Mergers and Acquisitions - Collar Contracts

Size: px
Start display at page:

Download "Mergers and Acquisitions - Collar Contracts"

Transcription

1 Mergers and Acquisitions - Collar Contracts An Chen University of Bonn joint with Christian Hilpert (University of Bonn) Seminar at the Institute of Financial Studies Chengdu, June 2012

2 Traditional M&A deals Traditional M&A deals: two main payment methods to the target all cash deals: fixed price deal stock-for-stock exchange: fixed ratio deal Risks involved in traditional M&A transactions: Pre-closing risk: the possibility that fluctuations of bidder and target stock prices will affect the terms of the deal and reduce the likelihood the deal closes. Post-closing risk: after the closing the possible failure of the target to perform up to expectations, thus resulting in overpayment major risk for the shareholders of the bidder An Chen Mergers and Acquisitions - Collar Contracts 2

3 Pre-closing instruments: Collars Collars were introduced to protect against extreme price fluctuations in the share prices of bidder and target: Fixed price collars and fixed ratio collars Collar-tailored M&A deals have both characteristics of traditional all-cash or stock-for-stock deals. Collars can be used by bidders to cap the payout to selling shareholders An Chen Mergers and Acquisitions - Collar Contracts 3

4 Fixed price collar (taken from Officer (2004)) First Community Banccorp Inc. - Banc One Corp., 1994, with K = 31.96$, U = 51$, L = 47$, a = , and b = Payoff Bidder stock price An Chen Mergers and Acquisitions - Collar Contracts 4

5 Fixed ratio collar (taken from Officer (2004)) BancFlorida Financial Corp. - First Union Corp., 1992, c = 0.669, U = $, L = $, K 1 = 28$, and K 2 = 30$. Payoff Bidder stock price An Chen Mergers and Acquisitions - Collar Contracts 5

6 Pre-closing instruments: walking-away provision A walking-away provision (sometimes referred to market out provision) was incorporated in a traditional M&A deal, as an alternative to or in conjunction with a collar offer. The walking-away feature allows one or both of the parties to terminate the negotiated mergers and acquisitions. Walking-away option (known as a sudden birth option): The target has the option to walk away from the deal if the bidder stock price falls below a certain level The bidder has the option to walk away from the deal if the bidder stock price exceeds a certain level An Chen Mergers and Acquisitions - Collar Contracts 6

7 Collar Offers and walking-away provisions Collar offers and walking-away provisions are usually not standardized and sometimes provided in complex forms. Examples: Verizon and Qwest Bid for MCI (2005); Walking-away provisions might be based on some index performance There might be multiple barriers in walking-away provisions. An Chen Mergers and Acquisitions - Collar Contracts 7

8 Collar offers and walking-away provisions Collars 12.98% 13.14% 16.39% 13.97% 13.10% 10.94% Walkaways 29.01% 24.82% 28.69% 27.94% 21.45% 9.38% Percentages of collars offers and walking-away provisions in M&A deals in the US (Source: An Chen Mergers and Acquisitions - Collar Contracts 8

9 Literature on collar offers Officer (2004, Journal of Finance): The main question: why are collars included in M&A transactions? The main result: the use of collars can reduce the possibility of renegotiation such that the ex ante expected costs of negotiation over the entire bid period can be reduced through collar offers. Officer (2006, Journal of Business): The author valued the implicit collar options in the M&A transactions. The author highlighted the need for more sophisticated approaches to valuation of collar options An Chen Mergers and Acquisitions - Collar Contracts 9

10 ...Literature Introduction Fuller (2003, The Financial Review): Collar offers are associated with significant positive abnormal returns for the target and significant negative abnormal return for the bidder Caselli et. al. (2006, Journal of Applied Corporate Finance): emphasize the use of collar contracts was mainly caused by the increasing stock market volatility. Little theoretical work done so far in valuing collar offers in a merger deal after the M&A announcement has been made and before the deal either goes through. An Chen Mergers and Acquisitions - Collar Contracts 10

11 What we do in our paper From the perspective of target, we develop an arbitrage-free and complete model to value fixed price and fixed ratio collars particularly value the walking-away provisions in the regular collar offers analyze the welfare implications of using collar contracts Objectives: The model is intended to be a tool to understand the prices for collar offers and to use it effectively in controlling risks involved in M&A deals. An Chen Mergers and Acquisitions - Collar Contracts 11

12 Agenda Introduction Introduction ( ) Model setup Payoff structure of target under a collar offer Adding the walking-away provision Valuation framework Conclusion An Chen Mergers and Acquisitions - Collar Contracts 12

13 Two Types of Collars Fixed price collar: Ψ FP (S 1 (T )) :=K1 {L<S1 (T )<U} Fixed ratio collar: + as 1 (T )1 {S1 (T ) L} + bs 1 (T )1 {S1 (T ) U} Ψ FR (S 1 (T )) :=cs 1 (T )1 {L<S1 (T )<U} + K 1 1 {S1 (T ) L} + K 2 1 {S1 (T ) U} [L, U]: collar width. a, b, K 1 and K 2 are usually chosen such that collars display continuous payoffs An Chen Mergers and Acquisitions - Collar Contracts 13

14 Fixed price collar First Community Banccorp Inc. - Banc One Corp., 1994, with K = 31.96$, U = 51$, L = 47$, a = , and b = Payoff Bidder stock price An Chen Mergers and Acquisitions - Collar Contracts 14

15 Fixed ratio collar BancFlorida Financial Corp. - First Union Corp., 1992, c = 0.669, U = $, L = $, K 1 = 28$, and K 2 = 30$. Payoff Bidder stock price An Chen Mergers and Acquisitions - Collar Contracts 15

16 Model Setup Introduction Black Scholes economy (under Q): Stocks dynamics : ds 1 (t) =(r q 1 )S 1 (t)dt + σ 1 S 1 (t)dw Q 1 (t), S 1(0) = S 1 (bidder s share price) ds 2 (t) =(r q 2 )S 2 (t)dt + σ 2 S 2 (t) (ρdw Q 1 (t) + ) 1 ρ 2 dw Q 2 (t) S 2 (0) = S 2 > 0 (target s share price) An Chen Mergers and Acquisitions - Collar Contracts 16

17 Pricing Formulas Time-zero arbitrage-free price of the fixed price collar: Π FP (S 1 ) =e rt K [ Φ ( ) ( )] Ū2 Φ L2 + as1 e q1t Φ ( ) L 1 bs 1 e q1t Φ ( ) Ū 1 Time-zero arbitrage-free price of the fixed ratio collar: Π FR (S 1 ) =ce q 1T S 1 [ Φ ( Ū 1 ) Φ ( L1 )] + K1 e rt Φ ( L 2 ) + K 2 e rt Φ ( Ū 2 ) An Chen Mergers and Acquisitions - Collar Contracts 17

18 Walking-away provisions Target payoff: Ψ Walk i = Ψ i (S 1 (T ), S 2 (T ))1 {τ>t } + S 2 (T )1 {τ T } Stopping times: Π Walk i τ L := inf{t : S 1 (t) L} τ U := inf{t : S 1 (t) U} τ := min{τ L, τ U } (S 1, S 2 ) available in semi-closed form in Black-Scholes model. An Chen Mergers and Acquisitions - Collar Contracts 18

19 Parameter choices The initial target s and bidder s share price is fixed at S 1 = S 2 = 100. We use r =0.05, T = 1, q 1 = q 2 = 0, σ 1 =σ 2 = 0.2, L = 80, U = 120, ρ = 0.5. Collars usually display continuous payoffs a = K L, b = K U, K 1 = c L, and K 2 = c U The price K and the exchange ratio c are determined such that the today s price of fixed price collar or fixed ratio collar equals the initial target price S 2. An Chen Mergers and Acquisitions - Collar Contracts 19

20 Effect of walking-away: fixed price collar Ρ 0.5 Ρ 0 Ρ An Chen Mergers and Acquisitions - Collar Contracts 20

21 Effects of σ 1 probability of size of payoff probability of premature size of payoff survival (τ > T ) upon survival walk-away (τ T ) upon premature walk-away (ρ > 0) σ 1 ( ) (ρ < 0) The today s price of this payoff Ψ tar can be roughly decomposed into the following sum of two products probability of survival size of payoff upon survival + probability of premature walk-away size of payoff upon premature walk-away An Chen Mergers and Acquisitions - Collar Contracts 21

22 Effect of walking-away: fixed ratio collar Ρ 0.5 Ρ 0 Ρ An Chen Mergers and Acquisitions - Collar Contracts 22

23 Power Utility Introduction Assume that the target s shareholders are assumed to own power utility: u(x) = x 1 γ 1 γ, γ > 0, γ 1 Share prices under real world measure P: Stocks dynamics : ds 1 (t) = (µ 1 q 1 )S 1 (t)dt + σ 1 S 1 (t)dw1 P (t) ( ds 2 (t) = (µ 2 q 2 )S 2 (t)dt + σ 2 S 2 (t) ρdw1 P (t) + ) 1 ρ 2 dw2 P (t) S 1 (0) = S 1 S 2 (0) = S 2 An Chen Mergers and Acquisitions - Collar Contracts 23

24 Expected utility - fixed price collar The expected utility of the target s shareholder: E P [u (Ψ FP )] [ = 1 as 1 e 1 γ + 1 [ 1 γ K 1 γ Φ [ + 1 bs 1 e 1 γ ( ] 1 γ µ 1 q 1 σ2 1 2 )T ) e 1 2 (1 γ)2 σ 2 1 T Φ ( L (1 γ)σ1 T (Ũ) )] Φ ( L ( ] 1 γ µ 1 q 1 σ2 1 2 )T ( e 1 2 (1 γ)2 σ 2 1 T Φ Ũ + (1 γ)σ ) 1 T. Semi-closed form solution if walk-away option included. An Chen Mergers and Acquisitions - Collar Contracts 24

25 Expected utility - fixed ratio collar The expected utility of the target s shareholder: E P [u (Ψ FR )] = 1 1 γ K 1 γ [ + 1 cs 1 e 1 γ [ Φ ) 1 Φ ( L + 1 ( ) 1 γ K 1 γ 2 Φ Ũ ( µ 1 q 1 σ2 1 2 )T ] 1 γ e 1 2 (1 γ)2 σ 2 1 T ) )] (Ũ (1 γ)σ1 T Φ ( L (1 γ)σ1 T Semi-closed form solution if walk-away option included. An Chen Mergers and Acquisitions - Collar Contracts 25

26 Certainty equivalents σ 1 CE NoM&A CE Cash CE Stock CE FP CE FR CE WA FP CE WA FR Certainty equivalents under different M&A deals for varying σ 1 of the bidder. We have chosen µ 2 r σ 2 = µ 1 r σ An Chen Mergers and Acquisitions - Collar Contracts 26

27 Certainty equivalents γ CE NoM&A CE Cash CE Stock CE FP CE FR CE WA FP CE WA FR Certainty equivalents under different M&A deals for varying risk aversion of the target. An Chen Mergers and Acquisitions - Collar Contracts 27

28 Conclusion Introduction Pricing of walking-away provisions (semi-closed form) Value depends heavily on underlying volatilities Collars can increase expected utility Mixed evidence for walking-away rights An Chen Mergers and Acquisitions - Collar Contracts 28

Portability, salary and asset price risk: a continuous-time expected utility comparison of DB and DC pension plans

Portability, salary and asset price risk: a continuous-time expected utility comparison of DB and DC pension plans Portability, salary and asset price risk: a continuous-time expected utility comparison of DB and DC pension plans An Chen University of Ulm joint with Filip Uzelac (University of Bonn) Seminar at SWUFE,

More information

Structural Models of Credit Risk and Some Applications

Structural Models of Credit Risk and Some Applications Structural Models of Credit Risk and Some Applications Albert Cohen Actuarial Science Program Department of Mathematics Department of Statistics and Probability albert@math.msu.edu August 29, 2018 Outline

More information

NEWCASTLE UNIVERSITY SCHOOL OF MATHEMATICS, STATISTICS & PHYSICS SEMESTER 1 SPECIMEN 2 MAS3904. Stochastic Financial Modelling. Time allowed: 2 hours

NEWCASTLE UNIVERSITY SCHOOL OF MATHEMATICS, STATISTICS & PHYSICS SEMESTER 1 SPECIMEN 2 MAS3904. Stochastic Financial Modelling. Time allowed: 2 hours NEWCASTLE UNIVERSITY SCHOOL OF MATHEMATICS, STATISTICS & PHYSICS SEMESTER 1 SPECIMEN 2 Stochastic Financial Modelling Time allowed: 2 hours Candidates should attempt all questions. Marks for each question

More information

Pricing Barrier Options under Local Volatility

Pricing Barrier Options under Local Volatility Abstract Pricing Barrier Options under Local Volatility Artur Sepp Mail: artursepp@hotmail.com, Web: www.hot.ee/seppar 16 November 2002 We study pricing under the local volatility. Our research is mainly

More information

Investment strategies and risk management for participating life insurance contracts

Investment strategies and risk management for participating life insurance contracts 1/20 Investment strategies and risk for participating life insurance contracts and Steven Haberman Cass Business School AFIR Colloquium Munich, September 2009 2/20 & Motivation Motivation New supervisory

More information

1 Parameterization of Binomial Models and Derivation of the Black-Scholes PDE.

1 Parameterization of Binomial Models and Derivation of the Black-Scholes PDE. 1 Parameterization of Binomial Models and Derivation of the Black-Scholes PDE. Previously we treated binomial models as a pure theoretical toy model for our complete economy. We turn to the issue of how

More information

How good are Portfolio Insurance Strategies?

How good are Portfolio Insurance Strategies? How good are Portfolio Insurance Strategies? S. Balder and A. Mahayni Department of Accounting and Finance, Mercator School of Management, University of Duisburg Essen September 2009, München S. Balder

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

Real Options and Game Theory in Incomplete Markets

Real Options and Game Theory in Incomplete Markets Real Options and Game Theory in Incomplete Markets M. Grasselli Mathematics and Statistics McMaster University IMPA - June 28, 2006 Strategic Decision Making Suppose we want to assign monetary values to

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

Asset Pricing Models with Underlying Time-varying Lévy Processes

Asset Pricing Models with Underlying Time-varying Lévy Processes Asset Pricing Models with Underlying Time-varying Lévy Processes Stochastics & Computational Finance 2015 Xuecan CUI Jang SCHILTZ University of Luxembourg July 9, 2015 Xuecan CUI, Jang SCHILTZ University

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

Greek parameters of nonlinear Black-Scholes equation

Greek parameters of nonlinear Black-Scholes equation International Journal of Mathematics and Soft Computing Vol.5, No.2 (2015), 69-74. ISSN Print : 2249-3328 ISSN Online: 2319-5215 Greek parameters of nonlinear Black-Scholes equation Purity J. Kiptum 1,

More information

The investment game in incomplete markets.

The investment game in incomplete markets. The investment game in incomplete markets. M. R. Grasselli Mathematics and Statistics McMaster University RIO 27 Buzios, October 24, 27 Successes and imitations of Real Options Real options accurately

More information

Black-Scholes Option Pricing

Black-Scholes Option Pricing Black-Scholes Option Pricing The pricing kernel furnishes an alternate derivation of the Black-Scholes formula for the price of a call option. Arbitrage is again the foundation for the theory. 1 Risk-Free

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

Chapter 15: Jump Processes and Incomplete Markets. 1 Jumps as One Explanation of Incomplete Markets

Chapter 15: Jump Processes and Incomplete Markets. 1 Jumps as One Explanation of Incomplete Markets Chapter 5: Jump Processes and Incomplete Markets Jumps as One Explanation of Incomplete Markets It is easy to argue that Brownian motion paths cannot model actual stock price movements properly in reality,

More information

The Black-Scholes Equation

The Black-Scholes Equation The Black-Scholes Equation MATH 472 Financial Mathematics J. Robert Buchanan 2018 Objectives In this lesson we will: derive the Black-Scholes partial differential equation using Itô s Lemma and no-arbitrage

More information

Lecture 3: Review of mathematical finance and derivative pricing models

Lecture 3: Review of mathematical finance and derivative pricing models Lecture 3: Review of mathematical finance and derivative pricing models Xiaoguang Wang STAT 598W January 21th, 2014 (STAT 598W) Lecture 3 1 / 51 Outline 1 Some model independent definitions and principals

More information

Credit Risk : Firm Value Model

Credit Risk : Firm Value Model Credit Risk : Firm Value Model Prof. Dr. Svetlozar Rachev Institute for Statistics and Mathematical Economics University of Karlsruhe and Karlsruhe Institute of Technology (KIT) Prof. Dr. Svetlozar Rachev

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

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

All Investors are Risk-averse Expected Utility Maximizers. Carole Bernard (UW), Jit Seng Chen (GGY) and Steven Vanduffel (Vrije Universiteit Brussel)

All Investors are Risk-averse Expected Utility Maximizers. Carole Bernard (UW), Jit Seng Chen (GGY) and Steven Vanduffel (Vrije Universiteit Brussel) All Investors are Risk-averse Expected Utility Maximizers Carole Bernard (UW), Jit Seng Chen (GGY) and Steven Vanduffel (Vrije Universiteit Brussel) First Name: Waterloo, April 2013. Last Name: UW ID #:

More information

M5MF6. Advanced Methods in Derivatives Pricing

M5MF6. Advanced Methods in Derivatives Pricing Course: Setter: M5MF6 Dr Antoine Jacquier MSc EXAMINATIONS IN MATHEMATICS AND FINANCE DEPARTMENT OF MATHEMATICS April 2016 M5MF6 Advanced Methods in Derivatives Pricing Setter s signature...........................................

More information

1 Implied Volatility from Local Volatility

1 Implied Volatility from Local Volatility Abstract We try to understand the Berestycki, Busca, and Florent () (BBF) result in the context of the work presented in Lectures and. Implied Volatility from Local Volatility. Current Plan as of March

More information

Option Pricing. Simple Arbitrage Relations. Payoffs to Call and Put Options. Black-Scholes Model. Put-Call Parity. Implied Volatility

Option Pricing. Simple Arbitrage Relations. Payoffs to Call and Put Options. Black-Scholes Model. Put-Call Parity. Implied Volatility Simple Arbitrage Relations Payoffs to Call and Put Options Black-Scholes Model Put-Call Parity Implied Volatility Option Pricing Options: Definitions A call option gives the buyer the right, but not the

More information

Optimal Investment with Deferred Capital Gains Taxes

Optimal Investment with Deferred Capital Gains Taxes Optimal Investment with Deferred Capital Gains Taxes A Simple Martingale Method Approach Frank Thomas Seifried University of Kaiserslautern March 20, 2009 F. Seifried (Kaiserslautern) Deferred Capital

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

Incorporating Managerial Cash-Flow Estimates and Risk Aversion to Value Real Options Projects. The Fields Institute for Mathematical Sciences

Incorporating Managerial Cash-Flow Estimates and Risk Aversion to Value Real Options Projects. The Fields Institute for Mathematical Sciences Incorporating Managerial Cash-Flow Estimates and Risk Aversion to Value Real Options Projects The Fields Institute for Mathematical Sciences Sebastian Jaimungal sebastian.jaimungal@utoronto.ca Yuri Lawryshyn

More information

Completeness and Hedging. Tomas Björk

Completeness and Hedging. Tomas Björk IV Completeness and Hedging Tomas Björk 1 Problems around Standard Black-Scholes We assumed that the derivative was traded. How do we price OTC products? Why is the option price independent of the expected

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

Option Pricing Model with Stepped Payoff

Option Pricing Model with Stepped Payoff Applied Mathematical Sciences, Vol., 08, no., - 8 HIARI Ltd, www.m-hikari.com https://doi.org/0.988/ams.08.7346 Option Pricing Model with Stepped Payoff Hernán Garzón G. Department of Mathematics Universidad

More information

All Investors are Risk-averse Expected Utility Maximizers

All Investors are Risk-averse Expected Utility Maximizers All Investors are Risk-averse Expected Utility Maximizers Carole Bernard (UW), Jit Seng Chen (GGY) and Steven Vanduffel (Vrije Universiteit Brussel) AFFI, Lyon, May 2013. Carole Bernard All Investors are

More information

Option Pricing Models for European Options

Option Pricing Models for European Options Chapter 2 Option Pricing Models for European Options 2.1 Continuous-time Model: Black-Scholes Model 2.1.1 Black-Scholes Assumptions We list the assumptions that we make for most of this notes. 1. The underlying

More information

1 Introduction. 2 Old Methodology BOARD OF GOVERNORS OF THE FEDERAL RESERVE SYSTEM DIVISION OF RESEARCH AND STATISTICS

1 Introduction. 2 Old Methodology BOARD OF GOVERNORS OF THE FEDERAL RESERVE SYSTEM DIVISION OF RESEARCH AND STATISTICS BOARD OF GOVERNORS OF THE FEDERAL RESERVE SYSTEM DIVISION OF RESEARCH AND STATISTICS Date: October 6, 3 To: From: Distribution Hao Zhou and Matthew Chesnes Subject: VIX Index Becomes Model Free and Based

More information

Economathematics. Problem Sheet 1. Zbigniew Palmowski. Ws 2 dw s = 1 t

Economathematics. Problem Sheet 1. Zbigniew Palmowski. Ws 2 dw s = 1 t Economathematics Problem Sheet 1 Zbigniew Palmowski 1. Calculate Ee X where X is a gaussian random variable with mean µ and volatility σ >.. Verify that where W is a Wiener process. Ws dw s = 1 3 W t 3

More information

VII. Incomplete Markets. Tomas Björk

VII. Incomplete Markets. Tomas Björk VII Incomplete Markets Tomas Björk 1 Typical Factor Model Setup Given: An underlying factor process X, which is not the price process of a traded asset, with P -dynamics dx t = µ (t, X t ) dt + σ (t, X

More information

Lecture 4. Finite difference and finite element methods

Lecture 4. Finite difference and finite element methods Finite difference and finite element methods Lecture 4 Outline Black-Scholes equation From expectation to PDE Goal: compute the value of European option with payoff g which is the conditional expectation

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

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 217 Instructor: Dr. Sateesh Mane c Sateesh R. Mane 217 13 Lecture 13 November 15, 217 Derivation of the Black-Scholes-Merton

More information

Lecture 15: Exotic Options: Barriers

Lecture 15: Exotic Options: Barriers Lecture 15: Exotic Options: Barriers Dr. Hanqing Jin Mathematical Institute University of Oxford Lecture 15: Exotic Options: Barriers p. 1/10 Barrier features For any options with payoff ξ at exercise

More information

Stochastic Volatility (Working Draft I)

Stochastic Volatility (Working Draft I) Stochastic Volatility (Working Draft I) Paul J. Atzberger General comments or corrections should be sent to: paulatz@cims.nyu.edu 1 Introduction When using the Black-Scholes-Merton model to price derivative

More information

Optimal Acquisition of a Partially Hedgeable House

Optimal Acquisition of a Partially Hedgeable House Optimal Acquisition of a Partially Hedgeable House Coşkun Çetin 1, Fernando Zapatero 2 1 Department of Mathematics and Statistics CSU Sacramento 2 Marshall School of Business USC November 14, 2009 WCMF,

More information

The investment game in incomplete markets

The investment game in incomplete markets The investment game in incomplete markets M. R. Grasselli Mathematics and Statistics McMaster University Pisa, May 23, 2008 Strategic decision making We are interested in assigning monetary values to strategic

More information

An overview of some financial models using BSDE with enlarged filtrations

An overview of some financial models using BSDE with enlarged filtrations An overview of some financial models using BSDE with enlarged filtrations Anne EYRAUD-LOISEL Workshop : Enlargement of Filtrations and Applications to Finance and Insurance May 31st - June 4th, 2010, Jena

More information

Uncertainty, Liquidity and Financial Cycles

Uncertainty, Liquidity and Financial Cycles Uncertainty, Liquidity and Financial Cycles Ge Zhou Zhejiang University Jan 2019, ASSA Ge Zhou (Zhejiang University) Uncertainty, Liquidity and Financial Cycles Jan 2019 1 / 26 2500.00 Recession SP 500

More information

Locally risk-minimizing vs. -hedging in stochastic vola

Locally risk-minimizing vs. -hedging in stochastic vola Locally risk-minimizing vs. -hedging in stochastic volatility models University of St. Andrews School of Economics and Finance August 29, 2007 joint work with R. Poulsen ( Kopenhagen )and K.R.Schenk-Hoppe

More information

Barrier options. In options only come into being if S t reaches B for some 0 t T, at which point they become an ordinary option.

Barrier options. In options only come into being if S t reaches B for some 0 t T, at which point they become an ordinary option. Barrier options A typical barrier option contract changes if the asset hits a specified level, the barrier. Barrier options are therefore path-dependent. Out options expire worthless if S t reaches the

More information

Crashcourse Interest Rate Models

Crashcourse Interest Rate Models Crashcourse Interest Rate Models Stefan Gerhold August 30, 2006 Interest Rate Models Model the evolution of the yield curve Can be used for forecasting the future yield curve or for pricing interest rate

More information

Combining Real Options and game theory in incomplete markets.

Combining Real Options and game theory in incomplete markets. Combining Real Options and game theory in incomplete markets. M. R. Grasselli Mathematics and Statistics McMaster University Further Developments in Quantitative Finance Edinburgh, July 11, 2007 Successes

More information

1.1 Basic Financial Derivatives: Forward Contracts and Options

1.1 Basic Financial Derivatives: Forward Contracts and Options Chapter 1 Preliminaries 1.1 Basic Financial Derivatives: Forward Contracts and Options A derivative is a financial instrument whose value depends on the values of other, more basic underlying variables

More information

The Black-Scholes Equation using Heat Equation

The Black-Scholes Equation using Heat Equation The Black-Scholes Equation using Heat Equation Peter Cassar May 0, 05 Assumptions of the Black-Scholes Model We have a risk free asset given by the price process, dbt = rbt The asset price follows a geometric

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

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

Heterogeneous Firm, Financial Market Integration and International Risk Sharing

Heterogeneous Firm, Financial Market Integration and International Risk Sharing Heterogeneous Firm, Financial Market Integration and International Risk Sharing Ming-Jen Chang, Shikuan Chen and Yen-Chen Wu National DongHwa University Thursday 22 nd November 2018 Department of Economics,

More information

An Asymptotic Expansion Formula for Up-and-Out Barrier Option Price under Stochastic Volatility Model

An Asymptotic Expansion Formula for Up-and-Out Barrier Option Price under Stochastic Volatility Model CIRJE-F-873 An Asymptotic Expansion Formula for Up-and-Out Option Price under Stochastic Volatility Model Takashi Kato Osaka University Akihiko Takahashi University of Tokyo Toshihiro Yamada Graduate School

More information

Risk Neutral Measures

Risk Neutral Measures CHPTER 4 Risk Neutral Measures Our aim in this section is to show how risk neutral measures can be used to price derivative securities. The key advantage is that under a risk neutral measure the discounted

More information

Hedging of Credit Derivatives in Models with Totally Unexpected Default

Hedging of Credit Derivatives in Models with Totally Unexpected Default Hedging of Credit Derivatives in Models with Totally Unexpected Default T. Bielecki, M. Jeanblanc and M. Rutkowski Carnegie Mellon University Pittsburgh, 6 February 2006 1 Based on N. Vaillant (2001) A

More information

IEOR E4703: Monte-Carlo Simulation

IEOR E4703: Monte-Carlo Simulation IEOR E4703: Monte-Carlo Simulation Simulating Stochastic Differential Equations Martin Haugh Department of Industrial Engineering and Operations Research Columbia University Email: martin.b.haugh@gmail.com

More information

Black-Scholes-Merton Model

Black-Scholes-Merton Model Black-Scholes-Merton Model Weerachart Kilenthong University of the Thai Chamber of Commerce c Kilenthong 2017 Weerachart Kilenthong University of the Thai Chamber Black-Scholes-Merton of Commerce Model

More information

MSC FINANCIAL ENGINEERING PRICING I, AUTUMN LECTURE 6: EXTENSIONS OF BLACK AND SCHOLES RAYMOND BRUMMELHUIS DEPARTMENT EMS BIRKBECK

MSC FINANCIAL ENGINEERING PRICING I, AUTUMN LECTURE 6: EXTENSIONS OF BLACK AND SCHOLES RAYMOND BRUMMELHUIS DEPARTMENT EMS BIRKBECK MSC FINANCIAL ENGINEERING PRICING I, AUTUMN 2010-2011 LECTURE 6: EXTENSIONS OF BLACK AND SCHOLES RAYMOND BRUMMELHUIS DEPARTMENT EMS BIRKBECK In this section we look at some easy extensions of the Black

More information

Robust Pricing and Hedging of Options on Variance

Robust Pricing and Hedging of Options on Variance Robust Pricing and Hedging of Options on Variance Alexander Cox Jiajie Wang University of Bath Bachelier 21, Toronto Financial Setting Option priced on an underlying asset S t Dynamics of S t unspecified,

More information

FINANCIAL PRICING MODELS

FINANCIAL PRICING MODELS Page 1-22 like equions FINANCIAL PRICING MODELS 20 de Setembro de 2013 PhD Page 1- Student 22 Contents Page 2-22 1 2 3 4 5 PhD Page 2- Student 22 Page 3-22 In 1973, Fischer Black and Myron Scholes presented

More information

Online Appendix to Financing Asset Sales and Business Cycles

Online Appendix to Financing Asset Sales and Business Cycles Online Appendix to Financing Asset Sales usiness Cycles Marc Arnold Dirk Hackbarth Tatjana Xenia Puhan August 31, 2015 University of St. allen, Rosenbergstrasse 52, 9000 St. allen, Switzerl. Telephone:

More information

Dynamic Portfolio Choice II

Dynamic Portfolio Choice II Dynamic Portfolio Choice II Dynamic Programming Leonid Kogan MIT, Sloan 15.450, Fall 2010 c Leonid Kogan ( MIT, Sloan ) Dynamic Portfolio Choice II 15.450, Fall 2010 1 / 35 Outline 1 Introduction to Dynamic

More information

Search, Moral Hazard, and Equilibrium Price Dispersion

Search, Moral Hazard, and Equilibrium Price Dispersion Search, Moral Hazard, and Equilibrium Price Dispersion S. Nuray Akin 1 Brennan C. Platt 2 1 Department of Economics University of Miami 2 Department of Economics Brigham Young University North American

More information

M3F22/M4F22/M5F22 EXAMINATION SOLUTIONS

M3F22/M4F22/M5F22 EXAMINATION SOLUTIONS M3F22/M4F22/M5F22 EXAMINATION SOLUTIONS 2016-17 Q1: Limited liability; bankruptcy; moral hazard. Limited liability. All business transactions involve an exchange of goods or services between a willing

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

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

Moral Hazard: Dynamic Models. Preliminary Lecture Notes

Moral Hazard: Dynamic Models. Preliminary Lecture Notes Moral Hazard: Dynamic Models Preliminary Lecture Notes Hongbin Cai and Xi Weng Department of Applied Economics, Guanghua School of Management Peking University November 2014 Contents 1 Static Moral Hazard

More information

Heston Stochastic Local Volatility Model

Heston Stochastic Local Volatility Model Heston Stochastic Local Volatility Model Klaus Spanderen 1 R/Finance 2016 University of Illinois, Chicago May 20-21, 2016 1 Joint work with Johannes Göttker-Schnetmann Klaus Spanderen Heston Stochastic

More information

AN ANALYTICALLY TRACTABLE UNCERTAIN VOLATILITY MODEL

AN ANALYTICALLY TRACTABLE UNCERTAIN VOLATILITY MODEL AN ANALYTICALLY TRACTABLE UNCERTAIN VOLATILITY MODEL FABIO MERCURIO BANCA IMI, MILAN http://www.fabiomercurio.it 1 Stylized facts Traders use the Black-Scholes formula to price plain-vanilla options. An

More information

Lévy models in finance

Lévy models in finance Lévy models in finance Ernesto Mordecki Universidad de la República, Montevideo, Uruguay PASI - Guanajuato - June 2010 Summary General aim: describe jummp modelling in finace through some relevant issues.

More information

An Asymptotic Expansion Formula for Up-and-Out Barrier Option Price under Stochastic Volatility Model

An Asymptotic Expansion Formula for Up-and-Out Barrier Option Price under Stochastic Volatility Model An Asymptotic Expansion Formula for Up-and-Out Option Price under Stochastic Volatility Model Takashi Kato Akihiko Takahashi Toshihiro Yamada arxiv:32.336v [q-fin.cp] 4 Feb 23 December 3, 22 Abstract This

More information

Option Approach to Risk-shifting Incentive Problem with Mutually Correlated Projects

Option Approach to Risk-shifting Incentive Problem with Mutually Correlated Projects Option Approach to Risk-shifting Incentive Problem with Mutually Correlated Projects Hiroshi Inoue 1, Zhanwei Yang 1, Masatoshi Miyake 1 School of Management, T okyo University of Science, Kuki-shi Saitama

More information

Banks and Liquidity Crises in Emerging Market Economies

Banks and Liquidity Crises in Emerging Market Economies Banks and Liquidity Crises in Emerging Market Economies Tarishi Matsuoka Tokyo Metropolitan University May, 2015 Tarishi Matsuoka (TMU) Banking Crises in Emerging Market Economies May, 2015 1 / 47 Introduction

More information

In chapter 5, we approximated the Black-Scholes model

In chapter 5, we approximated the Black-Scholes model Chapter 7 The Black-Scholes Equation In chapter 5, we approximated the Black-Scholes model ds t /S t = µ dt + σ dx t 7.1) with a suitable Binomial model and were able to derive a pricing formula for option

More information

Continuous Time Finance. Tomas Björk

Continuous Time Finance. Tomas Björk Continuous Time Finance Tomas Björk 1 II Stochastic Calculus Tomas Björk 2 Typical Setup Take as given the market price process, S(t), of some underlying asset. S(t) = price, at t, per unit of underlying

More information

The Life Cycle Model with Recursive Utility: Defined benefit vs defined contribution.

The Life Cycle Model with Recursive Utility: Defined benefit vs defined contribution. The Life Cycle Model with Recursive Utility: Defined benefit vs defined contribution. Knut K. Aase Norwegian School of Economics 5045 Bergen, Norway IACA/PBSS Colloquium Cancun 2017 June 6-7, 2017 1. Papers

More information

Convenience Yield-Based Pricing of Commodity Futures

Convenience Yield-Based Pricing of Commodity Futures Convenience Yield-Based Pricing of Commodity Futures Takashi Kanamura, J-POWER Energy Finance/ INREC 2010 at University Duisburg-Essen October 8th, 2010 1 Agenda 1. The objectives and results 2. The convenience

More information

European call option with inflation-linked strike

European call option with inflation-linked strike Mathematical Statistics Stockholm University European call option with inflation-linked strike Ola Hammarlid Research Report 2010:2 ISSN 1650-0377 Postal address: Mathematical Statistics Dept. of Mathematics

More information

Exploring Volatility Derivatives: New Advances in Modelling. Bruno Dupire Bloomberg L.P. NY

Exploring Volatility Derivatives: New Advances in Modelling. Bruno Dupire Bloomberg L.P. NY Exploring Volatility Derivatives: New Advances in Modelling Bruno Dupire Bloomberg L.P. NY bdupire@bloomberg.net Global Derivatives 2005, Paris May 25, 2005 1. Volatility Products Historical Volatility

More information

Valuing Early Stage Investments with Market Related Timing Risk

Valuing Early Stage Investments with Market Related Timing Risk Valuing Early Stage Investments with Market Related Timing Risk Matt Davison and Yuri Lawryshyn February 12, 216 Abstract In this work, we build on a previous real options approach that utilizes managerial

More information

The Welfare Cost of Asymmetric Information: Evidence from the U.K. Annuity Market

The Welfare Cost of Asymmetric Information: Evidence from the U.K. Annuity Market The Welfare Cost of Asymmetric Information: Evidence from the U.K. Annuity Market Liran Einav 1 Amy Finkelstein 2 Paul Schrimpf 3 1 Stanford and NBER 2 MIT and NBER 3 MIT Cowles 75th Anniversary Conference

More information

Multiscale Stochastic Volatility Models

Multiscale Stochastic Volatility Models Multiscale Stochastic Volatility Models Jean-Pierre Fouque University of California Santa Barbara 6th World Congress of the Bachelier Finance Society Toronto, June 25, 2010 Multiscale Stochastic Volatility

More information

Sparse Wavelet Methods for Option Pricing under Lévy Stochastic Volatility models

Sparse Wavelet Methods for Option Pricing under Lévy Stochastic Volatility models Sparse Wavelet Methods for Option Pricing under Lévy Stochastic Volatility models Norbert Hilber Seminar of Applied Mathematics ETH Zürich Workshop on Financial Modeling with Jump Processes p. 1/18 Outline

More information

Sample Path Large Deviations and Optimal Importance Sampling for Stochastic Volatility Models

Sample Path Large Deviations and Optimal Importance Sampling for Stochastic Volatility Models Sample Path Large Deviations and Optimal Importance Sampling for Stochastic Volatility Models Scott Robertson Carnegie Mellon University scottrob@andrew.cmu.edu http://www.math.cmu.edu/users/scottrob June

More information

Extensions to the Black Scholes Model

Extensions to the Black Scholes Model Lecture 16 Extensions to the Black Scholes Model 16.1 Dividends Dividend is a sum of money paid regularly (typically annually) by a company to its shareholders out of its profits (or reserves). In this

More information

7 th General AMaMeF and Swissquote Conference 2015

7 th General AMaMeF and Swissquote Conference 2015 Linear Credit Damien Ackerer Damir Filipović Swiss Finance Institute École Polytechnique Fédérale de Lausanne 7 th General AMaMeF and Swissquote Conference 2015 Overview 1 2 3 4 5 Credit Risk(s) Default

More information

Near-expiration behavior of implied volatility for exponential Lévy models

Near-expiration behavior of implied volatility for exponential Lévy models Near-expiration behavior of implied volatility for exponential Lévy models José E. Figueroa-López 1 1 Department of Statistics Purdue University Financial Mathematics Seminar The Stevanovich Center for

More information

Calibration Lecture 4: LSV and Model Uncertainty

Calibration Lecture 4: LSV and Model Uncertainty Calibration Lecture 4: LSV and Model Uncertainty March 2017 Recap: Heston model Recall the Heston stochastic volatility model ds t = rs t dt + Y t S t dw 1 t, dy t = κ(θ Y t ) dt + ξ Y t dw 2 t, where

More information

Credit Modeling and Credit Derivatives

Credit Modeling and Credit Derivatives IEOR E4706: Foundations of Financial Engineering c 2016 by Martin Haugh Credit Modeling and Credit Derivatives In these lecture notes we introduce the main approaches to credit modeling and we will largely

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

Managing Systematic Mortality Risk in Life Annuities: An Application of Longevity Derivatives

Managing Systematic Mortality Risk in Life Annuities: An Application of Longevity Derivatives Managing Systematic Mortality Risk in Life Annuities: An Application of Longevity Derivatives Simon Man Chung Fung, Katja Ignatieva and Michael Sherris School of Risk & Actuarial Studies University of

More information

The Use of Importance Sampling to Speed Up Stochastic Volatility Simulations

The Use of Importance Sampling to Speed Up Stochastic Volatility Simulations The Use of Importance Sampling to Speed Up Stochastic Volatility Simulations Stan Stilger June 6, 1 Fouque and Tullie use importance sampling for variance reduction in stochastic volatility simulations.

More information

Earnings smoothing and its effect on banks other actions

Earnings smoothing and its effect on banks other actions Earnings smoothing and its effect on banks other actions Shan Huang, with Jussi Keppo and Min Dai National University of Singapore October 17, 2015 Shan Huang, with Jussi Keppo and Min Dai Earnings (National

More information

Sudden stops, time inconsistency, and the duration of sovereign debt

Sudden stops, time inconsistency, and the duration of sovereign debt WP/13/174 Sudden stops, time inconsistency, and the duration of sovereign debt Juan Carlos Hatchondo and Leonardo Martinez 2013 International Monetary Fund WP/13/ IMF Working Paper IMF Institute for Capacity

More information

Power Options in Executive Compensation

Power Options in Executive Compensation Power Options in Executive Compensation Carole Bernard, Phelim Boyle and Jit Seng Chen Department of Finance, Grenoble Ecole de Management. School of Business and Economics, Wilfrid Laurier University.

More information

Applications of Lévy processes

Applications of Lévy processes Applications of Lévy processes Graduate lecture 29 January 2004 Matthias Winkel Departmental lecturer (Institute of Actuaries and Aon lecturer in Statistics) 6. Poisson point processes in fluctuation theory

More information

Deterministic Income under a Stochastic Interest Rate

Deterministic Income under a Stochastic Interest Rate Deterministic Income under a Stochastic Interest Rate Julia Eisenberg, TU Vienna Scientic Day, 1 Agenda 1 Classical Problem: Maximizing Discounted Dividends in a Brownian Risk Model 2 Maximizing Discounted

More information