One-Period Valuation Theory

Size: px
Start display at page:

Download "One-Period Valuation Theory"

Transcription

1 One-Period Valuation Theory Part 1: Basic Framework Chris Telmer March, 2013 Develop a simple framework for understanding what the pricing kernel is and how it s related to the economics of risk, return and decision-making under uncertainty. where q asset price q = E(md) m pricing kernel or stochastic discount factor d asset payoff 1 / 22 2 / 22 Basic Idea: State Prices Probability Space and Financial Markets Valuation of riskless cash flows: {c 1, c 2, c 3 } q 1 = 1 1+i 1 c 1 = d 1 c 1 Valuation of risky cash flows: { c 1, c 2, c 3 } S states of nature, s {1,2,...,S} Objective probabilities: P s = Prob(state =s) Securities market: q h 1 = ψ h 1c h 1 q l 1 = ψ l 1c l 1 q R N D (R N R S ) q 1 = q h 1 +q l 1 q asset prices D asset payoffs 3 / 22 4 / 22

2 and Payoffs Portfolio: θ R N : Unlimited short-sales Portfolio payoff: x θ = D θ R S Portfolio price: q θ = q θ R 1... (synonymously, q θ = q θ) Set of marketed securities: Complete markets, S = 2,N = 2: 2 1 q = 1 3 θ = 9 12 D θ = and q θ = 34.2 Φ = {x R S : x = D θ, θ R N } = span(d) If N = S then Φ = R S, complete markets If N < S then Φ is a linear subspace of R S, incomplete markets 5 / 22 6 / 22 (continued) Incomplete markets, S = 2,N = 1: [ 2 1 ] q = [1.4] Suppose that there exist numbers, ψ s > 0 such that q j = S ψ s d js s=1 We call the ψ s numbers state prices. That is, ψ s = cost of 1 dollar in state s ψ s d js = cost of d js dollars in state s. Value additivity. s ψ sd js = cost of d j1 dollars in state 1, and d j2 dollars in state 2, and... d js dollars in state S. Assets are just things that give you state-dependent payoffs. State prices just allow us to express an asset s price as the sum of the value of each of its state-dependent payoffs. 7 / 22 8 / 22

3 State Prices How Do We Find the State Prices? : ψ R S ++ s.t. q j = q = S D js ψ s for all j s= It costs 5.25 to get 4 if state 1 occurs and 7 if state 2 occurs. The implicit state prices the ψ vector that satisfies the above equations are 0.49 ψ = 0.47 We solve systems of linear equations. Continuing with the previous example: q = The equations q j = S s=1 D jsψ s, j = 1,2, are 5.25 = 4ψ 1 +7ψ = 2ψ 1 +3ψ 2 It costs 0.49 to get 1 if state 1 occurs. It costs = 1.96 to get 4 if state 1 occurs. The solution is ψ 1 = 0.49, ψ 2 = It costs = 5.25 to get 4 if state 1 occurs and 6 if state 2 occurs. 9 / / 22 Using Matrix Algebra If markets are complete: q = Dψ ψ = D 1 q A θ such that, either (a) q θ < 0 and D θ 0 or (b) q θ 0 and D θ > 0 Theorem: given (D, q), then ψ R S ++ s.t. q = Dψ No (1) Otherwise, No unique solution Strictly positive state prices, ψ, exist if and only if there do not exist arbitrage opportunities. See Practice Problems Note: state prices are not unique if markets are not complete. Critical issue in practice. 11 / / 22

4 Risk-free asset pays the same in all states. e.g., Without loss of generality let the payoff be 1: Price, denoted b, is sum of the state prices: Risk-free interest rate: b = s ψ s = ι ψ 1+i f 1 b = 1 ι ψ Financial markets Implicit state prices: ψ = D 1 (2/3 100/303) q = ( 2/ /303) Pure contingent claims: [ (D ) 1 = Risk-free interest rate: q = /30 1/30 1/303 4/303 [ = b = ψ ι = = i f 1 1 = 0.01 b ] ] 13 / / 22 (continued) (continued) Valuation: 10 Call Price(K = 30) = ψ = Put Price(K = 30) = ψ = Expected stuff: Expected Payoffs = DP = = / Expected Returns = =, 101/ ψ = Expected Returns = What s the risk premium on the stock? Why? How about a stock that pays: / = 101/ d = [10 40] 15 / / 22

5 Valuation Algorithm 1. Observe market data: (D,q) 2. Recover state prices: ψ = D 1 q 3. Value a new claim, d new : q new = ψ d new On-line sports betting Assignment 1 Potential pitfalls of arbitrage-free pricing Practice problem Expected returns often lurking Important caveats: Complete vs. incomplete markets Risk management Corporate financial leverage Spreadsheet 17 / / 22 -Free Pricing Arb-Free Pricing Risk Arb-Free Pricing Risk Recovery and valuation. No-arbitrage implies that state prices are inherent in prices/payoffs of traded assets. Valuation theory is the theory of recovering the state prices and then adding-up. Incomplete markets means that recovery is a non-unique, tricky business. It can lead to flawed decision making if not used appropriately. Remember: the hard math is usually a sophisticated version of ψ = D 1 q (from the market) followed by q = ψ d (from your client). Risk-neutral valuation is just a alternative way to write this. It often leads to confusion between risk-neutral valuation and risk neutrality. Don t mix them up. 19 / / 22

6 State Prices and Risk Financial Innovation Arb-Free Pricing Risk Interpretation and risk. A high state price means one of two things. Either a high probability or a high valuation. We call the latter a high marginal utility. The pricing kernel scales-out the probability, leaving us with the marginal utility. What is risk? A low payoff in a high marginal utility state. Key concept: state-contingent value assessment Arb-Free Pricing Risk What is Financial Innovation Article: John Kay Creating new, unspanned payoffs? s: TIPS, CDS. Or creating linear combinations of existing payoffs? s: UST Strips, mutual funds. Which is a better business to be in? Which benefits society most? 21 / / 22

One-Period Valuation Theory

One-Period Valuation Theory One-Period Valuation Theory Part 2: Chris Telmer March, 2013 1 / 44 1. Pricing kernel and financial risk 2. Linking state prices to portfolio choice Euler equation 3. Application: Corporate financial leverage

More information

( 0) ,...,S N ,S 2 ( 0)... S N S 2. N and a portfolio is created that way, the value of the portfolio at time 0 is: (0) N S N ( 1, ) +...

( 0) ,...,S N ,S 2 ( 0)... S N S 2. N and a portfolio is created that way, the value of the portfolio at time 0 is: (0) N S N ( 1, ) +... No-Arbitrage Pricing Theory Single-Period odel There are N securities denoted ( S,S,...,S N ), they can be stocks, bonds, or any securities, we assume they are all traded, and have prices available. Ω

More information

Carnegie Mellon University Graduate School of Industrial Administration

Carnegie Mellon University Graduate School of Industrial Administration Carnegie Mellon University Graduate School of Industrial Administration Chris Telmer Winter 2005 Final Examination Seminar in Finance 1 (47 720) Due: Thursday 3/3 at 5pm if you don t go to the skating

More information

Finance: Lecture 4 - No Arbitrage Pricing Chapters of DD Chapter 1 of Ross (2005)

Finance: Lecture 4 - No Arbitrage Pricing Chapters of DD Chapter 1 of Ross (2005) Finance: Lecture 4 - No Arbitrage Pricing Chapters 10-12 of DD Chapter 1 of Ross (2005) Prof. Alex Stomper MIT Sloan, IHS & VGSF March 2010 Alex Stomper (MIT, IHS & VGSF) Finance March 2010 1 / 15 Fundamental

More information

Modeling the Real Term Structure

Modeling the Real Term Structure Modeling the Real Term Structure (Inflation Risk) Chris Telmer May 2013 1 / 23 Old school Old school Prices Goods? Real Return Real Interest Rate TIPS Real yields : Model The Fisher equation defines the

More information

Finance: A Quantitative Introduction Chapter 7 - part 2 Option Pricing Foundations

Finance: A Quantitative Introduction Chapter 7 - part 2 Option Pricing Foundations Finance: A Quantitative Introduction Chapter 7 - part 2 Option Pricing Foundations Nico van der Wijst 1 Finance: A Quantitative Introduction c Cambridge University Press 1 The setting 2 3 4 2 Finance:

More information

4: SINGLE-PERIOD MARKET MODELS

4: SINGLE-PERIOD MARKET MODELS 4: SINGLE-PERIOD MARKET MODELS Marek Rutkowski School of Mathematics and Statistics University of Sydney Semester 2, 2016 M. Rutkowski (USydney) Slides 4: Single-Period Market Models 1 / 87 General Single-Period

More information

Pricing Kernel. v,x = p,y = p,ax, so p is a stochastic discount factor. One refers to p as the pricing kernel.

Pricing Kernel. v,x = p,y = p,ax, so p is a stochastic discount factor. One refers to p as the pricing kernel. Payoff Space The set of possible payoffs is the range R(A). This payoff space is a subspace of the state space and is a Euclidean space in its own right. 1 Pricing Kernel By the law of one price, two portfolios

More information

Chapter 10: Mixed strategies Nash equilibria, reaction curves and the equality of payoffs theorem

Chapter 10: Mixed strategies Nash equilibria, reaction curves and the equality of payoffs theorem Chapter 10: Mixed strategies Nash equilibria reaction curves and the equality of payoffs theorem Nash equilibrium: The concept of Nash equilibrium can be extended in a natural manner to the mixed strategies

More information

MATH 5510 Mathematical Models of Financial Derivatives. Topic 1 Risk neutral pricing principles under single-period securities models

MATH 5510 Mathematical Models of Financial Derivatives. Topic 1 Risk neutral pricing principles under single-period securities models MATH 5510 Mathematical Models of Financial Derivatives Topic 1 Risk neutral pricing principles under single-period securities models 1.1 Law of one price and Arrow securities 1.2 No-arbitrage theory and

More information

No-arbitrage Pricing Approach and Fundamental Theorem of Asset Pricing

No-arbitrage Pricing Approach and Fundamental Theorem of Asset Pricing No-arbitrage Pricing Approach and Fundamental Theorem of Asset Pricing presented by Yue Kuen KWOK Department of Mathematics Hong Kong University of Science and Technology 1 Parable of the bookmaker Taking

More information

Forward Contracts. Bjørn Eraker. January 12, Wisconsin School of Business

Forward Contracts. Bjørn Eraker. January 12, Wisconsin School of Business Wisconsin School of Business January 12, 2015 Basic definition A forward contract on some asset is an agreement today to purchase the asset at an agreed upon price (the forward price) today, for delivery

More information

Fundamental Theorems of Asset Pricing. 3.1 Arbitrage and risk neutral probability measures

Fundamental Theorems of Asset Pricing. 3.1 Arbitrage and risk neutral probability measures Lecture 3 Fundamental Theorems of Asset Pricing 3.1 Arbitrage and risk neutral probability measures Several important concepts were illustrated in the example in Lecture 2: arbitrage; risk neutral probability

More information

Mathematics in Finance

Mathematics in Finance Mathematics in Finance Robert Almgren University of Chicago Program on Financial Mathematics MAA Short Course San Antonio, Texas January 11-12, 1999 1 Robert Almgren 1/99 Mathematics in Finance 2 1. Pricing

More information

3. The Discount Factor

3. The Discount Factor 3. he Discount Factor Objectives Eplanation of - Eistence of Discount Factors: Necessary and Sufficient Conditions - Positive Discount Factors: Necessary and Sufficient Conditions Contents 3. he Discount

More information

Martingale Pricing Theory in Discrete-Time and Discrete-Space Models

Martingale Pricing Theory in Discrete-Time and Discrete-Space Models IEOR E4707: Foundations of Financial Engineering c 206 by Martin Haugh Martingale Pricing Theory in Discrete-Time and Discrete-Space Models These notes develop the theory of martingale pricing in a discrete-time,

More information

THE MARTINGALE METHOD DEMYSTIFIED

THE MARTINGALE METHOD DEMYSTIFIED THE MARTINGALE METHOD DEMYSTIFIED SIMON ELLERSGAARD NIELSEN Abstract. We consider the nitty gritty of the martingale approach to option pricing. These notes are largely based upon Björk s Arbitrage Theory

More information

3.2 No-arbitrage theory and risk neutral probability measure

3.2 No-arbitrage theory and risk neutral probability measure Mathematical Models in Economics and Finance Topic 3 Fundamental theorem of asset pricing 3.1 Law of one price and Arrow securities 3.2 No-arbitrage theory and risk neutral probability measure 3.3 Valuation

More information

ECON FINANCIAL ECONOMICS

ECON FINANCIAL ECONOMICS ECON 337901 FINANCIAL ECONOMICS Peter Ireland Boston College Spring 2018 These lecture notes by Peter Ireland are licensed under a Creative Commons Attribution-NonCommerical-ShareAlike 4.0 International

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

Introduction to Financial Mathematics and Engineering. A guide, based on lecture notes by Professor Chjan Lim. Julienne LaChance

Introduction to Financial Mathematics and Engineering. A guide, based on lecture notes by Professor Chjan Lim. Julienne LaChance Introduction to Financial Mathematics and Engineering A guide, based on lecture notes by Professor Chjan Lim Julienne LaChance Lecture 1. The Basics risk- involves an unknown outcome, but a known probability

More information

Basic Arbitrage Theory KTH Tomas Björk

Basic Arbitrage Theory KTH Tomas Björk Basic Arbitrage Theory KTH 2010 Tomas Björk Tomas Björk, 2010 Contents 1. Mathematics recap. (Ch 10-12) 2. Recap of the martingale approach. (Ch 10-12) 3. Change of numeraire. (Ch 26) Björk,T. Arbitrage

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

1 Asset Pricing: Replicating portfolios

1 Asset Pricing: Replicating portfolios Alberto Bisin Corporate Finance: Lecture Notes Class 1: Valuation updated November 17th, 2002 1 Asset Pricing: Replicating portfolios Consider an economy with two states of nature {s 1, s 2 } and with

More information

e62 Introduction to Optimization Fall 2016 Professor Benjamin Van Roy Homework 1 Solutions

e62 Introduction to Optimization Fall 2016 Professor Benjamin Van Roy Homework 1 Solutions e62 Introduction to Optimization Fall 26 Professor Benjamin Van Roy 267 Homework Solutions A. Python Practice Problem The script below will generate the required result. fb_list = #this list will contain

More information

Microeconomics of Banking: Lecture 3

Microeconomics of Banking: Lecture 3 Microeconomics of Banking: Lecture 3 Prof. Ronaldo CARPIO Oct. 9, 2015 Review of Last Week Consumer choice problem General equilibrium Contingent claims Risk aversion The optimal choice, x = (X, Y ), is

More information

3 Arbitrage pricing theory in discrete time.

3 Arbitrage pricing theory in discrete time. 3 Arbitrage pricing theory in discrete time. Orientation. In the examples studied in Chapter 1, we worked with a single period model and Gaussian returns; in this Chapter, we shall drop these assumptions

More information

Fundamental Theorem of Asset Pricing

Fundamental Theorem of Asset Pricing 5.450 Recitation o Arbitrage Roughly speaking, an arbitrage is a possibility of profit at zero cost. Often implicit is an assumption that such an arbitrage opportunity is scalable (can repeat it over and

More information

Lecture 8: Introduction to asset pricing

Lecture 8: Introduction to asset pricing THE UNIVERSITY OF SOUTHAMPTON Paul Klein Office: Murray Building, 3005 Email: p.klein@soton.ac.uk URL: http://paulklein.se Economics 3010 Topics in Macroeconomics 3 Autumn 2010 Lecture 8: Introduction

More information

COMP331/557. Chapter 6: Optimisation in Finance: Cash-Flow. (Cornuejols & Tütüncü, Chapter 3)

COMP331/557. Chapter 6: Optimisation in Finance: Cash-Flow. (Cornuejols & Tütüncü, Chapter 3) COMP331/557 Chapter 6: Optimisation in Finance: Cash-Flow (Cornuejols & Tütüncü, Chapter 3) 159 Cash-Flow Management Problem A company has the following net cash flow requirements (in 1000 s of ): Month

More information

Learning Martingale Measures to Price Options

Learning Martingale Measures to Price Options Learning Martingale Measures to Price Options Hung-Ching (Justin) Chen chenh3@cs.rpi.edu Malik Magdon-Ismail magdon@cs.rpi.edu April 14, 2006 Abstract We provide a framework for learning risk-neutral measures

More information

ECE 586BH: Problem Set 5: Problems and Solutions Multistage games, including repeated games, with observed moves

ECE 586BH: Problem Set 5: Problems and Solutions Multistage games, including repeated games, with observed moves University of Illinois Spring 01 ECE 586BH: Problem Set 5: Problems and Solutions Multistage games, including repeated games, with observed moves Due: Reading: Thursday, April 11 at beginning of class

More information

6: MULTI-PERIOD MARKET MODELS

6: MULTI-PERIOD MARKET MODELS 6: MULTI-PERIOD MARKET MODELS Marek Rutkowski School of Mathematics and Statistics University of Sydney Semester 2, 2016 M. Rutkowski (USydney) 6: Multi-Period Market Models 1 / 55 Outline We will examine

More information

Lecture 8: Asset pricing

Lecture 8: Asset pricing BURNABY SIMON FRASER UNIVERSITY BRITISH COLUMBIA Paul Klein Office: WMC 3635 Phone: (778) 782-9391 Email: paul klein 2@sfu.ca URL: http://paulklein.ca/newsite/teaching/483.php Economics 483 Advanced Topics

More information

Lecture 17. The model is parametrized by the time period, δt, and three fixed constant parameters, v, σ and the riskless rate r.

Lecture 17. The model is parametrized by the time period, δt, and three fixed constant parameters, v, σ and the riskless rate r. Lecture 7 Overture to continuous models Before rigorously deriving the acclaimed Black-Scholes pricing formula for the value of a European option, we developed a substantial body of material, in continuous

More information

Debt Contracts. Ram Singh. April 1, Department of Economics. Ram Singh (Delhi School of Economics) Debt Contracts April 1, / 14

Debt Contracts. Ram Singh. April 1, Department of Economics. Ram Singh (Delhi School of Economics) Debt Contracts April 1, / 14 Debt Contracts Ram Singh Department of Economics April 1, 215 Ram Singh (Delhi School of Economics) Debt Contracts April 1, 215 1 / 14 Debt Contracts I Innes (199, JET) Suppose Let There is a risk-neutral

More information

Portfolio Choice. := δi j, the basis is orthonormal. Expressed in terms of the natural basis, x = j. x j x j,

Portfolio Choice. := δi j, the basis is orthonormal. Expressed in terms of the natural basis, x = j. x j x j, Portfolio Choice Let us model portfolio choice formally in Euclidean space. There are n assets, and the portfolio space X = R n. A vector x X is a portfolio. Even though we like to see a vector as coordinate-free,

More information

LECTURE 2: MULTIPERIOD MODELS AND TREES

LECTURE 2: MULTIPERIOD MODELS AND TREES LECTURE 2: MULTIPERIOD MODELS AND TREES 1. Introduction One-period models, which were the subject of Lecture 1, are of limited usefulness in the pricing and hedging of derivative securities. In real-world

More information

Curriculum Map for Mathematics and Statistics MS (Predoctoral Studies in Mathematics) Pure* Math Applied** Math

Curriculum Map for Mathematics and Statistics MS (Predoctoral Studies in Mathematics) Pure* Math Applied** Math slkent@ysu.edu PHONE: 330-941-3302 Dept. Office Leave A Message MS (Predoctoral Studies in Mathematics) Pure* Math Applied** Math MATH 6980 Topology I MATH 6975 Complex Analysis I MATH 6965 Abstract Analysis

More information

Characterization of the Optimum

Characterization of the Optimum ECO 317 Economics of Uncertainty Fall Term 2009 Notes for lectures 5. Portfolio Allocation with One Riskless, One Risky Asset Characterization of the Optimum Consider a risk-averse, expected-utility-maximizing

More information

G5212: Game Theory. Mark Dean. Spring 2017

G5212: Game Theory. Mark Dean. Spring 2017 G5212: Game Theory Mark Dean Spring 2017 Why Game Theory? So far your microeconomic course has given you many tools for analyzing economic decision making What has it missed out? Sometimes, economic agents

More information

Valuation of derivative assets Lecture 8

Valuation of derivative assets Lecture 8 Valuation of derivative assets Lecture 8 Magnus Wiktorsson September 27, 2018 Magnus Wiktorsson L8 September 27, 2018 1 / 14 The risk neutral valuation formula Let X be contingent claim with maturity T.

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

Option Pricing. Chapter Discrete Time

Option Pricing. Chapter Discrete Time Chapter 7 Option Pricing 7.1 Discrete Time In the next section we will discuss the Black Scholes formula. To prepare for that, we will consider the much simpler problem of pricing options when there are

More information

Financial Economics Field Exam January 2008

Financial Economics Field Exam January 2008 Financial Economics Field Exam January 2008 There are two questions on the exam, representing Asset Pricing (236D = 234A) and Corporate Finance (234C). Please answer both questions to the best of your

More information

Stochastic Processes and Advanced Mathematical Finance. Multiperiod Binomial Tree Models

Stochastic Processes and Advanced Mathematical Finance. Multiperiod Binomial Tree Models 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

SYSM 6304: Risk and Decision Analysis Lecture 6: Pricing and Hedging Financial Derivatives

SYSM 6304: Risk and Decision Analysis Lecture 6: Pricing and Hedging Financial Derivatives SYSM 6304: Risk and Decision Analysis Lecture 6: Pricing and Hedging Financial Derivatives M. Vidyasagar Cecil & Ida Green Chair The University of Texas at Dallas Email: M.Vidyasagar@utdallas.edu October

More information

CHAPTER 2: STANDARD PRICING RESULTS UNDER DETERMINISTIC AND STOCHASTIC INTEREST RATES

CHAPTER 2: STANDARD PRICING RESULTS UNDER DETERMINISTIC AND STOCHASTIC INTEREST RATES CHAPTER 2: STANDARD PRICING RESULTS UNDER DETERMINISTIC AND STOCHASTIC INTEREST RATES Along with providing the way uncertainty is formalized in the considered economy, we establish in this chapter the

More information

BF212 Mathematical Methods for Finance

BF212 Mathematical Methods for Finance BF212 Mathematical Methods for Finance Academic Year: 2009-10 Semester: 2 Course Coordinator: William Leon Other Instructor(s): Pre-requisites: No. of AUs: 4 Cambridge G.C.E O Level Mathematics AB103 Business

More information

UNIVERSITY OF OSLO. Faculty of Mathematics and Natural Sciences

UNIVERSITY OF OSLO. Faculty of Mathematics and Natural Sciences UNIVERSITY OF OSLO Faculty of Mathematics and Natural Sciences Examination in MAT2700 Introduction to mathematical finance and investment theory. Day of examination: Monday, December 14, 2015. Examination

More information

Game Theory. Lecture Notes By Y. Narahari. Department of Computer Science and Automation Indian Institute of Science Bangalore, India October 2012

Game Theory. Lecture Notes By Y. Narahari. Department of Computer Science and Automation Indian Institute of Science Bangalore, India October 2012 Game Theory Lecture Notes By Y. Narahari Department of Computer Science and Automation Indian Institute of Science Bangalore, India October 22 COOPERATIVE GAME THEORY Correlated Strategies and Correlated

More information

Hedging and Pricing in the Binomial Model

Hedging and Pricing in the Binomial Model Hedging and Pricing in the Binomial Model Peter Carr Bloomberg LP and Courant Institute, NYU Continuous Time Finance Lecture 2 Wednesday, January 26th, 2005 One Period Model Initial Setup: 0 risk-free

More information

From Discrete Time to Continuous Time Modeling

From Discrete Time to Continuous Time Modeling From Discrete Time to Continuous Time Modeling Prof. S. Jaimungal, Department of Statistics, University of Toronto 2004 Arrow-Debreu Securities 2004 Prof. S. Jaimungal 2 Consider a simple one-period economy

More information

Martingale Approach to Pricing and Hedging

Martingale Approach to Pricing and Hedging Introduction and echniques Lecture 9 in Financial Mathematics UiO-SK451 Autumn 15 eacher:s. Ortiz-Latorre Martingale Approach to Pricing and Hedging 1 Risk Neutral Pricing Assume that we are in the basic

More information

Monte Carlo Methods in Structuring and Derivatives Pricing

Monte Carlo Methods in Structuring and Derivatives Pricing Monte Carlo Methods in Structuring and Derivatives Pricing Prof. Manuela Pedio (guest) 20263 Advanced Tools for Risk Management and Pricing Spring 2017 Outline and objectives The basic Monte Carlo algorithm

More information

1 Rational Expectations Equilibrium

1 Rational Expectations Equilibrium 1 Rational Expectations Euilibrium S - the (finite) set of states of the world - also use S to denote the number m - number of consumers K- number of physical commodities each trader has an endowment vector

More information

Lecture 16: Delta Hedging

Lecture 16: Delta Hedging Lecture 16: Delta Hedging We are now going to look at the construction of binomial trees as a first technique for pricing options in an approximative way. These techniques were first proposed in: J.C.

More information

Help Session 7. David Sovich. Washington University in St. Louis

Help Session 7. David Sovich. Washington University in St. Louis Help Session 7 Davi Sovich Washington University in St. Louis TODAY S AGENDA Toay we will learn how to price using Arrow securities We will then erive Q using Arrow securities ARROW SECURITIES IN THE BINOMIAL

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

Mean-Variance Hedging under Additional Market Information

Mean-Variance Hedging under Additional Market Information Mean-Variance Hedging under Additional Market Information Frank hierbach Department of Statistics University of Bonn Adenauerallee 24 42 53113 Bonn, Germany email: thierbach@finasto.uni-bonn.de Abstract

More information

Compulsory Assignment

Compulsory Assignment An Introduction to Mathematical Finance UiO-STK-MAT300 Autumn 2018 Professor: S. Ortiz-Latorre Compulsory Assignment Instructions: You may write your answers either by hand or on a computer for instance

More information

Financial Economics: Risk Sharing and Asset Pricing in General Equilibrium c

Financial Economics: Risk Sharing and Asset Pricing in General Equilibrium c 1 / 170 Contents Financial Economics: Risk Sharing and Asset Pricing in General Equilibrium c Lutz Arnold University of Regensburg Contents 1. Introduction 2. Two-period two-state model 3. Efficient risk

More information

Microeconomics Comprehensive Exam

Microeconomics Comprehensive Exam Microeconomics Comprehensive Exam June 2009 Instructions: (1) Please answer each of the four questions on separate pieces of paper. (2) When finished, please arrange your answers alphabetically (in the

More information

Definition 4.1. In a stochastic process T is called a stopping time if you can tell when it happens.

Definition 4.1. In a stochastic process T is called a stopping time if you can tell when it happens. 102 OPTIMAL STOPPING TIME 4. Optimal Stopping Time 4.1. Definitions. On the first day I explained the basic problem using one example in the book. On the second day I explained how the solution to the

More information

Mathematics in Finance

Mathematics in Finance Mathematics in Finance Robert Almgren University of Chicago MAA Short Course San Antonio, Texas January 11-12, 1999 2 Mathematics in Finance, Jan 11-12, 1999 Robert Almgren Contents 1 Completeness and

More information

European Contingent Claims

European Contingent Claims European Contingent Claims Seminar: Financial Modelling in Life Insurance organized by Dr. Nikolic and Dr. Meyhöfer Zhiwen Ning 13.05.2016 Zhiwen Ning European Contingent Claims 13.05.2016 1 / 23 outline

More information

Chapter 8. Markowitz Portfolio Theory. 8.1 Expected Returns and Covariance

Chapter 8. Markowitz Portfolio Theory. 8.1 Expected Returns and Covariance Chapter 8 Markowitz Portfolio Theory 8.1 Expected Returns and Covariance The main question in portfolio theory is the following: Given an initial capital V (0), and opportunities (buy or sell) in N securities

More information

Practice of Finance: Advanced Corporate Risk Management

Practice of Finance: Advanced Corporate Risk Management MIT OpenCourseWare http://ocw.mit.edu 15.997 Practice of Finance: Advanced Corporate Risk Management Spring 2009 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms.

More information

Lecture 2: Stochastic Discount Factor

Lecture 2: Stochastic Discount Factor Lecture 2: Stochastic Discount Factor Simon Gilchrist Boston Univerity and NBER EC 745 Fall, 2013 Stochastic Discount Factor (SDF) A stochastic discount factor is a stochastic process {M t,t+s } such that

More information

Follow links for Class Use and other Permissions. For more information send to:

Follow links for Class Use and other Permissions. For more information send  to: COPYRIGHT NOTICE: Costis Skiadas: Asset Pricing Theory is published by Princeton University Press and copyrighted, 2009, by Princeton University Press. All rights reserved. No part of this book may be

More information

sample-bookchapter 2015/7/7 9:44 page 1 #1 THE BINOMIAL MODEL

sample-bookchapter 2015/7/7 9:44 page 1 #1 THE BINOMIAL MODEL sample-bookchapter 2015/7/7 9:44 page 1 #1 1 THE BINOMIAL MODEL In this chapter we will study, in some detail, the simplest possible nontrivial model of a financial market the binomial model. This is a

More information

CONSISTENCY AMONG TRADING DESKS

CONSISTENCY AMONG TRADING DESKS CONSISTENCY AMONG TRADING DESKS David Heath 1 and Hyejin Ku 2 1 Department of Mathematical Sciences, Carnegie Mellon University, Pittsburgh, PA, USA, email:heath@andrew.cmu.edu 2 Department of Mathematics

More information

Stochastic Programming and Financial Analysis IE447. Midterm Review. Dr. Ted Ralphs

Stochastic Programming and Financial Analysis IE447. Midterm Review. Dr. Ted Ralphs Stochastic Programming and Financial Analysis IE447 Midterm Review Dr. Ted Ralphs IE447 Midterm Review 1 Forming a Mathematical Programming Model The general form of a mathematical programming model is:

More information

P s =(0,W 0 R) safe; P r =(W 0 σ,w 0 µ) risky; Beyond P r possible if leveraged borrowing OK Objective function Mean a (Std.Dev.

P s =(0,W 0 R) safe; P r =(W 0 σ,w 0 µ) risky; Beyond P r possible if leveraged borrowing OK Objective function Mean a (Std.Dev. ECO 305 FALL 2003 December 2 ORTFOLIO CHOICE One Riskless, One Risky Asset Safe asset: gross return rate R (1 plus interest rate) Risky asset: random gross return rate r Mean µ = E[r] >R,Varianceσ 2 =

More information

Credit Risk Models with Filtered Market Information

Credit Risk Models with Filtered Market Information Credit Risk Models with Filtered Market Information Rüdiger Frey Universität Leipzig Bressanone, July 2007 ruediger.frey@math.uni-leipzig.de www.math.uni-leipzig.de/~frey joint with Abdel Gabih and Thorsten

More information

A model for a large investor trading at market indifference prices

A model for a large investor trading at market indifference prices A model for a large investor trading at market indifference prices Dmitry Kramkov (joint work with Peter Bank) Carnegie Mellon University and University of Oxford 5th Oxford-Princeton Workshop on Financial

More information

CMSC 474, Introduction to Game Theory 16. Behavioral vs. Mixed Strategies

CMSC 474, Introduction to Game Theory 16. Behavioral vs. Mixed Strategies CMSC 474, Introduction to Game Theory 16. Behavioral vs. Mixed Strategies Mohammad T. Hajiaghayi University of Maryland Behavioral Strategies In imperfect-information extensive-form games, we can define

More information

DERIVATIVE SECURITIES Lecture 5: Fixed-income securities

DERIVATIVE SECURITIES Lecture 5: Fixed-income securities DERIVATIVE SECURITIES Lecture 5: Fixed-income securities Philip H. Dybvig Washington University in Saint Louis Interest rates Interest rate derivative pricing: general issues Bond and bond option pricing

More information

CHAPTER 17 OPTIONS AND CORPORATE FINANCE

CHAPTER 17 OPTIONS AND CORPORATE FINANCE CHAPTER 17 OPTIONS AND CORPORATE FINANCE Answers to Concept Questions 1. A call option confers the right, without the obligation, to buy an asset at a given price on or before a given date. A put option

More information

Risk-Neutral Probabilities

Risk-Neutral Probabilities Debt Instruments an Markets Risk-Neutral Probabilities Concepts Risk-Neutral Probabilities True Probabilities Risk-Neutral Pricing Risk-Neutral Probabilities Debt Instruments an Markets Reaings Tuckman,

More information

ECON FINANCIAL ECONOMICS

ECON FINANCIAL ECONOMICS ECON 337901 FINANCIAL ECONOMICS Peter Ireland Boston College February 19, 2019 These lecture notes by Peter Ireland are licensed under a Creative Commons Attribution-NonCommerical-ShareAlike 4.0 International

More information

Optimal investment and contingent claim valuation in illiquid markets

Optimal investment and contingent claim valuation in illiquid markets and contingent claim valuation in illiquid markets Teemu Pennanen King s College London Ari-Pekka Perkkiö Technische Universität Berlin 1 / 35 In most models of mathematical finance, there is at least

More information

CHAPTER 2 Concepts of Financial Economics and Asset Price Dynamics

CHAPTER 2 Concepts of Financial Economics and Asset Price Dynamics CHAPTER Concepts of Financial Economics and Asset Price Dynamics In the last chapter, we observe how the application of the no arbitrage argument enforces the forward price of a forward contract. The forward

More information

A No-Arbitrage Theorem for Uncertain Stock Model

A No-Arbitrage Theorem for Uncertain Stock Model Fuzzy Optim Decis Making manuscript No (will be inserted by the editor) A No-Arbitrage Theorem for Uncertain Stock Model Kai Yao Received: date / Accepted: date Abstract Stock model is used to describe

More information

Monte Carlo Methods in Financial Practice. Derivates Pricing and Arbitrage

Monte Carlo Methods in Financial Practice. Derivates Pricing and Arbitrage Derivates Pricing and Arbitrage What are Derivatives? Derivatives are complex financial products which come in many different forms. They are, simply said, a contract between two parties, which specify

More information

Financial Theory and Corporate Policy/ THIRD

Financial Theory and Corporate Policy/ THIRD Financial Theory and Corporate Policy/ THIRD EDITION THOMAS E COPELAND Professor of Finance University of California at Los Angeles Firm Consultant, Finance McKinsey & Company, Inc. J. FRED WESTON Cordner

More information

MATH3075/3975 FINANCIAL MATHEMATICS TUTORIAL PROBLEMS

MATH3075/3975 FINANCIAL MATHEMATICS TUTORIAL PROBLEMS MATH307/37 FINANCIAL MATHEMATICS TUTORIAL PROBLEMS School of Mathematics and Statistics Semester, 04 Tutorial problems should be used to test your mathematical skills and understanding of the lecture material.

More information

ADVANCED MACROECONOMIC TECHNIQUES NOTE 6a

ADVANCED MACROECONOMIC TECHNIQUES NOTE 6a 316-406 ADVANCED MACROECONOMIC TECHNIQUES NOTE 6a Chris Edmond hcpedmond@unimelb.edu.aui Introduction to consumption-based asset pricing We will begin our brief look at asset pricing with a review of the

More information

Game Theory. Lecture Notes By Y. Narahari. Department of Computer Science and Automation Indian Institute of Science Bangalore, India July 2012

Game Theory. Lecture Notes By Y. Narahari. Department of Computer Science and Automation Indian Institute of Science Bangalore, India July 2012 Game Theory Lecture Notes By Y. Narahari Department of Computer Science and Automation Indian Institute of Science Bangalore, India July 2012 The Revenue Equivalence Theorem Note: This is a only a draft

More information

Uncertainty in Equilibrium

Uncertainty in Equilibrium Uncertainty in Equilibrium Larry Blume May 1, 2007 1 Introduction The state-preference approach to uncertainty of Kenneth J. Arrow (1953) and Gérard Debreu (1959) lends itself rather easily to Walrasian

More information

Optimal stopping problems for a Brownian motion with a disorder on a finite interval

Optimal stopping problems for a Brownian motion with a disorder on a finite interval Optimal stopping problems for a Brownian motion with a disorder on a finite interval A. N. Shiryaev M. V. Zhitlukhin arxiv:1212.379v1 [math.st] 15 Dec 212 December 18, 212 Abstract We consider optimal

More information

Version 01 as of May 12, 2014 Author: Steven Sagona To be submitted to PRL (not really)

Version 01 as of May 12, 2014 Author: Steven Sagona To be submitted to PRL (not really) Version 01 as of May 12, 2014 Author: Steven Sagona To be submitted to PRL (not really) The Game Theory of Pokemon: AI implementing Nash Equilibrium (Dated: May 12, 2014) This paper is written to propose

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

Introduction to Probability Theory and Stochastic Processes for Finance Lecture Notes

Introduction to Probability Theory and Stochastic Processes for Finance Lecture Notes Introduction to Probability Theory and Stochastic Processes for Finance Lecture Notes Fabio Trojani Department of Economics, University of St. Gallen, Switzerland Correspondence address: Fabio Trojani,

More information

SOLUTION Fama Bliss and Risk Premiums in the Term Structure

SOLUTION Fama Bliss and Risk Premiums in the Term Structure SOLUTION Fama Bliss and Risk Premiums in the Term Structure Question (i EH Regression Results Holding period return year 3 year 4 year 5 year Intercept 0.0009 0.0011 0.0014 0.0015 (std err 0.003 0.0045

More information

Review for Quiz #2 Revised: October 31, 2015

Review for Quiz #2 Revised: October 31, 2015 ECON-UB 233 Dave Backus @ NYU Review for Quiz #2 Revised: October 31, 2015 I ll focus again on the big picture to give you a sense of what we ve done and how it fits together. For each topic/result/concept,

More information

9.1 Principal Component Analysis for Portfolios

9.1 Principal Component Analysis for Portfolios Chapter 9 Alpha Trading By the name of the strategies, an alpha trading strategy is to select and trade portfolios so the alpha is maximized. Two important mathematical objects are factor analysis and

More information

Economia Financiera Avanzada

Economia Financiera Avanzada Economia Financiera Avanzada José Fajardo EBAPE- Fundação Getulio Vargas Universidad del Pacífico, Julio 5 21, 2011 José Fajardo Economia Financiera Avanzada Prf. José Fajardo Two-Period Model: State-Preference

More information

Predicting the Market

Predicting the Market Predicting the Market April 28, 2012 Annual Conference on General Equilibrium and its Applications Steve Ross Franco Modigliani Professor of Financial Economics MIT The Importance of Forecasting Equity

More information

Slides III - Complete Markets

Slides III - Complete Markets Slides III - Complete Markets Julio Garín University of Georgia Macroeconomic Theory II (Ph.D.) Spring 2017 Macroeconomic Theory II Slides III - Complete Markets Spring 2017 1 / 33 Outline 1. Risk, Uncertainty,

More information