Lecture 1. Sergei Fedotov Introduction to Financial Mathematics. No tutorials in the first week

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Lecture 1 Sergei Fedotov 20912 - Introduction to Financial Mathematics No tutorials in the first week Sergei Fedotov (University of Manchester) 20912 2010 1 / 9

Plan de la présentation 1 Introduction Elementary economics background What is financial mathematics? The role of SDE s and PDE s 2 Time Value of Money 3 Continuous Model for Stock Price Sergei Fedotov (University of Manchester) 20912 2010 2 / 9

General Information Textbooks: J. Hull, Options, Futures and Other Derivatives, 7th Edition, Prentice-Hall, 2008. P. Wilmott, S. Howison and J. Dewynne, The Mathematics of Financial Derivatives: A Student Introduction, Cambridge University Press, 1995. Sergei Fedotov (University of Manchester) 20912 2010 3 / 9

General Information Textbooks: J. Hull, Options, Futures and Other Derivatives, 7th Edition, Prentice-Hall, 2008. P. Wilmott, S. Howison and J. Dewynne, The Mathematics of Financial Derivatives: A Student Introduction, Cambridge University Press, 1995. Assessment: In class test: 20% (12 March, Monday, week 7, 9.00 9.50, based on exercise sheets 1-4). 2 hours examination: 80% Sergei Fedotov (University of Manchester) 20912 2010 3 / 9

Elementary Economics Background This course is concerned with mathematical models for financial markets: Sergei Fedotov (University of Manchester) 20912 2010 4 / 9

Elementary Economics Background This course is concerned with mathematical models for financial markets: Stock Markets, such as NYSE(New York Stock Exchange), London Stock Exchange, etc. Sergei Fedotov (University of Manchester) 20912 2010 4 / 9

Elementary Economics Background This course is concerned with mathematical models for financial markets: Stock Markets, such as NYSE(New York Stock Exchange), London Stock Exchange, etc. Bond Markets, where participants buy and sell debt securities. Sergei Fedotov (University of Manchester) 20912 2010 4 / 9

Elementary Economics Background This course is concerned with mathematical models for financial markets: Stock Markets, such as NYSE(New York Stock Exchange), London Stock Exchange, etc. Bond Markets, where participants buy and sell debt securities. Futures and Option Markets, where the derivative products are traded. Example: European call option gives the holder the right (not obligation) to buy underlying asset at a prescribed time T for a specified price E. Option market is massive! More money is invested in options than in the underlying securities. The main purpose of this course is to determine the price of options. Sergei Fedotov (University of Manchester) 20912 2010 4 / 9

Elementary Economics Background This course is concerned with mathematical models for financial markets: Stock Markets, such as NYSE(New York Stock Exchange), London Stock Exchange, etc. Bond Markets, where participants buy and sell debt securities. Futures and Option Markets, where the derivative products are traded. Example: European call option gives the holder the right (not obligation) to buy underlying asset at a prescribed time T for a specified price E. Option market is massive! More money is invested in options than in the underlying securities. The main purpose of this course is to determine the price of options. Why stochastic differential equations (SDE s) and partial differential equations (PDE s)? Sergei Fedotov (University of Manchester) 20912 2010 4 / 9

Time value of money What is the future value V(t) at time t = T of an amount P invested or borrowed today at t = 0? Sergei Fedotov (University of Manchester) 20912 2010 5 / 9

Time value of money What is the future value V(t) at time t = T of an amount P invested or borrowed today at t = 0? Simple interest rate: V(T) = (1+rT)P (1) where r > 0 is the simple interest rate, T is expressed in years. Sergei Fedotov (University of Manchester) 20912 2010 5 / 9

Time value of money What is the future value V(t) at time t = T of an amount P invested or borrowed today at t = 0? Simple interest rate: V(T) = (1+rT)P (1) where r > 0 is the simple interest rate, T is expressed in years. Compound interest rate: V(T) = ( 1+ r m) mt P (2) where m is the number interest payments made per annum. Sergei Fedotov (University of Manchester) 20912 2010 5 / 9

Time value of money What is the future value V(t) at time t = T of an amount P invested or borrowed today at t = 0? Simple interest rate: V(T) = (1+rT)P (1) where r > 0 is the simple interest rate, T is expressed in years. Compound interest rate: V(T) = ( 1+ r m) mt P (2) where m is the number interest payments made per annum. Continuous compounding: In the limit m, we obtain V(T) = e rt P (3) since e = lim z ( 1+ 1 z) z. Throughout this course the interest rate r will be continuously compounded. Sergei Fedotov (University of Manchester) 20912 2010 5 / 9

Simple Model for Stock Price S(t) Let S(t) represent the stock price at time t. How to write an equation for this function? Sergei Fedotov (University of Manchester) 20912 2010 6 / 9

Simple Model for Stock Price S(t) Let S(t) represent the stock price at time t. How to write an equation for this function? Return (relative measure of change): where S = S(t +δt) S(t) S S (4) Sergei Fedotov (University of Manchester) 20912 2010 6 / 9

Simple Model for Stock Price S(t) Let S(t) represent the stock price at time t. How to write an equation for this function? Return (relative measure of change): where S = S(t +δt) S(t) In the limit δt 0 : How to model the return? S S ds S (4) (5) Sergei Fedotov (University of Manchester) 20912 2010 6 / 9

Simple Model for Stock Price S(t) Let S(t) represent the stock price at time t. How to write an equation for this function? Return (relative measure of change): where S = S(t +δt) S(t) In the limit δt 0 : S S ds S (4) (5) How to model the return? Let us decompose the return into two parts: deterministic and stochastic Sergei Fedotov (University of Manchester) 20912 2010 6 / 9

Modelling of Return Return: ds = µdt +σdw (6) S where µ is a measure of the expected rate of growth of the stock price. In general, µ = µ(s,t). In simpe models µ is taken to be constant (µ = 0.1 0.3). Sergei Fedotov (University of Manchester) 20912 2010 7 / 9

Modelling of Return Return: ds = µdt +σdw (6) S where µ is a measure of the expected rate of growth of the stock price. In general, µ = µ(s,t). In simpe models µ is taken to be constant (µ = 0.1 0.3). σdw describes the stochastic change in the stock price, where dw stands for W = W(t + t) W(t) as t 0 W(t) is a Wiener process σ is the volatility (σ = 0.2 0.5) Sergei Fedotov (University of Manchester) 20912 2010 7 / 9

Stochastic differential equation for stock price ds = µsdt +σsdw (7) Sergei Fedotov (University of Manchester) 20912 2010 8 / 9

Stochastic differential equation for stock price ds = µsdt +σsdw (7) Simple case: volatility σ = 0 ds = µsdt (8) Sergei Fedotov (University of Manchester) 20912 2010 8 / 9

Wiener process Definition. The standard Wiener process W(t) is a Gaussian process such that W(t) has independent increments: if u v s t, then W(t) W(s) and W(v) W(u) are independent W(s +t) W(s) is N(0,t) and W(0) = 0 Clearly EW(t) = 0 and EW 2 = t, where E is the expectation operator. Sergei Fedotov (University of Manchester) 20912 2010 9 / 9

Wiener process Definition. The standard Wiener process W(t) is a Gaussian process such that W(t) has independent increments: if u v s t, then W(t) W(s) and W(v) W(u) are independent W(s +t) W(s) is N(0,t) and W(0) = 0 Clearly EW(t) = 0 and EW 2 = t, where E is the expectation operator. The increment W = W(t + t) W(t) can be written as W = X ( t) 1 2, where X is a random variable with normal distribution with zero mean and unit variance: E W = 0 and E( W) 2 = t. X N(0,1) Sergei Fedotov (University of Manchester) 20912 2010 9 / 9