The Black-Scholes formula

Size: px
Start display at page:

Download "The Black-Scholes formula"

Transcription

1 Introduction History Revolution Aftermath V = SN(d + ) Ke rt N(d ) SCUM Math Night, December 7th, 2004

2 Introduction History Revolution Aftermath Markets and risk Options The Midas formula V = SN(d + ) Ke rt N(d ) It appears to be a simple, harmless formula, but it has been responsible for the making - and the losing - of unimaginable riches. It is a mathematical formula, and the ideas behind it are subtle. How is it that beautiful mathematics managed to get mixed up in the business of making money? And why aren t mathematicians doing better out of it?

3 Introduction History Revolution Aftermath Markets and risk Options Aristotle: B.C. The discussion of [wealth-getting] is not unworthy of philosophy, but to be engaged in [it] practically is illiberal and irksome. Thales call option: he pays a small deposit up front guaranteeing him the first call on a wine press (at an agreed rent). If the harvest is bad, he won t bother to exercise his option. But if the harvest is good, he does, makes a lot of money, and has his story told by Aristotle.

4 Introduction History Revolution Aftermath Markets and risk Options Chance and skill Aristotle thought that in the making of wealth too much was down to chance and not enough to human skill. Play Pause Resume Stop But what about the successes of traders who seem to have enough skill to pick the right stocks and beat the market?

5 Introduction History Revolution Aftermath Markets and risk Options Play Pause Resume Stop Markets are risky!

6 Introduction History Revolution Aftermath Markets and risk Options

7 Introduction History Revolution Aftermath Markets and risk Options Risk protection: selling Suppose you hold a stock and want to sell it in a year s time... A put option allows you to lock-in a minimum price for your stock, but to keep the unlimited upside. For example: the stock is currently at $50 and you protext yourself by purchasing a put option with strike price $50. When the contract expires, if the stock has risen to $60, you can sell it for $60. But if it has fallen to $40, you have the right to sell it for $50.

8 Introduction History Revolution Aftermath Markets and risk Options Risk protection: buying On the other hand, if you think you will want to invest in a particular stock, say in a month s time... A call option allows you to guarantee a maximum price you will have to pay. For example: the stock is currently at $50 and you protext yourself by purchasing a call option with strike price $50. When the contract expires, if the stock has risen to $60, you have the right to buy it for $50. But if it has fallen to $40, the you will buy it for $50.

9 Introduction History Revolution Aftermath Markets and risk Options (The initial stock price and strike price are both $1.)

10 Introduction History Revolution Aftermath Markets and risk Options Risk protection Option contracts come in many varieties puts, calls, butterfly spreads, condors, digital options, up-and-out options, swaptions,... They all involve the exchange of risk. How much is that uncertainty worth? Some people trade in options because want to be protected from risk. Others, because they want to take advantage of the increased leverage options provide. In the previous example, suppose the premium for the option is $2. If the stock goes up, the payoff is $10 and the profit is $8. A 400% profit! If the stock goes down, the payoff is zero and the premium is lost. A 100% loss!

11 Introduction History Revolution Aftermath Options trading Bachelier Gaining understanding A long,disreputable history 1600s - Holland. Tulip dealing is big business, and growers and dealers are trading in options to guarantee prices. Soon speculators are joining in and a thriving options market is born. But the market crashes, many speculators fail to honour their commitments, and the Dutch economy is brought to its knees. 1700s - London. Options are declared illegal! USA. Investment act legitimises options. Annual volume < 300, 000 contracts by April Chigaco. The CBOT starts trading listed call options on 16 stocks, with a first-day volume of 911 contracts Chigaco. The daily volume grows from 20,000 to over 200,000 contracts. So what happened to cause this explosive growth? - Mathematics!

12 Introduction History Revolution Aftermath Options trading Bachelier Gaining understanding The mathematicians are coming The search for a mathematical understanding of the behaviour of the market, and options pricing, has its beginning in the 1900 thesis of Louis Bachelier. Bachelier s thesis was titled Théorie de la Spéculation. He studies the movements of bond prices and associated options on the Parisian Bourse. He derives an analogy between the probability distribution of prices and the flow of heat. His price model is an example of Brownian motion - five years before Einstein s work on the subject. But his thesis was hardly noticed at the time - his career faltered and his work lay waiting until it was rediscovered more than fifty years later.

13 Introduction History Revolution Aftermath Options trading Bachelier Gaining understanding Brownian motion In 1827 Robert Brown observed pollen particles floating in water under the microscope and noted their jittery behaviour. In order to make sure that the motion was not due to the pollen being alive he did the same thing with dust particles. Bachelier models bond price movements in the same way Einstein later models the motion of particles under bombardment.(in fact he derives his results in three different ways.) Between any two points in time (t and t + t), the change in the bond price is a normally-distributed random variable following a bell-curve law. Any non-overlapping changes are independent. For times that are close together, the curve is peaked, and for longer times it is smeared out. This produces random, infinitely-long, but continuous curves.

14 Introduction History Revolution Aftermath Options trading Bachelier Gaining understanding Brownian motion in pictures

15 Introduction History Revolution Aftermath Options trading Bachelier Gaining understanding Rediscovery and enhancement In the 1930s and 40s, A. N. Kolmogorov, Kiyoshi Itô, Paul Lévy and Norbert Wiener put the mathematical description of Brownian motion on a much firmer basis, and Itô figures out how to do calculus on these random functions. Brownian motions are now called Wiener processes by the mathematicians. In 1955 Paul Samuelson turns his attention to option pricing. He and his students discover Bachelier s thesis. They also redefine Bachelier s model so that it refers to the logarithm of the stock price - this prevents the model from generating negative stock prices.

16 Introduction History Revolution Aftermath Options trading Bachelier Gaining understanding Geometric Brownian motion

17 Introduction History Revolution Aftermath Options trading Bachelier Gaining understanding The hunt is on In the period , people were working very hard indeed to try to solve the option pricing problem. Perhaps they had an inkling of how important such a discovery might be. Paul Samuelson - almost gets there. Guynemer Giguere - figures out boundary conditions Case Sprenkle - his model requires estimates of growth rates and investors risk-aversion. James Boness - translated Bachelier s thesis, creates an option model based on a discounted expected payoff. Henry McKean - wrote a book with Itô, a paper with Samuelson. Ed Thorp - he s even closer, building on Boness.

18 Introduction History Revolution Aftermath Options trading Bachelier Gaining understanding Almost there Play Pause Resume Stop

19 Introduction History Revolution Aftermath Convergence Balance The formula Publication Convergence In the late 1965 Fischer Black make the journey from physics to finance, joining the consulting firm Arthur D. Little. A couple of years later, Myron Scholes (hailing from our beloved northern goldmining regions) joins the faculty at MIT, and meets Black. Black and Scholes work on the option pricing problem. They realise that risk is the key - it is what is at the root of all the problems others are having, and it is what options are all about. They work on the idea of creating a small portfolio, consisting of just three items: S the stock. B a risk-free bond (a costless bank account). V the option.

20 Introduction History Revolution Aftermath Convergence Balance The formula Publication Make it go away... Their idea is to try to balance this porfolio (S, B and V ) so that the risk goes away. If the worth of the option is independent of individual preferences, then it just might be possible.... Here s what you can do. Start out by borrowing some money and investing it in S and V in some ratio. (Zero net investment.) Tomorrow, or when you next come to trade, the values of B, S and V have all changed. Your portfolio could be worth anything. But... if you choose your initial balance to minimise the uncertainty (the risk), could you get rid of it altogether? If you could, then you would know for sure the value of your portfolio tomorrow. Given that you invested nothing in it today, if its value is going to be anything but zero, you have found a money-making machine.

21 Introduction History Revolution Aftermath Convergence Balance The formula Publication Easy street? Your money-making machine is what is known as an arbitrage opportunity. The problem is that once word gets around, everybody wants a piece, and the effect of this is to puch prices the other way. The gap closes, and your machine does not work any more. Black and Scholes adopted the standard assumptions: that the grapevine works perfectly and instantaneously that there are no barriers to anyone entering into a trade, no matter how small or how often. The result of this is that these arbitrage opportunities do not exist. But this means that your perfectly-balanced portflio must still be worth nothing tomorrow. This is going to give you a handle on how the value of your option is changing with time.

22 Introduction History Revolution Aftermath Convergence Balance The formula Publication Perfect balance Consider a simplified model with these ingredients: a stock, which is currently at $50 and can move up to $60 or down to $30. a call option with strike price $45. a zero interest rate. Create a portfolio consisting of buying one stock, selling two options, and borrowing $30. If the stock goes up, the net value is $60-2 $15 - $30 = 0. If the stock goes down, the net value is $30 - $30 = 0. The value at the start must be zero - so V = $10.

23 Introduction History Revolution Aftermath Convergence Balance The formula Publication In continuous time In the previous example, we created a portfolio that was perfectly balanced - in all eventualities its value stayed at zero. Can we do this with a more realistic model? Well, the answer is no. Here s the best you can do if you rebalance once a day...

24 Introduction History Revolution Aftermath Convergence Balance The formula Publication

25 Introduction History Revolution Aftermath Convergence Balance The formula Publication Trading more often If turns out that you can do better if you rebalance once an hour...

26 Introduction History Revolution Aftermath Convergence Balance The formula Publication

27 Introduction History Revolution Aftermath Convergence Balance The formula Publication Robert Merton Merton arrived on the scene in 1968 and brought with him expertise in Itô calculus, and an understanding of continuous-time stochastic processes. He met Scholes in 1969 and it was he who figured out that their dream of perfect balance could be achieved by continuously adjusting their portfolio. Here s the result of our previous experiment, rebalancing every minute of the year...

28 Introduction History Revolution Aftermath Convergence Balance The formula Publication

29 Introduction History Revolution Aftermath Convergence Balance The formula Publication The balance equation Achieving perfect balance tells you that the value of your portfolio is stable over time, and the no arbitrage principle then forces the option value to depend on S and B and the time t in a particular way. If r is the continuously-compounded rate of interest earned by B, and σ is a measure of the volatility of S, then V t + rs V S + σ2 2 S 2 2 V S 2 = rv. This is what has become known as the Black-Scholes equation. It had already been solved by McKean, and the solution is the formula everyone had been looking for.

30 The formula Introduction History Revolution Aftermath Convergence Balance The formula Publication The value of a call option on an asset S, expiring at time T, with strike price K is V = SN(d + ) Ke rt N(d ), where N(x) is the cumulative normal distribution function, d ± = S/Ke rt ± σ2 T 2 σ T and r is the risk-free interest rate, continuously-compounded, and σ is the volatility of the asset. The balance is struck by selling N(d + ) units of the asset for every unit option bought. This is known as the delta, or hedge ratio.,

31 Introduction History Revolution Aftermath Convergence Balance The formula Publication The option value surface

32 Introduction History Revolution Aftermath Convergence Balance The formula Publication Getting it out Black and Scholes had a little trouble getting their paper published. They had to try three times the first two times the paper was rejected without even being reviewed! The suspicion is that Black s non-academic position may have had something to do with it. Merton had written his own version, more general than Black and Scholes, but he graciously delayed the publication of his until their paper appeared.

33 Introduction History Revolution Aftermath Nobel prizes LTCM Nobel s for almost all Myron Scholes Robert C. Merton

34 Introduction History Revolution Aftermath Nobel prizes LTCM Death of a dream Merton and Scholes wanted to see their ideas in practice. They teamed up with some of the top investors from Wall Street to form a new company - Long Term Capital Management. They raised $3 billion from investors, including many of the major banks, on the promise of using dynamic hedging (a.k.a. continuous rebalancing) on a huge scale to form a gigantic vacuum cleaner sucking up nickels from around the world. They were enormously successful - returning 20%, 43% and 41% to their investors in the first three years.

35 Introduction History Revolution Aftermath Nobel prizes LTCM Death of a dream But at the tail end of the century things started to go wrong. The trouble started in asia - markets were collapsing and deviating significantly from their historical norms. LTCM carried on as normal, convinced that things would stabilize. When Russia defaulted, the game was up. In order to prevent the global economic collapse that would have resulted from the failure of LTCM (!), the Federal Reserve had no choice but to bail out LTCM - to the tune of $3 billion.

36 Introduction History Revolution Aftermath Nobel prizes LTCM Summing up Mathematics plays an unexpectedly significant role in the operation of financial markets. Mathematics provides powerful tools for understanding and even controlling the nature and effects of uncertainty and risk. But some humility is called for!

Options and the Black-Scholes Model BY CHASE JAEGER

Options and the Black-Scholes Model BY CHASE JAEGER Options and the Black-Scholes Model BY CHASE JAEGER Defining Options A put option (usually just called a "put") is a financial contract between two parties, the writer (seller) and the buyer of the option.

More information

Randomness and Fractals

Randomness and Fractals Randomness and Fractals Why do so many physicists become traders? Gregory F. Lawler Department of Mathematics Department of Statistics University of Chicago September 25, 2011 1 / 24 Mathematics and the

More information

Some history. The random walk model. Lecture notes on forecasting Robert Nau Fuqua School of Business Duke University

Some history. The random walk model. Lecture notes on forecasting Robert Nau Fuqua School of Business Duke University Lecture notes on forecasting Robert Nau Fuqua School of Business Duke University http://people.duke.edu/~rnau/forecasting.htm The random walk model Some history Brownian motion is a random walk in continuous

More information

The Black-Scholes Model

The Black-Scholes Model IEOR E4706: Foundations of Financial Engineering c 2016 by Martin Haugh The Black-Scholes Model In these notes we will use Itô s Lemma and a replicating argument to derive the famous Black-Scholes formula

More information

How quantitative methods influence and shape finance industry

How quantitative methods influence and shape finance industry How quantitative methods influence and shape finance industry Marek Musiela UNSW December 2017 Non-quantitative talk about the role quantitative methods play in finance industry. Focus on investment banking,

More information

How Much Should You Pay For a Financial Derivative?

How Much Should You Pay For a Financial Derivative? City University of New York (CUNY) CUNY Academic Works Publications and Research New York City College of Technology Winter 2-26-2016 How Much Should You Pay For a Financial Derivative? Boyan Kostadinov

More information

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

Appendix to Supplement: What Determines Prices in the Futures and Options Markets? Appendix to Supplement: What Determines Prices in the Futures and Options Markets? 0 ne probably does need to be a rocket scientist to figure out the latest wrinkles in the pricing formulas used by professionals

More information

[AN INTRODUCTION TO THE BLACK-SCHOLES PDE MODEL]

[AN INTRODUCTION TO THE BLACK-SCHOLES PDE MODEL] 2013 University of New Mexico Scott Guernsey [AN INTRODUCTION TO THE BLACK-SCHOLES PDE MODEL] This paper will serve as background and proposal for an upcoming thesis paper on nonlinear Black- Scholes PDE

More information

BUSM 411: Derivatives and Fixed Income

BUSM 411: Derivatives and Fixed Income BUSM 411: Derivatives and Fixed Income 3. Uncertainty and Risk Uncertainty and risk lie at the core of everything we do in finance. In order to make intelligent investment and hedging decisions, we need

More information

FIN FINANCIAL INSTRUMENTS SPRING 2008

FIN FINANCIAL INSTRUMENTS SPRING 2008 FIN-40008 FINANCIAL INSTRUMENTS SPRING 2008 The Greeks Introduction We have studied how to price an option using the Black-Scholes formula. Now we wish to consider how the option price changes, either

More information

The Black-Scholes Model

The Black-Scholes Model The Black-Scholes Model Liuren Wu Options Markets Liuren Wu ( c ) The Black-Merton-Scholes Model colorhmoptions Markets 1 / 18 The Black-Merton-Scholes-Merton (BMS) model Black and Scholes (1973) and Merton

More information

Evaluating the Black-Scholes option pricing model using hedging simulations

Evaluating the Black-Scholes option pricing model using hedging simulations Bachelor Informatica Informatica Universiteit van Amsterdam Evaluating the Black-Scholes option pricing model using hedging simulations Wendy Günther CKN : 6052088 Wendy.Gunther@student.uva.nl June 24,

More information

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

Lecture 6: Option Pricing Using a One-step Binomial Tree. Thursday, September 12, 13 Lecture 6: Option Pricing Using a One-step Binomial Tree An over-simplified model with surprisingly general extensions a single time step from 0 to T two types of traded securities: stock S and a bond

More information

Risk Neutral Pricing Black-Scholes Formula Lecture 19. Dr. Vasily Strela (Morgan Stanley and MIT)

Risk Neutral Pricing Black-Scholes Formula Lecture 19. Dr. Vasily Strela (Morgan Stanley and MIT) Risk Neutral Pricing Black-Scholes Formula Lecture 19 Dr. Vasily Strela (Morgan Stanley and MIT) Risk Neutral Valuation: Two-Horse Race Example One horse has 20% chance to win another has 80% chance $10000

More information

The Black-Scholes Model

The Black-Scholes Model The Black-Scholes Model Liuren Wu Options Markets (Hull chapter: 12, 13, 14) Liuren Wu ( c ) The Black-Scholes Model colorhmoptions Markets 1 / 17 The Black-Scholes-Merton (BSM) model Black and Scholes

More information

1) Understanding Equity Options 2) Setting up Brokerage Systems

1) Understanding Equity Options 2) Setting up Brokerage Systems 1) Understanding Equity Options 2) Setting up Brokerage Systems M. Aras Orhan, 12.10.2013 FE 500 Intro to Financial Engineering 12.10.2013, ARAS ORHAN, Intro to Fin Eng, Boğaziçi University 1 Today s agenda

More information

Options Markets: Introduction

Options Markets: Introduction 17-2 Options Options Markets: Introduction Derivatives are securities that get their value from the price of other securities. Derivatives are contingent claims because their payoffs depend on the value

More information

Black Scholes Equation Luc Ashwin and Calum Keeley

Black Scholes Equation Luc Ashwin and Calum Keeley Black Scholes Equation Luc Ashwin and Calum Keeley In the world of finance, traders try to take as little risk as possible, to have a safe, but positive return. As George Box famously said, All models

More information

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

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 DERIVATIVES OPTIONS A. INTRODUCTION There are 2 Types of Options Calls: give the holder the RIGHT, at his discretion, to BUY a Specified number of a Specified Asset at a Specified Price on, or until, a

More information

University of Colorado at Boulder Leeds School of Business MBAX-6270 MBAX Introduction to Derivatives Part II Options Valuation

University of Colorado at Boulder Leeds School of Business MBAX-6270 MBAX Introduction to Derivatives Part II Options Valuation MBAX-6270 Introduction to Derivatives Part II Options Valuation Notation c p S 0 K T European call option price European put option price Stock price (today) Strike price Maturity of option Volatility

More information

Option Volatility & Arbitrage Opportunities

Option Volatility & Arbitrage Opportunities Louisiana State University LSU Digital Commons LSU Master's Theses Graduate School 2016 Option Volatility & Arbitrage Opportunities Mikael Boffetti Louisiana State University and Agricultural and Mechanical

More information

ECON FINANCIAL ECONOMICS

ECON FINANCIAL ECONOMICS ECON 337901 FINANCIAL ECONOMICS Peter Ireland Boston College Fall 2017 These lecture notes by Peter Ireland are licensed under a Creative Commons Attribution-NonCommerical-ShareAlike 4.0 International

More information

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

Queens College, CUNY, Department of Computer Science Computational Finance CSCI 365 / 765 Fall 2017 Instructor: Dr. Sateesh Mane. Queens College, CUNY, Department of Computer Science Computational Finance CSCI 365 / 765 Fall 2017 Instructor: Dr. Sateesh Mane c Sateesh R. Mane 2017 14 Lecture 14 November 15, 2017 Derivation of the

More information

The Black-Scholes PDE from Scratch

The Black-Scholes PDE from Scratch The Black-Scholes PDE from Scratch chris bemis November 27, 2006 0-0 Goal: Derive the Black-Scholes PDE To do this, we will need to: Come up with some dynamics for the stock returns Discuss Brownian motion

More information

Corporate Finance, Module 21: Option Valuation. Practice Problems. (The attached PDF file has better formatting.) Updated: July 7, 2005

Corporate Finance, Module 21: Option Valuation. Practice Problems. (The attached PDF file has better formatting.) Updated: July 7, 2005 Corporate Finance, Module 21: Option Valuation Practice Problems (The attached PDF file has better formatting.) Updated: July 7, 2005 {This posting has more information than is needed for the corporate

More information

ValueWalk Interview With Chris Abraham Of CVA Investment Management

ValueWalk Interview With Chris Abraham Of CVA Investment Management ValueWalk Interview With Chris Abraham Of CVA Investment Management ValueWalk Interview With Chris Abraham Of CVA Investment Management Rupert Hargreaves: You run a unique, value-based options strategy

More information

4. Black-Scholes Models and PDEs. Math6911 S08, HM Zhu

4. Black-Scholes Models and PDEs. Math6911 S08, HM Zhu 4. Black-Scholes Models and PDEs Math6911 S08, HM Zhu References 1. Chapter 13, J. Hull. Section.6, P. Brandimarte Outline Derivation of Black-Scholes equation Black-Scholes models for options Implied

More information

FURTHER ASPECTS OF GAMBLING WITH THE KELLY CRITERION. We consider two aspects of gambling with the Kelly criterion. First, we show that for

FURTHER ASPECTS OF GAMBLING WITH THE KELLY CRITERION. We consider two aspects of gambling with the Kelly criterion. First, we show that for FURTHER ASPECTS OF GAMBLING WITH THE KELLY CRITERION RAVI PHATARFOD *, Monash University Abstract We consider two aspects of gambling with the Kelly criterion. First, we show that for a wide range of final

More information

STRATEGIES WITH OPTIONS

STRATEGIES WITH OPTIONS MÄLARDALEN UNIVERSITY PROJECT DEPARTMENT OF MATHEMATICS AND PHYSICS ANALYTICAL FINANCE I, MT1410 TEACHER: JAN RÖMAN 2003-10-21 STRATEGIES WITH OPTIONS GROUP 3: MAGNUS SÖDERHOLTZ MAZYAR ROSTAMI SABAHUDIN

More information

Practical Hedging: From Theory to Practice. OSU Financial Mathematics Seminar May 5, 2008

Practical Hedging: From Theory to Practice. OSU Financial Mathematics Seminar May 5, 2008 Practical Hedging: From Theory to Practice OSU Financial Mathematics Seminar May 5, 008 Background Dynamic replication is a risk management technique used to mitigate market risk We hope to spend a certain

More information

Deriving and Solving the Black-Scholes Equation

Deriving and Solving the Black-Scholes Equation Introduction Deriving and Solving the Black-Scholes Equation Shane Moore April 27, 2014 The Black-Scholes equation, named after Fischer Black and Myron Scholes, is a partial differential equation, which

More information

Appendix A Financial Calculations

Appendix A Financial Calculations Derivatives Demystified: A Step-by-Step Guide to Forwards, Futures, Swaps and Options, Second Edition By Andrew M. Chisholm 010 John Wiley & Sons, Ltd. Appendix A Financial Calculations TIME VALUE OF MONEY

More information

Forwards, Futures, Options and Swaps

Forwards, Futures, Options and Swaps Forwards, Futures, Options and Swaps A derivative asset is any asset whose payoff, price or value depends on the payoff, price or value of another asset. The underlying or primitive asset may be almost

More information

Chapter 2 Black-Scholes

Chapter 2 Black-Scholes Chapter 2 Black-Scholes Through my parents and relatives I became interested in economics and, in particular, finance. My mother loved business and wanted me to work with her brother in his book publishing

More information

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

Queens College, CUNY, Department of Computer Science Computational Finance CSCI 365 / 765 Fall 2017 Instructor: Dr. Sateesh Mane. Queens College, CUNY, Department of Computer Science Computational Finance CSCI 365 / 765 Fall 2017 Instructor: Dr. Sateesh Mane c Sateesh R. Mane 2017 20 Lecture 20 Implied volatility November 30, 2017

More information

Options, Futures and Structured Products

Options, Futures and Structured Products Options, Futures and Structured Products Jos van Bommel Aalto Period 5 2017 Options Options calls and puts are key tools of financial engineers. A call option gives the holder the right (but not the obligation)

More information

Risk Neutral Pricing. to government bonds (provided that the government is reliable).

Risk Neutral Pricing. to government bonds (provided that the government is reliable). Risk Neutral Pricing 1 Introduction and History A classical problem, coming up frequently in practical business, is the valuation of future cash flows which are somewhat risky. By the term risky we mean

More information

TradeOptionsWithMe.com

TradeOptionsWithMe.com TradeOptionsWithMe.com 1 of 18 Option Trading Glossary This is the Glossary for important option trading terms. Some of these terms are rather easy and used extremely often, but some may even be new to

More information

Financial Derivatives Section 5

Financial Derivatives Section 5 Financial Derivatives Section 5 The Black and Scholes Model Michail Anthropelos anthropel@unipi.gr http://web.xrh.unipi.gr/faculty/anthropelos/ University of Piraeus Spring 2018 M. Anthropelos (Un. of

More information

FINANCIAL MATHEMATICS WITH ADVANCED TOPICS MTHE7013A

FINANCIAL MATHEMATICS WITH ADVANCED TOPICS MTHE7013A UNIVERSITY OF EAST ANGLIA School of Mathematics Main Series UG Examination 2016 17 FINANCIAL MATHEMATICS WITH ADVANCED TOPICS MTHE7013A Time allowed: 3 Hours Attempt QUESTIONS 1 and 2, and THREE other

More information

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

MASM006 UNIVERSITY OF EXETER SCHOOL OF ENGINEERING, COMPUTER SCIENCE AND MATHEMATICS MATHEMATICAL SCIENCES FINANCIAL MATHEMATICS. MASM006 UNIVERSITY OF EXETER SCHOOL OF ENGINEERING, COMPUTER SCIENCE AND MATHEMATICS MATHEMATICAL SCIENCES FINANCIAL MATHEMATICS May/June 2006 Time allowed: 2 HOURS. Examiner: Dr N.P. Byott This is a CLOSED

More information

Merton s Jump Diffusion Model. David Bonnemort, Yunhye Chu, Cory Steffen, Carl Tams

Merton s Jump Diffusion Model. David Bonnemort, Yunhye Chu, Cory Steffen, Carl Tams Merton s Jump Diffusion Model David Bonnemort, Yunhye Chu, Cory Steffen, Carl Tams Outline Background The Problem Research Summary & future direction Background Terms Option: (Call/Put) is a derivative

More information

Math 5760/6890 Introduction to Mathematical Finance

Math 5760/6890 Introduction to Mathematical Finance Math 5760/6890 Introduction to Mathematical Finance Instructor: Jingyi Zhu Office: LCB 335 Telephone:581-3236 E-mail: zhu@math.utah.edu Class web page: www.math.utah.edu/~zhu/5760_12f.html What you should

More information

1.1 Interest rates Time value of money

1.1 Interest rates Time value of money Lecture 1 Pre- Derivatives Basics Stocks and bonds are referred to as underlying basic assets in financial markets. Nowadays, more and more derivatives are constructed and traded whose payoffs depend on

More information

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

CHAPTER 10 OPTION PRICING - II. Derivatives and Risk Management By Rajiv Srivastava. Copyright Oxford University Press CHAPTER 10 OPTION PRICING - II Options Pricing II Intrinsic Value and Time Value Boundary Conditions for Option Pricing Arbitrage Based Relationship for Option Pricing Put Call Parity 2 Binomial Option

More information

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

Valuing Stock Options: The Black-Scholes-Merton Model. Chapter 13 Valuing Stock Options: The Black-Scholes-Merton Model Chapter 13 1 The Black-Scholes-Merton Random Walk Assumption l Consider a stock whose price is S l In a short period of time of length t the return

More information

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

Attempt QUESTIONS 1 and 2, and THREE other questions. Do not turn over until you are told to do so by the Invigilator. UNIVERSITY OF EAST ANGLIA School of Mathematics Main Series UG Examination 2016 17 FINANCIAL MATHEMATICS MTHE6026A Time allowed: 3 Hours Attempt QUESTIONS 1 and 2, and THREE other questions. Notes are

More information

Stats243 Introduction to Mathematical Finance

Stats243 Introduction to Mathematical Finance Stats243 Introduction to Mathematical Finance Haipeng Xing Department of Statistics Stanford University Summer 2006 Stats243, Xing, Summer 2007 1 Agenda Administrative, course description & reference,

More information

Iterated Dominance and Nash Equilibrium

Iterated Dominance and Nash Equilibrium Chapter 11 Iterated Dominance and Nash Equilibrium In the previous chapter we examined simultaneous move games in which each player had a dominant strategy; the Prisoner s Dilemma game was one example.

More information

Forex Illusions - 6 Illusions You Need to See Through to Win

Forex Illusions - 6 Illusions You Need to See Through to Win Forex Illusions - 6 Illusions You Need to See Through to Win See the Reality & Forex Trading Success can Be Yours! The myth of Forex trading is one which the public believes and they lose and its a whopping

More information

Aspects of Financial Mathematics:

Aspects of Financial Mathematics: Aspects of Financial Mathematics: Options, Derivatives, Arbitrage, and the Black-Scholes Pricing Formula J. Robert Buchanan Millersville University of Pennsylvania email: Bob.Buchanan@millersville.edu

More information

MFIN 7003 Module 2. Mathematical Techniques in Finance. Sessions B&C: Oct 12, 2015 Nov 28, 2015

MFIN 7003 Module 2. Mathematical Techniques in Finance. Sessions B&C: Oct 12, 2015 Nov 28, 2015 MFIN 7003 Module 2 Mathematical Techniques in Finance Sessions B&C: Oct 12, 2015 Nov 28, 2015 Instructor: Dr. Rujing Meng Room 922, K. K. Leung Building School of Economics and Finance The University of

More information

Mathematics of Finance Final Preparation December 19. To be thoroughly prepared for the final exam, you should

Mathematics of Finance Final Preparation December 19. To be thoroughly prepared for the final exam, you should Mathematics of Finance Final Preparation December 19 To be thoroughly prepared for the final exam, you should 1. know how to do the homework problems. 2. be able to provide (correct and complete!) definitions

More information

Department of Mathematics. Mathematics of Financial Derivatives

Department of Mathematics. Mathematics of Financial Derivatives Department of Mathematics MA408 Mathematics of Financial Derivatives Thursday 15th January, 2009 2pm 4pm Duration: 2 hours Attempt THREE questions MA408 Page 1 of 5 1. (a) Suppose 0 < E 1 < E 3 and E 2

More information

We discussed last time how the Girsanov theorem allows us to reweight probability measures to change the drift in an SDE.

We discussed last time how the Girsanov theorem allows us to reweight probability measures to change the drift in an SDE. Risk Neutral Pricing Thursday, May 12, 2011 2:03 PM We discussed last time how the Girsanov theorem allows us to reweight probability measures to change the drift in an SDE. This is used to construct a

More information

Lecture Quantitative Finance Spring Term 2015

Lecture Quantitative Finance Spring Term 2015 and Lecture Quantitative Finance Spring Term 2015 Prof. Dr. Erich Walter Farkas Lecture 06: March 26, 2015 1 / 47 Remember and Previous chapters: introduction to the theory of options put-call parity fundamentals

More information

Optimization in Financial Engineering in the Post-Boom Market

Optimization in Financial Engineering in the Post-Boom Market Optimization in Financial Engineering in the Post-Boom Market John R. Birge Northwestern University www.iems.northwestern.edu/~jrbirge SIAM Optimization Toronto May 2002 1 Introduction History of financial

More information

Pricing Options with Mathematical Models

Pricing Options with Mathematical Models Pricing Options with Mathematical Models 1. OVERVIEW Some of the content of these slides is based on material from the book Introduction to the Economics and Mathematics of Financial Markets by Jaksa Cvitanic

More information

Option pricing. School of Business C-thesis in Economics, 10p Course code: EN0270 Supervisor: Johan Lindén

Option pricing. School of Business C-thesis in Economics, 10p Course code: EN0270 Supervisor: Johan Lindén School of Business C-thesis in Economics, 1p Course code: EN27 Supervisor: Johan Lindén 25-5-3 Option pricing A Test of the Black & scholes theory using market data By Marlon Gerard Silos & Glyn Grimwade

More information

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

B. Combinations. 1. Synthetic Call (Put-Call Parity). 2. Writing a Covered Call. 3. Straddle, Strangle. 4. Spreads (Bull, Bear, Butterfly). 1 EG, Ch. 22; Options I. Overview. A. Definitions. 1. Option - contract in entitling holder to buy/sell a certain asset at or before a certain time at a specified price. Gives holder the right, but not

More information

Energy Price Processes

Energy Price Processes Energy Processes Used for Derivatives Pricing & Risk Management In this first of three articles, we will describe the most commonly used process, Geometric Brownian Motion, and in the second and third

More information

INVESTMENTS Class 2: Securities, Random Walk on Wall Street

INVESTMENTS Class 2: Securities, Random Walk on Wall Street 15.433 INVESTMENTS Class 2: Securities, Random Walk on Wall Street Reto R. Gallati MIT Sloan School of Management Spring 2003 February 5th 2003 Outline Probability Theory A brief review of probability

More information

Definition Pricing Risk management Second generation barrier options. Barrier Options. Arfima Financial Solutions

Definition Pricing Risk management Second generation barrier options. Barrier Options. Arfima Financial Solutions Arfima Financial Solutions Contents Definition 1 Definition 2 3 4 Contenido Definition 1 Definition 2 3 4 Definition Definition: A barrier option is an option on the underlying asset that is activated

More information

Black Scholes Option Valuation. Option Valuation Part III. Put Call Parity. Example 18.3 Black Scholes Put Valuation

Black Scholes Option Valuation. Option Valuation Part III. Put Call Parity. Example 18.3 Black Scholes Put Valuation Black Scholes Option Valuation Option Valuation Part III Example 18.3 Black Scholes Put Valuation Put Call Parity 1 Put Call Parity Another way to look at Put Call parity is Hedge Ratio C P = D (S F X)

More information

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

The Merton Model. A Structural Approach to Default Prediction. Agenda. Idea. Merton Model. The iterative approach. Example: Enron The Merton Model A Structural Approach to Default Prediction Agenda Idea Merton Model The iterative approach Example: Enron A solution using equity values and equity volatility Example: Enron 2 1 Idea

More information

STOCHASTIC CALCULUS AND BLACK-SCHOLES MODEL

STOCHASTIC CALCULUS AND BLACK-SCHOLES MODEL STOCHASTIC CALCULUS AND BLACK-SCHOLES MODEL YOUNGGEUN YOO Abstract. Ito s lemma is often used in Ito calculus to find the differentials of a stochastic process that depends on time. This paper will introduce

More information

Background. This section covers information that is needed to understand the rise and fall of LTCM.

Background. This section covers information that is needed to understand the rise and fall of LTCM. Introduction In the beginning of the 1900s academics became interested in how they analytically could construct mathematical models for trading in options. The entering of academics on the stock market

More information

Basic Tools of Finance (Chapter 27 in Mankiw & Taylor)

Basic Tools of Finance (Chapter 27 in Mankiw & Taylor) Basic Tools of Finance (Chapter 27 in Mankiw & Taylor) We have seen that the financial system coordinates saving and investment These are decisions made today that affect us in the future But the future

More information

MATH 425 EXERCISES G. BERKOLAIKO

MATH 425 EXERCISES G. BERKOLAIKO MATH 425 EXERCISES G. BERKOLAIKO 1. Definitions and basic properties of options and other derivatives 1.1. Summary. Definition of European call and put options, American call and put option, forward (futures)

More information

Should we fear derivatives? By Rene M Stulz, Journal of Economic Perspectives, Summer 2004

Should we fear derivatives? By Rene M Stulz, Journal of Economic Perspectives, Summer 2004 Should we fear derivatives? By Rene M Stulz, Journal of Economic Perspectives, Summer 2004 Derivatives are instruments whose payoffs are derived from an underlying asset. Plain vanilla derivatives include

More information

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

Advanced Topics in Derivative Pricing Models. Topic 4 - Variance products and volatility derivatives Advanced Topics in Derivative Pricing Models Topic 4 - Variance products and volatility derivatives 4.1 Volatility trading and replication of variance swaps 4.2 Volatility swaps 4.3 Pricing of discrete

More information

non linear Payoffs Markus K. Brunnermeier

non linear Payoffs Markus K. Brunnermeier Institutional Finance Lecture 10: Dynamic Arbitrage to Replicate non linear Payoffs Markus K. Brunnermeier Preceptor: Dong Beom Choi Princeton University 1 BINOMIAL OPTION PRICING Consider a European call

More information

Math489/889 Stochastic Processes and Advanced Mathematical Finance Solutions to Practice Problems

Math489/889 Stochastic Processes and Advanced Mathematical Finance Solutions to Practice Problems Math489/889 Stochastic Processes and Advanced Mathematical Finance Solutions to Practice Problems Steve Dunbar No Due Date: Practice Only. Find the mode (the value of the independent variable with the

More information

Chapter 5. Risk Handling Techniques: Diversification and Hedging. Risk Bearing Institutions. Additional Benefits. Chapter 5 Page 1

Chapter 5. Risk Handling Techniques: Diversification and Hedging. Risk Bearing Institutions. Additional Benefits. Chapter 5 Page 1 Chapter 5 Risk Handling Techniques: Diversification and Hedging Risk Bearing Institutions Bearing risk collectively Diversification Examples: Pension Plans Mutual Funds Insurance Companies Additional Benefits

More information

ECON Microeconomics II IRYNA DUDNYK. Auctions.

ECON Microeconomics II IRYNA DUDNYK. Auctions. Auctions. What is an auction? When and whhy do we need auctions? Auction is a mechanism of allocating a particular object at a certain price. Allocating part concerns who will get the object and the price

More information

Mathematics in Finance

Mathematics in Finance Mathematics in Finance Steven E. Shreve Department of Mathematical Sciences Carnegie Mellon University Pittsburgh, PA 15213 USA shreve@andrew.cmu.edu A Talk in the Series Probability in Science and Industry

More information

Lecture 4: Barrier Options

Lecture 4: Barrier Options Lecture 4: Barrier Options Jim Gatheral, Merrill Lynch Case Studies in Financial Modelling Course Notes, Courant Institute of Mathematical Sciences, Fall Term, 2001 I am grateful to Peter Friz for carefully

More information

UNIVERSITY OF AGDER EXAM. Faculty of Economicsand Social Sciences. Exam code: Exam name: Date: Time: Number of pages: Number of problems: Enclosure:

UNIVERSITY OF AGDER EXAM. Faculty of Economicsand Social Sciences. Exam code: Exam name: Date: Time: Number of pages: Number of problems: Enclosure: UNIVERSITY OF AGDER Faculty of Economicsand Social Sciences Exam code: Exam name: Date: Time: Number of pages: Number of problems: Enclosure: Exam aids: Comments: EXAM BE-411, ORDINARY EXAM Derivatives

More information

Pricing theory of financial derivatives

Pricing theory of financial derivatives Pricing theory of financial derivatives One-period securities model S denotes the price process {S(t) : t = 0, 1}, where S(t) = (S 1 (t) S 2 (t) S M (t)). Here, M is the number of securities. At t = 1,

More information

Optimization Models in Financial Engineering and Modeling Challenges

Optimization Models in Financial Engineering and Modeling Challenges Optimization Models in Financial Engineering and Modeling Challenges John Birge University of Chicago Booth School of Business JRBirge UIUC, 25 Mar 2009 1 Introduction History of financial engineering

More information

Learn To Trade Stock Options

Learn To Trade Stock Options Learn To Trade Stock Options Written by: Jason Ramus www.daytradingfearless.com Copyright: 2017 Table of contents: WHAT TO EXPECT FROM THIS MANUAL WHAT IS AN OPTION BASICS OF HOW AN OPTION WORKS RECOMMENDED

More information

Lecture 1 Definitions from finance

Lecture 1 Definitions from finance Lecture 1 s from finance Financial market instruments can be divided into two types. There are the underlying stocks shares, bonds, commodities, foreign currencies; and their derivatives, claims that promise

More information

Hedging. MATH 472 Financial Mathematics. J. Robert Buchanan

Hedging. MATH 472 Financial Mathematics. J. Robert Buchanan Hedging MATH 472 Financial Mathematics J. Robert Buchanan 2018 Introduction Definition Hedging is the practice of making a portfolio of investments less sensitive to changes in market variables. There

More information

Hedging Credit Derivatives in Intensity Based Models

Hedging Credit Derivatives in Intensity Based Models Hedging Credit Derivatives in Intensity Based Models PETER CARR Head of Quantitative Financial Research, Bloomberg LP, New York Director of the Masters Program in Math Finance, Courant Institute, NYU Stanford

More information

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

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

More information

FE610 Stochastic Calculus for Financial Engineers. Stevens Institute of Technology

FE610 Stochastic Calculus for Financial Engineers. Stevens Institute of Technology FE610 Stochastic Calculus for Financial Engineers Lecture 13. The Black-Scholes PDE Steve Yang Stevens Institute of Technology 04/25/2013 Outline 1 The Black-Scholes PDE 2 PDEs in Asset Pricing 3 Exotic

More information

Lecture Notes for Chapter 6. 1 Prototype model: a one-step binomial tree

Lecture Notes for Chapter 6. 1 Prototype model: a one-step binomial tree Lecture Notes for Chapter 6 This is the chapter that brings together the mathematical tools (Brownian motion, Itô calculus) and the financial justifications (no-arbitrage pricing) to produce the derivative

More information

CHAPTER 27: OPTION PRICING THEORY

CHAPTER 27: OPTION PRICING THEORY CHAPTER 27: OPTION PRICING THEORY 27-1 a. False. The reverse is true. b. True. Higher variance increases option value. c. True. Otherwise, arbitrage will be possible. d. False. Put-call parity can cut

More information

How Much Profits You Should Expect from Trading Forex

How Much Profits You Should Expect from Trading Forex How Much Profits You Should Expect from Trading Roman Sadowski Trading forex is full of misconceptions indeed. Many novice s come into trading forex through very smart marketing techniques. These techniques

More information

Stochastic Processes and Advanced Mathematical Finance. Brief History of Mathematical Finance

Stochastic Processes and Advanced Mathematical Finance. Brief History of Mathematical Finance Steven R. Dunbar Department of Mathematics 203 Avery Hall University of Nebraska-Lincoln Lincoln, NE 68588-0130 http://www.math.unl.edu Voice: 402-472-3731 Fax: 402-472-8466 Stochastic Processes and Advanced

More information

Next time you see a financial instrument that involves academics or Ph.D.s, steer clear of it. Especially those designed by Nobel Prize winners!

Next time you see a financial instrument that involves academics or Ph.D.s, steer clear of it. Especially those designed by Nobel Prize winners! Copyright 2009 Horsesmouth, LLC. All Rights Reserved. For the exclusive use of Horsesmouth Member: Jim Otar SEE BELOW FOR IMPORTANT RESTRICTIONS ON USE. Build Knowledge/Investment Theory & Strategy The

More information

Chapter 14. Exotic Options: I. Question Question Question Question The geometric averages for stocks will always be lower.

Chapter 14. Exotic Options: I. Question Question Question Question The geometric averages for stocks will always be lower. Chapter 14 Exotic Options: I Question 14.1 The geometric averages for stocks will always be lower. Question 14.2 The arithmetic average is 5 (three 5s, one 4, and one 6) and the geometric average is (5

More information

BINARY OPTIONS: A SMARTER WAY TO TRADE THE WORLD'S MARKETS NADEX.COM

BINARY OPTIONS: A SMARTER WAY TO TRADE THE WORLD'S MARKETS NADEX.COM BINARY OPTIONS: A SMARTER WAY TO TRADE THE WORLD'S MARKETS NADEX.COM CONTENTS To Be or Not To Be? That s a Binary Question Who Sets a Binary Option's Price? And How? Price Reflects Probability Actually,

More information

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

Reading: You should read Hull chapter 12 and perhaps the very first part of chapter 13. FIN-40008 FINANCIAL INSTRUMENTS SPRING 2008 Asset Price Dynamics Introduction These notes give assumptions of asset price returns that are derived from the efficient markets hypothesis. Although a hypothesis,

More information

arxiv: v2 [q-fin.gn] 13 Aug 2018

arxiv: v2 [q-fin.gn] 13 Aug 2018 A DERIVATION OF THE BLACK-SCHOLES OPTION PRICING MODEL USING A CENTRAL LIMIT THEOREM ARGUMENT RAJESHWARI MAJUMDAR, PHANUEL MARIANO, LOWEN PENG, AND ANTHONY SISTI arxiv:18040390v [q-fingn] 13 Aug 018 Abstract

More information

Find Private Lenders Now CHAPTER 10. At Last! How To. 114 Copyright 2010 Find Private Lenders Now, LLC All Rights Reserved

Find Private Lenders Now CHAPTER 10. At Last! How To. 114 Copyright 2010 Find Private Lenders Now, LLC All Rights Reserved CHAPTER 10 At Last! How To Structure Your Deal 114 Copyright 2010 Find Private Lenders Now, LLC All Rights Reserved 1. Terms You will need to come up with a loan-to-value that will work for your business

More information

The #1 Way To Make Weekly Income With Weekly Options. Jack Carter

The #1 Way To Make Weekly Income With Weekly Options. Jack Carter The #1 Way To Make Weekly Income With Weekly Options Jack Carter 1 Disclaimer: The risk of loss in trading options can be substantial, and you should carefully consider whether this trading is suitable

More information

Global Financial Management. Option Contracts

Global Financial Management. Option Contracts Global Financial Management Option Contracts Copyright 1997 by Alon Brav, Campbell R. Harvey, Ernst Maug and Stephen Gray. All rights reserved. No part of this lecture may be reproduced without the permission

More information

Derivative Securities Fall 2012 Final Exam Guidance Extended version includes full semester

Derivative Securities Fall 2012 Final Exam Guidance Extended version includes full semester Derivative Securities Fall 2012 Final Exam Guidance Extended version includes full semester Our exam is Wednesday, December 19, at the normal class place and time. You may bring two sheets of notes (8.5

More information

SAMPLE FINAL QUESTIONS. William L. Silber

SAMPLE FINAL QUESTIONS. William L. Silber SAMPLE FINAL QUESTIONS William L. Silber HOW TO PREPARE FOR THE FINAL: 1. Study in a group 2. Review the concept questions in the Before and After book 3. When you review the questions listed below, make

More information