Valuing Financial Futures with a Stochastic, Endogenous Index-Rate Covariance
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Updated Trading Participants' Trading Manual
Annexure 3 TRADING MANUAL BURSA MALAYSIA DERIVATIVES BHD TRADING MANUAL (Version 4.10) This manual is the intellectual property of BURSA MALAYSIA. No part of the manual is to be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording or any information storage and retrieval system, without permission in writing from Head of BMD Exchange Operations. TRADING MANUAL Version History Version Date Author Comments V 1.0 9 Aug 2010 BMDB Initial Version V 1.1 27 Aug 2010 BMDB Updated # 6.6.3 Review of Trades – Price Adjustments and Cancellations V1.2 6 Sep 2010 BMDB Inserted 15. Operator ID (“Tag 50 ID”) Required for All BMD orders traded on CME Globex V1.3 9 Sep 2010 BMDB Update 1. Introduction – 1.6 TPs’ compliance in relation to access, connectivity, specification or use of CME Globex V1.4 13 Sep 2010 BMDB Updated 13. Messaging And Market Performance Protection Policy V1.5 9 Nov 2011 BMDB Inserted 16 Negotiated Large Trade V1.6 18 Nov 2011 BMDB Amended section 16 for typo errors, consistency and clarity. V1.7 24 Nov 2011 BMDB Amended section 16 - Extended NLT cut-off time for FKLI, FKB3 and FMG5 to 4.00pm and for FCPO to 5.00pm. -Amended the NLT Facility Trade Registration form. V1.8 10 Feb 2012 BMDB Updated section 11 EFP to EFRP V1.9 23 Mar 2012 BMDB Amended sections 11 and 16 (forms and processes) V2.0 5 Apr 2012 BMDB Renamed to “Trading Manual” V2.1 14 May 2012 BMDB Updated Section 6 for OKLI and to align with CME practice V2.2 29 May 2012 BMDB i) Updated for OCPO ii) Change of terminology to be consistent with CME iii) Updated Sections 7.7 & 14.1 for consistency with Rules iv) Updated Sections 12.3 & 12.4 for accuracy v) Updated Section 3.1 on options naming convention V2.3 18 Feb 2013 BMDB Updated Section 16 NLT V2.4 3 Apr 2013 BMDB Updated Section 9 Circuit Breaker on timing V2.5 2 Jul 2013 BMDB Updated FGLD. -
Term Structure Models of Commodity Prices
TERM STRUCTURE MODELS OF COMMODITY PRICES Cahier de recherche du Cereg n°2003–9 Delphine LAUTIER ABSTRACT. This review article describes the main contributions in the literature on term structure models of commodity prices. A first section is devoted to the theoretical analysis of the term structure. It confines itself primarily to the traditional theories of commodity prices and to their explanation of the relationship between spot and futures prices. The normal backwardation and storage theories are however a bit limited when the whole term structure is taken into account. As a result, there is a need for an extension of the analysis for long-term horizon, which constitutes the second point of the section. Finally, a dynamic analysis of the term structure is presented. Section two is centred on term structure models of commodity prices. The presentation shows that these models differ on the nature and the number of factors used to describe uncertainty. Four different factors are generally used: the spot price, the convenience yield, the interest rate, and the long-term price. Section three reviews the main empirical results obtained with term structure models. First of all, simulations highlight the influence of the assumptions concerning the stochastic process retained for the state variables and the number of state variables. Then, the method usually employed for the estimation of the parameters is explained. Lastly, the models’ performances, namely their ability to reproduce the term structure of commodity prices, are presented. Section four exposes the two main applications of term structure models: hedging and valuation. Section five resumes the broad trends in the literature on commodity pricing during the 1990s and early 2000s, and proposes futures directions for research. -
EC3070 FINANCIAL DERIVATIVES GLOSSARY Ask Price the Bid Price
EC3070 FINANCIAL DERIVATIVES GLOSSARY Ask price The bid price. Arbitrage An arbitrage is a financial strategy yielding a riskless profit and requiring no investment. It commonly amounts to the successive purchase and sale, or vice versa, of an asset at differing prices in different markets. i.e. it involves buying cheap and selling dear or selling dear and buying cheap. Bid A bid is a proposal to buy. A typical convention for vocalising a bid is “p for n”: p being the proposed unit price and n being the number of units or contracts demanded. Backwardation Backwardation describes a situation where the amount of money required for the future delivery of an item is lower than the amount required for immediate delivery. Backwardation is a signal that the item in question is in short supply. The opposite market condition to backwardation is known as contango, which is when the spot price is lower than the futures price. In fact, there is some ambiguity in the usage of the term. According to the definition above, backwardation is when Fτ|0 <S0, where Fτ|0 is the current price for a delivery at time τ and S0 is the current spot price. In an alternative definition, backwardation exists when Fτ|0 <E(Fτ|t) with 0 <t<τ, which is when the expected future price at a later date exceeds the futures price settled at time t = 0. In modern usage, this is called normal backwardation. Buyer A buyer is a long position holder who has agreed to accept the delivery of a commodity at some future date. -
The Pricing of Stock Index Futures During the Asian Financial Crisis: Evidence from Four Asian Index Futures Markets”
“The Pricing of Stock Index Futures During the Asian Financial Crisis: Evidence from Four Asian Index Futures Markets” AUTHORS Janchung Wang Janchung Wang (2007). The Pricing of Stock Index Futures During the Asian ARTICLE INFO Financial Crisis: Evidence from Four Asian Index Futures Markets. Investment Management and Financial Innovations, 4(2) RELEASED ON Saturday, 23 June 2007 JOURNAL "Investment Management and Financial Innovations" FOUNDER LLC “Consulting Publishing Company “Business Perspectives” NUMBER OF REFERENCES NUMBER OF FIGURES NUMBER OF TABLES 0 0 0 © The author(s) 2021. This publication is an open access article. businessperspectives.org Investment Management and Financial Innovations, Volume 4, Issue 2, 2007 77 THE PRICING OF STOCK INDEX FUTURES DURING THE ASIAN FINANCIAL CRISIS: EVIDENCE FROM FOUR ASIAN INDEX FUTURES MARKETS Janchung Wang* Abstract Market imperfections are traditionally measured individually. Hsu and Wang (2004) and Wang and Hsu (2006) recently proposed the concept of the degree of market imperfections, which reflects the total effects of all market imperfections between the stock index futures market and its underlying index market when implementing arbitrage activities. This study discusses some useful applications of this concept. Furthermore, Hsu and Wang (2004) developed an imperfect market model for pricing stock index futures. This study further compares the relative pricing perform- ance of the cost of carry and the imperfect market models for four Asian index futures markets (particularly for the Asian crisis period). The evidence indicates that market imperfections are im- portant in determining the stock index futures prices for immature markets and turbulent periods with high market imperfections. Nevertheless, market imperfections are excluded from the cost of carry model. -
Foreign Exchange Training Manual
CONFIDENTIAL TREATMENT REQUESTED BY BARCLAYS SOURCE: LEHMAN LIVE LEHMAN BROTHERS FOREIGN EXCHANGE TRAINING MANUAL Confidential Treatment Requested By Lehman Brothers Holdings, Inc. LBEX-LL 3356480 CONFIDENTIAL TREATMENT REQUESTED BY BARCLAYS SOURCE: LEHMAN LIVE TABLE OF CONTENTS CONTENTS ....................................................................................................................................... PAGE FOREIGN EXCHANGE SPOT: INTRODUCTION ...................................................................... 1 FXSPOT: AN INTRODUCTION TO FOREIGN EXCHANGE SPOT TRANSACTIONS ........... 2 INTRODUCTION ...................................................................................................................... 2 WJ-IAT IS AN OUTRIGHT? ..................................................................................................... 3 VALUE DATES ........................................................................................................................... 4 CREDIT AND SETTLEMENT RISKS .................................................................................. 6 EXCHANGE RATE QUOTATION TERMS ...................................................................... 7 RECIPROCAL QUOTATION TERMS (RATES) ............................................................. 10 EXCHANGE RATE MOVEMENTS ................................................................................... 11 SHORTCUT ............................................................................................................................... -
Copyrighted Material
k Trim Size: 6in x 9in Sinclair583516 bindex.tex V1 - 05/04/2020 9:51 P.M. Page 219 INDEX Bid-ask spreads (total cost component), 200 A Bitcoin, 172–173, 172f Acceleration, 60 Black-Scholes-Merton (BSM) Adjustment repair, 86 assumptions/equation/model, 2–4, 6, Alpha decay, 15–16 Anchoring, 19 108, 113, 115, 183, 192 Arbitrage counterparty risk, 178–179 Black-Scholes-Merton (BSM) PDE, 5, 116 Arbitrage pricing theory (APT), 63 Bonds, 49–50 Bonferroni’s correction, usage, 23 k ASPX option profits, taxation, 187 219 k Asymmetric implied volatility skew, 191 Broken wing butterflies/condors, 99–100 ATM, 104, 106t, 123, 131t, 137 Butterflies, 95–100, 96f, 98t At-the-money covered call, delta level, 135 BXMD/BXM/BXY, 133, 134t Autocorrelation, 73f, 91 Availability heuristic, 19 C Average return, calculation, 24 Calendar spread, 100–102 Calls, 55f, 129–136, 129f, 132f, 142 B call spread, 130f, 131t, 142f, 143t Back-tested rules, performer sample, 23 implied volatility, level (example), 140t Backwardation, 61, 62 put-call parity/relationship, 95, 115, 116 Badly priced butterfly, returns (summary strike call, 118f, 120f statistics), 98t Capital asset pricing model (CAPM), Badly priced condor, returns (summary development, 63 statistics), 98t Cash flows, taxation rate, 6 Bankruptcy, risk (increase),COPYRIGHTED66 Catastrophe MATERIAL theory, 20 Bayesian model, usage, 30 Chicago Board Options Exchange (CBOE), 16, Behavioral biases, inefficiency, 67–68 36, 45–46, 133, 134f Behavioral finance, 16–21 CNDR index, 45, 45f Best, defining (possibility), 121 Commissions (total cost component), 200 Beta, 67–68, 68t, 82, 196 Commodities, 47–49, 48t, 49t BFLY index, 45, 46f Condors, 95–100, 96f, 97f, 98t, 104t Biases, 18–20, 23, 30, 113 Confidence, 61–62, 71–75, 80 k k Trim Size: 6in x 9in Sinclair583516 bindex.tex V1 - 05/04/2020 9:51 P.M. -
Essays in Risk Management for Crude Oil Markets
Essays in Risk Management for Crude Oil Markets by Abdullah Al Mansour A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree of Doctor of Philosophy in Applied Economics Waterloo, Ontario, Canada, 2012 c Abdullah Al Mansour 2012 I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, including any required final revisions, as accepted by my examiners. I understand that my thesis may be made electronically available to the public. ii Abstract This thesis consists of three essays on risk management in crude oil markets. In the first essay, the valuation of an oil sands project is studied using real options approach. Oil sands production consumes substantial amount of natural gas during extracting and upgrading. Natural gas prices are known to be stochastic and highly volatile which introduces a risk factor that needs to be taken into account. The essay studies the impact of this risk factor on the value of an oil sands project and its optimal operation. The essay takes into account the co-movement between crude oil and natural gas markets and, accordingly, proposes two models: one incorporates a long-run link between the two markets while the other has no such link. The valuation problem is solved using the Least Square Monte Carlo (LSMC) method proposed by Longstaff and Schwartz (2001) for valuing American options. The valuation results show that incorporating a long-run relationship between the two markets is a very crucial decision in the value of the project and in its optimal operation. -
Momentum Strategies in Commodity Futures Markets
EDHEC RISK AND ASSET MANAGEMENT RESEARCH CENTRE 393-400 promenade des Anglais 06202 Nice Cedex 3 Tel.: +33 (0)4 93 18 32 53 E-mail: [email protected] Web: www.edhec-risk.com Momentum Strategies in Commodity Futures Markets Joëlle Miffre Associate Professor of Finance, EDHEC Business School Georgios Rallis Cass Business School, Ph.D. Student ABSTRACT The article tests for the presence of short-term continuation and long-term reversal in commodity futures prices. While contrarian strategies do not work, the article identifies 13 profitable momentum strategies that generate 9.38% average return a year. A closer analysis of the constituents of the long-short portfolios reveals that the momentum strategies buy backwardated contracts and sell contangoed contracts. The correlation between the momentum returns and the returns of traditional asset classes is also found to be low, making the commodity-based relative-strength portfolios excellent candidates for inclusion in well-diversified portfolios. Keywords: Commodity futures, Momentum, Backwardation, Contango, Diversification JEL classification codes: G13, G14 Author for correspondence: Joëlle Miffre, Associate Professor of Finance, EDHEC Business School, 393 Promenade des Anglais, 06202, Nice, France, Tel: +33 (0)4 93 18 32 55, e-mail: [email protected] A version of this paper is forthcoming in the Journal of Banking and Finance. The authors would like to thank Chris Brooks and two anonymous referees for helpful comments. EDHEC is one of the top five business schools in France owing to the high quality of its academic staff (104 permanent lecturers from France and abroad) and its privileged relationship with professionals that the school has been developing since its establishment in 1906. -
Optimal Hedging Under Departures from the Cost-Of-Carry Valuation: Evidence from the Spanish Stock Index Futures Market
Journal of Banking & Finance 27 (2003) 1053–1078 www.elsevier.com/locate/econbase Optimal hedging under departures from the cost-of-carry valuation: Evidence from the Spanish stock index futures market Juan A. Lafuente a, Alfonso Novales b,* a Departamento de Finanzas y Contabilidad, Universidad Jaume I, 12071 Castellon, Spain b Departamento de Economııa Cuantitativa, Universidad Complutense, Somosaguas, 28223 Madrid, Spain Received 2 October 2000; accepted 11 January 2002 Abstract We provide an analytical discussion of the optimal hedge ratio under discrepancies between the futures market price and its theoretical valuation according to the cost-of-carry model. As- suming a geometric Brownian motion for spot prices, we model mispricing as a specific noise component in the dynamics of futures market prices. Empirical evidence on the model is pro- vided for the Spanish stock index futures. Ex-ante simulations with actual data reveal that hedge ratios that take into account the estimated, time varying, correlation between the com- mon and specific disturbances, lead to using a lower number of futures contracts than under a systematic unit ratio, without generally losing hedging effectiveness, while reducing transaction costs and capital requirements. Besides, the reduction in the number of contracts can be sub- stantial over some periods. Finally, a mean–variance expected utility function suggests that the economic benefits from an optimal hedge can be substantial. Ó 2003 Elsevier Science B.V. All rights reserved. JEL classification: C51; G11; G13 Keywords: Optimal hedging; Futures contract; Stock index; GARCH models; Mispricing 1. Introduction Since its launching in January 1992, the Ibex 35 futures contract quickly became the most actively traded derivative contract in Meff Renta Variable, the Spanish * Corresponding author. -
Options Trading
OPTIONS TRADING: THE HIDDEN REALITY RI$K DOCTOR GUIDE TO POSITION ADJUSTMENT AND HEDGING Charles M. Cottle ● OPTIONS: PERCEPTION AND DECEPTION and ● COULDA WOULDA SHOULDA revised and expanded www.RiskDoctor.com www.RiskIllustrated.com Chicago © Charles M. Cottle, 1996-2006 All rights reserved. No part of this publication may be printed, reproduced, stored in a retrieval system, or transmitted, emailed, uploaded in any form or by any means, electronic, mechanical photocopying, recording, or otherwise, without the prior written permission of the publisher. This publication is designed to provide accurate and authoritative information in regard to the subject matter covered. It is sold with the understanding that neither the author or the publisher is engaged in rendering legal, accounting, or other professional service. If legal advice or other expert assistance is required, the services of a competent professional person should be sought. From a Declaration of Principles jointly adopted by a Committee of the American Bar Association and a Committee of Publishers. Published by RiskDoctor, Inc. Library of Congress Cataloging-in-Publication Data Cottle, Charles M. Adapted from: Options: Perception and Deception Position Dissection, Risk Analysis and Defensive Trading Strategies / Charles M. Cottle p. cm. ISBN 1-55738-907-1 ©1996 1. Options (Finance) 2. Risk Management 1. Title HG6024.A3C68 1996 332.63’228__dc20 96-11870 and Coulda Woulda Shoulda ©2001 Printed in the United States of America ISBN 0-9778691-72 First Edition: January 2006 To Sarah, JoJo, Austin and Mom Thanks again to Scott Snyder, Shelly Brown, Brian Schaer for the OptionVantage Software Graphics, Allan Wolff, Adam Frank, Tharma Rajenthiran, Ravindra Ramlakhan, Victor Brancale, Rudi Prenzlin, Roger Kilgore, PJ Scardino, Morgan Parker, Carl Knox and Sarah Williams the angel who revived the Appendix and Chapter 10. -
ERIC C. CHANG Office Address Shanghai Advanced Institute Of
ERIC C. CHANG Office Address Shanghai Advanced Institute of Finance Shanghai Jiaotong University Room 610, 211 West Huaihai Road Shanghai, P.R. China, 200030 Tel: 86-21-6293-2129 E-mail: [email protected] EDUCATION 1982 Ph.D. in Finance (Major) and in Statistics and Econometrics (Minor) Purdue University (West Lafayette, Indiana USA) 1979 MBA in Finance Wright State University (Dayton, Ohio USA) 1974 B.S. in Civil Engineering Cheng Kung University (Taiwan) ACADEMIC APPOINTMENTS 2018 – present Professor in Finance Shanghai Advanced Institute of Finance Shanghai Jiaotong University (Shanghai, China) 2007 – 2018 Chung Hon-Dak Professor in Finance Faculty of Business and Economics The University of Hong Kong (Hong Kong) 1998 – 2018 Chair Professor of Finance (tenured) School of Business / School of Economics and Finance Faculty of Business and Economics The University of Hong Kong (Hong Kong) 1995 – 1998 Invesco Chair Professor of International Finance (tenured) The DuPree College of Management Georgia Institute of Technology (Atlanta, Georgia, USA) 2003 – 2009 Visiting Professor Executive MBA Program Fudan University (Shanghai, PRC) 2005 – 2009 Visiting Professor Executive Education Program Shenzhen Graduate School of Business Peking University (Shenzhen, PRC) 30/06/2019 Page 1 1986 – 1995 Assistant, Associate and Professor in Finance (tenured) College of Business and Administration University of Maryland (College Park, Maryland, USA) 1992 – 1994 Reader (Visiting) in Finance School of Business and Management Hong Kong University of -
Designing and Applying a Nonparametric Option Valuation Model
DOI: 10.5817/FAI2016-1-3 No. 1/2016 Designing and Applying a Nonparametric Option Valuation Model Jan Vlachý Czech Technical University in Prague Masaryk Institute of Advanced Studies Kolejní 2637/2a, 160 00 Praha 6 E-mail: [email protected] Abstract: This paper derives, tests and discusses a comprehensive and easy to use nonparametric option-valuation model, using a representative set of historical data on underlying asset returns jointly with an assumption of minimalistic implied information on current market trend and volatility expectations. Its testing on empirical data from Warsaw Stock Exchange trading for two distinct periods of 2014 suggests that such distribution-free models are capable of delivering useful market insights as well as applicability features, in particular wherever derivative markets are relatively new, incomplete, illiquid, or with regard to the valuation of real options. Keywords: option pricing, nonparametric simulation, inefficient markets, Warsaw Stock Exchange, WIG 20 Index JEL codes: C14, G13 Introduction Since inception of the Black-Scholes model (B-S), two distinct theoretical approaches have been predominantly used to derive the value of financial options (Black and Scholes, 1973, applied both). The first (equilibrium models), represented by e.g. Merton (1976), Cox et al. (1985), Hull and White (1987), assumes stochastic processes spanning the economy and estimates their parameters. The other (no-arbitrage models), by e.g. Cox and Ross (1976), Harrison and Kreps (1979), Rubinstein (1994), tries to calibrate to a set of market prices in complete markets. Both methods derive from the premise that all market prices are correct (in other words, markets are efficient) and therefore they cannot, by definition, allow profit opportunities.