Credit Default Swap Spreads and Variance Risk Premia∗
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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. -
Arithmetic Variance Swaps
Arithmetic variance swaps Article (Accepted Version) Leontsinis, Stamatis and Alexander, Carol (2017) Arithmetic variance swaps. Quantitative Finance, 17 (4). pp. 551-569. ISSN 1469-7688 This version is available from Sussex Research Online: http://sro.sussex.ac.uk/id/eprint/62303/ This document is made available in accordance with publisher policies and may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher’s version. Please see the URL above for details on accessing the published version. Copyright and reuse: Sussex Research Online is a digital repository of the research output of the University. Copyright and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable, the material made available in SRO has been checked for eligibility before being made available. Copies of full text items generally can be reproduced, displayed or performed and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. http://sro.sussex.ac.uk Arithmetic Variance Swaps Stamatis Leontsinisa and Carol Alexanderb a RwC Asset Management, London b School of Business, Management and Economics, University of Sussex To appear in Quantitative Finance, 2016 (in press) Abstract Biases in standard variance swap rates can induce substantial deviations below market rates. -
Further Developments in Volatility Derivatives Modeling
Introduction Prior work Parameter estimation Model vs market prices Conclusion Further Developments in Volatility Derivatives Modeling Jim Gatheral Global Derivatives Trading & Risk Management, Paris May 21, 2008 Introduction Prior work Parameter estimation Model vs market prices Conclusion Disclaimer The opinions expressed in this presentation are those of the author alone, and do not necessarily reflect the views of of Merrill Lynch, its subsidiaries or affiliates. Introduction Prior work Parameter estimation Model vs market prices Conclusion Motivation and context We would like to have a model that prices consistently 1 options on SPX 2 options on VIX 3 options on realized variance We believe there may be such a model because we can identify relationships between options on SPX, VIX and variance. For example: 1 Puts on SPX and calls on VIX both protect against market dislocations. 2 Bruno Dupire constructs an upper bound on the price of options on variance from the prices of index options. 3 The underlying of VIX options is the square-root of a forward-starting variance swap. The aim is not necessarily to find new relationships; the aim is to devise a tool for efficient determination of relative value. Introduction Prior work Parameter estimation Model vs market prices Conclusion Outline 1 Review of prior work Double Lognormal vs Double Heston 2 Parameter estimation Time series analysis of variance curves Time series analysis of SABR fits to SPX options 3 Model vs market prices Numerical techniques Pricing of options on VIX and SPX Options on realized variance 4 Conclusion Is the model right? Introduction Prior work Parameter estimation Model vs market prices Conclusion Review of prior work We found that double-mean reverting lognormal dynamics for SPX instantaneous variance gave reasonable fits to both SPX and VIX option volatility smiles. -
Credit Default Swap in a Financial Portfolio: Angel Or Devil?
Credit Default Swap in a financial portfolio: angel or devil? A study of the diversification effect of CDS during 2005-2010 Authors: Aliaksandra Vashkevich Hu DongWei Supervisor: Catherine Lions Student Umeå School of Business Spring semester 2010 Master thesis, one-year, 15 hp ACKNOWLEDGEMENT We would like to express our deep gratitude and appreciation to our supervisor Catherine Lions. Your valuable guidance and suggestions have helped us enormously in finalizing this thesis. We would also like to thank Rene Wiedner from Thomson Reuters who provided us with an access to Reuters 3000 Xtra database without which we would not be able to conduct this research. Furthermore, we would like to thank our families for all the love, support and understanding they gave us during the time of writing this thesis. Aliaksandra Vashkevich……………………………………………………Hu Dong Wei Umeå, May 2010 ii SUMMARY Credit derivative market has experienced an exponential growth during the last 10 years with credit default swap (CDS) as an undoubted leader within this group. CDS contract is a bilateral agreement where the seller of the financial instrument provides the buyer the right to get reimbursed in case of the default in exchange for a continuous payment expressed as a CDS spread multiplied by the notional amount of the underlying debt. Originally invented to transfer the credit risk from the risk-averse investor to that one who is more prone to take on an additional risk, recently the instrument has been actively employed by the speculators betting on the financial health of the underlying obligation. It is believed that CDS contributed to the recent turmoil on financial markets and served as a weapon of mass destruction exaggerating the systematic risk. -
Credit Derivatives Handbook
08 February 2007 Fixed Income Research http://www.credit-suisse.com/researchandanalytics Credit Derivatives Handbook Credit Strategy Contributors Ira Jersey +1 212 325 4674 [email protected] Alex Makedon +1 212 538 8340 [email protected] David Lee +1 212 325 6693 [email protected] This is the second edition of our Credit Derivatives Handbook. With the continuous growth of the derivatives market and new participants entering daily, the Handbook has become one of our most requested publications. Our goal is to make this publication as useful and as user friendly as possible, with information to analyze instruments and unique situations arising from market action. Since we first published the Handbook, new innovations have been developed in the credit derivatives market that have gone hand in hand with its exponential growth. New information included in this edition includes CDS Orphaning, Cash Settlement of Single-Name CDS, Variance Swaps, and more. We have broken the information into several convenient sections entitled "Credit Default Swap Products and Evaluation”, “Credit Default Swaptions and Instruments with Optionality”, “Capital Structure Arbitrage”, and “Structure Products: Baskets and Index Tranches.” We hope this publication is useful for those with various levels of experience ranging from novices to long-time practitioners, and we welcome feedback on any topics of interest. FOR IMPORTANT DISCLOSURE INFORMATION relating to analyst certification, the Firm’s rating system, and potential conflicts -
Volatility As Investment - Crash Protection with Calendar Spreads of Variance Swaps
Journal of Applied Operational Research (2014) 6(4), 243–254 © Tadbir Operational Research Group Ltd. All rights reserved. www.tadbir.ca ISSN 1735-8523 (Print), ISSN 1927-0089 (Online) Volatility as investment - crash protection with calendar spreads of variance swaps Uwe Wystup 1,* and Qixiang Zhou 2 1 MathFinance AG, Frankfurt, Germany 2 Frankfurt School of Finance & Management, Germany Abstract. Nowadays, volatility is not only a risk measure but can be also considered an individual asset class. Variance swaps, one of the main investment vehicles, can obtain pure exposure on realized volatility. In normal market phases, implied volatility is often higher than the realized volatility will turn out to be. We present a volatility investment strategy that can benefit from both negative risk premium and correlation of variance swaps to the underlying stock index. The empirical evidence demonstrates a significant diversification effect during the financial crisis by adding this strategy to an existing portfolio consisting of 70% stocks and 30% bonds. The back-testing analysis includes the last ten years of history of the S&P500 and the EUROSTOXX50. Keywords: volatility; investment strategy; stock index; crash protection; variance swap * Received July 2014. Accepted November 2014 Introduction Volatility is an important variable of the financial market. The accurate measurement of volatility is important not only for investment but also as an integral part of risk management. Generally, there are two methods used to assess volatility: The first one entails the application of time series methods in order to make statistical conclusions based on historical data. Examples of this method are ARCH/GARCH models. -
The Term Structure of Variance Swap Rates and Optimal Variance Swap Investments
JOURNAL OF FINANCIAL AND QUANTITATIVE ANALYSIS Vol. 45, No. 5, Oct. 2010, pp. 1279–1310 COPYRIGHT 2010, MICHAEL G. FOSTER SCHOOL OF BUSINESS, UNIVERSITY OF WASHINGTON, SEATTLE, WA 98195 doi:10.1017/S0022109010000463 The Term Structure of Variance Swap Rates and Optimal Variance Swap Investments Daniel Egloff, Markus Leippold, and Liuren Wu∗ Abstract This paper performs specification analysis on the term structure of variance swap rates on the S&P 500 index and studies the optimal investment decision on the variance swaps and the stock index. The analysis identifies 2 stochastic variance risk factors, which govern the short and long end of the variance swap term structure variation, respectively. The highly negative estimate for the market price of variance risk makes it optimal for an investor to take short positions in a short-term variance swap contract, long positions in a long-term variance swap contract, and short positions in the stock index. I. Introduction The financial market is becoming increasingly aware of the fact that the re- turn variance on stock indexes is stochastic (Engle (2004)) and the variance risk is heavily priced (Carr and Wu (2009)). Associated with this recognition is the development of a large number of variance-related derivative products. The most actively traded is the variance swap contract. The contract has 0 value at inception. At maturity, the long side of the variance swap contract receives the difference be- tween a standard measure of the realized variance and a fixed rate, called the vari- ance swap rate, determined at the inception of the contract. Traditional derivative contracts such as calls, puts, and straddles also have variance risk exposure, ∗Egloff, [email protected], QuantCatalyst, Hardturmstrasse 101, 8005 Zurich, Switzerland; Leippold, [email protected], University of Zurich, Swiss Banking Institute, Plattenstrasse 14, 8032 Zurich, Switzerland; and Wu, [email protected], Baruch College, Zicklin School of Business, One Bernard Baruch Way, Box B10-225, New York, NY 10010. -
The Price of Interest Rate Variance Risk and Optimal Investments in Interest Rate Derivatives
The price of interest rate variance risk and optimal investments in interest rate derivatives Anders B. Trolle Copenhagen Business School Abstract Recent research on unspanned stochastic variance raises the possibility that interest rate derivatives constitute an important component of optimal fixed income portfo- lios. In this paper, I estimate a flexible dynamic term structure model that allows for unspanned stochastic variance on an extensive data set of swaps and swaptions. I find that variance risk is predominantly unspanned by bonds, and that the price of risk on the unspanned variance factor is significantly larger in absolute value than the prices of risk on the term structure factors. Consequently, Sharpe ratios on variance sensitive derivatives are about three times larger than Sharpe ratios on bonds or short-term bond futures. These findings are corroborated by an analysis of the Treasury futures market, where the variance risk premium is estimated with a model independent approach. I then solve the dynamic portfolio choice problem for a long-term fixed income investor with and without access to interest rate derivatives and find substantial utility gains from participating in the derivatives market. JEL Classification: G11 Keywords: Portfolio choice, derivatives, stochastic variance, swaps, Treasury futures This version: December 2008 ——————————— I have benefitted from discussions with Giovanni Barone-Adesi, Michael Brennan, Wolfgang B¨uhler, Pierre Collin-Dufresne, David Lando, Francis Longstaff, Claus Munk, Carsten Sørensen and seminar participants at Copenhagen Business School. I am particularly grateful to Eduardo Schwartz for extensive comments. Some of the results in this paper were previously circulated under the title “Dynamic interest rate derivative strategies in the presence of unspanned stochastic volatility”. -
Variance Swap Payoffs, Risk Premia and Extreme Market Conditions
Variance swap payoffs, risk premia and extreme market conditions Jeroen V.K. Rombouts1, Lars Stentoft2 and Francesco Violante3 June 5, 2017 Abstract This paper estimates the Variance Risk Premium (VRP) directly from synthetic variance swap payoffs. Since variance swap payoffs are highly volatile, we extract the VRP by using signal extraction techniques based on a state-space representation of our model in combination with a simple economic constraint. Our approach, only requiring option implied volatilities and daily returns for the underlying, provides measurement error free estimates of the part of the VRP related to normal market conditions, and allows constructing variables indicating agents' expectations under extreme market conditions. The latter variables and the VRP generate different re- turn predictability on the major US indices. A factor model is proposed to extract a market VRP which turns out to be priced when considering Fama and French port- folios. Keywords: Variance risk premium; Variance swaps; Return predictability; Factor Model, Kalman filter, CAPM. JEL Classification: C12, C22, G12, G13 1ESSEC Business School, Av. B. Hirsch, Cergy Pontoise, France 95021. Phone: +33 1 3443 3049 - E-mail: [email protected] 2Department of Economics and Department of Statistical and Actuarial Sciences, University of Western Ontario, Social Science Centre, London, ON, Canada N6A 5C2, Phone: +1 519 661 2111 ext. 85311 - E-mail: [email protected] 3MEMOTEF - Sapienza Universit´adi Roma, Via del Castro Laurenziano 9, Roma, Italy 00161, and -
Credit Default Swap Auctions
Federal Reserve Bank of New York Staff Reports Credit Default Swap Auctions Jean Helwege Samuel Maurer Asani Sarkar Yuan Wang Staff Report no. 372 May 2009 This paper presents preliminary findings and is being distributed to economists and other interested readers solely to stimulate discussion and elicit comments. The views expressed in the paper are those of the authors and are not necessarily reflective of views at the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the authors. Credit Default Swap Auctions Jean Helwege, Samuel Maurer, Asani Sarkar, and Yuan Wang Federal Reserve Bank of New York Staff Reports, no. 372 May 2009 JEL classification: G10, G13, G33 Abstract The rapid growth of the credit default swap (CDS) market and the increased number of defaults in recent years have led to major changes in the way CDS contracts are settled when default occurs. Auctions are increasingly the mechanism used to settle these contracts, replacing physical transfers of defaulted bonds between CDS sellers and buyers. Indeed, auctions will become a standard feature of all recent CDS contracts from now on. In this paper, we examine all of the CDS auctions conducted to date and evaluate their efficacy by comparing the auction outcomes to prices of the underlying bonds in the secondary market. The auctions appear to have served their purpose, as we find no evidence of inefficiency in the process: Participation is high, open interest is low, and the auction prices are close to the prices observed in the bond market before and after each auction has occurred. -
Credit Derivatives
3 Credit Derivatives CHAPTER 7 Credit derivatives Collaterized debt obligation Credit default swap Credit spread options Credit linked notes Risks in credit derivatives Credit Derivatives •A credit derivative is a financial instrument whose value is determined by the default risk of the principal asset. •Financial assets like forward, options and swaps form a part of Credit derivatives •Borrowers can default and the lender will need protection against such default and in reality, a credit derivative is a way to insure such losses Credit Derivatives •Credit default swaps (CDS), total return swap, credit default swap options, collateralized debt obligations (CDO) and credit spread forwards are some examples of credit derivatives •The credit quality of the borrower as well as the third party plays an important role in determining the credit derivative’s value Credit Derivatives •Credit derivatives are fundamentally divided into two categories: funded credit derivatives and unfunded credit derivatives. •There is a contract between both the parties stating the responsibility of each party with regard to its payment without resorting to any asset class Credit Derivatives •The level of risk differs in different cases depending on the third party and a fee is decided based on the appropriate risk level by both the parties. •Financial assets like forward, options and swaps form a part of Credit derivatives •The price for these instruments changes with change in the credit risk of agents such as investors and government Credit derivatives Collaterized debt obligation Credit default swap Credit spread options Credit linked notes Risks in credit derivatives Collaterized Debt obligation •CDOs or Collateralized Debt Obligation are financial instruments that banks and other financial institutions use to repackage individual loans into a product sold to investors on the secondary market. -
Counterparty Risk and Counterparty Choice in the Credit Default Swap Market∗
Counterparty Risk and Counterparty Choice in the Credit Default Swap Market∗ Wenxin Du Salil Gadgil Michael B. Gordy Clara Vega November 2018 Abstract We investigate how market participants price and manage counterparty credit risk in the post-crisis period using confidential trade repository data on single-name credit default swap (CDS) transactions. We find that counterparty risk has a modest impact on the pricing of CDS contracts, but a large impact on the choice of counterparties. We show that market participants are significantly less likely to trade with counterparties whose credit risk is highly correlated with the credit risk of the reference entities and with counterparties whose credit quality is low. Our results suggest that credit rationing may arise under wider circumstances than previously recognized. Keywords: Counterparty credit risk, credit default swaps, central clearing, credit rationing, counterparty choice. JEL Classifications: G12, G13, G24 ∗W. Du, M. Gordy and C. Vega are with the Federal Reserve Board, 20th and C Streets NW, Washington, DC 20551, USA. S. Gadgil is at UCLA Anderson School of Management, 110 Westwood Plaza, Los Ange- les, CA 90095, USA. The authors can be reached via email at [email protected], [email protected], [email protected], and [email protected]. We are grateful to DTCC for providing the data. We have benefitted from helpful comments from Robert Avery, Aaron Brown, Sean Campbell, Eduardo Canabarro, Audrey Costabile, Jorge Cruz Lopez, Michael Gibson, Jon Gregory, Erik Heitfield, Greg