Causes of Market Anomalies of Crude Oil Calendar Spreads: Does Theory of Storage Address the Issue?”
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Machine Learning Based Intraday Calibration of End of Day Implied Volatility Surfaces
DEGREE PROJECT IN MATHEMATICS, SECOND CYCLE, 30 CREDITS STOCKHOLM, SWEDEN 2020 Machine Learning Based Intraday Calibration of End of Day Implied Volatility Surfaces CHRISTOPHER HERRON ANDRÉ ZACHRISSON KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF ENGINEERING SCIENCES Machine Learning Based Intraday Calibration of End of Day Implied Volatility Surfaces CHRISTOPHER HERRON ANDRÉ ZACHRISSON Degree Projects in Mathematical Statistics (30 ECTS credits) Master's Programme in Applied and Computational Mathematics (120 credits) KTH Royal Institute of Technology year 2020 Supervisor at Nasdaq Technology AB: Sebastian Lindberg Supervisor at KTH: Fredrik Viklund Examiner at KTH: Fredrik Viklund TRITA-SCI-GRU 2020:081 MAT-E 2020:044 Royal Institute of Technology School of Engineering Sciences KTH SCI SE-100 44 Stockholm, Sweden URL: www.kth.se/sci Abstract The implied volatility surface plays an important role for Front office and Risk Manage- ment functions at Nasdaq and other financial institutions which require mark-to-market of derivative books intraday in order to properly value their instruments and measure risk in trading activities. Based on the aforementioned business needs, being able to calibrate an end of day implied volatility surface based on new market information is a sought after trait. In this thesis a statistical learning approach is used to calibrate the implied volatility surface intraday. This is done by using OMXS30-2019 implied volatil- ity surface data in combination with market information from close to at the money options and feeding it into 3 Machine Learning models. The models, including Feed For- ward Neural Network, Recurrent Neural Network and Gaussian Process, were compared based on optimal input and data preprocessing steps. -
Futures and Options Workbook
EEXAMININGXAMINING FUTURES AND OPTIONS TABLE OF 130 Grain Exchange Building 400 South 4th Street Minneapolis, MN 55415 www.mgex.com [email protected] 800.827.4746 612.321.7101 Fax: 612.339.1155 Acknowledgements We express our appreciation to those who generously gave their time and effort in reviewing this publication. MGEX members and member firm personnel DePaul University Professor Jin Choi Southern Illinois University Associate Professor Dwight R. Sanders National Futures Association (Glossary of Terms) INTRODUCTION: THE POWER OF CHOICE 2 SECTION I: HISTORY History of MGEX 3 SECTION II: THE FUTURES MARKET Futures Contracts 4 The Participants 4 Exchange Services 5 TEST Sections I & II 6 Answers Sections I & II 7 SECTION III: HEDGING AND THE BASIS The Basis 8 Short Hedge Example 9 Long Hedge Example 9 TEST Section III 10 Answers Section III 12 SECTION IV: THE POWER OF OPTIONS Definitions 13 Options and Futures Comparison Diagram 14 Option Prices 15 Intrinsic Value 15 Time Value 15 Time Value Cap Diagram 15 Options Classifications 16 Options Exercise 16 F CONTENTS Deltas 16 Examples 16 TEST Section IV 18 Answers Section IV 20 SECTION V: OPTIONS STRATEGIES Option Use and Price 21 Hedging with Options 22 TEST Section V 23 Answers Section V 24 CONCLUSION 25 GLOSSARY 26 THE POWER OF CHOICE How do commercial buyers and sellers of volatile commodities protect themselves from the ever-changing and unpredictable nature of today’s business climate? They use a practice called hedging. This time-tested practice has become a stan- dard in many industries. Hedging can be defined as taking offsetting positions in related markets. -
Evaluating the Performance of the WTI
An Evaluation of the Performance of Oil Price Benchmarks During the Financial Crisis Craig Pirrong Professor of Finance Energy Markets Director, Global Energy Management Institute Bauer College of Business University of Houston I. IntroDuction The events of late‐summer, 2008 through the spring of 2009 have attracted considerable attention to the performance of oil price benchmarks, most notably the Chicago Mercantile Exchange’s West Texas Intermediate crude oil contract (“WTI” or “CL” hereafter) and ICE Futures’ Brent crude oil contract (“Brent futures” or “CB” hereafter). In particular, the behavior of spreads between the prices of futures contracts of different maturities, and between futures prices and cash prices during the period following the Lehman Brothers collapse has sparked allegations that futures prices have become disconnected from the underlying cash market fundamentals. The WTI contract has been the subject of particular criticisms alleging the unrepresentativeness of the Midcontinent market as a global price benchmark. I have analyzed extensive data from the crude oil cash and futures markets to evaluate the performance of the WTI and Brent futures contracts during the LH2008‐FH2009 period. Although the analysis focuses on this period, it relies on data extending back to 1990 in order to put the performance in historical context. I have also incorporated some data on physical crude market fundamentals, most 1 notably stocks, as these are essential in providing an evaluation of contract performance and the relation between pricing and fundamentals. My conclusions are as follows: 1. The October, 2008‐March 2009 period was one of historically unprecedented volatility. By a variety of measures, volatility in this period was extremely high, even compared to the months surrounding the First Gulf War, previously the highest volatility period in the modern oil trading era. -
VERTICAL SPREADS: Taking Advantage of Intrinsic Option Value
Advanced Option Trading Strategies: Lecture 1 Vertical Spreads – The simplest spread consists of buying one option and selling another to reduce the cost of the trade and participate in the directional movement of an underlying security. These trades are considered to be the easiest to implement and monitor. A vertical spread is intended to offer an improved opportunity to profit with reduced risk to the options trader. A vertical spread may be one of two basic types: (1) a debit vertical spread or (2) a credit vertical spread. Each of these two basic types can be written as either bullish or bearish positions. A debit spread is written when you expect the stock movement to occur over an intermediate or long- term period [60 to 120 days], whereas a credit spread is typically used when you want to take advantage of a short term stock price movement [60 days or less]. VERTICAL SPREADS: Taking Advantage of Intrinsic Option Value Debit Vertical Spreads Bull Call Spread During March, you decide that PFE is going to make a large up move over the next four months going into the Summer. This position is due to your research on the portfolio of drugs now in the pipeline and recent phase 3 trials that are going through FDA approval. PFE is currently trading at $27.92 [on March 12, 2013] per share, and you believe it will be at least $30 by June 21st, 2013. The following is the option chain listing on March 12th for PFE. View By Expiration: Mar 13 | Apr 13 | May 13 | Jun 13 | Sep 13 | Dec 13 | Jan 14 | Jan 15 Call Options Expire at close Friday, -
A Glossary of Securities and Financial Terms
A Glossary of Securities and Financial Terms (English to Traditional Chinese) 9-times Restriction Rule 九倍限制規則 24-spread rule 24 個價位規則 1 A AAAC see Academic and Accreditation Advisory Committee【SFC】 ABS see asset-backed securities ACCA see Association of Chartered Certified Accountants, The ACG see Asia-Pacific Central Securities Depository Group ACIHK see ACI-The Financial Markets of Hong Kong ADB see Asian Development Bank ADR see American depositary receipt AFTA see ASEAN Free Trade Area AGM see annual general meeting AIB see Audit Investigation Board AIM see Alternative Investment Market【UK】 AIMR see Association for Investment Management and Research AMCHAM see American Chamber of Commerce AMEX see American Stock Exchange AMS see Automatic Order Matching and Execution System AMS/2 see Automatic Order Matching and Execution System / Second Generation AMS/3 see Automatic Order Matching and Execution System / Third Generation ANNA see Association of National Numbering Agencies AOI see All Ordinaries Index AOSEF see Asian and Oceanian Stock Exchanges Federation APEC see Asia Pacific Economic Cooperation API see Application Programming Interface APRC see Asia Pacific Regional Committee of IOSCO ARM see adjustable rate mortgage ASAC see Asian Securities' Analysts Council ASC see Accounting Society of China 2 ASEAN see Association of South-East Asian Nations ASIC see Australian Securities and Investments Commission AST system see automated screen trading system ASX see Australian Stock Exchange ATI see Account Transfer Instruction ABF Hong -
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. -
Spread Scanner Guide Spread Scanner Guide
Spread Scanner Guide Spread Scanner Guide ..................................................................................................................1 Introduction ...................................................................................................................................2 Structure of this document ...........................................................................................................2 The strategies coverage .................................................................................................................2 Spread Scanner interface..............................................................................................................3 Using the Spread Scanner............................................................................................................3 Profile pane..................................................................................................................................3 Position Selection pane................................................................................................................5 Stock Selection pane....................................................................................................................5 Position Criteria pane ..................................................................................................................7 Additional Parameters pane.........................................................................................................7 Results section .............................................................................................................................8 -
Encana Distinguished Lecture Series
Oil Futures Prices and OPEC Spare Capacity J.P. Morgan Center for Commodities Encana Distinguished Lecture Series September 18, 2014 Ms. Hilary Till, Principal, Premia Risk Consultancy, Inc., http://www.premiarisk.com; Research Associate, EDHEC-Risk Institute, http://www.edhec-risk.com; and Co-Editor, Intelligent Commodity Investing, http://www.riskbooks.com/intelligent-commodity-investing Disclaimers • This presentation is provided for educational purposes only and should not be construed as investment advice or an offer or solicitation to buy or sell securities or other financial instruments. • The opinions expressed during this presentation are the personal opinions of Hilary Till and do not necessarily reflect those of other organizations with which Ms. Till is affiliated. • The information contained in this presentation has been assembled from sources believed to be reliable, but is not guaranteed by the presenter. • Any (inadvertent) errors and omissions are the responsibility of Ms. Till alone. 2 Oil Futures Prices and OPEC Spare Capacity I. Crude Oil’s Importance for Commodity Indexes II. Structural Curve Shape of Individual Futures Contracts III. Structural Curve Shape and the Implications for Crude Oil Futures Contracts IV. Commodity Futures Curve Shape and Inventories Icon above is based on the statue in the Chicago Board of Trade plaza. 3 Oil Futures Prices and OPEC Spare Capacity V. Special Features of Crude Oil Markets VI. What Happens When OPEC Spare Capacity Becomes Quite Low? VII. The Plausible Link Between OPEC Spare Capacity and a Crude Oil Futures Curve Shape VIII. Current (Official) Expectations on OPEC Spare Capacity IX. Trading and Investment Conclusion 4 Oil Futures Prices and OPEC Spare Capacity Appendix A: Portfolio-Level Returns from Rebalancing Appendix B: Month-to-Month Factors Influencing a Crude Oil Futures Curve Appendix C: Consideration of the “1986 Oil Tactic” 5 I. -
Copyrighted Material
Index AA estimate, 68–69 At-the-money (ATM) SPX variance Affine jump diffusion (AJD), 15–16 levels/skews, 39f AJD. See Affine jump diffusion Avellaneda, Marco, 114, 163 Alfonsi, Aurelien,´ 163 American Airlines (AMR), negative book Bakshi, Gurdip, 66, 163 value, 84 Bakshi-Cao-Chen (BCC) parameters, 40, 66, American implied volatilities, 82 67f, 70f, 146, 152, 154f American options, 82 Barrier level, Amortizing options, 135 distribution, 86 Andersen, Leif, 24, 67, 68, 163 equal to strike, 108–109 Andreasen, Jesper, 67, 68, 163 Barrier options, 107, 114. See also Annualized Heston convexity adjustment, Out-of-the-money barrier options 145f applications, 120 Annualized Heston VXB convexity barrier window, 120 adjustment, 160f definitions, 107–108 Ansatz, 32–33 discrete monitoring, adjustment, 117–119 application, 34 knock-in options, 107 Arbitrage, 78–79. See also Capital structure knock-out options, 107, 108 arbitrage limiting cases, 108–109 avoidance, 26 live-out options, 116, 117f calendar spread arbitrage, 26 one-touch options, 110, 111f, 112f, 115 vertical spread arbitrage, 26, 78 out-of-the-money barrier, 114–115 Arrow-Debreu prices, 8–9 Parisian options, 120 Asymptotics, summary, 100 rebate, 108 Benaim, Shalom, 98, 163 At-the-money (ATM) implied volatility (or Berestycki, Henri, 26, 163 variance), 34, 37, 39, 79, 104 Bessel functions, 23, 151. See also Modified structure, computation, 60 Bessel function At-the-money (ATM) lookback (hindsight) weights, 149 option, 119 Bid/offer spread, 26 At-the-money (ATM) option, 70, 78, 126, minimization, -
VIX Futures As a Market Timing Indicator
Journal of Risk and Financial Management Article VIX Futures as a Market Timing Indicator Athanasios P. Fassas 1 and Nikolas Hourvouliades 2,* 1 Department of Accounting and Finance, University of Thessaly, Larissa 41110, Greece 2 Department of Business Studies, American College of Thessaloniki, Thessaloniki 55535, Greece * Correspondence: [email protected]; Tel.: +30-2310-398385 Received: 10 June 2019; Accepted: 28 June 2019; Published: 1 July 2019 Abstract: Our work relates to the literature supporting that the VIX also mirrors investor sentiment and, thus, contains useful information regarding future S&P500 returns. The objective of this empirical analysis is to verify if the shape of the volatility futures term structure has signaling effects regarding future equity price movements, as several investors believe. Our findings generally support the hypothesis that the VIX term structure can be employed as a contrarian market timing indicator. The empirical analysis of this study has important practical implications for financial market practitioners, as it shows that they can use the VIX futures term structure not only as a proxy of market expectations on forward volatility, but also as a stock market timing tool. Keywords: VIX futures; volatility term structure; future equity returns; S&P500 1. Introduction A fundamental principle of finance is the positive expected return-risk trade-off. In this paper, we examine the dynamic dependencies between future equity returns and the term structure of VIX futures, i.e., the curve that connects daily settlement prices of individual VIX futures contracts to maturities across time. This study extends the VIX futures-related literature by testing the market timing ability of the VIX futures term structure regarding future stock movements. -
What's Price Got to Do with Term Structure?
What’s Price Got To Do With Term Structure? An Introduction to the Change in Realized Roll Yields: Redefining How Forward Curves Are Measured Contributors: Historically, investors have been drawn to the systematic return opportunities, or beta, of commodities due to their potentially inflation-hedging and Jodie Gunzberg, CFA diversifying properties. However, because contango was a persistent market Vice President, Commodities condition from 2005 to 2011, occurring in 93% of the months during that time, [email protected] roll yield had a negative impact on returns. As a result, it may have seemed to some that the liquidity risk premium had disappeared. Marya Alsati-Morad Associate Director, Commodities However, as discussed in our paper published in September 2013, entitled [email protected] “Identifying Return Opportunities in A Demand-Driven World Economy,” the environment may be changing. Specifically, the world economy may be Peter Tsui shifting from one driven by expansion of supply to one driven by expansion of Director, Index Research & Design demand, which could have a significant impact on commodity performance. [email protected] This impact would be directly related to two hallmarks of a world economy driven by expansion of demand: the increasing persistence of backwardation and the more frequent flipping of term structures. In order to benefit in this changing economic environment, the key is to implement flexibility to keep pace with the quickly changing term structures. To achieve flexibility, there are two primary ways to modify the first-generation ® flagship index, the S&P GSCI . The first method allows an index to select contracts with expirations that are either near- or longer-dated based on the commodity futures’ term structure. -
Structural Position-Taking in Crude Oil Futures Contracts
Structural Position-Taking in Crude Oil Futures Contracts November 2015 Hilary Till Research Associate, EDHEC-Risk Institute Principal, Premia Research LLC Abstract Should an investor enter into long-term positions in oil futures contracts? In answering this question, this paper will cover the following three considerations: (1) the case for structural positions in crude oil futures contracts; (2) useful indicators for avoiding crash risk; and (3) financial asset diversification for downside hedging of oil price risk. This paper will conclude by noting the conditions under which one might consider including oil futures contracts in an investment portfolio. This paper is provided for educational purposes only and should not be construed as investment advice or an offer or solicitation to buy or sell securities or other financial instruments. The views expressed in this article are the personal opinions of Hilary Till and do not necessarily reflect the views of institutions with which Ms. Till is affiliated. Research assistance from Katherine Farren, CAIA, of Premia Risk Consultancy, Inc. is gratefully acknowledged. EDHEC is one of the top five business schools in France. Its reputation is built on the high quality of its faculty and the privileged relationship with professionals that the school has cultivated since its establishment in 1906. EDHEC Business School has decided to draw on its extensive knowledge of the professional environment and has therefore focused its research on themes that satisfy the needs of professionals. EDHEC pursues an active research policy in the field of finance. EDHEC-Risk Institute carries out numerous research programmes in the areas of asset allocation and risk management in both the 2 traditional and alternative investment universes.