KØBENHAVNS UNIVERSITET (Blok 2, 2011/2012) Naturvidenskabelig kandidateksamen Continuous time finance (FinKont) TIME ALLOWED : 3 hours
|
|
- Berenice Maxwell
- 6 years ago
- Views:
Transcription
1 This question paper consists of 3 printed pages FinKont KØBENHAVNS UNIVERSITET (Blok 2, 211/212) Naturvidenskabelig kandidateksamen Continuous time finance (FinKont) TIME ALLOWED : 3 hours This exam paper consists of 3 pages and 3 main questions, consisting of several subquestions. Economize with your time: Do not copy the text in the problems, and when possible refer to results from the syllabus without providing proofs. All written aids are allowed. You are allowed to write your answers in pencil. Problem 1 Let W (t) denote a Brownian motion and let T be a fixed time. Define the two processes X(t) = sin ( W (t) ) Y (t) = cos ( W (t) ). (a) Show that the process (X(t), Y (t)) solves the (2-dimensional) stochastic differential equation dx(t) = 1 X(t) dt + Y (t) dw (t), X() = 2 dy (t) = 1 Y (t) dt X(t) dw (t), Y () = 1. 2 (b) (i) Find a function f(t) such that M(t) = f(t)x(t) is a martingale. (ii) Find a constant z and a process h(t) such that sin ( W (T ) ) = z + T h(t) dw (t). (c) Let λ R be a constant. Show that E[W (T )e λw (T ) ] = λt e λ2 T/2. 1
2 Problem 2 Consider a standard Black-Scholes model, that is, a model consisting of a bank account B(t) with P-dynamics given by db(t) = rb(t) dt and a stock S(t) with P-dynamics given by ds(t) = αs(t) dt + σs(t) d W (t), S() = s > where r >, α R, σ > are constants and W (t) is a P-Brownian motion. Let T > be a given and fixed (expiry) date. As usual, let h(t) = ( h (t), h 1 (t) ) be a portfolio where h (t) is the number of units of the bank account at time t and h 1 (t) is the number of shares in the stock at time t. (a) Consider the portfolio h(t) = ( h (t), h 1 (t) ) = ( S(t)/B(t), B(t)/S(t) ). Determine whether the portfolio h is self-financing or not. Consider the square root option that at time T pays X = S(T ). Let F (t, s) be the pricing function of the option, that is, the arbitrage free price of the option at time t is given by π(t, X) = F (t, S(t)). (b) (i) Which equation does the pricing function F solve? (ii) Determine the arbitrage free price of the option at time t < T. Consider a new simple option X = Φ(S(T )) where the pay off function is given by Φ(s) = s log(s). (c) Determine the arbitrage free price of the option at time t < T. (Hint: one might use the result of Problem 1(c)). Problem 3 Consider a two-dimensional Black-Scholes model. The market model consists of three assets: A bank account B(t) and two stocks S 1 (t) and S 2 (t). For constant interest rate r, P-dynamics of B(t) are given by db(t) = rb(t) dt. The P-dynamics of S 1 (t) and S 2 (t) are given by ds 1 (t) = α 1 S 1 (t) dt + σ 1 S 1 (t) d W (t), S 1 () = s 1 > ds 2 (t) = α 2 S 2 (t) dt + σ 2 S 2 (t) d W (t), S 2 () = s 2 > where α 1, α 2 R, σ 1, σ 2 > are constants, and W (t) is a P-Brownian motion. 2
3 Let T > be a given and fixed (expiry) date. FinKont (a) Derive a condition such that the model is arbitrage free and complete. Assume that the market is arbitrage free and complete. Consider the option that at time T pays 1 if S 1 (T ) is strictly greater than S 2 (T ) and zero otherwise. (b) (i) Determine the arbitrage free price of the option at time t < T. (ii) Derive a hedge for the option. For the remainder of this problem assume that β = α 1 r σ 1 α 2 r σ 2 >. (c) Show that the model is not arbitrage free. Consider the portfolio where h 1 (t) = 1/(σ 1 S 1 (t)) is the number of shares in the stock 1 at time t, h 2 (t) = 1/(σ 2 S 2 (t)) is the number of shares in the stock 2 at time t, and choose the number of units of the bank account h (t) to make the portfolio self-financing. Let V h (t) denote the associated value process. Assume that the initial value of the portfolio is zero, that is, V h () =. (d) (i) Argue that h (t) = (V h (t) h 1 (t)s 1 (t) h 2 (t)s 2 (t))/b(t). (ii) Show that the portfolio is an arbitrage. END 3
4 This question paper consists of 3 printed pages FinKont KØBENHAVNS UNIVERSITET (Blok 2, 212/213) Naturvidenskabelig kandidateksamen Continuous time finance (FinKont) TIME ALLOWED : 3 hours This exam paper consists of 3 pages and 3 main questions, consisting of several subquestions. Use your time wisely: Do not copy the text of the problems, and when possible refer to results from the syllabus without providing proofs. All aids are allowed. You are allowed to write your answers in pencil. Problem 1 Let W (t) denote a Brownian motion and let T be a fixed time. (a) Use Feynman-Kac representation formula to solve the following boundary value problem in the domain of [, T ] (, ) (b) F t (t, x) + rxf x (t, x) + σ2 2 x2 F xx (t, x) = rf (t, x) for t < T where r R, σ > and K > are constants. F (T, x) = (x K) 2 ( T ) (i) Compute the mean value of exp t dw (t). (ii) Find a process h(t) such that ( T ) [ ( T )] exp t dw (t) = E exp t dw (t) + T h(t) dw (t). (c) Find the explicit solution to the following stochastic differential equation dx(t) = X(t) dt + e t dw (t), X() = x. 4
5 Problem 2 Consider a standard Black-Scholes model, that is, a model consisting of a bank account B(t) with P-dynamics given by db(t) = rb(t) dt and a stock S(t) with P-dynamics given by ds(t) = αs(t) dt + σs(t) d W (t), S() = s > where r R, α R and σ > are constants and W (t) is a P-Brownian motion. Let T > be a given and fixed (expiry) date. Let h (t) = (1 u) V h (t) B(t) and h 1(t) = u V h (t) S(t) be a self-financing portfolio where u is a constant and set V h () = 1. As usual, h (t) is the number of units of the bank account at time t and h 1 (t) is the number of shares in the stock at time t. (a) Find u such that the processes B(t)/V h (t) and S(t)/V h (t) both are martingales. Consider the derivative that at time T pays X = log(v h (T )). (b) Determine the arbitrage free price of the derivative at time t < T. Problem 3 Let W 1 (t) and W 2 (t) be two independent P-Brownian motions. The filtration is the one generated by the two Brownian motions, F t = σ( W 1 (s), W 2 (s) s t). Consider a market model with two assets: A bank account B(t) and a stock S 1 (t). For constant interest rate r, P-dynamics of B(t) are given by The P-dynamics of S 1 (t) is given by db(t) = rb(t) dt. ds 1 (t) = α 1 S 1 (t) dt + σ 11 S 1 (t) d W 1 (t) + σ 12 S 1 (t) d W 2 (t), S 1 () = s 1 > where α 1 R, σ 11 > and σ 12 > are constants. Let T > be a given and fixed (expiry) date. 5
6 (a) Is the model arbitrage free? Is the model complete? (b) Show that the call option X = (S 1 (T ) K) +, has a price process that does not depend on the choice of equivalent martingale measure. Moreover, determine the price process (arbitrage free price) of the call option at time t < T. (c) Show that the derivative Y = W 2 (T ), has a price process that do depend on the choice of equivalent martingale measure. For the remainder of this problem assume that we extend the market model to include a second stock with price process S 2 (t). The P-dynamics of S 2 (t) is given by ds 2 (t) = α 2 S 2 (t) dt + σ 22 S 2 (t) d W 2 (t), S 2 () = s 2 > where α 2 R and σ 22 > are constants. Thus, the new model (B, S 1, S 2 ) is a two-dimensional Black-Scholes model. (d) Is the model arbitrage free? Is the model complete? (e) (i) Determine the arbitrage free price of derivative Y at time t < T. (ii) Derive a hedge for derivative Y. END 6
7 This question paper consists of 4 printed pages FinKont KØBENHAVNS UNIVERSITET (Blok 2, 213/214) Naturvidenskabelig kandidateksamen Continuous time finance (FinKont) TIME ALLOWED : 3 hours This exam paper consists of 4 pages and 3 main questions, consisting of several subquestions. Use your time wisely: Do not copy the text of the problems, and when possible refer to results from the syllabus without providing proofs. All aids are allowed. You are allowed to write your answers in pencil. Problem 1 Let W (t) denote a Brownian motion and let F t = Ft W T be a fixed time. = σ(w (s) s t). Let Let X(t) be a geometric Brownian motion given by dx(t) = αx(t) dt + σx(t) dw (t) and X() = x > where α R and σ > are constants. Let M(t) be a process given by M(t) = a + e αt( bx(t) + cx(t) 2α/σ2 ) where a, b, c R are constants. (a) Show that M(t) is a martingale. Consider the stochastic differential equation dy (t) = ( t 2 Y (t) + α(t) ) dt + β(t) dw (t) and Y () = y where α(t) and β(t) are deterministic functions. 7
8 (b) (i) Show that the stochastic differential equation has a solution of the form ( Y (t) = e t3 /3 y + t and determine the function f(s). f(s)α(s) ds + (ii) Determine the distribution of Y (t). t ) f(s)β(s) dw (s) (c) (i) Compute the function g(t, x) such that g(t, W (t)) = E[W 4 (T ) F t ]. (ii) Find a constant z and a process h(t) such that W 4 (T ) = z+ T h(s) dw (s). Problem 2 Consider a standard Black-Scholes model, that is, a model consisting of a bank account B(t) with P-dynamics given by db(t) = rb(t) dt and a stock S(t) with P-dynamics given by ds(t) = αs(t) dt + σs(t) d W (t), S() = s > where r R, α R and σ > are constants and W (t) is a P-Brownian motion. Let T > be a given and fixed (expiry) date. Let h(t) = ( h (t), h 1 (t) ) be a portfolio where h (t) is the number of units of the bank account at time t and h 1 (t) is the number of shares in the stock at time t. Consider the derivative whose payoff at time T is X = 1 T T S(u) du and set I(t) = t S(u) du. (a) Determine the pricing function G(t, s, i) such that the arbitrage free price of the derivative at time t < T is given by Π(t, X) = G(t, S(t), I(t)). (Hint: you might use Fubini for conditional expectation: E[ b X(u)du F] = a b E[X(u) F] du). a Turn 8 over
9 Consider the self financing portfolio given by h 1 (t) = G s (t, S(t), I(t)) and h (t) = (V h (t) h 1 (t)s(t))/b(t). Assume that the initial value of the portfolio is V h () = G(, s, ). (b) Show that the derivative X can be hedged by h(t) = (h (t), h 1 (t)). Let F (t, s) be the solution to the partial differential equation F t (t, s) + rsf s (t, s) σ2 s 2 F ss (t, s) = rf (t, s) for t < T and s > F (T, s) = (s K) +. Thus, F (t, s) is the pricing function for a call option, expiry date T with strike K and with volatility σ >. Consider a portfolio given by h 1 (t) = F s (t, S(t)) and h (t) = e rt( F (t, S(t)) S(t)F s (t, S(t) ). (c) (i) Show that V h (T ) = (S(T ) K) +. (ii) Is h a hedge for the call option? Problem 3 Consider a two-dimensional Black-Scholes model. The market model consists of three assets: A bank account B(t) and two stocks S 1 (t) and S 2 (t). The P- dynamics of B(t) are given by db(t) = rb(t) dt, B() = 1 where r > is a constant. The P-dynamics of S 1 (t) and S 2 (t) are given by ds 1 (t) = α 1 S 1 (t) dt + σ 1 S 1 (t) d W 1 (t), S 1 () = s 1 > ds 2 (t) = α 2 S 2 (t) dt + σ 2 S 2 (t) ( ρ d W 1 (t) + 1 ρ 2 d W 2 (t) ), S 2 () = s 2 > where α 1, α 2 R, σ 1, σ 2 >, 1 < ρ < 1 are constants, and W 1 (t) and W 2 (t) are two independent P-Brownian motions. The filtration is the one generated by the two Brownian motions, that is, F t = σ( W 1 (s), W 2 (s) s t). Let T > be a given and fixed (expiry) date. (a) (i) Show that the model is arbitrage free and complete. (ii) What is the dynamics of S 1 (t) and S 2 (t) under the equivalent martingale measure? 9
10 Set L = e rt S 1 (T )/S 1 () and define a new probability measure d Q = LdQ. FinKont (b) What is the distribution of S 2 (T )/S 1 (T ) under the probability measure Q? Consider the derivative that at time T pays X = ( S 2 (T ) S 1 (T ) ) +. Let F (t, s1, s 2 ) be the pricing function of the derivative. (c) Compute the arbitrage free price of the derivative at time t =. (d) Which equation does the pricing function solve? END 1
11 This question paper consists of 3 printed pages FinKont KØBENHAVNS UNIVERSITET (Blok 2, 214/215) Naturvidenskabelig kandidateksamen Continuous time finance (FinKont) TIME ALLOWED : 3 hours This exam paper consists of 3 pages and 2 main questions, consisting of several subquestions. Use your time wisely: Do not copy the text of the problems, and when possible refer to results from the syllabus without providing proofs. All aids are allowed. You are allowed to write your answers in pencil. Problem 1 Let W (t) denote a Brownian motion and let F t = F W t = σ(w (s) s t). Let Z(t) be a process given by where α > is a constant. Z(t) = t (a) Determine the distribution of Z(t). u α dw (u) tα (b) (i) Is Z(t) an Ito process? (ii) Is Z(t) a martingale? Let F (t, x) be the solution to the partial differential equation F t (t, x) = α(x)f x (t, x) F xx(t, x) for t > and x R F (, x) = Φ(x) where α(x) and Φ(x) are given bounded continuous functions. 11
12 Let X(t) be the solution to the stochastic differential equation dx(t) = α ( X(t) ) dt + dw (t) X() = x. (c) (i) Show that the solution F (t, x) has the stochastic representation F (t, x) = E x [ Φ ( X(t) )]. (Hint: Consider the process ( t s, X(s) ) where t is given and fixed). (ii) Show that F (t, x) can be expressed by [ ( t F (t, x) = E x exp α ( W (u) ) dw (u) 1 2 (Hint: Girsanov theorem). t α 2( W (u) ) ) du Φ ( W (t) )]. Problem 2 Consider a standard Black-Scholes model, that is, a model consisting of a bank account B(t) with P-dynamics given by db(t) = rb(t) dt and a stock S(t) with P-dynamics given by ds(t) = αs(t) dt + σs(t) d W (t), S() = s > where r R, α R and σ > are constants and W (t) is a P-Brownian motion. Let T > be a given and fixed (expiry) date. Let h(t) = ( h (t), h 1 (t) ) be a portfolio where h (t) is the number of units of the bank account at time t and h 1 (t) is the number of shares in the stock at time t. Let u(t) = ( u (t), u 1 (t) ) be the relative portfolio. Assume that the relative portfolio u (t) =.2 and u 1 (t) =.8 is self-financing and that the initial value of the portfolio is 1. (a) Compute explicitly the corresponding portfolio h(t) = ( h (t), h 1 (t) ) as a function of W (t) and the parameters. 12
13 Consider a simple derivative X = Φ(S(T )) where the payoff function is given by K 2 s if s K 1 Φ(s) = K 2 K 1 if K 1 < s K 2 s K 1 if s > K 2 where < K 1 < K 2. (b) Find a hedging portfolio for derivative X. Consider a new derivative that at time T pays Y = Φ 1 ( S(T ) ) Φ2 ( S(T ) ) where the payoffs are given by Φ 1 (s) = ( log(s) K ) + and Φ2 (s) = ( K log(s) ) +. (c) Determine the arbitrage free price of derivative Y at time t < T. Let λ = (α r)/σ be the market price of risk and define the process Y (t) = e λ W (t) (r+λ 2 /2)t. Let V h (t) be the value process of a self-financing portfolio h(t) = ( h (t), h 1 (t) ). (d) (i) Show that Y (t) solves a stochastic differential equation. (ii) Show that Y (t)v h (t) is a martingale. (e) Show that if V h () = and V h (t) for all t then V h (t) = for all t. Consider a derivative that at time T pays Z and let π(t) denote the arbitrage free price at time t. (f) Show that π() = E P[ Y (T )Z ]. Let Q be the equivalent martingale measure and let L(t) be the associated Likelihood process. (g) Show that Y (t) = e rt L(t). END 13
14 This question paper consists of 3 printed pages FinKont KØBENHAVNS UNIVERSITET (Blok 2, 215/216) Naturvidenskabelig kandidateksamen Continuous time finance (FinKont) TIME ALLOWED : 3 hours This exam paper consists of 3 pages and 3 main questions, consisting of several subquestions. Use your time wisely: Do not copy the text of the problems, and when possible refer to results from the syllabus without providing proofs. All aids are allowed. You are allowed to write your answers in pencil. Problem 1 Let W (t) denote a Brownian motion and let F t = Ft W T > be a given and fixed time. = σ(w (s) s t). Let Let X(t) be a process given by (a) X(t) = t 1 dw (u) for t < T. T u (i) Show that the stochastic integral X(t) is well defined. That is, show that the integrand belongs to the class 2 [, t] for any t < T. (ii) Compute the mean value of X(t) and the variance of X(t). Consider the stochastic differential equation for t < T. dy (t) = Y (t) T t dt + dw (t) and Y () = (b) Show that Y (t) = (T t)x(t) solves the stochastic differential equation. (c) Show that Y (t) as t T in L 2. (Hint: Recall that X n X in L 2 if E[(X n X) 2 ] ). 14
15 Problem 2 Consider a standard Black-Scholes model, that is, a model consisting of a bank account B(t) with P-dynamics given by db(t) = rb(t) dt, B() = 1 and a stock S(t) with P-dynamics given by ds(t) = αs(t) dt + σs(t) d W (t), S() = s > where r R, α R and σ > are constants and W (t) is a P-Brownian motion. Let T > be a given and fixed (expiry) date. Let h(t) = ( h (t), h 1 (t) ) be a portfolio where h (t) is the number of units of the bank account at time t and h 1 (t) is the number of shares in the stock at time t. Consider the portfolio h(t) = ( h (t), h 1 (t) ) = (.5S(t),.5B(t) ). (a) Is the portfolio h self-financing? Consider the derivative that at time T pays X = ( log ( S(T ) )) 2 and let F (t, s) be the pricing function of the derivative. (b) (i) Determine the arbitrage free price of derivative X at time t =. (ii) Determine the equation satisfied by the pricing function F (t, s). Let C(t, s; K) denote the Black-Scholes price at time t of an European call option with strike price K and expiry date T when the current price of the underlying stock is s. (c) Show that C(t, s; K) is a convex function of K. That is, to show that C(t, s; (1 a)k 1 + ak 2 ) (1 a)c(t, s; K 1 ) + ac(t, s; K 2 ) for any a 1 and any < K 1 < K 2. 15
16 Consider the derivative that at time T pays Y = ( S(T ) cs(t ) ) + where c > is a constant and < T < T is a fixed date. (d) Determine the arbitrage free price of derivative Y at time t = T. (e) (i) Determine the arbitrage free price of derivative Y at time t < T. (ii) Find a hedging portfolio for derivative Y. Problem 3 Consider a n-dimensional Black-Scholes model. The market model consists of (n+1) assets: A bank account B(t) and n stocks S 1 (t),..., S n (t). The P-dynamics of B(t) is db(t) = rb(t) dt, B() = 1 where r R is a constant interest rate. The P-dynamics of S i (t) is ds i (t) = α i S i (t) dt + σ i S i (t) d W i (t), S i () = s i > for i = 1,..., n where α 1,..., α n R and σ 1 >,..., σ n > are constants and W 1 (t),..., W n (t) are n independent P-Brownian motions. The filtration is the one generated by the n Brownian motions, that is, F t = σ( W 1 (s),..., W n (s) s t). Let T > be a given and fixed (expiry) date. (a) (i) Is the model arbitrage free? (ii) Is the model complete? Consider the derivative that at time T pays X = n ( Si (T ) b i ) K i i=1 where b 1 >,..., b n > and K 1 >,..., K n > are constants. (b) Determine the arbitrage free price of derivative X at time t =. END 16
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 informationValuation of derivative assets Lecture 6
Valuation of derivative assets Lecture 6 Magnus Wiktorsson September 14, 2017 Magnus Wiktorsson L6 September 14, 2017 1 / 13 Feynman-Kac representation This is the link between a class of Partial Differential
More informationRisk 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 informationAMH4 - ADVANCED OPTION PRICING. Contents
AMH4 - ADVANCED OPTION PRICING ANDREW TULLOCH Contents 1. Theory of Option Pricing 2 2. Black-Scholes PDE Method 4 3. Martingale method 4 4. Monte Carlo methods 5 4.1. Method of antithetic variances 5
More informationFinance II. May 27, F (t, x)+αx f t x σ2 x 2 2 F F (T,x) = ln(x).
Finance II May 27, 25 1.-15. All notation should be clearly defined. Arguments should be complete and careful. 1. (a) Solve the boundary value problem F (t, x)+αx f t x + 1 2 σ2 x 2 2 F (t, x) x2 =, F
More informationOption pricing in the stochastic volatility model of Barndorff-Nielsen and Shephard
Option pricing in the stochastic volatility model of Barndorff-Nielsen and Shephard Indifference pricing and the minimal entropy martingale measure Fred Espen Benth Centre of Mathematics for Applications
More informationStochastic Processes and Stochastic Calculus - 9 Complete and Incomplete Market Models
Stochastic Processes and Stochastic Calculus - 9 Complete and Incomplete Market Models Eni Musta Università degli studi di Pisa San Miniato - 16 September 2016 Overview 1 Self-financing portfolio 2 Complete
More informationM5MF6. 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 informationThe 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 informationLecture 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 informationStochastic Differential equations as applied to pricing of options
Stochastic Differential equations as applied to pricing of options By Yasin LUT Supevisor:Prof. Tuomo Kauranne December 2010 Introduction Pricing an European call option Conclusion INTRODUCTION A stochastic
More information1.1 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 informationContinuous 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 informationSTOCHASTIC CALCULUS AND BLACK-SCHOLES MODEL
STOCHASTIC CALCULUS AND BLACK-SCHOLES MODEL YOUNGGEUN YOO Abstract. Ito s lemma is often used in Ito calculus to find the differentials of a stochastic process that depends on time. This paper will introduce
More informationValuation 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 informationMASM006 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 informationLecture 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 informationMartingale 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 informationNEWCASTLE 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 informationChapter 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 informationMSc Financial Engineering CHRISTMAS ASSIGNMENT: MERTON S JUMP-DIFFUSION MODEL. To be handed in by monday January 28, 2013
MSc Financial Engineering 2012-13 CHRISTMAS ASSIGNMENT: MERTON S JUMP-DIFFUSION MODEL To be handed in by monday January 28, 2013 Department EMS, Birkbeck Introduction The assignment consists of Reading
More informationMATH3075/3975 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 informationOptimal trading strategies under arbitrage
Optimal trading strategies under arbitrage Johannes Ruf Columbia University, Department of Statistics The Third Western Conference in Mathematical Finance November 14, 2009 How should an investor trade
More informationLecture 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 informationStochastic Differential Equations in Finance and Monte Carlo Simulations
Stochastic Differential Equations in Finance and Department of Statistics and Modelling Science University of Strathclyde Glasgow, G1 1XH China 2009 Outline Stochastic Modelling in Asset Prices 1 Stochastic
More informationPAPER 27 STOCHASTIC CALCULUS AND APPLICATIONS
MATHEMATICAL TRIPOS Part III Thursday, 5 June, 214 1:3 pm to 4:3 pm PAPER 27 STOCHASTIC CALCULUS AND APPLICATIONS Attempt no more than FOUR questions. There are SIX questions in total. The questions carry
More informationCompleteness 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 informationMath 6810 (Probability) Fall Lecture notes
Math 6810 (Probability) Fall 2012 Lecture notes Pieter Allaart University of North Texas April 16, 2013 2 Text: Introduction to Stochastic Calculus with Applications, by Fima C. Klebaner (3rd edition),
More informationExam Quantitative Finance (35V5A1)
Exam Quantitative Finance (35V5A1) Part I: Discrete-time finance Exercise 1 (20 points) a. Provide the definition of the pricing kernel k q. Relate this pricing kernel to the set of discount factors D
More informationθ(t ) = T f(0, T ) + σ2 T
1 Derivatives Pricing and Financial Modelling Andrew Cairns: room M3.08 E-mail: A.Cairns@ma.hw.ac.uk Tutorial 10 1. (Ho-Lee) Let X(T ) = T 0 W t dt. (a) What is the distribution of X(T )? (b) Find E[exp(
More informationForwards and Futures. Chapter Basics of forwards and futures Forwards
Chapter 7 Forwards and Futures Copyright c 2008 2011 Hyeong In Choi, All rights reserved. 7.1 Basics of forwards and futures The financial assets typically stocks we have been dealing with so far are the
More informationFrom 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 informationSPDE and portfolio choice (joint work with M. Musiela) Princeton University. Thaleia Zariphopoulou The University of Texas at Austin
SPDE and portfolio choice (joint work with M. Musiela) Princeton University November 2007 Thaleia Zariphopoulou The University of Texas at Austin 1 Performance measurement of investment strategies 2 Market
More informationIlliquidity, Credit risk and Merton s model
Illiquidity, Credit risk and Merton s model (joint work with J. Dong and L. Korobenko) A. Deniz Sezer University of Calgary April 28, 2016 Merton s model of corporate debt A corporate bond is a contingent
More information1 Mathematics in a Pill 1.1 PROBABILITY SPACE AND RANDOM VARIABLES. A probability triple P consists of the following components:
1 Mathematics in a Pill The purpose of this chapter is to give a brief outline of the probability theory underlying the mathematics inside the book, and to introduce necessary notation and conventions
More informationRisk Neutral Valuation
copyright 2012 Christian Fries 1 / 51 Risk Neutral Valuation Christian Fries Version 2.2 http://www.christian-fries.de/finmath April 19-20, 2012 copyright 2012 Christian Fries 2 / 51 Outline Notation Differential
More informationChapter 3: Black-Scholes Equation and Its Numerical Evaluation
Chapter 3: Black-Scholes Equation and Its Numerical Evaluation 3.1 Itô Integral 3.1.1 Convergence in the Mean and Stieltjes Integral Definition 3.1 (Convergence in the Mean) A sequence {X n } n ln of random
More informationEnlargement of filtration
Enlargement of filtration Bernardo D Auria email: bernardo.dauria@uc3m.es web: www.est.uc3m.es/bdauria July 6, 2017 ICMAT / UC3M Enlargement of Filtration Enlargement of Filtration ([1] 5.9) If G is a
More informationSTOCHASTIC INTEGRALS
Stat 391/FinMath 346 Lecture 8 STOCHASTIC INTEGRALS X t = CONTINUOUS PROCESS θ t = PORTFOLIO: #X t HELD AT t { St : STOCK PRICE M t : MG W t : BROWNIAN MOTION DISCRETE TIME: = t < t 1
More informationAdvanced Stochastic Processes.
Advanced Stochastic Processes. David Gamarnik LECTURE 16 Applications of Ito calculus to finance Lecture outline Trading strategies Black Scholes option pricing formula 16.1. Security price processes,
More informationHedging of swaptions in a Lévy driven Heath-Jarrow-Morton framework
Hedging of swaptions in a Lévy driven Heath-Jarrow-Morton framework Kathrin Glau, Nele Vandaele, Michèle Vanmaele Bachelier Finance Society World Congress 2010 June 22-26, 2010 Nele Vandaele Hedging of
More informationVariance Reduction for Monte Carlo Simulation in a Stochastic Volatility Environment
Variance Reduction for Monte Carlo Simulation in a Stochastic Volatility Environment Jean-Pierre Fouque Tracey Andrew Tullie December 11, 21 Abstract We propose a variance reduction method for Monte Carlo
More informationBIRKBECK (University of London) MSc EXAMINATION FOR INTERNAL STUDENTS MSc FINANCIAL ENGINEERING DEPARTMENT OF ECONOMICS, MATHEMATICS AND STATIS- TICS
BIRKBECK (University of London) MSc EXAMINATION FOR INTERNAL STUDENTS MSc FINANCIAL ENGINEERING DEPARTMENT OF ECONOMICS, MATHEMATICS AND STATIS- TICS PRICING EMMS014S7 Tuesday, May 31 2011, 10:00am-13.15pm
More informationHedging under Arbitrage
Hedging under Arbitrage Johannes Ruf Columbia University, Department of Statistics Modeling and Managing Financial Risks January 12, 2011 Motivation Given: a frictionless market of stocks with continuous
More informationStochastic Modelling in Finance
in Finance Department of Mathematics and Statistics University of Strathclyde Glasgow, G1 1XH April 2010 Outline and Probability 1 and Probability 2 Linear modelling Nonlinear modelling 3 The Black Scholes
More informationis a standard Brownian motion.
Stochastic Calculus Final Examination Solutions June 7, 25 There are 2 problems and points each.. (Property of Brownian Bridge) Let Bt = {B t, t B = } be a Brownian bridge, and define dx t = Xt dt + db
More informationCONTINUOUS TIME PRICING AND TRADING: A REVIEW, WITH SOME EXTRA PIECES
CONTINUOUS TIME PRICING AND TRADING: A REVIEW, WITH SOME EXTRA PIECES THE SOURCE OF A PRICE IS ALWAYS A TRADING STRATEGY SPECIAL CASES WHERE TRADING STRATEGY IS INDEPENDENT OF PROBABILITY MEASURE COMPLETENESS,
More informationBasic Concepts and Examples in Finance
Basic Concepts and Examples in Finance Bernardo D Auria email: bernardo.dauria@uc3m.es web: www.est.uc3m.es/bdauria July 5, 2017 ICMAT / UC3M The Financial Market The Financial Market We assume there are
More informationRMSC 4005 Stochastic Calculus for Finance and Risk. 1 Exercises. (c) Let X = {X n } n=0 be a {F n }-supermartingale. Show that.
1. EXERCISES RMSC 45 Stochastic Calculus for Finance and Risk Exercises 1 Exercises 1. (a) Let X = {X n } n= be a {F n }-martingale. Show that E(X n ) = E(X ) n N (b) Let X = {X n } n= be a {F n }-submartingale.
More informationSolving the Black-Scholes Equation
Solving the Black-Scholes Equation An Undergraduate Introduction to Financial Mathematics J. Robert Buchanan 2014 Initial Value Problem for the European Call The main objective of this lesson is solving
More informationMAS452/MAS6052. MAS452/MAS Turn Over SCHOOL OF MATHEMATICS AND STATISTICS. Stochastic Processes and Financial Mathematics
t r t r2 r t SCHOOL OF MATHEMATICS AND STATISTICS Stochastic Processes and Financial Mathematics Spring Semester 2017 2018 3 hours t s s tt t q st s 1 r s r t r s rts t q st s r t r r t Please leave this
More informationBasic 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 informationStochastic Volatility
Stochastic Volatility A Gentle Introduction Fredrik Armerin Department of Mathematics Royal Institute of Technology, Stockholm, Sweden Contents 1 Introduction 2 1.1 Volatility................................
More informationDefinition 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 informationBrownian Motion. Richard Lockhart. Simon Fraser University. STAT 870 Summer 2011
Brownian Motion Richard Lockhart Simon Fraser University STAT 870 Summer 2011 Richard Lockhart (Simon Fraser University) Brownian Motion STAT 870 Summer 2011 1 / 33 Purposes of Today s Lecture Describe
More informationStochastic Calculus for Finance II - some Solutions to Chapter IV
Stochastic Calculus for Finance II - some Solutions to Chapter IV Matthias Thul Last Update: June 9, 25 Exercise 4. This proof is fully analogous to the one of Theorem 4.2.. We want to show that for s
More informationPricing 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 informationEconomics has never been a science - and it is even less now than a few years ago. Paul Samuelson. Funeral by funeral, theory advances Paul Samuelson
Economics has never been a science - and it is even less now than a few years ago. Paul Samuelson Funeral by funeral, theory advances Paul Samuelson Economics is extremely useful as a form of employment
More information25857 Interest Rate Modelling
25857 UTS Business School University of Technology Sydney Chapter 20. Change of Numeraire May 15, 2014 1/36 Chapter 20. Change of Numeraire 1 The Radon-Nikodym Derivative 2 Option Pricing under Stochastic
More informationEuropean 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 informationErrata, Mahler Study Aids for Exam 3/M, Spring 2010 HCM, 1/26/13 Page 1
Errata, Mahler Study Aids for Exam 3/M, Spring 2010 HCM, 1/26/13 Page 1 1B, p. 72: (60%)(0.39) + (40%)(0.75) = 0.534. 1D, page 131, solution to the first Exercise: 2.5 2.5 λ(t) dt = 3t 2 dt 2 2 = t 3 ]
More informationRobust 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 informationHow to hedge Asian options in fractional Black-Scholes model
How to hedge Asian options in fractional Black-Scholes model Heikki ikanmäki Jena, March 29, 211 Fractional Lévy processes 1/36 Outline of the talk 1. Introduction 2. Main results 3. Methodology 4. Conclusions
More informationFinancial Derivatives Section 5
Financial Derivatives Section 5 The Black and Scholes Model Michail Anthropelos anthropel@unipi.gr http://web.xrh.unipi.gr/faculty/anthropelos/ University of Piraeus Spring 2018 M. Anthropelos (Un. of
More informationOption Pricing. 1 Introduction. Mrinal K. Ghosh
Option Pricing Mrinal K. Ghosh 1 Introduction We first introduce the basic terminology in option pricing. Option: An option is the right, but not the obligation to buy (or sell) an asset under specified
More informationPath Dependent British Options
Path Dependent British Options Kristoffer J Glover (Joint work with G. Peskir and F. Samee) School of Finance and Economics University of Technology, Sydney 18th August 2009 (PDE & Mathematical Finance
More information(1) Consider a European call option and a European put option on a nondividend-paying stock. You are given:
(1) Consider a European call option and a European put option on a nondividend-paying stock. You are given: (i) The current price of the stock is $60. (ii) The call option currently sells for $0.15 more
More informationOption Pricing with Long Memory Stochastic Volatility Models
Option Pricing with Long Memory Stochastic Volatility Models Zhigang Tong Thesis submitted to the Faculty of Graduate and Postdoctoral Studies in partial fulfillment of the requirements for the degree
More informationPAPER 211 ADVANCED FINANCIAL MODELS
MATHEMATICAL TRIPOS Part III Friday, 27 May, 2016 1:30 pm to 4:30 pm PAPER 211 ADVANCED FINANCIAL MODELS Attempt no more than FOUR questions. There are SIX questions in total. The questions carry equal
More informationThe 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 informationMulti-Asset Options. A Numerical Study VILHELM NIKLASSON FRIDA TIVEDAL. Master s thesis in Engineering Mathematics and Computational Science
Multi-Asset Options A Numerical Study Master s thesis in Engineering Mathematics and Computational Science VILHELM NIKLASSON FRIDA TIVEDAL Department of Mathematical Sciences Chalmers University of Technology
More informationAn Introduction to Point Processes. from a. Martingale Point of View
An Introduction to Point Processes from a Martingale Point of View Tomas Björk KTH, 211 Preliminary, incomplete, and probably with lots of typos 2 Contents I The Mathematics of Counting Processes 5 1 Counting
More informationArbitrage, Martingales, and Pricing Kernels
Arbitrage, Martingales, and Pricing Kernels Arbitrage, Martingales, and Pricing Kernels 1/ 36 Introduction A contingent claim s price process can be transformed into a martingale process by 1 Adjusting
More informationYoungrok Lee and Jaesung Lee
orean J. Math. 3 015, No. 1, pp. 81 91 http://dx.doi.org/10.11568/kjm.015.3.1.81 LOCAL VOLATILITY FOR QUANTO OPTION PRICES WITH STOCHASTIC INTEREST RATES Youngrok Lee and Jaesung Lee Abstract. This paper
More informationMSC 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 informationSolving the Black-Scholes Equation
Solving the Black-Scholes Equation An Undergraduate Introduction to Financial Mathematics J. Robert Buchanan 2010 Initial Value Problem for the European Call rf = F t + rsf S + 1 2 σ2 S 2 F SS for (S,
More informationMASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.265/15.070J Fall 2013 Lecture 19 11/20/2013. Applications of Ito calculus to finance
MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.265/15.7J Fall 213 Lecture 19 11/2/213 Applications of Ito calculus to finance Content. 1. Trading strategies 2. Black-Scholes option pricing formula 1 Security
More informationOption 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 information3 Ito formula and processes
3 Ito formula and processes 3.1 Ito formula Let f be a differentiable function. If g is another differentiable function, we have by the chain rule d dt f(g(t)) = f (g(t))g (t), which in the differential
More informationLecture 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( ) since this is the benefit of buying the asset at the strike price rather
Review of some financial models for MAT 483 Parity and Other Option Relationships The basic parity relationship for European options with the same strike price and the same time to expiration is: C( KT
More informationExponential utility maximization under partial information
Exponential utility maximization under partial information Marina Santacroce Politecnico di Torino Joint work with M. Mania AMaMeF 5-1 May, 28 Pitesti, May 1th, 28 Outline Expected utility maximization
More informationBasic Concepts in Mathematical Finance
Chapter 1 Basic Concepts in Mathematical Finance In this chapter, we give an overview of basic concepts in mathematical finance theory, and then explain those concepts in very simple cases, namely in the
More information(c) Consider a standard Black-Scholes market described in detail in
Tentamen i 5B1575 Finansiella Derivat. Måndag 27 augusti 2007 kl. 14.00 19.00. Examinator: Camilla Landén, tel 790 8466. Tillåtna hjälpmedel: Inga. Allmänna anvisningar: Lösningarna skall vara lättläsliga
More informationAsymptotic Method for Singularity in Path-Dependent Option Pricing
Asymptotic Method for Singularity in Path-Dependent Option Pricing Sang-Hyeon Park, Jeong-Hoon Kim Dept. Math. Yonsei University June 2010 Singularity in Path-Dependent June 2010 Option Pricing 1 / 21
More informationIntroduction Taylor s Theorem Einstein s Theory Bachelier s Probability Law Brownian Motion Itô s Calculus. Itô s Calculus.
Itô s Calculus Christopher Ting Christopher Ting http://www.mysmu.edu/faculty/christophert/ : christopherting@smu.edu.sg : 6828 0364 : LKCSB 5036 October 21, 2016 Christopher Ting QF 101 Week 10 October
More informationPricing 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 informationPDE Methods for the Maximum Drawdown
PDE Methods for the Maximum Drawdown Libor Pospisil, Jan Vecer Columbia University, Department of Statistics, New York, NY 127, USA April 1, 28 Abstract Maximum drawdown is a risk measure that plays an
More informationApplication of Stochastic Calculus to Price a Quanto Spread
Application of Stochastic Calculus to Price a Quanto Spread Christopher Ting http://www.mysmu.edu/faculty/christophert/ Algorithmic Quantitative Finance July 15, 2017 Christopher Ting July 15, 2017 1/33
More informationReading: You should read Hull chapter 12 and perhaps the very first part of chapter 13.
FIN-40008 FINANCIAL INSTRUMENTS SPRING 2008 Asset Price Dynamics Introduction These notes give assumptions of asset price returns that are derived from the efficient markets hypothesis. Although a hypothesis,
More informationThe 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 informationMath 623 (IOE 623), Winter 2008: Final exam
Math 623 (IOE 623), Winter 2008: Final exam Name: Student ID: This is a closed book exam. You may bring up to ten one sided A4 pages of notes to the exam. You may also use a calculator but not its memory
More informationStochastic Calculus, Application of Real Analysis in Finance
, Application of Real Analysis in Finance Workshop for Young Mathematicians in Korea Seungkyu Lee Pohang University of Science and Technology August 4th, 2010 Contents 1 BINOMIAL ASSET PRICING MODEL Contents
More informationThe stochastic calculus
Gdansk A schedule of the lecture Stochastic differential equations Ito calculus, Ito process Ornstein - Uhlenbeck (OU) process Heston model Stopping time for OU process Stochastic differential equations
More informationGreek 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 informationStochastic Processes and Financial Mathematics (part two) Dr Nic Freeman
Stochastic Processes and Financial Mathematics (part two) Dr Nic Freeman April 25, 218 Contents 9 The transition to continuous time 3 1 Brownian motion 5 1.1 The limit of random walks...............................
More informationand K = 10 The volatility a in our model describes the amount of random noise in the stock price. Y{x,t) = -J-{t,x) = xy/t- t<pn{d+{t-t,x))
-5b- 3.3. THE GREEKS Theta #(t, x) of a call option with T = 0.75 and K = 10 Rho g{t,x) of a call option with T = 0.75 and K = 10 The volatility a in our model describes the amount of random noise in the
More informationLocal Volatility Dynamic Models
René Carmona Bendheim Center for Finance Department of Operations Research & Financial Engineering Princeton University Columbia November 9, 27 Contents Joint work with Sergey Nadtochyi Motivation 1 Understanding
More information1 The continuous time limit
Derivative Securities, Courant Institute, Fall 2008 http://www.math.nyu.edu/faculty/goodman/teaching/derivsec08/index.html Jonathan Goodman and Keith Lewis Supplementary notes and comments, Section 3 1
More informationOptions. An Undergraduate Introduction to Financial Mathematics. J. Robert Buchanan. J. Robert Buchanan Options
Options An Undergraduate Introduction to Financial Mathematics J. Robert Buchanan 2014 Definitions and Terminology Definition An option is the right, but not the obligation, to buy or sell a security such
More information