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Incentives for Central Clearing and the Evolution of Otc Derivatives
INCENTIVES FOR CENTRAL CLEARING AND THE EVOLUTION OF OTC DERIVATIVES – [email protected] A CCP12 5F No.55 Yuanmingyuan Rd. Huangpu District, Shanghai, China REPORT February 2019 TABLE OF CONTENTS TABLE OF CONTENTS................................................................................................... 2 EXECUTIVE SUMMARY ................................................................................................. 5 1. MARKET OVERVIEW ............................................................................................. 8 1.1 CENTRAL CLEARING RATES OF OUTSTANDING TRADES ..................... 8 1.2 MARKET STRUCTURE – COMPRESSION AND BACKLOADING ............... 9 1.3 CURRENT CLEARING RATES ................................................................... 11 1.4 INITIAL MARGIN HELD AT CCPS .............................................................. 16 1.5 UNCLEARED MARKETS ............................................................................ 17 1.5.1 FX OPTIONS ...................................................................................... 18 1.5.2 SWAPTIONS ...................................................................................... 19 1.5.3 EUROPE ............................................................................................ 21 2. TRADE PROCESSING ......................................................................................... 23 2.1 TRADE PROCESSING OF NON-CLEARED TRADES ............................... 23 2.1.1 CUSTODIAL ARRANGEMENTS ....................................................... -
Section 1256 and Foreign Currency Derivatives
Section 1256 and Foreign Currency Derivatives Viva Hammer1 Mark-to-market taxation was considered “a fundamental departure from the concept of income realization in the U.S. tax law”2 when it was introduced in 1981. Congress was only game to propose the concept because of rampant “straddle” shelters that were undermining the U.S. tax system and commodities derivatives markets. Early in tax history, the Supreme Court articulated the realization principle as a Constitutional limitation on Congress’ taxing power. But in 1981, lawmakers makers felt confident imposing mark-to-market on exchange traded futures contracts because of the exchanges’ system of variation margin. However, when in 1982 non-exchange foreign currency traders asked to come within the ambit of mark-to-market taxation, Congress acceded to their demands even though this market had no equivalent to variation margin. This opportunistic rather than policy-driven history has spawned a great debate amongst tax practitioners as to the scope of the mark-to-market rule governing foreign currency contracts. Several recent cases have added fuel to the debate. The Straddle Shelters of the 1970s Straddle shelters were developed to exploit several structural flaws in the U.S. tax system: (1) the vast gulf between ordinary income tax rate (maximum 70%) and long term capital gain rate (28%), (2) the arbitrary distinction between capital gain and ordinary income, making it relatively easy to convert one to the other, and (3) the non- economic tax treatment of derivative contracts. Straddle shelters were so pervasive that in 1978 it was estimated that more than 75% of the open interest in silver futures were entered into to accommodate tax straddles and demand for U.S. -
Understanding Swap Spread.Pdf
Understanding and modelling swap spreads By Fabio Cortes of the Bank’s Foreign Exchange Division. Interest rate swap agreements were developed for the transfer of interest rate risk. Volumes have grown rapidly in recent years and now the swap market not only fulfils this purpose, but is also used to extract information about market expectations and to provide benchmark rates against which to compare returns on fixed-income securities such as corporate and government bonds. This article explains what swaps are; what information might be extracted from them; and what appear to have been the main drivers of swap spreads in recent years. Some quantitative relationships are explored using ten-year swap spreads in the United States and the United Kingdom as examples. Introduction priced efficiently at all times, swap spreads may be altered by perceptions of the economic outlook and A swap is an agreement between two parties to exchange supply and demand imbalances in both the swap and cash flows in the future. The most common type of the government bond markets. interest rate swap is a ‘plain vanilla fixed-for-floating’ interest rate swap(1) where one party wants to receive The volume of swap transactions has increased rapidly floating (variable) interest rate payments over a given in recent years (see Chart 1). Swaps are the largest period, and is prepared to pay the other party a fixed type of traded interest rate derivatives in the OTC rate to receive those floating payments. The floating (over-the-counter)(4) market, accounting for over 75% of rate is agreed in advance with reference to a specific short-term market rate (usually three-month or Chart 1 six-month Libor).(2) The fixed rate is called the swap rate OTC interest rate contracts by instrument in all and should reflect, among other things, the value each currencies Total interest rate swaps outstanding party attributes to the series of floating-rate payments to Total forward-rate agreements outstanding Total option contracts outstanding US$ trillions be made over the life of the contract. -
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. -
Dixit-Pindyck and Arrow-Fisher-Hanemann-Henry Option Concepts in a Finance Framework
Dixit-Pindyck and Arrow-Fisher-Hanemann-Henry Option Concepts in a Finance Framework January 12, 2015 Abstract We look at the debate on the equivalence of the Dixit-Pindyck (DP) and Arrow-Fisher- Hanemann-Henry (AFHH) option values. Casting the problem into a financial framework allows to disentangle the discussion without unnecessarily introducing new definitions. Instead, the option values can be easily translated to meaningful terms of financial option pricing. We find that the DP option value can easily be described as time-value of an American plain-vanilla option, while the AFHH option value is an exotic chooser option. Although the option values can be numerically equal, they differ for interesting, i.e. non-trivial investment decisions and benefit-cost analyses. We find that for applied work, compared to the Dixit-Pindyck value, the AFHH concept has only limited use. Keywords: Benefit cost analysis, irreversibility, option, quasi-option value, real option, uncertainty. Abbreviations: i.e.: id est; e.g.: exemplum gratia. 1 Introduction In the recent decades, the real options1 concept gained a large foothold in the strat- egy and investment literature, even more so with Dixit & Pindyck (1994)'s (DP) seminal volume on investment under uncertainty. In environmental economics, the importance of irreversibility has already been known since the contributions of Arrow & Fisher (1974), Henry (1974), and Hanemann (1989) (AFHH) on quasi-options. As Fisher (2000) notes, a unification of the two option concepts would have the benefit of applying the vast results of real option pricing in environmental issues. In his 1The term real option has been coined by Myers (1977). -
Derivative Valuation Methodologies for Real Estate Investments
Derivative valuation methodologies for real estate investments Revised September 2016 Proprietary and confidential Executive summary Chatham Financial is the largest independent interest rate and foreign exchange risk management consulting company, serving clients in the areas of interest rate risk, foreign currency exposure, accounting compliance, and debt valuations. As part of its service offering, Chatham provides daily valuations for tens of thousands of interest rate, foreign currency, and commodity derivatives. The interest rate derivatives valued include swaps, cross currency swaps, basis swaps, swaptions, cancellable swaps, caps, floors, collars, corridors, and interest rate options in over 50 market standard indices. The foreign exchange derivatives valued nightly include FX forwards, FX options, and FX collars in all of the major currency pairs and many emerging market currency pairs. The commodity derivatives valued include commodity swaps and commodity options. We currently support all major commodity types traded on the CME, CBOT, ICE, and the LME. Summary of process and controls – FX and IR instruments Each day at 4:00 p.m. Eastern time, our systems take a “snapshot” of the market to obtain close of business rates. Our systems pull over 9,500 rates including LIBOR fixings, Eurodollar futures, swap rates, exchange rates, treasuries, etc. This market data is obtained via direct feeds from Bloomberg and Reuters and from Inter-Dealer Brokers. After the data is pulled into the system, it goes through the rates control process. In this process, each rate is compared to its historical values. Any rate that has changed more than the mean and related standard deviation would indicate as normal is considered an outlier and is flagged for further investigation by the Analytics team. -
Financial Derivatives 1
Giulia Iori, Financial Derivatives 1 Financial Derivatives Giulia Iori Giulia Iori, Financial Derivatives 2 Contents • Introduction to Financial Markets and Financial Derivatives • Review of Probability and Random Variable • Vanilla Option Pricing. – Random Walk – Binomial model. – Stochastic Processes. ∗ Martingales ∗ Wiener process ∗ Some basic properties of the Stochastic Integral ∗ Ito’s Lemma – Black-Scholes model: portfolio replication approach. – The Greeks: Delta hedging, Gamma hedging. – Change of probability measures and Bayes Formula. – Girsanov Theorem. – Black-Scholes model: risk neutral evaluation. – Feynman-Kac Formula and Risk neutral pricing. – Change of Numeraire Theorem. • Interest Rate Models • Overview of Exotic Derivatives • Energy and Weather Derivatives Giulia Iori, Financial Derivatives 3 Overview of Financial Markets Functions of Financial Markets: Financial markets determine the prices of assets, provide a place for exchanging assets and lower costs of transacting. This aids the resource allocation process for the whole economy. • price discovery process • provide liquidity • reduce search costs • reduce information costs Market Efficiency: • Operational efficiency: fees charged by professional reflect true cost of providing those services. • price efficiency: prices reflect the true values of assets. – Weak efficiency: current price reflect information embodied in past price movements. – Semistrong efficiency: current price reflect information embodied in past price movements and public information. – Strong efficiency: current price reflect information embodied in past price movements and all public and private information. Brief history: Birth of shareholding enterprise, Muscovy Company (1553), East India Company (1600), Hudson’s Bay Company (1668). Trading starts on the shares of these com- pany. Amsterdam stock exchange (1611), Austrian Bourse in Vienna (1771). In London coffee houses where brokers meet. -
Swap Curve Building at Factset: the Multi-Curve Framework
www.factset.com SWAP CURVE BUILDING AT FACTSET: THE MULTI-CURVE FRAMEWORK By Tom P. Davis Vice President, Director, Research, Fixed Income and Derivatives QRD Figo Liu Financial Engineer, Fixed Income and Derivatives QRD Swap Curve Building at FactSet Tom P. Davis Figo Liu [email protected] [email protected] 1 Introduction The interest rate swap (IRS) market is the third largest market in the U.S. for interest rate securities after U.S. Treasuries and mortgage backed securities (MBS), as demonstrated by Table 1. Interest rate swap curves are important not just for valuing swaps, but also for their role in determining the market expectation of future LIBOR fixings, since many financial securities have coupons that are set based on this fixing. Financial markets changed significantly due to the global financial crisis (GFC) of 2008, none more so than the IRS market. The market changes were so disruptive that they caused a reexamination of the entire foundation of quantitative finance. Security Type Gross Market Value U.S. Treasuries 17.57 Trillion USD U.S. Mortgage Backed Securities 10.076 Trillion USD Interest Rate Derivatives 1.434 Trillion USD Table 1: U.S. market sizes as of Q4 2017. The U.S. Treasury and the Interest Rate Derivatives data are taken from the Bank of International Settlements, and the U.S. mortgage data is taken from the Federal Reserve Bank of St. Louis. The IRD market may look small in comparison; however, the notional amount outstanding is 156.5 trillion USD. To begin to understand why these changes were so disruptive, a basic refresher on IRS is useful. -
Finance II (Dirección Financiera II) Apuntes Del Material Docente
Finance II (Dirección Financiera II) Apuntes del Material Docente Szabolcs István Blazsek-Ayala Table of contents Fixed-income securities 1 Derivatives 27 A note on traditional return and log return 78 Financial statements, financial ratios 80 Company valuation 100 Coca-Cola DCF valuation 135 Bond characteristics A bond is a security that is issued in FIXED-INCOME connection with a borrowing arrangement. SECURITIES The borrower issues (i.e. sells) a bond to the lender for some amount of cash. The arrangement obliges the issuer to make specified payments to the bondholder on specified dates. Bond characteristics Bond characteristics A typical bond obliges the issuer to make When the bond matures, the issuer repays semiannual payments of interest to the the debt by paying the bondholder the bondholder for the life of the bond. bond’s par value (or face value ). These are called coupon payments . The coupon rate of the bond serves to Most bonds have coupons that investors determine the interest payment: would clip off and present to claim the The annual payment is the coupon rate interest payment. times the bond’s par value. Bond characteristics Example The contract between the issuer and the A bond with par value EUR1000 and coupon bondholder contains: rate of 8%. 1. Coupon rate The bondholder is then entitled to a payment of 8% of EUR1000, or EUR80 per year, for the 2. Maturity date stated life of the bond, 30 years. 3. Par value The EUR80 payment typically comes in two semiannual installments of EUR40 each. At the end of the 30-year life of the bond, the issuer also pays the EUR1000 value to the bondholder. -
Value at Risk for Linear and Non-Linear Derivatives
Value at Risk for Linear and Non-Linear Derivatives by Clemens U. Frei (Under the direction of John T. Scruggs) Abstract This paper examines the question whether standard parametric Value at Risk approaches, such as the delta-normal and the delta-gamma approach and their assumptions are appropriate for derivative positions such as forward and option contracts. The delta-normal and delta-gamma approaches are both methods based on a first-order or on a second-order Taylor series expansion. We will see that the delta-normal method is reliable for linear derivatives although it can lead to signif- icant approximation errors in the case of non-linearity. The delta-gamma method provides a better approximation because this method includes second order-effects. The main problem with delta-gamma methods is the estimation of the quantile of the profit and loss distribution. Empiric results by other authors suggest the use of a Cornish-Fisher expansion. The delta-gamma method when using a Cornish-Fisher expansion provides an approximation which is close to the results calculated by Monte Carlo Simulation methods but is computationally more efficient. Index words: Value at Risk, Variance-Covariance approach, Delta-Normal approach, Delta-Gamma approach, Market Risk, Derivatives, Taylor series expansion. Value at Risk for Linear and Non-Linear Derivatives by Clemens U. Frei Vordiplom, University of Bielefeld, Germany, 2000 A Thesis Submitted to the Graduate Faculty of The University of Georgia in Partial Fulfillment of the Requirements for the Degree Master of Arts Athens, Georgia 2003 °c 2003 Clemens U. Frei All Rights Reserved Value at Risk for Linear and Non-Linear Derivatives by Clemens U. -
Derivative Instruments and Hedging Activities
www.pwc.com 2015 Derivative instruments and hedging activities www.pwc.com Derivative instruments and hedging activities 2013 Second edition, July 2015 Copyright © 2013-2015 PricewaterhouseCoopers LLP, a Delaware limited liability partnership. All rights reserved. PwC refers to the United States member firm, and may sometimes refer to the PwC network. Each member firm is a separate legal entity. Please see www.pwc.com/structure for further details. This publication has been prepared for general information on matters of interest only, and does not constitute professional advice on facts and circumstances specific to any person or entity. You should not act upon the information contained in this publication without obtaining specific professional advice. No representation or warranty (express or implied) is given as to the accuracy or completeness of the information contained in this publication. The information contained in this material was not intended or written to be used, and cannot be used, for purposes of avoiding penalties or sanctions imposed by any government or other regulatory body. PricewaterhouseCoopers LLP, its members, employees and agents shall not be responsible for any loss sustained by any person or entity who relies on this publication. The content of this publication is based on information available as of March 31, 2013. Accordingly, certain aspects of this publication may be superseded as new guidance or interpretations emerge. Financial statement preparers and other users of this publication are therefore cautioned to stay abreast of and carefully evaluate subsequent authoritative and interpretative guidance that is issued. This publication has been updated to reflect new and updated authoritative and interpretative guidance since the 2012 edition. -
Solution to the Chooser Question
Solution to the Chooser Question The payoff of the chooser option at time 1 is given by max[C(S1,X,1),P(S1,X,1)], where C(S1,X,1) is the value of a call option that matures at time 2, with exercise price X and stock price S1. Put call parity implies that at time 1, C(S1,X,1)- P(S1,X,1)=S1-X/R. Substituting in for the value of the put, the chooser payoff at time 1 is given by max[C(S1,X,1),C(S1,X,1)- S1+X/R]= C(S1,X,1)+max[0,X/R-S1]. But, max[0,X/R-S1] is the payoff of a put option that expires at time 1, with exercise price X/R. So, at time 0, the value of the chooser must be equal to C(S0,X,2)+P(S0,X/R,1). We can then use put call parity again to substitute out the value of the one period put in terms of a one period call, giving us the final result that the 2 chooser payoff equals C(S0,X,2)+ C(S0,X/R,1)-S0+X/R . You would likely purchase the chooser option of you wanted a positive payoff in the tails of the distribution of the underlying return in the future. To solve for the value of the chooser, we work recursively through the tree. The call option payoffs are given by Cuu=Max(15.625-10,0)=5.625 Cu C0 Cud=Max(10-10,0)=0 Cd Cdd=Max(6.4-10,0)=0 Clearly, after the first down move, the call is worthless.