In the following questions, let Bt denote a Brownian motion with Bo = 0. (a) Show...
In the following questions, let Bt denote a Brownian motion with B0 = 0. Let Xn, n-0, 1, 2, denote a biased random walk given by X0 0 and Xn+1 = Xn+Yn+1, where {Yn} are i.i.d. random variables with N(-1,1) distribution. Show that MnX +2nXn +n(n - 1) is a martingale. Let Xn, n-0, 1, 2, denote a biased random walk given by X0 0 and Xn+1 = Xn+Yn+1, where {Yn} are i.i.d. random variables with N(-1,1) distribution. Show that...
In the following questions, let Bt denote a Brownian motion with B0 = 0. Consider a discrete time risk model U-2 + Σ Y" where {Yi) are iid random variables with N(2,1) distribution. Derive the lower bound for the survival probability, P(Un 〉 0, for all n 0, 1, 2, ). Justify your arguments. Consider a discrete time risk model U-2 + Σ Y" where {Yi) are iid random variables with N(2,1) distribution. Derive the lower bound for the survival...
In the following questions, let Bt denote a Brownian motion with B0 = 0. Consider a discrete time risk model U-2 + Σ Y" where {Yi) are iid random variables with N(2,1) distribution. Derive the lower bound for the survival probability, P(Un 〉 0, for all n 0, 1, 2, ). Justify your arguments. Consider a discrete time risk model U-2 + Σ Y" where {Yi) are iid random variables with N(2,1) distribution. Derive the lower bound for the survival...
In the following questions, let Bt denote a Brownian motion with B0 = 0. Let Xt be the solution of SDE dX, = 3X, dt + 2XtdBt and Xo = 1. (a) Write down the SDE for Yt-eatXt, where a is a constant. (b) Find the value of a such that Yt is a martingale, and give the mean and variance of Y, in this case. Let Xt be the solution of SDE dX, = 3X, dt + 2XtdBt and...
let {X(t), 1 2 0} denote a Brownian motion 8.1. Let Y(t) = tx(1/t). (a) What is the distribution of Y(t)? (b) Compute Cov(Y(s), Y()) (c) Argue that {Y(t), t 2 0] is also Brownian motion (d) Let Using (c) present an argument that let {X(t), 1 2 0} denote a Brownian motion 8.1. Let Y(t) = tx(1/t). (a) What is the distribution of Y(t)? (b) Compute Cov(Y(s), Y()) (c) Argue that {Y(t), t 2 0] is also Brownian motion...
3. Let U-Bt- tB be Brownian bridge on [0, 1], where {BiJosesi is a Brownian process (i) Show E(Ut0 (ii) Show Cov(U,, Ut) s(1- t) for 0 s ts1. (ii) Let Xg(t)B Find functions g and h such that X, has the same covariance as a Brownian bridge. 3. Let U-Bt- tB be Brownian bridge on [0, 1], where {BiJosesi is a Brownian process (i) Show E(Ut0 (ii) Show Cov(U,, Ut) s(1- t) for 0 s ts1. (ii) Let Xg(t)B...
Suppose X, Y and Z are three different random variables. Let X obey Bernoulli Distribution. The probability distribution function is p(x) = Let Y obeys the standard Normal (Gaussian) distribution, which can be written as Y ∼ N(0, 1). X and Y are independent. Meanwhile, let Z = XY . (a) What is the Expectation (mean value) of X? (b) Are Y and Z independent? (Just clarify, do not need to prove) (c) Show that Z is also a standard...
1. Let X and Y have a discrete joint distribution with ( P(X = x, Y = y) = {1, 10, if (x, y) = (-1,1) if x = y = 0 elsewhere Show that X and Y are uncorrelated but not independent. [5 points] 2. Let X and Y have a discrete joint distribution with f(-1,0) = 0, f(-1,1) = 1/4, f(0,0) = 1/6, f(0, 1) = 0, $(1,0) = 1/12, f(1,1) = 1/2. Show that (a) the two...
2. Let Bt denote a Brownian motion. Consider the Black-Scholes model for the price of stock St, 2 So-1 and the savings account is given by β,-ea (a) Solve the equation for the price of the stock St and show that it is not a (b) Explain what is meant by an Equivalent Martingale Measure (EMM) martingale. State the Girsanov theorem. Give the expression for Bt under the EMM Q, hence derive the expression for St under the EMM, and...
1. Let Wt denote a standard Brownian motion. Evaluate the following expectationE[|Wt+t Wt|],where | · | denote absolute value. V [(Wt -Ws)2]. 2. Let Wt denote a Brownian motion. Derive the stochastic dierential equation for dXt andgroup the drift and diusion coecients together for the following stochastic processes:(a) Xt = Wt2(b) Xt =t+eWt(c) Xt = Wt3 3tWt(d) Xt = et+Wt(e) Xt = e2t sin(Wt)(f) Xt =eWt2t