Monte Carlo Simulation



Similar documents
The Intuition Behind Option Valuation: A Teaching Note

VALUATION IN DERIVATIVES MARKETS

How To Value Options In Black-Scholes Model

Discussions of Monte Carlo Simulation in Option Pricing TIANYI SHI, Y LAURENT LIU PROF. RENATO FERES MATH 350 RESEARCH PAPER

Valuing equity-based payments

Introduction to Options. Derivatives

Option Premium = Intrinsic. Speculative Value. Value

Financial Options: Pricing and Hedging

CS 522 Computational Tools and Methods in Finance Robert Jarrow Lecture 1: Equity Options

Lecture 6: Option Pricing Using a One-step Binomial Tree. Friday, September 14, 12

The Master of Science in Finance (English Program) - MSF. Department of Banking and Finance. Chulalongkorn Business School. Chulalongkorn University

Review of Basic Options Concepts and Terminology

Lecture 12. Options Strategies

Options/1. Prof. Ian Giddy

Futures Price d,f $ 0.65 = (1.05) (1.04)

Management of Asian and Cliquet Option Exposures for Insurance Companies: SPVA applications (I)

Return to Risk Limited website: Overview of Options An Introduction

Chapter 21 Valuing Options

Chapter 11 Options. Main Issues. Introduction to Options. Use of Options. Properties of Option Prices. Valuation Models of Options.

Lecture 12: The Black-Scholes Model Steven Skiena. skiena

Fin 3710 Investment Analysis Professor Rui Yao CHAPTER 14: OPTIONS MARKETS

A Simulation-Based lntroduction Using Excel

Derivatives: Principles and Practice

Option Valuation. Chapter 21

Financial Mathematics Exam

Value of Equity and Per Share Value when there are options and warrants outstanding. Aswath Damodaran

Equity Release Options and Guarantees Duncan Rawlinson

WHOLE OF LIFE SUPERANNUATION

NOVEMBER 2010 VOLATILITY AS AN ASSET CLASS

Investing In Volatility

Option Pricing Theory and Applications. Aswath Damodaran

On Black-Scholes Equation, Black- Scholes Formula and Binary Option Price

Introduction to Financial Models for Management and Planning

Option Values. Option Valuation. Call Option Value before Expiration. Determinants of Call Option Values

Introduction to Equity Derivatives

The Option to Delay!

Equity Value and Per Share Value: A Test

2. Exercising the option - buying or selling asset by using option. 3. Strike (or exercise) price - price at which asset may be bought or sold

Options: Valuation and (No) Arbitrage

Comparing the performance of retail unit trusts and capital guaranteed notes

Effective downside risk management

Third Edition. Philippe Jorion GARP. WILEY John Wiley & Sons, Inc.

An Introduction to the Asset Class. Convertible Bonds

CHAPTER 22: FUTURES MARKETS

GN47: Stochastic Modelling of Economic Risks in Life Insurance

2015 Exam 2 Syllabus Financial Mathematics Exam

第 9 讲 : 股 票 期 权 定 价 : B-S 模 型 Valuing Stock Options: The Black-Scholes Model

Option Values. Determinants of Call Option Values. CHAPTER 16 Option Valuation. Figure 16.1 Call Option Value Before Expiration

CHAPTER 22: FUTURES MARKETS

Option Portfolio Modeling

Assignment 2: Option Pricing and the Black-Scholes formula The University of British Columbia Science One CS Instructor: Michael Gelbart

FIN FINANCIAL INSTRUMENTS SPRING 2008

ANALYSIS OF FIXED INCOME SECURITIES

Investment Portfolio Management and Effective Asset Allocation for Institutional and Private Banking Clients

Chapter 22 Real Options

How To Sell A Callable Bond

BINOMIAL OPTION PRICING

Test 4 Created: 3:05:28 PM CDT 1. The buyer of a call option has the choice to exercise, but the writer of the call option has: A.

What can property offer an institutional investor?

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

The Promise and Peril of Real Options

CHAPTER 21: OPTION VALUATION

How To Become A Life Insurance Agent

FINANCIAL ECONOMICS OPTION PRICING

TPPE17 Corporate Finance 1(5) SOLUTIONS RE-EXAMS 2014 II + III

VALUATION OF FIXED INCOME SECURITIES. Presented By Sade Odunaiya Partner, Risk Management Alliance Consulting

Using simulation to calculate the NPV of a project

Black-Scholes Equation for Option Pricing

The Investment Implications of Solvency II

CHAPTER 21: OPTION VALUATION

Portfolio Management for institutional investors

Stocks paying discrete dividends: modelling and option pricing

NOTES ON THE BANK OF ENGLAND OPTION-IMPLIED PROBABILITY DENSITY FUNCTIONS

CHAPTER 15: THE TERM STRUCTURE OF INTEREST RATES

CHAPTER 15: THE TERM STRUCTURE OF INTEREST RATES

American and European. Put Option

Who Should Consider Using Covered Calls?

READING 14: LIFETIME FINANCIAL ADVICE: HUMAN CAPITAL, ASSET ALLOCATION, AND INSURANCE

SUPER COMPUTER CONSULTING INC.

The Valuation of Currency Options

An Incomplete Market Approach to Employee Stock Option Valuation

Chapter 8 Financial Options and Applications in Corporate Finance ANSWERS TO END-OF-CHAPTER QUESTIONS

Digital Options. and d 1 = d 2 + σ τ, P int = e rτ[ KN( d 2) FN( d 1) ], with d 2 = ln(f/k) σ2 τ/2

t = Calculate the implied interest rates and graph the term structure of interest rates. t = X t = t = 1 2 3

A Comparison of Option Pricing Models

Weekly Relative Value

Financial Engineering g and Actuarial Science In the Life Insurance Industry

Session IX: Lecturer: Dr. Jose Olmo. Module: Economics of Financial Markets. MSc. Financial Economics

Valuation of Structured Products

The University of Texas Investment Management Company Derivative Investment Policy

Hedging. An Undergraduate Introduction to Financial Mathematics. J. Robert Buchanan. J. Robert Buchanan Hedging

Pricing American Options on Leveraged Exchange. Traded Funds in the Binomial Pricing Model

Transcription:

Monte Carlo Simulation Palisade User Conference 2007 Real Options Analysis Dr. Colin Beardsley, Managing Director Risk-Return Solutions Pty Limited www.riskreturnsolutions.com

The Plot Today We will review firstly basic option concepts and terminology both for financial options and for real options We will then introduce the concept of Risk Neutrality We will discuss how the Black-Scholes Option Pricing Model (BSOPM) can be used to value real options We will use a version of the BSOPM to value embedded options in long term property leases and how to exploit volatility in the property market

A word of caution! Options are difficult and real options are real difficult Because of time constraints, I have oversimplified some of the concepts and, certainly, some of the mathematics behind option pricing theory @ RISK Monte Carlo simulation is an ideal approach for valuing both real and financial options most of the books and literature focus on binomial modelling Excel example of multi-period model but this approach is not flexible enough I will be happy to go further into the subject with any of you who are interested during the conference

Volatility Volatility is the speed at which the value of the underlying asset tends to diverge randomly away from and around today s value Higher volatility means a larger expected speed of divergence Very important! The more volatile the underlying the more valuable is the option Real options analysis assumed each value driving factor is subject to an unforcastable random walk or, in a special case of Monte Carlo simulation a user defined probability distribution

Valuing Real Options: Comparison of variables for financial and real options n.b. Real Options are much, much longer than financial options Stock price changes continually NPV of potential investment changes continually Underlying asset of stock Potential physical or intellectual investment Fixed price at which we can buy (call) or sell (put) a unit of stock Time to expiration Stock value uncertainty Riskless interest rate Fixed price at which we can make a business investment or sell it up Time until opportunity disappears Project uncertainty Riskless interest rate (as adjusted by Market Price of Risk)

Why Real Options....? The actual market place is characterised by change, uncertainty and competitive interactions. So the realisation of cash flows is far more random and as future cash flows resolve management may have valuable flexibility to alter its operating strategy in order to capitalise on favourable future opportunities or to mitigate losses. Management s flexibility to adapt its future actions in response to altered future market conditions expands an investment opportunity s value by improving its upside potential while limiting downside losses relative to management s initial expectations under passive management. The resultant asymmetry caused by management flexibility calls for an expanded NPV rule reflecting: Passive NPV of expected cash flows + value of options from active management

Case Study - Property Derivatives: A very simple first look at Risk Neutrality Property value = $100,000,000 Required return Risk Premium Risk Free Rate = 9% p.a. = 3% p.a. = 6% p.a. Using this simple example, first we need to discuss what happens when we value in a risk averse world and in a risk neutral world

Our Risk Averse World Discounted Property Value in one year s time is the return on the property discounted by the Risk Free Rate (6% p.a.) plus a Risk Premium called The Market Price of Risk (3% p.a.): $100,000,000*(1 + 9.0%[Return]) (1 + 6.0%[RFR] + 3.0%[Risk Premium]) = $100,000,000

A Risk Neutral World This approach neutralizes investors risk preferences at source the risk premium is subtracted from the required return. The payoff is then discounted by the Risk Free Rate. Risk Neutrality is critical for valuing random payoffs. All payoffs high or low represent investment opportunity not risk. $100,000,000*(1 + 9.0% (1 + 6.0%) 3.0%) = $100,000,000

But Real Options Are Different Animals!!! Valuing projects (including property) using derivative techniques is different from conventional DCF valuation techniques. The classic Black-Scholes model assumes the value of the property (the underlying) follows two combined processes which result in a series of stochastic (random) outcomes: 1. A periodic drift reflecting expected return, plus 2. A random element reflecting jolts in the market (volatility)

Behaviour of Property Prices (1): Drift Model of behaviour of property prices (1) Property value 16 14 12 10 8 6 4 2 0 Time Drift

Behaviour of Property Prices (2): Random Jolts Model of behaviour of property prices (2) Property value 12 10 8 6 4 2 0-2 -4 Time Drift Random

Generalised Property Process (3): Geometric Brownian Motion Model of behaviour of property prices (3) 15 Property value 10 5 0-5 Time Random Element Projected path Drift

Valuing Real Options in Property: Path dependency makes options natural candidates for simulation where we can examine easily the risk/return characteristics of the project. We can project the future value of the underlying asset and then designate an output cell or cells to be the discounted value of the put or call options embedded in the project. The mean of the output cell is the fair value of the real option. We will focus on the property market which is a natural candidate for real options there is a growing market for Property Derivatives

Deriving Rentals Rentals are assumed to be derived from property values much in the same way as a dividend is derived from a share The whole package of residual property value plus rentals is then discounted by the Risk Free Rate The Risk Free Rate is derived from government bond rate as the Zero Yield Curve which can also be modelled as a stochastic process

Modelling the underlying Clearly, modelling the underlying asset is critical We need to build a robust econometric model based on as much data as possible NeuralTools and StatTools are useful for analysing the data Another useful tool is the Distribution Fitting utility in @RISK Excel example re monthly gold prices Basic model for property prices - Excel example of Monte Carlo underlying path the output for the underlying forms a lognormal distribution

Simulated Risk Neutral Nominal Property Price $100 million - 25 years, 10% Volatility, 6% Risk Free Rate

The Three Ps of Property Derivatives: Probability Present Values Path dependency @RISK handles all of these easily

Background on Property Leases In a number of commercial property markets leases are negotiated in the basis of upwards only rent reviews Such reviews happen every five (5) years and the lease is marked to market as a function of growth in the underlying property Should property values fall then lease payments remain fixed at the level of the last review

The Problem... As an asset class, property is illiquid involving substantial transaction costs due to: The large size of each individual transaction Stamp duties Valuation and legal fees Incomplete market information Every property asset is complex and unique

The Solution - Not Asset Securitisation but Real Options Don t t buy or sell the physical property Instead - buy, sell, or swap some or all of the rental cash flows derived from the property Such cash flows can be valued using derivative pricing theory and bond pricing methods

A Closer Look... Any slice of the rentals were valued in the UK market for a 25 year lease Fifth Slice Years 21-25 140,687 Fourth Slice Fourth Slice Years 16-20 Years 21-25 198,381 122,617 Third Slice Third Slice Third Slice Years 11-15 Years 16-20 Years 21-25 198,577 180,104 111,320 Second Slice Second Slice Second Slice Second Slice Years 6-10 Years 11-15 Years 16-20 Years 21-25 250,691 181,142 164,291 101,546 Annuity Annuity Annuity Annuity Annuity Years 1-5 Years 6-10 Years 11-15 Years 16-20 Years 21-25 1,291,978 995,310 719,181 652,278 403,164

What is the market for Property Rental Derivatives? Funds holding property wishing to gain leverage on their investment. Corporate owners of property seeking to release cash flow Developers wishing to sell forward future rentals to release cash Investors seeking long term fixed rate investments Funds wishing to swap risk to diversify their portfolio

What are the benefits of Property Rental Derivatives? No stamp duty on transfer Minimal legal fees Credit can be enhanced Structure can be securitised The seller never parts with the property Swaps require only netting out of cash flows at reset dates

The rental cash flows which are derived from the property: Inherit the stochastic properties of the underlying property asset and using @RISK can handle correlations, IF/OR statements, and all the functions in Excel with RISKOptimizer being used to maximise real option values Are discounted at the spot rates derived from the risk free rate yield curve (for the rental uplifts) Can be separated into fixed and variable characteristics Can be analysed to assess the sensitivity to assumptions such as user specified distributions (non-normal), normal), jumps, crashes, mean reverting yields, interest rate changes etc. Example case study spreadsheet