Building a Superior Volatility Mousetrap
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Form Dated March 20, 2007 Swaption Template (Full Underlying Confirmation)
Form Dated March 20, 2007 Swaption template (Full Underlying Confirmation) CONFIRMATION DATE: [Date] TO: [Party B] Telephone No.: [number] Facsimile No.: [number] Attention: [name] FROM: [Party A] SUBJECT: Swaption on [CDX.NA.[IG/HY/XO].____] [specify sector, if any] [specify series, if any] [specify version, if any] REF NO: [Reference number] The purpose of this communication (this “Confirmation”) is to set forth the terms and conditions of the Swaption entered into on the Swaption Trade Date specified below (the “Swaption Transaction”) between [Party A] (“Party A”) and [counterparty’s name] (“Party B”). This Confirmation constitutes a “Confirmation” as referred to in the ISDA Master Agreement specified below. The definitions and provisions contained in the 2000 ISDA Definitions (the “2000 Definitions”) and the 2003 ISDA Credit Derivatives Definitions as supplemented by the May 2003 Supplement to the 2003 ISDA Credit Derivatives Definitions (together, the “Credit Derivatives Definitions”), each as published by the International Swaps and Derivatives Association, Inc. are incorporated into this Confirmation. In the event of any inconsistency between the 2000 Definitions or the Credit Derivatives Definitions and this Confirmation, this Confirmation will govern. In the event of any inconsistency between the 2000 Definitions and the Credit Derivatives Definitions, the Credit Derivatives Definitions will govern in the case of the terms of the Underlying Swap Transaction and the 2000 Definitions will govern in other cases. For the purposes of the 2000 Definitions, each reference therein to Buyer and to Seller shall be deemed to refer to “Swaption Buyer” and to “Swaption Seller”, respectively. This Confirmation supplements, forms a part of and is subject to the ISDA Master Agreement dated as of [ ], as amended and supplemented from time to time (the “Agreement”) between Party A and Party B. -
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. -
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. -
5. Caps, Floors, and Swaptions
Options on LIBOR based instruments Valuation of LIBOR options Local volatility models The SABR model Volatility cube Interest Rate and Credit Models 5. Caps, Floors, and Swaptions Andrew Lesniewski Baruch College New York Spring 2019 A. Lesniewski Interest Rate and Credit Models Options on LIBOR based instruments Valuation of LIBOR options Local volatility models The SABR model Volatility cube Outline 1 Options on LIBOR based instruments 2 Valuation of LIBOR options 3 Local volatility models 4 The SABR model 5 Volatility cube A. Lesniewski Interest Rate and Credit Models Options on LIBOR based instruments Valuation of LIBOR options Local volatility models The SABR model Volatility cube Options on LIBOR based instruments Interest rates fluctuate as a consequence of macroeconomic conditions, central bank actions, and supply and demand. The existence of the term structure of rates, i.e. the fact that the level of a rate depends on the maturity of the underlying loan, makes the dynamics of rates is highly complex. While a good analogy to the price dynamics of an equity is a particle moving in a medium exerting random shocks to it, a natural way of thinking about the evolution of rates is that of a string moving in a random environment where the shocks can hit any location along its length. A. Lesniewski Interest Rate and Credit Models Options on LIBOR based instruments Valuation of LIBOR options Local volatility models The SABR model Volatility cube Options on LIBOR based instruments Additional complications arise from the presence of various spreads between rates, as discussed in Lecture Notes #1, which reflect credit quality of the borrowing entity, liquidity of the instrument, or other market conditions. -
Interest Rate Modelling and Derivative Pricing
Interest Rate Modelling and Derivative Pricing Sebastian Schlenkrich HU Berlin, Department of Mathematics WS, 2019/20 Part III Vanilla Option Models p. 140 Outline Vanilla Interest Rate Options SABR Model for Vanilla Options Summary Swaption Pricing p. 141 Outline Vanilla Interest Rate Options SABR Model for Vanilla Options Summary Swaption Pricing p. 142 Outline Vanilla Interest Rate Options Call Rights, Options and Forward Starting Swaps European Swaptions Basic Swaption Pricing Models Implied Volatilities and Market Quotations p. 143 Now we have a first look at the cancellation option Interbank swap deal example Bank A may decide to early terminate deal in 10, 11, 12,.. years. p. 144 We represent cancellation as entering an opposite deal L1 Lm ✻ ✻ ✻ ✻ ✻ ✻ ✻ ✻ ✻ ✻ ✻ ✻ T˜0 T˜k 1 T˜m − ✲ T0 TE Tl 1 Tn − ❄ ❄ ❄ ❄ ❄ ❄ K K [cancelled swap] = [full swap] + [opposite forward starting swap] K ✻ ✻ Tl 1 Tn − ✲ TE T˜k 1 T˜m − ❄ ❄ ❄ ❄ Lm p. 145 Option to cancel is equivalent to option to enter opposite forward starting swap K ✻ ✻ Tl 1 Tn − ✲ TE T˜k 1 T˜m − ❄ ❄ ❄ ❄ Lm ◮ At option exercise time TE present value of remaining (opposite) swap is n m Swap δ V (TE ) = K · τi · P(TE , Ti ) − L (TE , T˜j 1, T˜j 1 + δ) · τ˜j · P(TE , T˜j ) . − − i=l j=k X X future fixed leg future float leg | {z } | {z } ◮ Option to enter represents the right but not the obligation to enter swap. ◮ Rational market participant will exercise if swap present value is positive, i.e. Option Swap V (TE ) = max V (TE ), 0 . -
Introduction to Black's Model for Interest Rate
INTRODUCTION TO BLACK'S MODEL FOR INTEREST RATE DERIVATIVES GRAEME WEST AND LYDIA WEST, FINANCIAL MODELLING AGENCY© Contents 1. Introduction 2 2. European Bond Options2 2.1. Different volatility measures3 3. Caplets and Floorlets3 4. Caps and Floors4 4.1. A call/put on rates is a put/call on a bond4 4.2. Greeks 5 5. Stripping Black caps into caplets7 6. Swaptions 10 6.1. Valuation 11 6.2. Greeks 12 7. Why Black is useless for exotics 13 8. Exercises 13 Date: July 11, 2011. 1 2 GRAEME WEST AND LYDIA WEST, FINANCIAL MODELLING AGENCY© Bibliography 15 1. Introduction We consider the Black Model for futures/forwards which is the market standard for quoting prices (via implied volatilities). Black[1976] considered the problem of writing options on commodity futures and this was the first \natural" extension of the Black-Scholes model. This model also is used to price options on interest rates and interest rate sensitive instruments such as bonds. Since the Black-Scholes analysis assumes constant (or deterministic) interest rates, and so forward interest rates are realised, it is difficult initially to see how this model applies to interest rate dependent derivatives. However, if f is a forward interest rate, it can be shown that it is consistent to assume that • The discounting process can be taken to be the existing yield curve. • The forward rates are stochastic and log-normally distributed. The forward rates will be log-normally distributed in what is called the T -forward measure, where T is the pay date of the option. -
Ice Crude Oil
ICE CRUDE OIL Intercontinental Exchange® (ICE®) became a center for global petroleum risk management and trading with its acquisition of the International Petroleum Exchange® (IPE®) in June 2001, which is today known as ICE Futures Europe®. IPE was established in 1980 in response to the immense volatility that resulted from the oil price shocks of the 1970s. As IPE’s short-term physical markets evolved and the need to hedge emerged, the exchange offered its first contract, Gas Oil futures. In June 1988, the exchange successfully launched the Brent Crude futures contract. Today, ICE’s FSA-regulated energy futures exchange conducts nearly half the world’s trade in crude oil futures. Along with the benchmark Brent crude oil, West Texas Intermediate (WTI) crude oil and gasoil futures contracts, ICE Futures Europe also offers a full range of futures and options contracts on emissions, U.K. natural gas, U.K power and coal. THE BRENT CRUDE MARKET Brent has served as a leading global benchmark for Atlantic Oseberg-Ekofisk family of North Sea crude oils, each of which Basin crude oils in general, and low-sulfur (“sweet”) crude has a separate delivery point. Many of the crude oils traded oils in particular, since the commercialization of the U.K. and as a basis to Brent actually are traded as a basis to Dated Norwegian sectors of the North Sea in the 1970s. These crude Brent, a cargo loading within the next 10-21 days (23 days on oils include most grades produced from Nigeria and Angola, a Friday). In a circular turn, the active cash swap market for as well as U.S. -
Tax Treatment of Derivatives
United States Viva Hammer* Tax Treatment of Derivatives 1. Introduction instruments, as well as principles of general applicability. Often, the nature of the derivative instrument will dictate The US federal income taxation of derivative instruments whether it is taxed as a capital asset or an ordinary asset is determined under numerous tax rules set forth in the US (see discussion of section 1256 contracts, below). In other tax code, the regulations thereunder (and supplemented instances, the nature of the taxpayer will dictate whether it by various forms of published and unpublished guidance is taxed as a capital asset or an ordinary asset (see discus- from the US tax authorities and by the case law).1 These tax sion of dealers versus traders, below). rules dictate the US federal income taxation of derivative instruments without regard to applicable accounting rules. Generally, the starting point will be to determine whether the instrument is a “capital asset” or an “ordinary asset” The tax rules applicable to derivative instruments have in the hands of the taxpayer. Section 1221 defines “capital developed over time in piecemeal fashion. There are no assets” by exclusion – unless an asset falls within one of general principles governing the taxation of derivatives eight enumerated exceptions, it is viewed as a capital asset. in the United States. Every transaction must be examined Exceptions to capital asset treatment relevant to taxpayers in light of these piecemeal rules. Key considerations for transacting in derivative instruments include the excep- issuers and holders of derivative instruments under US tions for (1) hedging transactions3 and (2) “commodities tax principles will include the character of income, gain, derivative financial instruments” held by a “commodities loss and deduction related to the instrument (ordinary derivatives dealer”.4 vs. -
An Analysis of OTC Interest Rate Derivatives Transactions: Implications for Public Reporting
Federal Reserve Bank of New York Staff Reports An Analysis of OTC Interest Rate Derivatives Transactions: Implications for Public Reporting Michael Fleming John Jackson Ada Li Asani Sarkar Patricia Zobel Staff Report No. 557 March 2012 Revised October 2012 FRBNY Staff REPORTS This paper presents preliminary fi ndings and is being distributed to economists and other interested readers solely to stimulate discussion and elicit comments. The views expressed in this paper are those of the authors and are not necessarily refl ective 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. An Analysis of OTC Interest Rate Derivatives Transactions: Implications for Public Reporting Michael Fleming, John Jackson, Ada Li, Asani Sarkar, and Patricia Zobel Federal Reserve Bank of New York Staff Reports, no. 557 March 2012; revised October 2012 JEL classifi cation: G12, G13, G18 Abstract This paper examines the over-the-counter (OTC) interest rate derivatives (IRD) market in order to inform the design of post-trade price reporting. Our analysis uses a novel transaction-level data set to examine trading activity, the composition of market participants, levels of product standardization, and market-making behavior. We fi nd that trading activity in the IRD market is dispersed across a broad array of product types, currency denominations, and maturities, leading to more than 10,500 observed unique product combinations. While a select group of standard instruments trade with relative frequency and may provide timely and pertinent price information for market partici- pants, many other IRD instruments trade infrequently and with diverse contract terms, limiting the impact on price formation from the reporting of those transactions. -
Pricing Financial Derivatives Under the Regime-Switching Models Mengzhe Zhang
Pricing Financial Derivatives Under the Regime-Switching Models Mengzhe Zhang A thesis in fulfilment of the requirements the degree of Doctor of Philosophy School of Mathematics and Statistics Faculty of Science, University of New South of Wales, Australia 19th April 2017 Acknowledgement First of all, I would like to thank my supervisor Dr Leung Lung Chan for his valuable guidance, helpful comments and enlightening advice throughout the preparation of this thesis. I also want to thank my parents for their love, support and encouragement throughout my graduate study time at the University of NSW. Last but not the least, I would like to thank my friends- Dr Xin Gao, Dr Xin Zhang, Dr Wanchuang Zhu, Dr Philip Chen and Dr Jinghao Huang from the Math school of UNSW and Dr Zhuo Chen, Dr Xueting Zhang, Dr Tyler Kwong, Dr Henry Rui, Mr Tianyu Cai, Mr Zhongyuan Liu, Mr Yue Peng and Mr Huaizhou Li from the Business school of UNSW. i Contents 1 Introduction1 1.1 BS-Type Model with Regime-Switching.................5 1.2 Heston's Model with Regime-Switching.................6 2 Asymptotics for Option Prices with Regime-Switching Model: Short- Time and Large-Time9 2.1 Introduction................................9 2.2 BS Model with Regime-Switching.................... 13 2.3 Small Time Asymptotics for Option Prices............... 13 2.3.1 Out-of-the-Money and In-the-Money.............. 13 2.3.2 At-the-Money........................... 25 2.3.3 Numerical Results........................ 35 2.4 Large-Maturity Asymptotics for Option Prices............. 39 ii 2.5 Calibration................................ 53 2.6 Conclusion................................. 57 3 Saddlepoint Approximations to Option Price in A Regime-Switching Model 59 3.1 Introduction............................... -
White Paper Volatility: Instruments and Strategies
White Paper Volatility: Instruments and Strategies Clemens H. Glaffig Panathea Capital Partners GmbH & Co. KG, Freiburg, Germany July 30, 2019 This paper is for informational purposes only and is not intended to constitute an offer, advice, or recommendation in any way. Panathea assumes no responsibility for the content or completeness of the information contained in this document. Table of Contents 0. Introduction ......................................................................................................................................... 1 1. Ihe VIX Index .................................................................................................................................... 2 1.1 General Comments and Performance ......................................................................................... 2 What Does it mean to have a VIX of 20% .......................................................................... 2 A nerdy side note ................................................................................................................. 2 1.2 The Calculation of the VIX Index ............................................................................................. 4 1.3 Mathematical formalism: How to derive the VIX valuation formula ...................................... 5 1.4 VIX Futures .............................................................................................................................. 6 The Pricing of VIX Futures ................................................................................................ -
Form 6781 Contracts and Straddles ▶ Go to for the Latest Information
Gains and Losses From Section 1256 OMB No. 1545-0644 Form 6781 Contracts and Straddles ▶ Go to www.irs.gov/Form6781 for the latest information. 2020 Department of the Treasury Attachment Internal Revenue Service ▶ Attach to your tax return. Sequence No. 82 Name(s) shown on tax return Identifying number Check all applicable boxes. A Mixed straddle election C Mixed straddle account election See instructions. B Straddle-by-straddle identification election D Net section 1256 contracts loss election Part I Section 1256 Contracts Marked to Market (a) Identification of account (b) (Loss) (c) Gain 1 2 Add the amounts on line 1 in columns (b) and (c) . 2 ( ) 3 Net gain or (loss). Combine line 2, columns (b) and (c) . 3 4 Form 1099-B adjustments. See instructions and attach statement . 4 5 Combine lines 3 and 4 . 5 Note: If line 5 shows a net gain, skip line 6 and enter the gain on line 7. Partnerships and S corporations, see instructions. 6 If you have a net section 1256 contracts loss and checked box D above, enter the amount of loss to be carried back. Enter the loss as a positive number. If you didn’t check box D, enter -0- . 6 7 Combine lines 5 and 6 . 7 8 Short-term capital gain or (loss). Multiply line 7 by 40% (0.40). Enter here and include on line 4 of Schedule D or on Form 8949. See instructions . 8 9 Long-term capital gain or (loss). Multiply line 7 by 60% (0.60). Enter here and include on line 11 of Schedule D or on Form 8949.