Derivative Securities: Lecture 4 Introduction to option pricing

Similar documents
Lecture 2: Bayesian inference - Discrete probability models

The Black-Scholes Formula

Investment. Net Present Value. Stream of payments A 0, A 1, Consol: same payment forever Common interest rate r

European and American options with a single payment of dividends. (About formula Roll, Geske & Whaley) Mark Ioffe. Abstract

1 Lecture: pp

GUIDE FOR SUPERVISORS 1. This event runs most efficiently with two to four extra volunteers to help proctor students and grade the student

How to represent a joint, or a marginal distribution?

Partial Fraction Expansion

General Non-Arbitrage Model. I. Partial Differential Equation for Pricing A. Traded Underlying Security

Lecture 1: Numerical Integration The Trapezoidal and Simpson s Rule

UNIT #5 EXPONENTIAL AND LOGARITHMIC FUNCTIONS

2. The Laplace Transform

Boyce/DiPrima 9 th ed, Ch 2.1: Linear Equations; Method of Integrating Factors

ASYMPTOTICS FOR GREEKS UNDER THE CONSTANT ELASTICITY OF VARIANCE MODEL. Oleg L. Kritski 1, Vladimir F. Zalmezh Tomsk Polytechnic University, Russia

DSP-First, 2/e. This Lecture: LECTURE #3 Complex Exponentials & Complex Numbers. Introduce more tools for manipulating complex numbers

Elementary Differential Equations and Boundary Value Problems

Economics 302 (Sec. 001) Intermediate Macroeconomic Theory and Policy (Spring 2011) 4/25/2011. UW Madison

Institute of Actuaries of India

On the Accuracy of Binomial Model for the Valuation of Standard Options with Dividend Yield in the Context of Black-Scholes Model

( ) ( ) + = ( ) + ( )

Department of Chemical Engineering University of Tennessee Prof. David Keffer. Course Lecture Notes SIXTEEN

( ) ( ) ( ) 0. dt dt dt ME203 PROBLEM SET #6. 1. Text Section 4.5

Representing Knowledge. CS 188: Artificial Intelligence Fall Properties of BNs. Independence? Reachability (the Bayes Ball) Example

Midterm exam 2, April 7, 2009 (solutions)

Einstein s Field Equations in Cosmology Using Harrison s Formula

4.1 The Uniform Distribution Def n: A c.r.v. X has a continuous uniform distribution on [a, b] when its pdf is = 1 a x b

An Indian Journal FULL PAPER. Trade Science Inc. A stage-structured model of a single-species with density-dependent and birth pulses ABSTRACT

Final Exam : Solutions

Sections 3.1 and 3.4 Exponential Functions (Growth and Decay)

, University. 1and. y T. since. g g

Math 3301 Homework Set 6 Solutions 10 Points. = +. The guess for the particular P ( ) ( ) ( ) ( ) ( ) ( ) ( ) cos 2 t : 4D= 2

5. An object moving along an x-coordinate axis with its scale measured in meters has a velocity of 6t

Study of Tyre Damping Ratio and In-Plane Time Domain Simulation with Modal Parameter Tyre Model (MPTM)

Decline Curves. Exponential decline (constant fractional decline) Harmonic decline, and Hyperbolic decline.

Wireless Networking Guide

= x. I (x,y ) Example: Translation. Operations depend on pixel s Coordinates. Context free. Independent of pixel values. I(x,y) Forward mapping:

A Simple Method for Determining the Manoeuvring Indices K and T from Zigzag Trial Data

(ΔM s ) > (Δ M D ) PARITY CONDITIONS IN INTERNATIONAL FINANCE AND CURRENCY FORECASTING INFLATION ARBITRAGE AND THE LAW OF ONE PRICE

Lecture-V Stochastic Processes and the Basic Term-Structure Equation 1 Stochastic Processes Any variable whose value changes over time in an uncertain

On Jackson's Theorem

NEWBERRY FOREST MGT UNIT Stand Level Information Compartment: 10 Entry Year: 2001

Chap.3 Laplace Transform

1973 AP Calculus BC: Section I

Double Slits in Space and Time

Chapter 5 The Laplace Transform. x(t) input y(t) output Dynamic System

2-d Motion: Constant Acceleration

Economics 302 (Sec. 001) Intermediate Macroeconomic Theory and Policy (Spring 2011) 3/28/2012. UW Madison

The Moúõ. ExplÉüers. Fun Facts. WÉüd Proèô. Parts oì Sp. Zoú Animal Roêks

Phys463.nb Conductivity. Another equivalent definition of the Fermi velocity is

On the Determination of Capital Charges in a Discounted Cash Flow Model. Eric R. Ulm Georgia State University

REPETITION before the exam PART 2, Transform Methods. Laplace transforms: τ dτ. L1. Derive the formulas : L2. Find the Laplace transform F(s) if.

A L A BA M A L A W R E V IE W

Dynamics of Bloch Electrons 1

COMPSCI 230 Discrete Math Trees March 21, / 22

Poisson process Markov process

a dt a dt a dt dt If 1, then the poles in the transfer function are complex conjugates. Let s look at f t H t f s / s. So, for a 2 nd order system:

T h e C S E T I P r o j e c t

Material-Balance-Time During Linear and Radial Flow

Applied Statistics and Probability for Engineers, 6 th edition October 17, 2016

Transfer function and the Laplace transformation

Reinforcement learning

Discussion 06 Solutions

Exponential and Logarithmic Equations and Properties of Logarithms. Properties. Properties. log. Exponential. Logarithmic.

The fundamental mass balance equation is ( 1 ) where: I = inputs P = production O = outputs L = losses A = accumulation

1. Inverse Matrix 4[(3 7) (02)] 1[(0 7) (3 2)] Recall that the inverse of A is equal to:

X-CAPM: An Extrapolative Capital Asset Pricing Model

P a g e 5 1 of R e p o r t P B 4 / 0 9

(, ) which is a positively sloping curve showing (Y,r) for which the money market is in equilibrium. The P = (1.4)

Supporting Online Materials for

FINITE DIFFERENCE APPROACH TO WAVE GUIDE MODES COMPUTATION

EXERCISE - 01 CHECK YOUR GRASP

u(x) = e x 2 y + 2 ) Integrate and solve for x (1 + x)y + y = cos x Answer: Divide both sides by 1 + x and solve for y. y = x y + cos x

The angle between L and the z-axis is found from

F This leads to an unstable mode which is not observable at the output thus cannot be controlled by feeding back.

I. OBJECTIVE OF THE EXPERIMENT.

Circular Motion. Radians. One revolution is equivalent to which is also equivalent to 2π radians. Therefore we can.

3(8 ) (8 x x ) 3x x (8 )

CS 188: Artificial Intelligence Fall Probabilistic Models

Financial Econometrics Jeffrey R. Russell Midterm Winter 2009 SOLUTIONS

7 Wave Equation in Higher Dimensions

Chapter 2 : Fundamental parameters of antennas

Performance Evaluation of Balanced Pension Plans

Continous system: differential equations

X-CAPM: An Extrapolative Capital Asset Pricing Model

X-CAPM: An Extrapolative Capital Asset Pricing Model

CSE 245: Computer Aided Circuit Simulation and Verification

Finite-Sample Effects on the Standardized Returns of the Tokyo Stock Exchange

On a problem of Graham By E. ERDŐS and E. SZEMERÉDI (Budapest) GRAHAM stated the following conjecture : Let p be a prime and a 1,..., ap p non-zero re

Chapter 3 Common Families of Distributions

2.1. Differential Equations and Solutions #3, 4, 17, 20, 24, 35

OH BOY! Story. N a r r a t iv e a n d o bj e c t s th ea t e r Fo r a l l a g e s, fr o m th e a ge of 9

Lecture 16 (Momentum and Impulse, Collisions and Conservation of Momentum) Physics Spring 2017 Douglas Fields

Unit Root Time Series. Univariate random walk

Physics 160 Lecture 3. R. Johnson April 6, 2015

Inventory Analysis and Management. Multi-Period Stochastic Models: Optimality of (s, S) Policy for K-Convex Objective Functions

An Automatic Door Sensor Using Image Processing

Chapter 4 Circular and Curvilinear Motions

SHINGLETON FOREST AREA Stand Level Information Compartment: 44 Entry Year: 2009

Volatility. Many economic series, and most financial series, display conditional volatility

COHORT MBA. Exponential function. MATH review (part2) by Lucian Mitroiu. The LOG and EXP functions. Properties: e e. lim.

Transcription:

Divaiv cuiis: Lcu 4 Inoducion o oion icing oucs: J. Hull 7 h diion Avllanda and Launc () Yahoo!Financ & assod wbsis

Oion Picing In vious lcus w covd owad icing and h imoanc o cos-o cay W also covd Pu-all Paiy which can b viwd as laion ha should hold bwn uoan-syl us and calls wih h sam xiaion Pu-call aiy can b sn as icing convsions laiv o owads on h sam undlying ass Wha oh laions xis bwn oions and sads on h sam undlying ass?

all ad all ad: Long a call wih sik sho a call wih sik L (L>) L inc h ayo is non-ngaiv h valu o h sad mus b osiiv L all alll L all alll ad maks mony i h ic o h undlying gos u

Pu ad Pu ad: Long a u wih sik L sho a u wih sik L (L>) L inc h ayo is non-ngaiv h valu o h sad mus b osiiv P L Pu PuL L PuL Pu ad maks mony i h ic o h undlying gos down

Buly ad Buly sad: Long call wih sik long call wih sik L sho calls wih sik (+L)/ (+L)/ L inc h sad has non-ngaiv ayo i mus hav osiiv valu B L ( L) / L all alll all Bulis mak $ i h sock ic is na (+L)/ a xiaion.

addl addl: Long call and long u wih h sam sik - + addls mak mony i h sock ic movs away om h sik and nds a om i

angl angl: Long u wih sik long call wih sik L L>. L angl is also non-dicional lik a saddl bu maks $ only i h sock movs vy a away. addls and sangls a on usd o xss viws abou volailiy o h undlying sock and a non-dicional.

Risk-vsal Risk-vsal : Long u wih sik sho call wih sik L L>. L Dicional sad. an b sn as inancing a u by slling an usid call.

alnda ad alnda ad: ho call wih mauiy Long call wih mauiy < am sik Mauiy Mauiy I h undlying ays no dividnds bwn and hn h long mauiy call is abov ininsic valu a im. alndas hav osiiv valu. Fo Amican oions calndas always hav osiiv valu

Rconsucing all ics om Buly ads Assum o simliciy a counabl and ha h sock ic can only ak valus on h laic all n all all n numb o siks n n n n 3... A call can b viwd as a oolio o call sads A call sad can b viwd as a oolio o buly sads m m 3... Bi i i i +

alls as su-osiions o buly sads n n n n n n i i i i n w B w w B n B n B all h wighs cosond o valus o Buly sads cnd a ach. In aicula hy a osiiv

Fom wighs o obabiliis max max. ; ) valus (assuming ha h sock can only ak PV $ all w B w w

Fis momn o is h owad ic all F q q A call wih sik is h oion o buy h sock a o a im Is valu is ho h sn valu o h owad ic (ay now g sock la). I ollows ha h is momn o is h owad ic. I also ollows ha u ics a givn by a simila omula namly Pu ( ) all q F

Gnal Payos Any wic diniabl uncion () can b xssd as a combinaion o u and call ayos using h omula (his is us aylo xansion) hus a uoan-syl ayo can b viwd as a sad o us and calls. By linaiy o icing dy Y Y dy Y Y F dy Y Y F F F F '' '' '' ' ' F F F F dy Y Y dy Y Y F dy Y Y all dy Y Y Pu '' '' ' '' '' ) ( ) ( ) ( ) ( claim wih ayo a Fai valu o

Fundamnal hom o icing (on iod modl) An abiag oouniy is a oolio o divaiv scuiis and cash which has h ollowing ois: - h ayo is non-ngaiv in all uu sas o h mak - h ic o h oolio is o o ngaiv (a cdi) Assum ha ach scuiy has a uniqu ic (i.. assum bid-o). I h a no abiag oouniis hn h xiss a obabiliy disibuion o uu sas o h mak such ha o any uncion () h ic o a scuiy wih ayo () is P onvsly i such a obabiliy xiss h a no abiag oouniis

Pacical Alicaion o uoan Oions A icing masu is a obabiliy o uu ics o h undlying ass wih h oy ha F I w dmin a suiabl icing masu hn all uoan oions wih xiaion da should hav valu givn by all Pu h main issu is hn o dmin a suiabl icing masu in h al acical wold.

Wha dos a icing masu achiv in h cas o oions? all(;) F Oion ai valu is a smoohd ou vsion o h ayo h icing masu givs a modl o comu h oion s ai valu as a uncion o h ic o h undlying ass h sik and h mauiy

h Black-chols Modl Assum ha h icing masu is log-nomal i.. log-uns a nomal ~ - ~ N Z q Z X q q dy N X y y X

all icing wih h Black-chols modl ln / / / d d d d d d d d q A d d d all A A q A A q A A q A A q A A q q

Black-chols Fomula x q q d x N F F d F d d N d N q Ball ln ln cumulaiv nomal disibuion

Black-chols Fomula a wok =$48 =$5 =6% sigma=4% q=

Muli-iod ass modl Divaiv scuiis may dnd on mulil xiaion/cash-low das. Fuhmo h -iod modl dscibd abov is igid in h sns ha i canno ic Amican-syl oions. W consid insad a mo alisic aoach o icing basd on h saisics o sock uns ov sho iods o im (.g. day). W assum ha h undlying ic has uns saisying W also assum ha succssiv uns a uncolad. ~ N

Modling h un o a ic imsis (OHL) Ln Modl closing ics o xaml. h % changs bwn closing ics a nomal and uncolad = closing ic o iod (-)

Paamiaion annualid sandad dviaion annualid xcd un % daily sandad dviaion => 5.9% annualid sandad dviaion 5.9 5 5

Picing Divaivs L us modl h valu o a divaiv scuiy as a uncion o h undlying ass ic and h im o xiaion... hang in mak valu ov on iod : o o V V

h hdging agumn onsid a oolio which is long divaiv and sho socks. Assum divaiv dos no ay dividnds q q V q V q V V PNL including inancing and dividnds : Poi and loss

Analying h sidual m o o o o h sidual m has ssnially o xcd un (vanishing x. un in h limi D_>.) ondiional xcaion o silon

h ai valu o ou divaiv scuiy is h PNL o h long sho oolio o divaiv and ba shas has xcd valu his oolio has no xosu o h sock ic changs. ho i () sns h ``ai valu o h divaiv h oolio should hav o a o un (w alady ook ino acc is inancing). hus: his is h Black-chols aial dinial quaion (PD). ) ( ) ( o q o PNL q

Amican-syl calls & us onsid a call oion on an undlying ass aying dividnds coninuously. inc h oion can b xcisd anyim w hav max. () h minal condiion a = cosonds o h inal ayo max. hus h uncion () should saisy h Black-chols PD in h gion o h ()-lan o which sic inqualiy holds in () and i should b qual o max(-) ohwis. h soluion o his oblm is don numically and will b addssd in h nx lcu.