What's Price Got to Do with Term Structure?
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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. -
Forward Contracts and Futures a Forward Is an Agreement Between Two Parties to Buy Or Sell an Asset at a Pre-Determined Future Time for a Certain Price
Forward contracts and futures A forward is an agreement between two parties to buy or sell an asset at a pre-determined future time for a certain price. Goal To hedge against the price fluctuation of commodity. • Intension of purchase decided earlier, actual transaction done later. • The forward contract needs to specify the delivery price, amount, quality, delivery date, means of delivery, etc. Potential default of either party: writer or holder. Terminal payoff from forward contract payoff payoff K − ST ST − K K ST ST K long position short position K = delivery price, ST = asset price at maturity Zero-sum game between the writer (short position) and owner (long position). Since it costs nothing to enter into a forward contract, the terminal payoff is the investor’s total gain or loss from the contract. Forward price for a forward contract is defined as the delivery price which make the value of the contract at initiation be zero. Question Does it relate to the expected value of the commodity on the delivery date? Forward price = spot price + cost of fund + storage cost cost of carry Example • Spot price of one ton of wood is $10,000 • 6-month interest income from $10,000 is $400 • storage cost of one ton of wood is $300 6-month forward price of one ton of wood = $10,000 + 400 + $300 = $10,700. Explanation Suppose the forward price deviates too much from $10,700, the construction firm would prefer to buy the wood now and store that for 6 months (though the cost of storage may be higher). -
Pricing of Index Options Using Black's Model
Global Journal of Management and Business Research Volume 12 Issue 3 Version 1.0 March 2012 Type: Double Blind Peer Reviewed International Research Journal Publisher: Global Journals Inc. (USA) Online ISSN: 2249-4588 & Print ISSN: 0975-5853 Pricing of Index Options Using Black’s Model By Dr. S. K. Mitra Institute of Management Technology Nagpur Abstract - Stock index futures sometimes suffer from ‘a negative cost-of-carry’ bias, as future prices of stock index frequently trade less than their theoretical value that include carrying costs. Since commencement of Nifty future trading in India, Nifty future always traded below the theoretical prices. This distortion of future prices also spills over to option pricing and increase difference between actual price of Nifty options and the prices calculated using the famous Black-Scholes formula. Fisher Black tried to address the negative cost of carry effect by using forward prices in the option pricing model instead of spot prices. Black’s model is found useful for valuing options on physical commodities where discounted value of future price was found to be a better substitute of spot prices as an input to value options. In this study the theoretical prices of Nifty options using both Black Formula and Black-Scholes Formula were compared with actual prices in the market. It was observed that for valuing Nifty Options, Black Formula had given better result compared to Black-Scholes. Keywords : Options Pricing, Cost of carry, Black-Scholes model, Black’s model. GJMBR - B Classification : FOR Code:150507, 150504, JEL Code: G12 , G13, M31 PricingofIndexOptionsUsingBlacksModel Strictly as per the compliance and regulations of: © 2012. -
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. -
Monte Carlo Strategies in Option Pricing for Sabr Model
MONTE CARLO STRATEGIES IN OPTION PRICING FOR SABR MODEL Leicheng Yin A dissertation submitted to the faculty of the University of North Carolina at Chapel Hill in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Statistics and Operations Research. Chapel Hill 2015 Approved by: Chuanshu Ji Vidyadhar Kulkarni Nilay Argon Kai Zhang Serhan Ziya c 2015 Leicheng Yin ALL RIGHTS RESERVED ii ABSTRACT LEICHENG YIN: MONTE CARLO STRATEGIES IN OPTION PRICING FOR SABR MODEL (Under the direction of Chuanshu Ji) Option pricing problems have always been a hot topic in mathematical finance. The SABR model is a stochastic volatility model, which attempts to capture the volatility smile in derivatives markets. To price options under SABR model, there are analytical and probability approaches. The probability approach i.e. the Monte Carlo method suffers from computation inefficiency due to high dimensional state spaces. In this work, we adopt the probability approach for pricing options under the SABR model. The novelty of our contribution lies in reducing the dimensionality of Monte Carlo simulation from the high dimensional state space (time series of the underlying asset) to the 2-D or 3-D random vectors (certain summary statistics of the volatility path). iii To Mom and Dad iv ACKNOWLEDGEMENTS First, I would like to thank my advisor, Professor Chuanshu Ji, who gave me great instruction and advice on my research. As my mentor and friend, Chuanshu also offered me generous help to my career and provided me with great advice about life. Studying from and working with him was a precious experience to me. -
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. -
Forward and Futures Contracts
FIN-40008 FINANCIAL INSTRUMENTS SPRING 2008 Forward and Futures Contracts These notes explore forward and futures contracts, what they are and how they are used. We will learn how to price forward contracts by using arbitrage and replication arguments that are fundamental to derivative pricing. We shall also learn about the similarities and differences between forward and futures markets and the differences between forward and futures markets and prices. We shall also consider how forward and future prices are related to spot market prices. Keywords: Arbitrage, Replication, Hedging, Synthetic, Speculator, Forward Value, Maintainable Margin, Limit Order, Market Order, Stop Order, Back- wardation, Contango, Underlying, Derivative. Reading: You should read Hull chapters 1 (which covers option payoffs as well) and chapters 2 and 5. 1 Background From the 1970s financial markets became riskier with larger swings in interest rates and equity and commodity prices. In response to this increase in risk, financial institutions looked for new ways to reduce the risks they faced. The way found was the development of exchange traded derivative securities. Derivative securities are assets linked to the payments on some underlying security or index of securities. Many derivative securities had been traded over the counter for a long time but it was from this time that volume of trading activity in derivatives grew most rapidly. The most important types of derivatives are futures, options and swaps. An option gives the holder the right to buy or sell the underlying asset at a specified date for a pre-specified price. A future gives the holder the 1 2 FIN-40008 FINANCIAL INSTRUMENTS obligation to buy or sell the underlying asset at a specified date for a pre- specified price. -
Term Structure Lattice Models
Term Structure Models: IEOR E4710 Spring 2005 °c 2005 by Martin Haugh Term Structure Lattice Models 1 The Term-Structure of Interest Rates If a bank lends you money for one year and lends money to someone else for ten years, it is very likely that the rate of interest charged for the one-year loan will di®er from that charged for the ten-year loan. Term-structure theory has as its basis the idea that loans of di®erent maturities should incur di®erent rates of interest. This basis is grounded in reality and allows for a much richer and more realistic theory than that provided by the yield-to-maturity (YTM) framework1. We ¯rst describe some of the basic concepts and notation that we need for studying term-structure models. In these notes we will often assume that there are m compounding periods per year, but it should be clear what changes need to be made for continuous-time models and di®erent compounding conventions. Time can be measured in periods or years, but it should be clear from the context what convention we are using. Spot Rates: Spot rates are the basic interest rates that de¯ne the term structure. De¯ned on an annual basis, the spot rate, st, is the rate of interest charged for lending money from today (t = 0) until time t. In particular, 2 mt this implies that if you lend A dollars for t years today, you will receive A(1 + st=m) dollars when the t years have elapsed. -
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. -
Using VIX to Help Trade Options
The Option Pit Method Understanding and Trading VIX Option Pit What we will cover in PART 1 • What VIX is and what it is not • What VIX measures • The nature of volatility • A look at the SPX straddle for an Easy VIX • Ways to trade VIX profitably What the heck is the VIX? VIX Facts • VIX has not gone below 8% or above 100% since 2008 • You cannot buy it or sell it • What it measures changes every week • It does not measure fear or complacency • The long term average for VIX is around 20 More VIX facts • Options on VIX only settle to VIX cash once per week • The VIX Index is generated from SPX options with a bid and an offer • At least 100 option series make up the VIX • The time to calculate VIX is measured in minutes VIX measures SPX 30 day implied volatility • Why 30 days? Well, that was all that was available when VIX was invented. • The calendar is very important to trading VIX • Most importantly: VIX DOES NOT MEASURE IV of options expiring this week or next week in the SPX • VIX uses the IV of the SPX options with 23 to 37 days to expiration. VIX is a volatility direction with a limit Volatility as a direction does not compound like A stock, it reverts to a mean Definition of Volatility • Basically the range of a stock over a certain period of time – In the case of the VIX, we are talking about the SPX only • There are RVX (Russell 2000) and TYVIX (10-Year Treasury Note) among others • There is a VIX for AAPL and a VIX for GOOGL So what is Volatility? • A 15% volatility on a $100 stock for 1 year would give us a range of $85 to $115 with a 68.2% degree of confidence. -
Forward and Future Implied Volatility
May 24, 2011 10:49 WSPC/S0219-0249 104-IJTAF SPI-J071 S0219024911006590 International Journal of Theoretical and Applied Finance Vol. 14, No. 3 (2011) 407–432 c World Scientific Publishing Company DOI: 10.1142/S0219024911006590 FORWARD AND FUTURE IMPLIED VOLATILITY PAUL GLASSERMAN Columbia Business School [email protected] QI WU∗ Department of APAM Columbia University 200 S.W. Mudd Building New York, NY 10027, USA [email protected] Received 14 June 2010 Accepted 12 January 2011 We address the problem of defining and calculating forward volatility implied by option prices when the underlying asset is driven by a stochastic volatility process. We exam- ine alternative notions of forward implied volatility and the information required to extract these measures from the prices of European options at fixed maturities. We then specialize to the SABR model and show how the asymptotic expansion of the bivariate transition density in Wu (forthcoming) allows calibration of the SABR model with piecewise constant parameters and calculation of forward volatility. We then inves- tigate empirically whether current option prices at multiple maturities contain useful information in predicting future option prices and future implied volatility. We under- take this investigation using data on options on the euro-dollar, sterling-dollar, and dollar-yen exchange rates. We find that prices across maturities do indeed have pre- dictive value. Moreover, we find that model-based forward volatility extracts this pred- icative information better than a standard “model-free” measure of forward volatility and better than spot implied volatility. The enhancement to out-of-sample forecasting accuracy gained from model-based forward volatility is greatest at longer forecasting horizons.