A Review of Term Structure Estimation Methods
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Bootstrapping the Interest-Rate Term Structure
Bootstrapping the interest-rate term structure Marco Marchioro www.marchioro.org October 20th, 2012 Advanced Derivatives, Interest Rate Models 2010-2012 c Marco Marchioro Bootstrapping the interest-rate term structure 1 Summary (1/2) • Market quotes of deposit rates, IR futures, and swaps • Need for a consistent interest-rate curve • Instantaneous forward rate • Parametric form of discount curves • Choice of curve nodes Advanced Derivatives, Interest Rate Models 2010-2012 c Marco Marchioro Bootstrapping the interest-rate term structure 2 Summary (2/2) • Bootstrapping quoted deposit rates • Bootstrapping using quoted interest-rate futures • Bootstrapping using quoted swap rates • QuantLib, bootstrapping, and rate helpers • Derivatives on foreign-exchange rates • Sensitivities of interest-rate portfolios (DV01) • Hedging portfolio with interest-rate risk Advanced Derivatives, Interest Rate Models 2010-2012 c Marco Marchioro Bootstrapping the interest-rate term structure 3 Major liquid quoted interest-rate derivatives For any given major currency (EUR, USD, GBP, JPY, ...) • Deposit rates • Interest-rate futures (FRA not reliable!) • Interest-rate swaps Advanced Derivatives, Interest Rate Models 2010-2012 c Marco Marchioro Bootstrapping the interest-rate term structure 4 Quotes from Financial Times Advanced Derivatives, Interest Rate Models 2010-2012 c Marco Marchioro Bootstrapping the interest-rate term structure 5 Consistent interest-rate curve We need a consistent interest-rate curve in order to • Understand the current market conditions -
MAS362/MAS462/MAS6053 Financial Mathematics Problem Sheet 1
MAS362/MAS462/MAS6053 Financial Mathematics Problem Sheet 1 1. Consider a £100, 000 mortgage paying a fixed annual rate of 5% which is com- pounded monthly. What are the monthly repayments if the mortgage is to be repaid in 25 years? 2. You want to deposit your savings for a year and you have the choice of three accounts. The first pays 5% interest per annum, compounded yearly. The second pays 4.8% interest per annum, compounded twice a year. The third pays 4.9% interest per annum, compounded continuously. Which one should you choose? 3. Consider any traded asset whose value vT in T years is known with certainty. −rT Prove that the current value of the asset must be vT e where r is the continuously- compounded T -years interest rate. 4. A perpetual bond is a bond with no maturity, i.e., it pays a fixed payment at fixed intervals forever.1 Under the assumption of constant (continuously compounded) interest rates of 5%, what is the price of a perpetual bond with face value £100 paying annual coupon of 2.50% once a year and whose first coupon payment is due in three months? 5. The prices of zero coupon bonds with face value of £100 and maturity dates in 6, 12 and 18 months are £98, £96 and £93.5 respectively. The price of a 8% bond maturing in 2 years with semiannual coupons is £107. Use the bootstrap method to find the two-year discount factor and spot rates. 6. Consider the following zero-coupon bonds with face value of £100: Time to maturity Annual interest Bond price (in years) (in £) 0.5 0 97.8 1. -
How Did Too Big to Fail Become Such a Problem for Broker-Dealers?
How did Too Big to Fail become such a problem for broker-dealers? Speculation by Andy Atkeson March 2014 Proximate Cause • By 2008, Broker Dealers had big balance sheets • Historical experience with rapid contraction of broker dealer balance sheets and bank runs raised unpleasant memories for central bankers • No satisfactory legal or administrative procedure for “resolving” failed broker dealers • So the Fed wrestled with the question of whether broker dealers were too big to fail Why do Central Bankers care? • Historically, deposit taking “Banks” held three main assets • Non-financial commercial paper • Government securities • Demandable collateralized loans to broker-dealers • Much like money market mutual funds (MMMF’s) today • Many historical (pre-Fed) banking crises (runs) associated with sharp changes in the volume and interest rates on loans to broker dealers • Similar to what happened with MMMF’s after Lehman? • Much discussion of directions for central bank policy and regulation • New York Clearing House 1873 • National Monetary Commission 1910 • Pecora Hearings 1933 • Friedman and Schwartz 1963 Questions I want to consider • How would you fit Broker Dealers into the growth model? • What economic function do they perform in facilitating trade of securities and financing margin and short positions in securities? • What would such a theory say about the size of broker dealer value added and balance sheets? • What would be lost (socially) if we dramatically reduced broker dealer balance sheets by regulation? • Are broker-dealer liabilities -
Asset Allocation, Time Diversification and Portfolio Optimization for Retirement
Technology and Investment, 2011, 2, 92-104 doi:10.4236/ti.2011.22010 Published Online May 2011 (http://www.SciRP.org/journal/ti) Asset Allocation, Time Diversification and Portfolio Optimization for Retirement Kamphol Panyagometh NIDA Business School, Bangkok, Thailand E-mail: [email protected], [email protected] Received February 17, 2011; revised April 6, 2011; accepted April 10, 2011 Abstract Using the data of stock, commodity and bond indexes from 2002 to November 2010, this research was car- ried out by employing Bootstrapping Simulation technique to find an optimal portfolio (portfolio optimiza- tion) for retirement, and the effect of diversification based on increased length of investment period (time diversification) with respect to the lengths of retirement investment period and the amounts required for spending after retirement in various occasions. The study analyzed for an optimal allocation of common stock, commodity and government bond to achieve the target rate of return for retirement by minimizing the portfolio risk as measured from the standard deviation. Apart from the standard deviation of the rate of return of the investment portfolio, this study also viewed the risk based on the Value at Risk concept to study the downside risk of the investment portfolio for retirement. Keywords: Asset Allocation, Time Diversification, Portfolio Optimization, Bootstrapping Simulation 1. Introduction bond in investment portfolio (portfolio optimization) for retirement, and the effect of diversification based on in- Nowadays -
Implied Correlations in CDO Tranches
Implied Correlations in CDO Tranches a, b c,⋆ Nicole Lehnert ∗, Frank Altrock , Svetlozar T. Rachev , Stefan Tr¨uck d, Andr´eWilch b aUniversit¨at Karlsruhe, Germany bCredit Risk Management, WestLB AG, Germany cUniversit¨at Karlsruhe, Germany and University of California, Santa Barbara, USA dQueensland University of Technology, Australia Abstract Market quotes of CDO tranches constitute a market view on correlation at differ- ent points in the portfolio capital structure and thus on the shape of the portfolio loss distribution. We investigate different calibrations of the CreditRisk+ model to examine its ability to reproduce iTraxx tranche quotes. Using initial model calibra- tion, CreditRisk+ clearly underestimates senior tranche losses. While sensitivities to correlation are too low, by increasing PD volatility up to about 3 times of the default probability for each name CreditRisk+ produces tails which are fat enough to meet market tranche losses. Additionally, we find that, similar to the correlation skew in the large pool model, to meet market quotes for each tranche a different PD volatility vector has to be used. ⋆ Rachev gratefully acknowledges research support by grants from Division of Math- ematical, Life and Physical Sciences, College of Letters and Science, University of California, Santa Barbara, the German Research Foundation (DFG) and the Ger- man Academic Exchange Service (DAAD). ∗ Corresponding author. email: nicole.lehnert@d-fine.de 20 December 2005 1 Introduction Credit derivatives started actively trading in the mid 1990s, exhibiting im- pressive growth rates over the last years. Due to new regulatory requirements there is an increasing demand by holders of securitisable assets to sell assets or to transfer risks of their assets. -
Investment Banking Compliance
© Practising Law Institute Chapter 49 Investment Banking Compliance Russell D. Sacks* Partner, Shearman & Sterling LLP Richard B. Alsop Partner, Shearman & Sterling LLP [Chapter 49 is current as of June 15, 2018.] § 49:1 Information § 49:1.1 Insider Trading [A] Generally [B] Legal Framework [B][1] Securities Exchange Act § 10(b) [B][2] Insider Trading and Securities Fraud Enforcement Act § 49:1.2 Information Barriers [A] Generally [B] Effective Information Barriers: Minimum Elements [B][1] Written Policies and Procedures [B][2] Wall-Crossing Procedures [B][3] Restricted List and Watch List [B][4] Surveillance of Trading Activity * The authors gratefully acknowledge the contributions to this chapter of former co-author and former partner Robert Evans III, and the contribu- tions of Shearman & Sterling LLP associate Steven R. Blau for his work coordinating the chapter. (Broker-Dealer Reg., Rel. #14, 9/18) 49–1 © Practising Law Institute BROKER-DEALER REGULATION [B][5] Physical and Electronic Separation [B][6] Training and Education Programs [B][7] Employee Attestation § 49:1.3 Sales Practices; Testing-the-Waters and Gun-Jumping § 49:1.4 2012 OCIE Report on the Use of Material Nonpublic Information by Broker-Dealers [A] Sources of MNPI [B] Control Structure [B][1] Issues Identified [B][2] Control Room [B][3] “Above the Wall” Designations [B][4] Materiality Determinations [B][5] Oversight of Non-Transactional Sources of MNPI [B][6] Compliance with Oral Confidentiality Agreements [B][7] Personal Trading Problems [C] Access Controls [C][1] -
Understanding Interest Rates Mishkin, Chapter 4:Part B (Pp. 80-89)
Understanding Interest Rates Mishkin, Chapter 4:Part B (pp. 80-89) Prof. Leigh Tesfatsion Economics Department Iowa State University Last Revised: 21 February 2011 Mishkin Chapter 4: Part B (pp. 80-89) Key In-Class Discussion Questions & Issues Reading bond pages in financial news outlets “Interest rate” versus “return rate” “Nominal rate” vs. “real rate” What is “interest rate risk”? Whose risk is it? Reading Bond Pages •• WeWe willwill taketake aa looklook atat aa typicaltypical bondbond pagepage appearingappearing inin financialfinancial sectionsection ofof aa newspapernewspaper •• TheseThese bondbond pagespages covercover – U.S. Treasury (“government”) bonds and notes – U.S. Treasury bills – Corporate bonds Example of a Bond Page of a Newspaper Wall Street Journal, Jan 12, 2006 Types of U.S. Government Bonds Treasury Bills (Zero-coupon) discount bonds Face value paid at maturity Maturities up to one year Treasury Notes Coupon bonds Coupon payments paid semiannually Face value paid at maturity Maturities from 1 to 10 years U.S. Government Bonds…Continued Treasury Bonds Coupon bonds Coupon payments paid semiannually Face value paid at maturity Maturities over 10 years The 30-year bond is called the long bond. Treasury Strips Collection of (zero-coupon) discount bonds Created by separately “stripping” the coupons and face value from a Treasury bond or note. U.S. Government Bonds … Continued • Low default risk. Considered to be risk-free. • Interest exempt from state and local taxes. • Initial issues sold in Treasury auctions (primary market) • Thereafter regularly traded (resold) in an OTC market (secondary market). Corporate Bonds • Corporate Coupon Bonds − Secured by real property − Ownership of the property reverts to the bondholders upon default. -
Estimation of Zero-Coupon Curves in Datametrics
Estimation of zero-coupon curves in DataMetrics Allan Malz RiskMetrics Group [email protected] DataMetrics is modifying its technique for estimating zero-coupon interbank and gov- ernment benchmark curves. The new algorithm is employed together with additional synchronized input data to deliver better-quality curves. The modified technique assumes the instantaneous forward rate is a constant between the maturity dates of observable interest rates. Together, the flat forward technique and new input data increase pricing and risk measurement accuracy, particularly at the short end. The flat forward technique is shown to be preferable to plausible alternative approaches. DataMetrics is modifying the bootstrapping technique it uses to estimate zero-coupon curves. The modified bootstrapping technique assumes the instantaneous forward interest rate is a constant between observed bond or other security maturities. We therefore refer to it as the “flat forward” technique. DataMetrics applies it to a range of interbank and government benchmark zero-coupon curves in both key currencies and emerging markets. The new algorithm is being employed together with additional input data to deliver better-quality curves. Together, the flat forward technique and new input data provide several advantages: • The underlying data for the interbank and government curves, particularly the government bonds, can be sparse. For example, there are only 6 U.S. Treasury benchmarks, of which 3 are T-bills and 3 are coupon bonds. The flat forward approach avoids potentially adding spurious information to that contained in the modest available underlying data set, while still permitting accurate pricing. • It permits DataMetrics to estimate time series of spot interest rates with any time to maturity ranging from overnight to 30 years, applying any desired compounding interval or day count convention uniformly across the curve. -
Fabozzi Course.Pdf
Asset Valuation Debt Investments: Analysis and Valuation Joel M. Shulman, Ph.D, CFA Study Session # 15 – Level I CFA CANDIDATE READINGS: Fixed Income Analysis for the Chartered Financial Analyst Program: Level I and II Readings, Frank J. Fabozzi (Frank J. Fabozzi Associates, 2000) “Introduction to the Valuation of Fixed Income Securities,” Ch. 5 “Yield Measures, Spot Rates, and Forward Rates,” Ch. 6 “Introduction to Measurement of Interest Rate Risk,” Ch. 7 © 2002 Shulman Review/The Princeton Review Fixed Income Valuation 2 Learning Outcome Statements Introduction to the Valuation of Fixed Income Securities Chapter 5, Fabozzi The candidate should be able to a) Describe the fundamental principles of bond valuation; b) Explain the three steps in the valuation process; c) Explain what is meant by a bond’s cash flow; d) Discuss the difficulties of estimating the expected cash flows for some types of bonds and identify the bonds for which estimating the expected cash flows is difficult; e) Compute the value of a bond, given the expected cash flows and the appropriate discount rates; f) Explain how the value of a bond changes if the discount rate increases or decreases and compute the change in value that is attributable to the rate change; g) Explain how the price of a bond changes as the bond approaches its maturity date and compute the change in value that is attributable to the passage of time; h) Compute the value of a zero-coupon bond; i) Compute the dirty price of a bond, accrued interest, and clean price of a bond that is between coupon -
Credit Derivatives – Pricing and Bootstrapping
Credit Derivatives – Pricing and Bootstrapping Author: Mi Sun University College London MSc Financial Computing Project 2009-2010 Project Supervisor: Christopher Clack Submission Date: 15 September 2010 Disclaimer: This report is submitted as part requirement for the MSc Degree in Financial Computing at University College London. It is substantially the result of my own work except where explicitly indicated in the text. The report may be freely copied and distributed provided the source is explicitly acknowledged. MSc Financial Computing Project 2009-2010 by Mi Sun Abstract This project explores different pricing models for credit derivatives and implements the bootstrapping method for the survival curve and base correlation. The credit derivatives discussed in this report include credit default swap (CDS) and collateralized debt obligation (CDO). The main aim of the project is to make sure that there is no arbitrage opportunity between quoted (CDS and index CDO tranches) instruments and unquoted (bespoke CDO tranches) instruments. In doing so, the objectives include obtaining the CDS survival curve from market spreads. Then together with the standardized index CDO tranche spreads, the CDS survival curve is an input parameter for obtaining the base correlation. Finally using the base correlation, the bespoke (i.e. customized) CDO tranche can be priced consistently. There are seven chapters. The first one introduces the background and underlying logic of the whole project. The second chapter starts to introduce the pricing of credit default swaps (CDSs), and discusses the bootstrapping and interpolation of the CDS survival curve. The third chapter moves on to introduce the pricing of collateralized debt obligations (CDOs), and investigates two models for building the CDO tranche survival curve. -
Bootstrapping the Illiquidity by Ametrano and Bianchetti
BOOTSTRAPPING THE ILLIQUIDITY MULTIPLE YIELD CURVES CONSTRUCTION FOR MARKET COHERENT FORWARD RATES ESTIMATION FERDINANDO M. AMETRANO AND MARCO BIANCHETTI Abstract. The large basis spreads observed on the interest rate mar- ket since the liquidity crisis of summer 2007 imply that di®erent yield curves are required for market coherent estimation of forward rates with di®erent tenors (e.g. Euribor 3 months, Euribor 6 months, etc.). In this paper we review the methodology for bootstrapping multi- ple interest rate yield curves, each homogeneous in the underlying rate tenor, from non-homogeneous plain vanilla instruments quoted on the market, such as Deposits, Forward Rate Agreements, Futures, Swaps, and Basis Swaps. The approach includes turn of year e®ects and is ro- bust to deliver smooth yield curves and to ensure non-negative rates also in highly stressed market situations, characterized by crazy roller coaster shapes of the market quotations. The concrete EUR market case is analyzed in detail, using the open source QuantLib implementation of the proposed algorithms. 1. Introduction Pricing complex interest rate derivatives requires modeling the future dy- namics of the yield curve term structure. Most of the literature assumes the existence of the current yield curve as given, and its construction is often neglected, or even obscured, as it is considered more an art than a sci- ence. Actually any yield curve term structure modeling approach will fail to produce good/reasonable prices if the current term structure is not correct. Financial institutions, software houses and practitioners have developed their own proprietary methodologies in order to extract the yield curve term structure from quoted prices of a ¯nite number of liquid market instruments. -
Credit Curve Estimation and Corporate Bonds in the South African Market
Credit Curve Estimation and Corporate Bonds in the South African Market by Peter-John Clift Assignment presented in partial fulfilment of the requirements for the degree of Master of Commerce in Financial Risk Management in the Faculty of Economics and Management Sciences at Stellenbosch University Supervisor: Prof. W.J. Conradie March 2020 Stellenbosch University https://scholar.sun.ac.za ii PLAGIARISM DECLARATION 1. Plagiarism is the use of ideas, material and other intellectual property of another’s work and to present it as my own. 2. I agree that plagiarism is a punishable offence because it constitutes theft. 3. I also understand that direct translations are plagiarism. 4. Accordingly, all quotations and contributions from any source whatsoever (including the internet) have been cited fully. I understand that the reproduction of text without quotation marks (even when the source is cited) is plagiarism. 5. I declare that the work contained in this assignment, except otherwise stated, is my original work and that I have not previously (in its entirety or in part) submitted it for grading in this module/assignment or another module/assignment. Copyright © 2020 Stellenbosch University All rights reserved Stellenbosch University https://scholar.sun.ac.za iii Acknowledgements Prof. W.J. Conradie for his patience and guidance throughout. In my almost decade long relationship with Stellenbosch University he has been instrumental in influencing and shaping my future. Mr Carel van der Merwe (almost Dr), who provided the initial topic, as well as valuable and insightful guidance around numerous technical aspects. The Department of Statistics and Actuarial Science, for the valuable education I received, and excellence exhibited by everyone involved in this department.