiment. This method is immune to small sample biases present in subsampling methods. • Our results show for co-movements between risky spread products that the correlation structure resembles a straddle, where conditional correlations monotonically increase with increasing market stress and increasing market rallies. This finding is novel and contrasts patterns observed in equity markets. • We find a skew shape in conditional correlations in fixed-income markets between flight-to-quality assets and risky spread products in cross-movements. Conditional correlations are very negative during periods of stress but monotonically fade with market recoveries.","PeriodicalId":53711,"journal":{"name":"Journal of Fixed Income","volume":"30 1","pages":"83 - 107"},"PeriodicalIF":0.0,"publicationDate":"2020-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47847474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"(Systematic) Investing in Emerging Market Debt","authors":"J. Brooks, Scott Richardson, Zhikai Xu","doi":"10.2139/ssrn.3531590","DOIUrl":"https://doi.org/10.2139/ssrn.3531590","url":null,"abstract":"The authors extend the analysis of systematic investment approaches to emerging market (EM) fixed income. They focus on hard currency bonds issued by emerging sovereign and quasi-sovereign entities. They find that systematic exposures linked to carry, defensive, momentum, and valuation themes are well compensated and lowly correlated in EM markets. A transaction-cost and liquidity aware long-only portfolio generates an information ratio above 1. They further show that an excess of benchmark returns for a broad set of EM managers is (i) largely explained by passive exposures to EM corporate credit excess returns and EM local currency returns, and (ii) has nontrivial macroeconomic exposures (growth, inflation, volatility, and liquidity). A systematic approach to EM debt may be a powerful diversifier. TOPICS: Emerging markets, currency Key Findings • We find that a systematic approach to active risk taking “works” in emerging market (EM) fixed income. Exposures linked to carry, defensive, momentum and valuation themes have been well compensated in EM markets. • We further find that an excess of benchmark returns for incumbent EM managers contains a lot of traditional beta and significant macroeconomic sensitivities. • There is potentially a large diversification benefit for a well-crafted systematic long-only portfolio of EM bonds.","PeriodicalId":53711,"journal":{"name":"Journal of Fixed Income","volume":"30 1","pages":"44 - 61"},"PeriodicalIF":0.0,"publicationDate":"2020-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47033325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biases in CDS Spreads after the CDS Big Bang","authors":"Xinjie Wang, Hongjun Yan, Z. Zhong","doi":"10.2139/ssrn.3510916","DOIUrl":"https://doi.org/10.2139/ssrn.3510916","url":null,"abstract":"The International Swaps and Derivatives Association (ISDA) credit default swap (CDS) standard model assumes a single flat hazard rate (default intensity) rather than a term structure of hazard rates. This assumption introduces biases into CDS spreads for empirical research after the CDS Big Bang. This article is the first to document the biases and provide a simple correction scheme. We quantify the biases using a large panel of CDS data for the period from April 2010 to October 2016. The correction is important for measures based on differences in CDS spreads, such as CDS-bond basis. TOPICS: Credit default swaps, credit risk management Key Findings • The flat hazard rate assumption in the International Swaps and Derivatives Association, Inc., credit default swap (CDS) standard model introduces biases into CDS spreads for empirical research after the CDS Big Bang. • We provide a simple correction scheme to address the biases. • The correction is important for measures based on differences in CDS spreads, such as CDS-bond basis.","PeriodicalId":53711,"journal":{"name":"Journal of Fixed Income","volume":"30 1","pages":"71 - 80"},"PeriodicalIF":0.0,"publicationDate":"2020-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42110712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Index Effect in the Corporate Bond Market","authors":"Friedrich-Carl Franz","doi":"10.2139/ssrn.3462393","DOIUrl":"https://doi.org/10.2139/ssrn.3462393","url":null,"abstract":"The author finds large and statistically significant abnormal returns of USD-denominated corporate bonds, which were up- or downgraded in the Bloomberg Barclays Investment Grade and High Yield Index from 2012 to 2018. Downgrades face a strong negative preannouncement drift with a subsequent reversal. For upgrades, the drift is smaller in magnitude and the reversal nonexistent. In contrast to the preannouncement drift, the reversal seems to be related to price pressure, which is caused by index-linked trading. This hypothesis is supported by an analysis of actual exchange-traded fund trading behavior with respect to credit rating changes. TOPICS: Fixed income and structured finance, exchange-traded funds and applications Key Findings • There are large and statistically significant abnormal returns of USD-denominated corporate bonds, which were up- or downgraded in the Bloomberg Barclays Investment Grade and High Yield Index from 2012 to 2018. • Downgrades face a strong negative preannouncement drift with a subsequent reversal. For upgrades, the drift is smaller in magnitude and the reversal nonexistent. • In contrast to the preannouncement drift, the reversal seems to be related to price pressure, which is caused by index-linked trading. This hypothesis is supported by an analysis of actual ETF trading behavior with respect to credit rating changes.","PeriodicalId":53711,"journal":{"name":"Journal of Fixed Income","volume":"30 1","pages":"46 - 69"},"PeriodicalIF":0.0,"publicationDate":"2020-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45720754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implied Asset Value Volatility from a New Structural Model of Credit Risk","authors":"J. Chen","doi":"10.3905/jfi.2019.1.076","DOIUrl":"https://doi.org/10.3905/jfi.2019.1.076","url":null,"abstract":"Well-known structural models of credit risk have been shown to underpredict credit spreads, and these models all assume a lognormal firm value diffusion process (FVDP). In this article, I present the formula for pricing corporate liabilities using a normal FVDP that allows negative firm value scenarios that are plausible in real life but are not considered by the lognormal FVDP. And I further show that model-implied asset value volatility from the normal FVDP, unlike those from lognormal structural models, are very close to the empirically estimated asset value volatility for investment-grade companies of different leverage ratios. The same pattern of model-implied asset volatility versus estimates of historical asset volatility is observed from both credit default swap spread and historical default-loss data. Thus, the normal model, by incorporating the economic consideration of negative firm value, is able to explain both observed level of credit spreads and historical default experience with estimates of realized asset value volatility. TOPICS: Fixed income and structured finance, fixed income portfolio management, credit risk management Key Findings • By considering the full range of firm value, the new structural model of credit risk can relate traded credit spreads to empirically estimated asset value volatility. • Thus, real-time readings of model-implied asset volatility may be used to quantify the difference between an issuer’s credit quality and its credit spreads. • The new model also demonstrates that investment-grade (IG) credit ratings correctly predicting IG companies’ expected default risk, because for IG companies their historical default rate-implied asset value volatility agrees well with estimated historical asset value volatility.","PeriodicalId":53711,"journal":{"name":"Journal of Fixed Income","volume":"29 1","pages":"38 - 52"},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44053944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sovereign Bonds in Emerging Asia: Do Investors Demand Liquidity Premium?","authors":"Rintu Anthony, Krishna Prasanna","doi":"10.3905/jfi.2019.1.079","DOIUrl":"https://doi.org/10.3905/jfi.2019.1.079","url":null,"abstract":"This study explores how liquidity premium is priced in emerging bond markets and has implications for the investors, because these markets exhibit lower liquidity levels and behave differently from the developed West. Liquidity risk epitomizes higher trading costs, lower trading speed, and higher price impact of large trades. The study investigates pricing implications of these liquidity dimensions across a wide term structure of sovereign bonds. We also identify the most prominent liquidity component that causes yield spread changes and drives investment decisions. Our study comprises nine bond classes, ranging from 3-month to 10-year bonds, across six emerging Asian markets. We observe that the liquidity risk increases along with the term to maturity of the bond. Our empirical results reveal that the price impact dimension is vital for short-term investments. The trading cost and trading frequency dimensions are priced in the medium-term and long-term bonds. It was also observed that investors consider the trading cost as a more important element than the trading frequency and price impact dimensions. TOPICS: Emerging markets, project finance, statistical methods, credit risk management Key Findings • Liquidity risk increases with the term to maturity of the bond. • Higher price impact generated by large trades is found to determine investment decisions in short-term bonds while trading cost and frequency are found important for medium- and long-term investments. • In general, investors consider trading cost as a more important element than other dimensions of liquidity while investing in emerging markets.","PeriodicalId":53711,"journal":{"name":"Journal of Fixed Income","volume":"29 1","pages":"77 - 87"},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46831554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Complete Model for Pricing CoCo Bonds","authors":"Krasimir Milanov, O. Kounchev, F. Fabozzi","doi":"10.3905/jfi.2019.1.077","DOIUrl":"https://doi.org/10.3905/jfi.2019.1.077","url":null,"abstract":"Contingent convertible (CoCo) bonds comprise a specialized market segment of the contingent capital market, an instrument that offers a valuation challenge to investment professionals. In this article, we develop new pricing models for these bonds that provide a methodology useful to both equity and fixed-income investors. We develop models in terms of the free boundary value problem where the spatial variable is the underlying stock price. These models allow the calculation of delta and gamma, as well as any kind of interest rate measure (i.e., duration and convexity) including the callability feature. Moreover, we revise the closed-form solution of a well-known model suggested for CoCo bond pricing such that it meets all practical needs. We use this explicit solution for testing the accuracy of their numerical methods. Two approaches are used based on the assumption about the dynamics of the underlying stock price. The first approach is based on the primary assumptions about the market used in the development of the Black-Scholes option pricing model; the second approach involves credit risk modeling by means of jump-to-default stock price dynamics. TOPICS: Project finance, fixed income and structured finance, derivatives, quantitative methods, credit risk management Key Findings • Two improved models for pricing contingent convertible (CoCo) bonds are developed using (1) a framework entirely based on the assumptions of the Black-Scholes option-pricing model and (2) a framework involving credit risk modeling by means of jump-to-default stock price dynamics. • The numerical models allow for not only CoCo bond pricing for a given interest rate term structure but also the calculation of delta, gamma, and any kind of duration and convexity for CoCo bonds including the callability feature. • Unlike other proposed CoCo bond pricing models that have been oriented to one investor group, the models presented in this article are useful for both equity investors and fixed income investors.","PeriodicalId":53711,"journal":{"name":"Journal of Fixed Income","volume":"29 1","pages":"53 - 67"},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41519909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}