Important Concepts LECTURE 3.2: OPTION PRICING MODELS: THE BLACK-SCHOLES-MERTON MODEL. Applications of Logarithms and Exponentials in Finance

Similar documents
Appendix: Basics of Options and Option Pricing Option Payoffs

CHAPTER 10 OPTION PRICING - II. Derivatives and Risk Management By Rajiv Srivastava. Copyright Oxford University Press

Valuing Stock Options: The Black-Scholes-Merton Model. Chapter 13

Appendix A Financial Calculations

Option pricing models

OPTIONS. Options: Definitions. Definitions (Cont) Price of Call at Maturity and Payoff. Payoff from Holding Stock and Riskfree Bond

Pricing Interest Rate Options with the Black Futures Option Model

Finance 527: Lecture 31, Options V3

Chapter 9 - Mechanics of Options Markets

ECON FINANCIAL ECONOMICS

In general, the value of any asset is the present value of the expected cash flows on

The Merton Model. A Structural Approach to Default Prediction. Agenda. Idea. Merton Model. The iterative approach. Example: Enron

Rationale. Learning about return and risk from the historical record and beta estimation. T Bills and Inflation

Lecture 3: Interest Rate Forwards and Options

The Black-Scholes Model

15 American. Option Pricing. Answers to Questions and Problems

Advanced Corporate Finance. 5. Options (a refresher)

Rationale Reference Nattawut Jenwittayaroje, Ph.D., CFA Expected Return and Standard Deviation Example: Ending Price =

Options (2) Class 20 Financial Management,

Investment Guarantees Chapter 7. Investment Guarantees Chapter 7: Option Pricing Theory. Key Exam Topics in This Lesson.

Mathematics in Finance

Evaluating the Black-Scholes option pricing model using hedging simulations

Any asset that derives its value from another underlying asset is called a derivative asset. The underlying asset could be any asset - for example, a

Advanced Topics in Derivative Pricing Models. Topic 4 - Variance products and volatility derivatives

Derivatives Questions Question 1 Explain carefully the difference between hedging, speculation, and arbitrage.

Applying the Principles of Quantitative Finance to the Construction of Model-Free Volatility Indices

Black-Scholes-Merton Model

Estimating 90-Day Market Volatility with VIX and VXV

The Black-Scholes Model

Lecture Notes: Basic Concepts in Option Pricing - The Black and Scholes Model (Continued)

Math 5760/6890 Introduction to Mathematical Finance

B. Combinations. 1. Synthetic Call (Put-Call Parity). 2. Writing a Covered Call. 3. Straddle, Strangle. 4. Spreads (Bull, Bear, Butterfly).

Risk Neutral Valuation, the Black-

Review of Derivatives I. Matti Suominen, Aalto

Model Calibration and Hedging

Risk Management Using Derivatives Securities

Queens College, CUNY, Department of Computer Science Computational Finance CSCI 365 / 765 Fall 2017 Instructor: Dr. Sateesh Mane.

Valuing Put Options with Put-Call Parity S + P C = [X/(1+r f ) t ] + [D P /(1+r f ) t ] CFA Examination DERIVATIVES OPTIONS Page 1 of 6

OPTION VALUATION Fall 2000

Financial Derivatives Section 5

Discounting a mean reverting cash flow

BUSM 411: Derivatives and Fixed Income

I. Reading. A. BKM, Chapter 20, Section B. BKM, Chapter 21, ignore Section 21.3 and skim Section 21.5.

Volatility of Asset Returns

P-7. Table of Contents. Module 1: Introductory Derivatives

Trading Volatility Using Options: a French Case

Section 6.5. The Central Limit Theorem

Financial Markets & Risk

UNIVERSITY OF SOUTH AFRICA

Preference-Free Option Pricing with Path-Dependent Volatility: A Closed-Form Approach

Introduction to Financial Derivatives

Queens College, CUNY, Department of Computer Science Computational Finance CSCI 365 / 765 Spring 2018 Instructor: Dr. Sateesh Mane.

[AN INTRODUCTION TO THE BLACK-SCHOLES PDE MODEL]

Solutions of Exercises on Black Scholes model and pricing financial derivatives MQF: ACTU. 468 S you can also use d 2 = d 1 σ T

... especially dynamic volatility

Options Markets: Introduction

FINANCIAL OPTION ANALYSIS HANDOUTS

Board Meeting Handout Financial Instruments: Liabilities and Equity May 5, 2004

1 A Brief History of. Chapter. Risk and Return. Dollar Returns. PercentReturn. Learning Objectives. A Brief History of Risk and Return

FINANCIAL MATHEMATICS WITH ADVANCED TOPICS MTHE7013A

Attempt QUESTIONS 1 and 2, and THREE other questions. Do not turn over until you are told to do so by the Invigilator.

S u =$55. S u =S (1+u) S=$50. S d =$48.5. S d =S (1+d) C u = $5 = Max{55-50,0} $1.06. C u = Max{Su-X,0} (1+r) (1+r) $1.06. C d = $0 = Max{48.

Final Exam. Please answer all four questions. Each question carries 25% of the total grade.

MASM006 UNIVERSITY OF EXETER SCHOOL OF ENGINEERING, COMPUTER SCIENCE AND MATHEMATICS MATHEMATICAL SCIENCES FINANCIAL MATHEMATICS.

Derivatives Analysis & Valuation (Futures)

Credit Risk and Underlying Asset Risk *

About Black-Sholes formula, volatility, implied volatility and math. statistics.

due Saturday May 26, 2018, 12:00 noon

Asset Allocation in the 21 st Century

Monetary Economics Measuring Asset Returns. Gerald P. Dwyer Fall 2015

Implied Volatilities

Lecture 6: Option Pricing Using a One-step Binomial Tree. Thursday, September 12, 13

Dynamic Hedging and PDE Valuation

Hedging Derivative Securities with VIX Derivatives: A Discrete-Time -Arbitrage Approach

Economic Risk and Decision Analysis for Oil and Gas Industry CE School of Engineering and Technology Asian Institute of Technology

INVESTMENTS Class 2: Securities, Random Walk on Wall Street

LECTURE 12. Volatility is the question on the B/S which assumes constant SD throughout the exercise period - The time series of implied volatility

Lecture 2: Swaps. Topics Covered. The concept of a swap

UNIVERSITÀ DEGLI STUDI DI TORINO SCHOOL OF MANAGEMENT AND ECONOMICS SIMULATION MODELS FOR ECONOMICS. Final Report. Stop-Loss Strategy

Introduction to Financial Derivatives

VOLATILITY AND COST ESTIMATING

Lecture 1.2: Advanced Option Strategies

Sensex Realized Volatility Index (REALVOL)

Risk-neutral Binomial Option Valuation

Appendix to Supplement: What Determines Prices in the Futures and Options Markets?

Module 10:Application of stochastic processes in areas like finance Lecture 36:Black-Scholes Model. Stochastic Differential Equation.

OPTION PRICING: A TIME SERIES ALTERNATIVE TO BLACK-SCHOLES David R. Roberts

Department of Mathematics. Mathematics of Financial Derivatives

Aspects of Financial Mathematics:

The Black-Scholes-Merton Model

Modelling the Term Structure of Hong Kong Inter-Bank Offered Rates (HIBOR)

MS-E2114 Investment Science Exercise 10/2016, Solutions

Lesson Exponential Models & Logarithms

Econ 174 Financial Insurance Fall 2000 Allan Timmermann. Final Exam. Please answer all four questions. Each question carries 25% of the total grade.

Edgeworth Binomial Trees

Risk and Return: Past and Prologue

Some Important Concepts in Financial and Derivative Markets. Some Important Concepts in Financial and Derivative Markets

Options, American Style. Comparison of American Options and European Options

CHAPTER 3. Compound Interest

Reading: You should read Hull chapter 12 and perhaps the very first part of chapter 13.

Transcription:

Important Concepts The Black Scholes Merton (BSM) option pricing model LECTURE 3.2: OPTION PRICING MODELS: THE BLACK-SCHOLES-MERTON MODEL Black Scholes Merton Model as the Limit of the Binomial Model Origins of the Black Scholes Merton Formula A Nobel Formula 01135534: Financial Modelling Nattawut Jenwittayaroje, PhD, CFA NIDA Business School National Institute of Development Administration How to adjust the model to accommodate dividends The concepts of historical and implied volatility Estimating the Volatility BSM option pricing model for put options. 1 2 Black Scholes Merton Model as the Limit of the Binomial Model Applications of Logarithms and Exponentials in Finance Recall the binomial model and the notion of a dynamic risk free hedge in which no arbitrage opportunities are available. See the value of $1 invested for one year at 6% with various compounding frequencies.. Compounding period per year 1 (annually) 2 (semiannually) $1 invested for one year at 6% Consider the DCRB June 125 call option. Figure 5.1 shows the model price for an increasing number of time steps. The binomial model is in discrete time. As you decrease the length of each time step, it converges to continuous time. Conversion between discrete compounding and continuous compounding. 4 (quarterly) 12 (monthly) 52 (weekly) 365 (yearly) 10,000 times a year 100,000 times a year times a year The binomial model converges to the Black Scholes Merton Model as the number of time periods increases. 3 4

Origins of the Black Scholes Merton Formula Black, Scholes, Merton and the 1997 Nobel Prize F. Black and M. S. Scholes. The Pricing of Options and Corporate Liabilities. Journal of Political Economy, 81 (May June 1973), 637 659. R. C. Merton. The Theory of Rational Option Pricing. Bell Journal of Economics and Management Science, 4 (Spring 1973), 141 183. A Nobel Formula The Black Scholes Merton model gives the correct formula for a European call under certain assumptions. The general idea of the Black Scholes Merton model is the same as that of the binomial model, except that in BSM model, trading occurs continuously. So in BSM, a hedge portfolio is established and maintained by constantly adjusting the relative proportions of stock and options, a process called dynamic trading. The model is derived with complex mathematics but is easily understandable. The Black Scholes Merton formula 5 6 where A Nobel Formula (continued) N(d 1 ), N(d 2 ) = cumulative normal probability A Digression on Using the Normal Distribution The familiar normal, bell shaped curve (Figure 5.5) See Table 5.1 for determining the normal probability for d 1 and d 2. This gives you N(d 1 ) and N(d 2 ). σ = annualized standard deviation (volatility) of the continuously compounded (log) return on the stock r c = continuously compounded riskfree rate S 0 = current stock price X = exercise price T = time to expiration in years 7 8

The cumulative probabilities of the standard normal distribution A Nobel Formula (continued) A Numerical Example Price the DCRB June 125 call S 0 = 125.94, X = 125, r c = ln(1.0456) = 0.0446, where 4.56% is simple risk free rate, and 4.46% is continuously compounded risk free rate T = 0.0959, = 0.83. 9 10 Black Scholes Merton Model When the Stock Pays Dividends Known Discrete Dividends Assume a single dividend of D t where the ex dividend date is time t during the option s life. Subtract present value of dividends from stock price. Adjusted stock price, S, is inserted into the B S M model. See Table 5.3 for example. Black-Scholes-Merton Model When the Stock Pays Discrete Dividends Continuous Dividend Yield Assume the stock pays dividends continuously at the rate of. Subtract present value of dividends from stock price. Adjusted stock price, S, is inserted into the B S model. See Table 5.4 for example. This approach could also be used if the underlying is a foreign currency, where the yield is replaced by the continuously compounded foreign risk free rate. 11 12

Black-Scholes-Merton Model When the Stock Pays Continuous Dividends Put Option Pricing Models Restate put call parity with continuous discounting Substituting the B S M formula for C above gives the B S M put option pricing model The put option can also be represented as; where N(d 1 ) and N(d 2 ) are the same as in the call model. Note calculation of put price: 13 14 Estimating the Volatility Estimating the Historical Volatility There are two approaches to estimating volatility: 1) the historical volatility, and 2) the implied volatility. Historical Volatility The historical volatility estimate is based on the assumption that the volatility that prevailed over the recent past will continue to hold in the future. The historical volatility is estimated from a sample of recent continuously compounded returns on the stock. This is the volatility over a recent time period. Collect daily (weekly, or monthly) returns on the stock. Convert each return to its continuously compounded equivalent by taking ln(1 + return). Calculate variance. Annualize by multiplying by 250 (daily returns), 52 (weekly returns) or 12 (monthly returns). Take square root. See Table 5.6 for example with DCRB. 15 16

Estimating the Implied Volatility Implied Volatility This is the volatility implied when the market price of the option is set to the model price. Figure 5.17 illustrates the procedure. Substitute estimates of the volatility into the B S M formula until the market price converges to the model price. Interpreting the Implied Volatility The CBOE has constructed indices of implied volatility of one month at themoney options based on the S&P 500 (VIX) and Nasdaq (VXN). See Figure 5.20. A number of studies have examined whether implied volatility is a good predictor of the future volatility of a stock. A general consensus is that implied volatility is a better reflection of the appropriate volatility for pricing an option than is the historical volatility. 17 18 Interpreting the Implied Volatility S&P500 from Sep 2007 to May 2011 VIX is usually referred to as the fear index. It represents one measure of the market s expectation of stock market (annualized) volatility over the next 30 day period. Summary Figure 5.21 shows the relationship between call, put, underlying asset, risk free bond, put call parity, and Black Scholes Merton call and put option pricing models. VIX from Sep 2007 to May 2011 For example, if VIX is 20%, the S&P500 is expected to move up or down about 20/sqrt(12) = 5.8% over the next 30 day period. Or there is a 68% likelihood (one SD) that the magnitude of the S&P500 s 30-day return will be less than 5.8% (either up or down). Source: www.bloomberg.com 19 20