Implied volatility formula of European Power Option Pricing



Similar documents
Load Balancing Algorithm Based on QoS Awareness Applied in Wireless Networks

Physics. Lesson Plan #9 Energy, Work and Simple Machines David V. Fansler Beddingfield High School

HEAT TRANSFER ANALYSIS OF LNG TRANSFER LINE

I N S T I T U T D E S T A T I S T I Q U E B I O S T A T I S T I Q U E E T S C I E N C E S A C T U A R I E L L E S (I S B A)

Derivations and Applications of Greek Letters Review and

Problem Solving Session 1: Electric Dipoles and Torque

Designing of Closed Loop Controller for 3 Phase to 3 Phase Power Conversion Using Matrix Converter

Should I Stay or Should I Go? Migration under Uncertainty: A New Approach

Handout 3. Free Electron Gas in 2D and 1D

The (Bad?) Timing of Mutual Fund Investors. Oded Braverman,* Shmuel Kandel,** and Avi Wohl*** First version: February 2005 This version: August 2005

Factors that Influence Memory

Reach Versus Competition in Channels with Internet and Traditional Retailers

Question 3: How do you find the relative extrema of a function?

5.4 Exponential Functions: Differentiation and Integration TOOTLIFTST:

Magic Message Maker Amaze your customers with this Gift of Caring communication piece

Instruction: Solving Exponential Equations without Logarithms. This lecture uses a four-step process to solve exponential equations:

DEGRADATION MODEL OF BREAST IMAGING BY DISPERSED RADIATION

How Much Should a Firm Borrow. Effect of tax shields. Capital Structure Theory. Capital Structure & Corporate Taxes

An AnyLogic Simulation Model for Power and Performance Analysis of Data Centres

Sale Mode Choice of Product Extended Warranty based on the Service Level

New Basis Functions. Section 8. Complex Fourier Series

THE NAVAJO NATION Department of Personnel Management JOB VACANCY ANNOUNCEMENT INFORMATION SYSTEMS TECHNICIAN

The Casino Experience

Incorporating Statistical Process Control and Statistical Quality Control Techniques into a Quality Assurance Program

Probabilistic maintenance and asset management on moveable storm surge barriers

A Note on Approximating. the Normal Distribution Function

A Systematic Approach to the Comparison of Roles in the Software Development Processes

Coordinate Systems L. M. Kalnins, March 2009

Chapter 7 Yielding criteria

QUANTITATIVE METHODS CLASSES WEEK SEVEN

Tank Level GPRS/GSM Wireless Monitoring System Solutions

Section 7.4: Exponential Growth and Decay

Analytical Proof of Newton's Force Laws

Trading Volume and Serial Correlation in Stock Returns in Pakistan. Abstract

Econ 371: Answer Key for Problem Set 1 (Chapter 12-13)

Basis risk. When speaking about forward or futures contracts, basis risk is the market

Gravity and the Earth Newtonian Gravity and Earth Rotation Effects

Exotic Options: Pricing Path-Dependent single Barrier Option contracts

High Voltage Cables. Figure Layout of three, single-core cables

Before attempting to connect or operate this product, please read these instructions carefully and save this manual for future use.

FEE-HELP INFORMATION SHEET FOR DOMESTIC FULL FEE STUDENTS

fiziks Institute for NET/JRF, GATE, IIT JAM, JEST, TIFR and GRE in PHYSICAL SCIENCES NUCLEAR AND PARTICLE PHYSICS NET/JRF (JUNE-2011)

at 10 knots to avoid the hurricane, what could be the maximum CPA? 59 miles - 54 nm STEP 1 Ship s Speed Radius (e-r) 10 k nm every 6 minutes

Vector Calculus: Are you ready? Vectors in 2D and 3D Space: Review

Research on Risk Assessment of the Transformer Based on Life Cycle Cost

Controlling the Money Supply: Bond Purchases in the Open Market

Valuation of Floating Rate Bonds 1

Ilona V. Tregub, ScD., Professor

The transport performance evaluation system building of logistics enterprises

IT Update - August 2006

FACULTY SALARIES FALL NKU CUPA Data Compared To Published National Data

Sharp bounds for Sándor mean in terms of arithmetic, geometric and harmonic means

Graphs of Equations. A coordinate system is a way to graphically show the relationship between 2 quantities.

IBM Research Smarter Transportation Analytics

YIELD TO MATURITY ACCRUED INTEREST QUOTED PRICE INVOICE PRICE

A Theoretical Model of Public Response to the Homeland Security Advisory System

Aegis Identity Software, Inc. Experts in Identity Management 100% Focused on Education

INITIAL MARGIN CALCULATION ON DERIVATIVE MARKETS OPTION VALUATION FORMULAS

WORKING PAPER. Design Of Extended Warranties In Supply Chains

Determining solar characteristics using planetary data

Financing Terms in the EOQ Model

Design for Cyclic Loading

Superconducting gravimeter calibration by co-located gravity observations results from GWR C025

Questions & Answers Chapter 10 Software Reliability Prediction, Allocation and Demonstration Testing

An Epidemic Model of Mobile Phone Virus

Solutions to Problems: Chapter 7

190 km³ Evaporation Precipitation. Flensburg. Kiel. Bremerhaven Wilhelmshaven

A Newer Secure Communication, File Encryption and User Identification based Cloud Security Architecture

Similarity transformation methods in the analysis of the two dimensional steady compressible laminar boundary layer

by John Donald, Lecturer, School of Accounting, Economics and Finance, Deakin University, Australia

Lecture 3: Diffusion: Fick s first law

Spring 2014 Course Guide

Standardized Coefficients

Skills Needed for Success in Calculus 1

Chapter 3 Savings, Present Value and Ricardian Equivalence

A statistical development of fixed odds betting rules in soccer

FI3300 Corporate Finance

9:6.4 Sample Questions/Requests for Managing Underwriter Candidates

Mathematics. Mathematics 3. hsn.uk.net. Higher HSN23000

UNIT CIRCLE TRIGONOMETRY

Adverse Selection and Moral Hazard in a Model With 2 States of the World

Effect of Unemployment Insurance Tax On Wages and Employment: A Partial Equilibrium Analysis

Who uses our services? We have a growing customer base. with institutions all around the globe.

A Note on Risky Bond Valuation

AP Calculus AB 2008 Scoring Guidelines

Episode 401: Newton s law of universal gravitation

Chapter 3. Electric Potential

Mechanics 1: Motion in a Central Force Field

Converting knowledge Into Practice

YARN PROPERTIES MEASUREMENT: AN OPTICAL APPROACH

A Model for Antenna-Plasma Wave Coupling towards Control of Uniformity in Slot-Excited Microwave Discharges

Transcription:

Impli volatility fomula of Euopan Pow Option Picing Jingwi Liu * ing hn chool of Mathmatics an ystm cincs, Bihang Univsity, LMIB of th Ministy of Eucation,, Bijing, 009, P.R hina Abstact:W iv th impli volatility stimation fomula in Euopan pow call options picing, wh th payoff functions a in th fom of V T an V T 0 spctivly. Using quaatic Taylo appoimations, W vlop th computing fomula of impli volatility in Euopan pow call option an tn th taitional impli volatility fomula of hals J.oao, t al 996 to gnal pow option picing. An th Mont-alo simulations a also givn. ywos: Euopan Pow option; Impli volatility;taylo sis; Mont-alo simulation;. Intouction In cnt cas, financial ivativs picing attacts much mo attntion in both conomic an statistical fils. o th pactical pupos, impli volatility, which stimats th lvl of financial ivativ s isk, is a most impotant paamt in th Black-chols Euopan option picing mol an Mton s Euopan option picing mol [,]. As volatility is a masu of unctainty of th pic tn fo th futu, many woks ass th poblm, an vlop iffnt statgis. In 976, Latan an Rnlman suggst to us impli volatilitis in financial makts sach[3]. Butl an chacht 986 psnt an stimato of th Black-chols option picing foluma by Taylo sis pansion of th Black-chols fomula [4]. hauhuy 996 popos anoth Taylo pansion mtho to plac th Taylo pansion of Butl an chacht [5]. Using quaatic Taylo appoimations, oao an Mill 996 obtain a clos fomula of impli volatility stimation[6]. Utilizing th thi o Taylo sis pansion, Li 005 vlop a nw clos fomula of impli volatility [6]. An, th simulation sult of [7] show that Li s fomula is significantly btt than th oao Mill fomula. Howv, Li s fomula is also mo compl than oao Mill fomula. Euopan pow option picing is a hot sach fil of financial ivativ option picing [8]. In this pap, w iv a nw fomula to comput Euopan pow option impli volatility in th sach famwok of oao an Mill996[6], an giv clos fomula of impli volatility in th pow option picing famwok of Liu 007 [8]. Th st of th pap is oganiz as follows. In sction, Euopan pow call option picing fomula is intouc. In sction 3, th impli volatility stimation fomula a iv. In sction 4, th Mont-alo simulations a givn. Th conclusion is givn in sction 5.. Euopan pow option. lassical Euopan option picing fomula In th classical isk-nutal makt,, t, P, th pic of an asst t0 t at tim t is suppos to b a gomtic Bownian motion, * osponing autho: jwliu@buaa.u.cn

t t Bt t wh is isk-f intst at, is volatility, B t is stana Bownian motion an t Bs, 0 s t. At option piation tim T, payoff valu of th Euopan call option is V T, wh is th stik pic, T is th assts pic at tim T. By th no-abitag thoy, th valu of a taitional Euopan call option pic is stat as T t wh T t T t T t T t, T t o stuying mo convninc, w not T t as th tim th option pis, thn th fomula can b wittn as wh T t,. Euopan pow option picing fomula In o to ominat th comptition an attact mo customs, financial ngins us option thoy an analysis mthos to sign a vaity of options with iffnt chaactistics of nw vaitis. Accoing to th ns of th financial makt, th a many typs of innovativ options, pow options is a nw option typ. Pow option is a simpl non-lina paymnt options. W tak th pow call option fo th stuy, th a two paymnt foms fo -pow 0 option with option piationt an stik pic V 3 T V 4 T w nam fomula 3 as th fist Euopan pow call options, an fomula 4 as th scon Euopan pow call options. Th fist Euopan call pow option picing fomula of fomula 3 is as follows [9], t t wh, An, th scon Euopan pow call option picing fomula bas on fomula 4 is as follows [8], t t 6 5

3 wh, Obviously, fomula taks th spcial cas of fomula 5 an fomula 6 with. 3. Impli volatility fomula in Euopan pow option 3. Impli volatility fomula in fist Euopan pow option o th fist Euopan call pow options, w us th pansion of th nomal istibution function 40 6 5 3 into th fomula5, an not,. W obtain / Etning to, w obtain Thn w can gt a quaatic quation about

Dnot 0 7, w gt W, omula 7 changs to + W =0 8 inc cofficint W coul not kp intical sign, th cas of lagst oot bcoms vy compl. Whil W 0 0, all al oots of fomula 8 a, as non-ngativ, th lagst oot is only if W 9 W 8 0. 0 Whil W 0 0, if th two al oots ist, th, as lagst oot is also non-ngativ. It coul b only if W 0 8W 0. 3. Impli volatility fomula in scon Euopan pow option imilaly, fo scon Euopan call pow options, w us th pansion of th nomal istibution function 3 6 4 5 40

5 into th fomula 6. Dnot,, w can gt / Epaning th fomula with, w can gt Thn, w can also gt a quaatic quation about, 0 Again, w not, thfo W Thn fomula changs to W + =0 Though th vaiabls of an a iffnt fom thos in sction 3., th fomula an fomula 8 kp intical fom. Th sam iscussion is as follows.

Whil W 0 0, all al oots of fomula a, as non-ngativ, th lagst oot is only if W W 8 0. 0 3 Whil W 0 0, if th two al oots ist, th, as lagst oot is also non-ngativ. It coul b W 4 8 0. only if W uthmo, th fomula8 with will b th cosponing fomula of oao an Mill s sult 996 in [6]. 4. umical imulation Lt th oiginal pic of th unlying asst 0 at tim t 0, option piation att, tu tun stana volatility 5%, isk-f intst at 0.00, fo th stik pic, w st 0. 9 Discount,. 0 Paity,. Pmium, an {0.4,0.6,0.8,.0,.,.4,.6,.8,.0} spctivly. Th calculation stps a as follows:. Th unlying asst pic t is simulat accoing to th fomula, wh, th T Bownian motion Bt 0,, 00. o ach, th call option pic t of two kins of Euopan option pow mols a calculat accoing to th fomula 5 an 6 spctivly un th alization of B,..., B... Accoing to th fomula 9 0 an fomula 3 4, w calculat th impli volatility i i, i,, at th tim T T ; W fin th ins to flct th anom compl of ou pimnt. #{ i 0, i,,..., } n, which mans th istnc of oots in fomula 8. L ˆ i, wh L L #{ i 0, i,,..., }, which mans th avag impli i volatility fo on simulation. 6

L i =, which masus th ivgnc g of volatility stimation L i in on simulation. 3. Rpat th pimnt fom stp to stp fo M=00 tims, an th avag sults of n,, a pot in th Tabl an Tabl. Tabl. Impli volatility stimation of fist Euopan call pow option 0.9 0.4 0.6 0.8..4.6.8.0 n 0.0093 0.058 0.335 0.98 0.3056 0.3646 0.4067 0.4450 0.474 0.346 0.77 0.8 0.98 0.74 0.354 0.394 0.46 0.46 0.063 0.053 0.043 0.03 0.064 0.067 0.030 0.007 0.0083 n 0.563 0.509 0.557 0.534 0.5360 0.5408 0.5476 0.5539 0.5595.0 0.335 0.357 0.379 0.40 0.45 0.450 0.473 0.498 0.54 0.07 0.050 0.08 0.008 0.0085 0.0066 0.0053 0.0048 0.0055 n 0.505 0.548 0.5300 0.5359 0.544 0.5464 0.5530 0.5584 0.5633.0 0.30 0.349 0.373 0.397 0.4 0.446 0.470 0.497 0.54 0.087 0.057 0.034 0.00 0.0089 0.0067 0.0053 0.0045 0.0053 Tabl. Impli volatility stimation of scon Euopan call pow option 0.9 0.4 0.6 0.8..4.6.8.0 n 0.075 0.3 0.5 0.98 0.46 0.99 0.36 0.45 0.493 0.50 0.69 0.90 0.98 0.3 0.33 0.334 0.350 0.359 0.077 0.056 0.033 0.03 0.03 0.00 0.008 0.093 0.09 n 0.563 0.509 0.557 0.534 0.5360 0.5408 0.5476 0.5539 0.5595.0 0.335 0.357 0.379 0.40 0.45 0.450 0.473 0.498 0.54 0.07 0.050 0.08 0.008 0.0085 0.0066 0.0053 0.0048 0.0055 n 0.578 0.54 0.599 0.5359 0.54 0.5475 0.5545 0.5590 0.5658.0 0.33 0.35 0.374 0.397 0.40 0.445 0.470 0.498 0.55 0.074 0.054 0.03 0.00 0.0089 0.0068 0.0050 0.004 0.005 om th abov simulations, w can conclu that th n in flct th succssful 7

stimation pobability in Euopan call pow option picing mol, as th compl of stochastic nvionmnt, th n with 0.9 is small than that of an.0 in both two kin of Euopan call pow option. Th accuacy stimation of volatility of pow option pic is slight high in ang of than th cas of. Howv, th is still th cas that th volatility stimation is mo accuat than that with, fo ampl, in Tabl, whn 0.4, 0.9,though its n in is vy low. Th pimntal sults patly suppot th conclusion of [8]. om futh invstigation in ou sach show that if moifying th valu of to guaant 0 as iscuss in [6], th volatility viation g will is. Thfo, w pot th n in to flct th ffctivnss of fomula8 with pow option pic. An, th accuacy of volatility stimation invsly flcts th fitting g with iffnt pow option. om Tabl an Tabl, w can conclu that th ists pow option mol btt than taitional option pic in impli volatility stimation. An, th appciat pow in slction will b ou futh sach intst. 5. onclusion In this pap, with th quaatic Taylo appoimations popos by oao an Mill 996, w iv th clos fomula of impli volatility in two kin of Euopan call pow option picing, th simulation with Mont-alo mtho also show th ffctivnss of ou mol in impli volatility stimation. Th futu wok will focus on th pow option picing slction an appli ou mol to al option ata application. Rfncs [] Black, chols M. Th picing of options an copoat liabilitis [J]. Jounal of Political Economy, 973, 8 3 :637-655. [] Mton R. Th Thoy of Rational Option Picinsa[J]. Bll Jounal of conomic managmnt scinc, 973, 4: 4-83. [3] Latan, H.A., Rnlman R.J.. tana viation of stock pic atios impli by option pmia [J], Jounal of inanc. 976, 3: 369-38. [4] Butl J.., chacht B. Unbias Estimation of th Black-chols omula [J]. Jounal of inancial Economics, 986, 5 3 : 34-357. [5] hauhuy M. M. An Appoimatly Unbias Estimato fo Th Thotical Black-chols Euopan all Valuation[J]. Bulltin of Economic Rsach, 989, 37-46. [6] oao,.j., Mill, J, T.W.. A not on a simpl, accuat fomula to comput impli stana viations [J]. Jounal of Banking &inanc. 996, 0:595-603 [7] Li.. A nw fomula fo computing impli volatility[j]. Appli Mathmatics an omputation.005, 70: 6-65. [8] Liu J.W. Th tatistical Poptis of Paamts an Impli Volatility fom Euopan Pow unction all Option. Application of tatistics an Managmnt [J].007,66: 09-06. [9] Wang Y.J, Zhou.W., Zhang Y.Th Picing of Euopan Pow Options[J].Jounal of Gansu cinc. 005, 7 : - 3. 8