The proposed mechanism for what we term the destabilization hypothesis is that an exogenous shock triggers large redemptions by fund investors, requiring fund managers to sell securities to raise cash, leading to further drops in security prices and increased systemic risk. Although a large body literature finds little evidence of fund-driven fire-sales in bond markets, the destabilization hypothesis has seen renewed interest among academics and policymakers in the context of bond funds. We examine the impact of shocks on US bond fund flows by sub-asset class and by type of investment vehicle. The time-series analysis we conducted shows that a risk-off shock to markets does not necessarily result in large bond fund outflows. Accordingly, we conclude that there is little evidence that bond funds are a source of systemic risk, particularly bond exchange-traded funds. We also find no evidence of a non-linear response of flows to large shocks.
{"title":"Bond Mutual Fund and Exchange-Traded Fund Flows in Stressed Markets: Empirical Evidence on the Destabilization Hypothesis","authors":"Stephen Laipply, Ananth Madhavan","doi":"10.3905/jfi.2022.1.151","DOIUrl":"https://doi.org/10.3905/jfi.2022.1.151","url":null,"abstract":"The proposed mechanism for what we term the destabilization hypothesis is that an exogenous shock triggers large redemptions by fund investors, requiring fund managers to sell securities to raise cash, leading to further drops in security prices and increased systemic risk. Although a large body literature finds little evidence of fund-driven fire-sales in bond markets, the destabilization hypothesis has seen renewed interest among academics and policymakers in the context of bond funds. We examine the impact of shocks on US bond fund flows by sub-asset class and by type of investment vehicle. The time-series analysis we conducted shows that a risk-off shock to markets does not necessarily result in large bond fund outflows. Accordingly, we conclude that there is little evidence that bond funds are a source of systemic risk, particularly bond exchange-traded funds. We also find no evidence of a non-linear response of flows to large shocks.","PeriodicalId":53711,"journal":{"name":"Journal of Fixed Income","volume":" ","pages":"6 - 19"},"PeriodicalIF":0.0,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46504262","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}
Ren‐Raw Chen, Dean Leistikow, You-Tseng Su, S. Yeh
In this article, we determine the quality option value of Ultra Treasury bond futures contracts, which allow deliverable bonds between 25 and 30 years to maturity, and compare them with the new regular Treasury bond futures, which allow deliverable bonds between 15 and 25 years to maturity. We use the arbitrage-free Ho-Lee model for the valuation. Using weekly data from March 25, 2011, until April 16, 2021, after the Ultra futures contract was introduced, we discover that (1) that quality option value is higher for the Ultra futures than the new regular futures, (2) the Ho-Lee model consistently underprices the market, and (3) the “dry spell” period predicted by Ben-Abdallah and Breton in 2017 is only partially supported.
{"title":"Ultra Treasury Bond Futures","authors":"Ren‐Raw Chen, Dean Leistikow, You-Tseng Su, S. Yeh","doi":"10.3905/jfi.2022.1.150","DOIUrl":"https://doi.org/10.3905/jfi.2022.1.150","url":null,"abstract":"In this article, we determine the quality option value of Ultra Treasury bond futures contracts, which allow deliverable bonds between 25 and 30 years to maturity, and compare them with the new regular Treasury bond futures, which allow deliverable bonds between 15 and 25 years to maturity. We use the arbitrage-free Ho-Lee model for the valuation. Using weekly data from March 25, 2011, until April 16, 2021, after the Ultra futures contract was introduced, we discover that (1) that quality option value is higher for the Ultra futures than the new regular futures, (2) the Ho-Lee model consistently underprices the market, and (3) the “dry spell” period predicted by Ben-Abdallah and Breton in 2017 is only partially supported.","PeriodicalId":53711,"journal":{"name":"Journal of Fixed Income","volume":"32 1","pages":"117 - 139"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44710784","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}
The COVID-19 pandemic has had an initial and outsized negative impact on bond exchange-traded funds (ETFs), causing concerns for financial stability. Using a large panel of US bond ETFs, we conduct a comprehensive examination of the impact of the pandemic on ETF valuation discounts. We find the change in COVID-19 deaths to be significantly related to the valuation discounts of government bond ETFs and corporate bond ETFs, with investment-grade corporate bond ETFs showing greater sensitivity. These valuation discounts reversed dramatically after the Federal Reserve announced its intentions to purchase corporate bonds and bond ETFs. Government economic policies to combat the pandemic are also negatively related to the valuation discounts of corporate bond ETFs. These findings are evidence of the efficacy of broad-based liquidity support on restoring financial stability in the bond ETF market at a time of enormously stressed market sentiment and massive pricing dislocations.
{"title":"COVID-19 Pandemic and Bond ETF Valuation Discount","authors":"Hongfei Tang, Kangzhen Xie, X. Xu","doi":"10.3905/jfi.2022.1.148","DOIUrl":"https://doi.org/10.3905/jfi.2022.1.148","url":null,"abstract":"The COVID-19 pandemic has had an initial and outsized negative impact on bond exchange-traded funds (ETFs), causing concerns for financial stability. Using a large panel of US bond ETFs, we conduct a comprehensive examination of the impact of the pandemic on ETF valuation discounts. We find the change in COVID-19 deaths to be significantly related to the valuation discounts of government bond ETFs and corporate bond ETFs, with investment-grade corporate bond ETFs showing greater sensitivity. These valuation discounts reversed dramatically after the Federal Reserve announced its intentions to purchase corporate bonds and bond ETFs. Government economic policies to combat the pandemic are also negatively related to the valuation discounts of corporate bond ETFs. These findings are evidence of the efficacy of broad-based liquidity support on restoring financial stability in the bond ETF market at a time of enormously stressed market sentiment and massive pricing dislocations.","PeriodicalId":53711,"journal":{"name":"Journal of Fixed Income","volume":"32 1","pages":"83 - 115"},"PeriodicalIF":0.0,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44679066","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}
Using structural models for credit default swaps has been difficult. Existing models all adopt shortcuts as approximations. In this article, we provide an accurate and efficient solution to the price of the credit default swap. The main result is a Theorem in section 2. In an empirical study, we show how our model can properly capture credit default swap exposure to interest rate volatility and asset volatility. Furthermore, we apply the new model to study (1) the interactions among market, credit, and interest risks; (2) the consistency with the reduced-form credit risk models; and (3) implications to capital structure arbitrage.
{"title":"An Exact Structural Model for Evaluating Credit Default Swaps: Theory and Empirical Evidence","authors":"Ren‐Raw Chen, Pei-lin Hsieh","doi":"10.3905/jfi.2022.1.149","DOIUrl":"https://doi.org/10.3905/jfi.2022.1.149","url":null,"abstract":"Using structural models for credit default swaps has been difficult. Existing models all adopt shortcuts as approximations. In this article, we provide an accurate and efficient solution to the price of the credit default swap. The main result is a Theorem in section 2. In an empirical study, we show how our model can properly capture credit default swap exposure to interest rate volatility and asset volatility. Furthermore, we apply the new model to study (1) the interactions among market, credit, and interest risks; (2) the consistency with the reduced-form credit risk models; and (3) implications to capital structure arbitrage.","PeriodicalId":53711,"journal":{"name":"Journal of Fixed Income","volume":"32 1","pages":"20 - 48"},"PeriodicalIF":0.0,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45351955","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}
We use Google internet search volumes to measure households’ pessimism about overall market-wide credit health in the economy and show that this “household default sentiment” is positively correlated with the credit default swap (CDS) spread level in the market. However, while household default sentiment might drive the cost of credit to some degree, either directly or indirectly through its effect on the stock market, we find the stock market’s opinion about the credit risk in the economy (default probabilities backed out from structural models) to be much more important in explaining credit spreads. The rather weak link between household sentiment and CDS spreads, meanwhile, is consistent with the almost complete absence of retail investors (households) in the institutional investor-dominated credit derivatives market. The results are essentially the same, whether we look at market-wide CDS indexes or single-name CDS contracts, and whether we exclude the financial crisis or not.
{"title":"Internet Searches, Household Sentiment, and Credit Spreads","authors":"H. Byström","doi":"10.3905/jfi.2022.1.146","DOIUrl":"https://doi.org/10.3905/jfi.2022.1.146","url":null,"abstract":"We use Google internet search volumes to measure households’ pessimism about overall market-wide credit health in the economy and show that this “household default sentiment” is positively correlated with the credit default swap (CDS) spread level in the market. However, while household default sentiment might drive the cost of credit to some degree, either directly or indirectly through its effect on the stock market, we find the stock market’s opinion about the credit risk in the economy (default probabilities backed out from structural models) to be much more important in explaining credit spreads. The rather weak link between household sentiment and CDS spreads, meanwhile, is consistent with the almost complete absence of retail investors (households) in the institutional investor-dominated credit derivatives market. The results are essentially the same, whether we look at market-wide CDS indexes or single-name CDS contracts, and whether we exclude the financial crisis or not.","PeriodicalId":53711,"journal":{"name":"Journal of Fixed Income","volume":"32 1","pages":"6 - 19"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41581497","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}
In this article, we extend the 1978 Breeden–Litzenberger method of extracting state prices from option prices, showing how portfolios of butterfly spreads can be combined with right and left tail spreads to nonparametrically extract discrete state prices from option prices. We derive how those state prices should be biased estimates of true, objective probabilities. For interest rate options, we show that the biases can vary predictably over time (sometimes too high, sometimes too low), as the correlation of interest rates with consumption and wealth has changed signs over time. Consumption betas and proper risk premiums on bonds and of their state prices are at times predictably positive and at times predictably negative. We apply our technique to provide a brief 20-year history of central bank intervention impacts in the US, UK, and Eurozone from 2003 to 2022. Movements in state prices are quite large in the Financial Panic of 2008–2009, as well as in the European Sovereign Debt Crisis of 2010–2013, with Brexit and the Trump elections in 2016, and with the coronavirus pandemic in 2020–2021. Tapering in 2013 and 2022 and liftoffs in rates in 2015 and 2022 were shown to strongly shift state price distributions back toward the symmetry of 2003–2007. We show that central banks dramatically impacted entire state price distributions, not just levels of rates.
{"title":"Central Bank Policy Impacts on the Distribution of State Prices for Future Interest Rates, 2003–2022","authors":"Douglas T. Breeden, R. Litzenberger","doi":"10.3905/jfi.2022.1.145","DOIUrl":"https://doi.org/10.3905/jfi.2022.1.145","url":null,"abstract":"In this article, we extend the 1978 Breeden–Litzenberger method of extracting state prices from option prices, showing how portfolios of butterfly spreads can be combined with right and left tail spreads to nonparametrically extract discrete state prices from option prices. We derive how those state prices should be biased estimates of true, objective probabilities. For interest rate options, we show that the biases can vary predictably over time (sometimes too high, sometimes too low), as the correlation of interest rates with consumption and wealth has changed signs over time. Consumption betas and proper risk premiums on bonds and of their state prices are at times predictably positive and at times predictably negative. We apply our technique to provide a brief 20-year history of central bank intervention impacts in the US, UK, and Eurozone from 2003 to 2022. Movements in state prices are quite large in the Financial Panic of 2008–2009, as well as in the European Sovereign Debt Crisis of 2010–2013, with Brexit and the Trump elections in 2016, and with the coronavirus pandemic in 2020–2021. Tapering in 2013 and 2022 and liftoffs in rates in 2015 and 2022 were shown to strongly shift state price distributions back toward the symmetry of 2003–2007. We show that central banks dramatically impacted entire state price distributions, not just levels of rates.","PeriodicalId":53711,"journal":{"name":"Journal of Fixed Income","volume":"32 1","pages":"64 - 92"},"PeriodicalIF":0.0,"publicationDate":"2022-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45154889","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}
Arik Ben Dor, Albert Desclée, L. Dynkin, Jay Hyman, Jeffrey Meli, S. Polbennikov
Quantitative techniques have long been used to measure and control risk in credit portfolios. More recently, interest has grown in a systematic approach to generating alpha in credit, with the promise of improved scalability and lower management expenses. We review several signals that seek alpha in credit, including value, equity momentum, equity short interest, and post-earnings announcement drift, and demonstrate that such strategies can effectively complement a more fundamental approach. We also show how systematic strategies can exploit index inefficiencies, such as the overselling and subsequent recovery of fallen angels. Company ratings on environmental, social, and governance issues have become central to portfolio management, and we discuss various aspects of their use: how to measure their performance, how to glean alpha signals from them, and how to most effectively constrain them. Finally, liquidity and transaction costs have always been key concerns for credit portfolio managers. We discuss how the liquidity landscape has evolved with the rise in exchange-traded funds and portfolio trading in corporate bonds. Putting it all together, we discuss portfolio construction techniques that can optimally combine signals and integrate transaction costs.
{"title":"Quantitative Management of Credit Portfolios","authors":"Arik Ben Dor, Albert Desclée, L. Dynkin, Jay Hyman, Jeffrey Meli, S. Polbennikov","doi":"10.3905/jfi.2022.1.144","DOIUrl":"https://doi.org/10.3905/jfi.2022.1.144","url":null,"abstract":"Quantitative techniques have long been used to measure and control risk in credit portfolios. More recently, interest has grown in a systematic approach to generating alpha in credit, with the promise of improved scalability and lower management expenses. We review several signals that seek alpha in credit, including value, equity momentum, equity short interest, and post-earnings announcement drift, and demonstrate that such strategies can effectively complement a more fundamental approach. We also show how systematic strategies can exploit index inefficiencies, such as the overselling and subsequent recovery of fallen angels. Company ratings on environmental, social, and governance issues have become central to portfolio management, and we discuss various aspects of their use: how to measure their performance, how to glean alpha signals from them, and how to most effectively constrain them. Finally, liquidity and transaction costs have always been key concerns for credit portfolio managers. We discuss how the liquidity landscape has evolved with the rise in exchange-traded funds and portfolio trading in corporate bonds. Putting it all together, we discuss portfolio construction techniques that can optimally combine signals and integrate transaction costs.","PeriodicalId":53711,"journal":{"name":"Journal of Fixed Income","volume":"32 1","pages":"93 - 141"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43942792","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}
This empirical performance attribution methodology provides an objective alternative to the existing practice of employing proprietary model–dependent systems with portfolio composition information. With only a time series of portfolio returns, this methodology detects multidimensional risk exposures, whether intended or unintended. The results allow for comparison of styles, risk exposures, and sources of performance across managers. Furthermore, as part of a well-designed internal investment process, this independent attribution methodology delivers a feedback mechanism for identifying systematic biases in analytical models that need correction.
{"title":"Fixed Income Performance Attribution: An Objective Methodology","authors":"Stanley J. Kon","doi":"10.3905/jfi.2022.1.143","DOIUrl":"https://doi.org/10.3905/jfi.2022.1.143","url":null,"abstract":"This empirical performance attribution methodology provides an objective alternative to the existing practice of employing proprietary model–dependent systems with portfolio composition information. With only a time series of portfolio returns, this methodology detects multidimensional risk exposures, whether intended or unintended. The results allow for comparison of styles, risk exposures, and sources of performance across managers. Furthermore, as part of a well-designed internal investment process, this independent attribution methodology delivers a feedback mechanism for identifying systematic biases in analytical models that need correction.","PeriodicalId":53711,"journal":{"name":"Journal of Fixed Income","volume":"32 1","pages":"142 - 159"},"PeriodicalIF":0.0,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45894809","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}
The inaugural issue of The Journal of Fixed Income led with an article by a junior professor at Duke University (me) who linked the slope of the yield curve—the difference between long-term and short-term yields—to future economic growth. Thirty years later, this article assess the out-of-sample performance of the yield curve indicator. Four recessions have come and gone since the original article was submitted to The Journal of Fixed Income in 1990. Each time the yield curve has inverted prior to the recession. This article also provides some additional background regarding the genesis of the idea.
《固定收益杂志》的创刊号以杜克大学(Duke University)一位年轻教授的一篇文章开头，他将收益率曲线的斜率——长期和短期收益率之差——与未来经济增长联系起来。三十年后，本文评估了收益率曲线指标的样本外表现。自1990年《固定收益杂志》(the Journal of Fixed Income)发表这篇文章以来，已经经历了四次经济衰退。每次在经济衰退之前，收益率曲线都是倒挂的。本文还提供了一些关于这个想法起源的额外背景。
{"title":"The Term Structure and World Economic Growth: A Retrospective and 30 Years of Out-of-sample Evidence","authors":"Campbell R. Harvey","doi":"10.3905/jfi.2022.1.142","DOIUrl":"https://doi.org/10.3905/jfi.2022.1.142","url":null,"abstract":"The inaugural issue of The Journal of Fixed Income led with an article by a junior professor at Duke University (me) who linked the slope of the yield curve—the difference between long-term and short-term yields—to future economic growth. Thirty years later, this article assess the out-of-sample performance of the yield curve indicator. Four recessions have come and gone since the original article was submitted to The Journal of Fixed Income in 1990. Each time the yield curve has inverted prior to the recession. This article also provides some additional background regarding the genesis of the idea.","PeriodicalId":53711,"journal":{"name":"Journal of Fixed Income","volume":"32 1","pages":"53 - 63"},"PeriodicalIF":0.0,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45123684","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}
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