The Relationship Between CDS and Bond Spreads
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The TIPS-Treasury Bond Puzzle
The TIPS-Treasury Bond Puzzle Matthias Fleckenstein, Francis A. Longstaff and Hanno Lustig The Journal of Finance, October 2014 Presented By: Rafael A. Porsani The TIPS-Treasury Bond Puzzle 1 / 55 Introduction The TIPS-Treasury Bond Puzzle 2 / 55 Introduction (1) Treasury bond and the Treasury Inflation-Protected Securities (TIPS) markets: two of the largest and most actively traded fixed-income markets in the world. Find that there is persistent mispricing on a massive scale across them. Treasury bonds are consistently overpriced relative to TIPS. Price of a Treasury bond can exceed that of an inflation-swapped TIPS issue exactly matching the cash flows of the Treasury bond by more than $20 per $100 notional amount. One of the largest examples of arbitrage ever documented. The TIPS-Treasury Bond Puzzle 3 / 55 Introduction (2) Use TIPS plus inflation swaps to create synthetic Treasury bond. Price differences between the synthetic Treasury bond and the nominal Treasury bond: arbitrage opportunities. Average size of the mispricing: 54.5 basis points, but can exceed 200 basis points for some pairs. I The average size of this mispricing is orders of magnitude larger than transaction costs. The TIPS-Treasury Bond Puzzle 4 / 55 Introduction (3) What drives the mispricing? Slow-moving capital may help explain why mispricing persists. Is TIPS-Treasury mispricing related to changes in capital available to hedge funds? Answer: Yes. Mispricing gets smaller as more capital gets to the hedge fund sector. The TIPS-Treasury Bond Puzzle 5 / 55 Introduction (4) Also find that: Correlation in arbitrage strategies: size of TIPS-Treasury arbitrage is correlated with arbitrage mispricing in other markets. -
Bond Basics: What Are Bonds?
Bond Basics: What Are Bonds? Have you ever borrowed money? Of course you have! Whether we hit our parents up for a few bucks to buy candy as children or asked the bank for a mortgage, most of us have borrowed money at some point in our lives. Just as people need money, so do companies and governments. A company needs funds to expand into new markets, while governments need money for everything from infrastructure to social programs. The problem large organizations run into is that they typically need far more money than the average bank can provide. The solution is to raise money by issuing bonds (or other debt instruments) to a public market. Thousands of investors then each lend a portion of the capital needed. Really, a bond is nothing more than a loan for which you are the lender. The organization that sells a bond is known as the issuer. You can think of a bond as an IOU given by a borrower (the issuer) to a lender (the investor). Of course, nobody would loan his or her hard-earned money for nothing. The issuer of a bond must pay the investor something extra for the privilege of using his or her money. This "extra" comes in the form of interest payments, which are made at a predetermined rate and schedule. The interest rate is often referred to as the coupon. The date on which the issuer has to repay the amount borrowed (known as face value) is called the maturity date. Bonds are known as fixed- income securities because you know the exact amount of cash you'll get back if you hold the security until maturity. -
A Collateral Theory of Endogenous Debt Maturity
Finance and Economics Discussion Series Divisions of Research & Statistics and Monetary Affairs Federal Reserve Board, Washington, D.C. A Collateral Theory of Endogenous Debt Maturity R. Matthew Darst and Ehraz Refayet 2017-057 Please cite this paper as: Darst, R. Matthew, and Ehraz Refayet (2017). \A Collateral Theory of Endogenous Debt Maturity," Finance and Economics Discussion Series 2017-057. Washington: Board of Gov- ernors of the Federal Reserve System, https://doi.org/10.17016/FEDS.2017.057. NOTE: Staff working papers in the Finance and Economics Discussion Series (FEDS) are preliminary materials circulated to stimulate discussion and critical comment. The analysis and conclusions set forth are those of the authors and do not indicate concurrence by other members of the research staff or the Board of Governors. References in publications to the Finance and Economics Discussion Series (other than acknowledgement) should be cleared with the author(s) to protect the tentative character of these papers. A Collateral Theory of Endogenous Debt Maturity∗ R. Matthew Darsty Ehraz Refayetz May 16, 2017 Abstract This paper studies optimal debt maturity when firms cannot issue state contingent claims and must back promises with collateral. We establish a trade- off between long-term borrowing costs and short-term rollover costs. Issuing both long- and short-term debt balances financing costs because different debt maturities allow firms to cater risky promises across time to investors most willing to hold risk. Contrary to existing theories predicated on information frictions or liquidity risk, we show that collateral is sufficient to explain the joint issuance of different types of debt: safe “money-like” debt, risky short- and long- term debt. -
The Valuation of Credit Default Swap with Counterparty Risk and Collateralization Tim Xiao
The Valuation of Credit Default Swap with Counterparty Risk and Collateralization Tim Xiao To cite this version: Tim Xiao. The Valuation of Credit Default Swap with Counterparty Risk and Collateralization. 2019. hal-02174170 HAL Id: hal-02174170 https://hal.archives-ouvertes.fr/hal-02174170 Preprint submitted on 5 Jul 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. The Valuation of Credit Default Swap with Counterparty Risk and Collateralization Tim Xiao1 ABSTRACT This article presents a new model for valuing a credit default swap (CDS) contract that is affected by multiple credit risks of the buyer, seller and reference entity. We show that default dependency has a significant impact on asset pricing. In fact, correlated default risk is one of the most pervasive threats in financial markets. We also show that a fully collateralized CDS is not equivalent to a risk-free one. In other words, full collateralization cannot eliminate counterparty risk completely in the CDS market. Key Words: valuation model; credit risk modeling; collateralization; correlation, CDS. 1 Email: [email protected] Url: https://finpricing.com/ 1 Introduction There are two primary types of models that attempt to describe default processes in the literature: structural models and reduced-form (or intensity) models. -
Collateralized Debt Obligations – an Overview by Matthieu Royer, PRMIA NY Steering Committee Member Vice President – Portfolio Coordination, CALYON in the Americas
Collateralized Debt Obligations – an overview By Matthieu Royer, PRMIA NY Steering Committee Member Vice President – Portfolio Coordination, CALYON in the Americas What commonly is referred to as “Collateralized debt obligations” or CDOs are securitization of a pool of asset (generally non-mortgage), in other words a securitized interest. The underlying assets (a.k.a. collateral) usually comprise loans or other debt instruments. A CDO may be called a collateralized loan obligation (CLO) or collateralized bond obligation (CBO) if it holds only loans or bonds, respectively. Investors bear the “structured” credit risk of the collateral. Typically, multiple tranches (or notes) of securities are issued by the CDO, offering investors various composite of maturity and credit risk characteristics. Tranches are categorized as senior, mezzanine, and subordinated/equity, according to their degree of credit risk. If there are defaults or the CDO's collateral otherwise underperforms/migrates/early amortize, scheduled payments to senior tranches take precedence over those of mezzanine tranches, and scheduled payments to mezzanine tranches take precedence over those to subordinated/equity tranches. This is referred to as the “Cash Flow Waterfall”. Senior and mezzanine tranches are typically rated by one or more of the rating agencies, with the former receiving ratings equivalent of “A” to “AAA” and the latter receiving ratings of “B” to “BBB”. The ratings reflect both the expected credit quality of the underlying pool of collateral as well as how much protection a given tranch is afforded by tranches that are subordinate to it (i.e. acting as credit enhancement). The sponsoring organization of the CDO establishes a special purpose vehicle to hold collateral and issue securities. -
Principal Investment Strategy Main Risks
Class Investor I Y PORTFOLIO TURNOVER Ticker DHRAX DHRIX DHRYX The fund pays transaction costs, such as commissions, when it Before you invest, you may want to review the fund’s Prospectus, which buys and sells securities (or “turns over” its portfolio). A higher contains information about the fund and its risks. The fund’s Prospectus and portfolio turnover rate may indicate higher transaction costs and Statement of Additional Information, both dated February 28, 2021, are may result in higher taxes when fund shares are held in a taxable incorporated by reference into this Summary Prospectus. For free paper or account. These costs, which are not reflected in annual fund electronic copies of the fund’s Prospectus and other information about the operating expenses or in the Example, affect the fund’s fund, go to http://www.diamond-hill.com/mutual-funds/documents.fs, email a performance. During the most recent fiscal year, the fund’s request to [email protected], call 888-226-5595, or ask any financial portfolio turnover rate was 28% of the average value of advisor, bank, or broker-dealer who offers shares of the fund. its portfolio. Investment Objective Principal Investment Strategy The investment objective of the Diamond Hill Core Bond Fund is to maximize total return consistent with the preservation of Under normal market conditions, the fund intends to provide capital. total return by investing at least 80% of its net assets (plus any amounts borrowed for investment purposes) in a diversified Fees and Expenses of the Fund portfolio of investment grade, fixed income securities, including This table describes the fees and expenses that you may pay if bonds, debt securities and other similar U.S. -
Interest Rate Options
Interest Rate Options Saurav Sen April 2001 Contents 1. Caps and Floors 2 1.1. Defintions . 2 1.2. Plain Vanilla Caps . 2 1.2.1. Caplets . 3 1.2.2. Caps . 4 1.2.3. Bootstrapping the Forward Volatility Curve . 4 1.2.4. Caplet as a Put Option on a Zero-Coupon Bond . 5 1.2.5. Hedging Caps . 6 1.3. Floors . 7 1.3.1. Pricing and Hedging . 7 1.3.2. Put-Call Parity . 7 1.3.3. At-the-money (ATM) Caps and Floors . 7 1.4. Digital Caps . 8 1.4.1. Pricing . 8 1.4.2. Hedging . 8 1.5. Other Exotic Caps and Floors . 9 1.5.1. Knock-In Caps . 9 1.5.2. LIBOR Reset Caps . 9 1.5.3. Auto Caps . 9 1.5.4. Chooser Caps . 9 1.5.5. CMS Caps and Floors . 9 2. Swap Options 10 2.1. Swaps: A Brief Review of Essentials . 10 2.2. Swaptions . 11 2.2.1. Definitions . 11 2.2.2. Payoff Structure . 11 2.2.3. Pricing . 12 2.2.4. Put-Call Parity and Moneyness for Swaptions . 13 2.2.5. Hedging . 13 2.3. Constant Maturity Swaps . 13 2.3.1. Definition . 13 2.3.2. Pricing . 14 1 2.3.3. Approximate CMS Convexity Correction . 14 2.3.4. Pricing (continued) . 15 2.3.5. CMS Summary . 15 2.4. Other Swap Options . 16 2.4.1. LIBOR in Arrears Swaps . 16 2.4.2. Bermudan Swaptions . 16 2.4.3. Hybrid Structures . 17 Appendix: The Black Model 17 A.1. -
How Much Do Banks Use Credit Derivatives to Reduce Risk?
How much do banks use credit derivatives to reduce risk? Bernadette A. Minton, René Stulz, and Rohan Williamson* June 2006 This paper examines the use of credit derivatives by US bank holding companies from 1999 to 2003 with assets in excess of one billion dollars. Using the Federal Reserve Bank of Chicago Bank Holding Company Database, we find that in 2003 only 19 large banks out of 345 use credit derivatives. Though few banks use credit derivatives, the assets of these banks represent on average two thirds of the assets of bank holding companies with assets in excess of $1 billion. To the extent that banks have positions in credit derivatives, they tend to be used more for dealer activities than for hedging activities. Nevertheless, a majority of the banks that use credit derivative are net buyers of credit protection. Banks are more likely to be net protection buyers if they engage in asset securitization, originate foreign loans, and have lower capital ratios. The likelihood of a bank being a net protection buyer is positively related to the percentage of commercial and industrial loans in a bank’s loan portfolio and negatively or not related to other types of bank loans. The use of credit derivatives by banks is limited because adverse selection and moral hazard problems make the market for credit derivatives illiquid for the typical credit exposures of banks. *Respectively, Associate Professor, The Ohio State University; Everett D. Reese Chair of Banking and Monetary Economics, The Ohio State University and NBER; and Associate Professor, Georgetown University. We are grateful to Jim O’Brien and Mark Carey for discussions. -
The Synthetic Collateralised Debt Obligation: Analysing the Super-Senior Swap Element
The Synthetic Collateralised Debt Obligation: analysing the Super-Senior Swap element Nicoletta Baldini * July 2003 Basic Facts In a typical cash flow securitization a SPV (Special Purpose Vehicle) transfers interest income and principal repayments from a portfolio of risky assets, the so called asset pool, to a prioritized set of tranches. The level of credit exposure of every single tranche depends upon its level of subordination: so, the junior tranche will be the first to bear the effect of a credit deterioration of the asset pool, and senior tranches the last. The asset pool can be made up by either any type of debt instrument, mainly bonds or bank loans, or Credit Default Swaps (CDS) in which the SPV sells protection1. When the asset pool is made up solely of CDS contracts we talk of ‘synthetic’ Collateralized Debt Obligations (CDOs); in the so called ‘semi-synthetic’ CDOs, instead, the asset pool is made up by both debt instruments and CDS contracts. The tranches backed by the asset pool can be funded or not, depending upon the fact that the final investor purchases a true debt instrument (note) or a mere synthetic credit exposure. Generally, when the asset pool is constituted by debt instruments, the SPV issues notes (usually divided in more tranches) which are sold to the final investor; in synthetic CDOs, instead, tranches are represented by basket CDSs with which the final investor sells protection to the SPV. In any case all the tranches can be interpreted as percentile basket credit derivatives and their degree of subordination determines the percentiles of the asset pool loss distribution concerning them It is not unusual to find both funded and unfunded tranches within the same securitisation: this is the case for synthetic CDOs (but the same could occur with semi-synthetic CDOs) in which notes are issued and the raised cash is invested in risk free bonds that serve as collateral. -
Understanding the Z-Spread Moorad Choudhry*
Learning Curve September 2005 Understanding the Z-Spread Moorad Choudhry* © YieldCurve.com 2005 A key measure of relative value of a corporate bond is its swap spread. This is the basis point spread over the interest-rate swap curve, and is a measure of the credit risk of the bond. In its simplest form, the swap spread can be measured as the difference between the yield-to-maturity of the bond and the interest rate given by a straight-line interpolation of the swap curve. In practice traders use the asset-swap spread and the Z- spread as the main measures of relative value. The government bond spread is also considered. We consider the two main spread measures in this paper. Asset-swap spread An asset swap is a package that combines an interest-rate swap with a cash bond, the effect of the combined package being to transform the interest-rate basis of the bond. Typically, a fixed-rate bond will be combined with an interest-rate swap in which the bond holder pays fixed coupon and received floating coupon. The floating-coupon will be a spread over Libor (see Choudhry et al 2001). This spread is the asset-swap spread and is a function of the credit risk of the bond over and above interbank credit risk.1 Asset swaps may be transacted at par or at the bond’s market price, usually par. This means that the asset swap value is made up of the difference between the bond’s market price and par, as well as the difference between the bond coupon and the swap fixed rate. -
Implied Volatility Modeling
Implied Volatility Modeling Sarves Verma, Gunhan Mehmet Ertosun, Wei Wang, Benjamin Ambruster, Kay Giesecke I Introduction Although Black-Scholes formula is very popular among market practitioners, when applied to call and put options, it often reduces to a means of quoting options in terms of another parameter, the implied volatility. Further, the function σ BS TK ),(: ⎯⎯→ σ BS TK ),( t t ………………………………(1) is called the implied volatility surface. Two significant features of the surface is worth mentioning”: a) the non-flat profile of the surface which is often called the ‘smile’or the ‘skew’ suggests that the Black-Scholes formula is inefficient to price options b) the level of implied volatilities changes with time thus deforming it continuously. Since, the black- scholes model fails to model volatility, modeling implied volatility has become an active area of research. At present, volatility is modeled in primarily four different ways which are : a) The stochastic volatility model which assumes a stochastic nature of volatility [1]. The problem with this approach often lies in finding the market price of volatility risk which can’t be observed in the market. b) The deterministic volatility function (DVF) which assumes that volatility is a function of time alone and is completely deterministic [2,3]. This fails because as mentioned before the implied volatility surface changes with time continuously and is unpredictable at a given point of time. Ergo, the lattice model [2] & the Dupire approach [3] often fail[4] c) a factor based approach which assumes that implied volatility can be constructed by forming basis vectors. Further, one can use implied volatility as a mean reverting Ornstein-Ulhenbeck process for estimating implied volatility[5]. -
Evidence from SME Bond Markets
Temi di discussione (Working Papers) Asymmetric information in corporate lending: evidence from SME bond markets by Alessandra Iannamorelli, Stefano Nobili, Antonio Scalia and Luana Zaccaria September 2020 September Number 1292 Temi di discussione (Working Papers) Asymmetric information in corporate lending: evidence from SME bond markets by Alessandra Iannamorelli, Stefano Nobili, Antonio Scalia and Luana Zaccaria Number 1292 - September 2020 The papers published in the Temi di discussione series describe preliminary results and are made available to the public to encourage discussion and elicit comments. The views expressed in the articles are those of the authors and do not involve the responsibility of the Bank. Editorial Board: Federico Cingano, Marianna Riggi, Monica Andini, Audinga Baltrunaite, Marco Bottone, Davide Delle Monache, Sara Formai, Francesco Franceschi, Salvatore Lo Bello, Juho Taneli Makinen, Luca Metelli, Mario Pietrunti, Marco Savegnago. Editorial Assistants: Alessandra Giammarco, Roberto Marano. ISSN 1594-7939 (print) ISSN 2281-3950 (online) Printed by the Printing and Publishing Division of the Bank of Italy ASYMMETRIC INFORMATION IN CORPORATE LENDING: EVIDENCE FROM SME BOND MARKETS by Alessandra Iannamorelli†, Stefano Nobili†, Antonio Scalia† and Luana Zaccaria‡ Abstract Using a comprehensive dataset of Italian SMEs, we find that differences between private and public information on creditworthiness affect firms’ decisions to issue debt securities. Surprisingly, our evidence supports positive (rather than adverse) selection. Holding public information constant, firms with better private fundamentals are more likely to access bond markets. Additionally, credit conditions improve for issuers following the bond placement, compared with a matched sample of non-issuers. These results are consistent with a model where banks offer more flexibility than markets during financial distress and firms may use market lending to signal credit quality to outside stakeholders.