Suppose you simulate the price path of stock HHF using a geometric Brownian motion model with µ = 0.1, o = 0.2, and time step At = 1/52 (weekly). Let St be the price of the stock at time t. If So = 100, and the first simulated (randomly selected) standard normal variable is e = -0.591, what is the simulated return over the next week?

Suppose you simulate the price path of stock HHF using a geometric Brownian motion model with µ = 0.1, o = 0.2, and time step At = 1/52 (weekly). Let St be the price of the stock at time t. If So = 100, and the first simulated (randomly selected) standard normal variable is e = -0.591, what is the simulated return over the next week?

College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter6: Exponential And Logarithmic Functions

Section6.8: Fitting Exponential Models To Data

Problem 3TI: Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to...

See similar textbooks

Similar questions

Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to 2012. a. Let x represent time in years starting with x=0 for the year 1997. Let y represent the number of seals in thousands. Use logistic regression to fit a model to these data. b. Use the model to predict the seal population for the year 2020. c. To the nearest whole number, what is the limiting value of this model?
The operator of a pumping station has observed that demand for water during early afternoon hours has an approximately exponential distribution with mean 1000 cfs (cubic feet per second). a)Of the three randomly selected afternoons, what is the probability that on at least two afternoons the demand will exceed 700 cfs?
Consider the CAPM. The risk-free rate is 6% and the expected return on the market is 18%. What is the expected return on a stock with a beta of 1.3 when market is efficient?
a. What is the probability that the lifetime X of the first component exceeds 3? b. What are the marginal pdf's of X and Y? Are the two lifetimes independent? x. What is the probability that the lifetime of at least one component exceeds 3?
The operator of a pumping station has observed that demand for water during early afternoon hours has an approximately exponential distribution with mean 100 cfs (cubic feet per second).a) Find the probability that the demand will exceed 200 cfs during the early afternoon on arandomly selected day.b) What water-pumping capacity should the station maintain during early afternoons sothat the probability that demand will exceed capacity on a randomly selected day isonly .01?
The operator of a pumping station has observed that demand for water during early afternoon hours has an approximately exponential distribution with mean 1000 cfs (cubic feet per second). b) What water-pumping capacity should the station maintain during early afternoons so that the probability that demand will be below the capacity on a randomly selected day is 0.995? c) Of the three randomly selected afternoons, what is the probability that on at least two afternoons the demand will exceed 700 cfs?
The operator of a pumping station has observed that demand for waterduring early afternoon hours has an approximately exponential distribution with mean 1000cfs (cubic feet per second).a) Find the probability that the demand will exceed 700 cfs during the early afternoonon a randomly selected day.b) What water-pumping capacity should the station maintain during early afternoons sothat the probability that demand will be below the capacity on a randomly selectedday is 0.995?c) Of the three randomly selected afternoons, what is the probability that on at least twoafternoons the demand will exceed 700 cfs? 2. Let Y1 and Y2 be random variables with joint density functionf(y1, y2) = (6/7(y^2+y1y2/2) 0 < y1 < 1, 0 < y2 < 2,0, elsewherea) Find marginal density functions. Are Y1 and Y2 independent?b) Find P(0 < Y1 < 0.3, −2 < Y2 < 1).c) Find P(0.6 < Y1 < 1|0 < Y2 < 1). 3.The joint density function of Y1 and Y2 is given byf(y1, y2) = (y1 + y2), 0 <…
Find the critical value t alpha/2. 99%; n=17; standard deviation is unknown; population appears to be normally distributed.
The following data consists of the times to relapse and the times to death following relapse of 10 bone marrow transplant patients. In the sample patients 4 and 6 were alive in relapse at the end of the study and patients 7–10 were alive, free of relapse at the end of the study. Suppose the time to relapse had an exponential distribution with hazard rate lambda and the time to death in relapse had a Weibull distribution with parameters theta and alpha (a) Construct the likelihood for the relapse rate lambda. (c) Suppose we were only allowed to observe a patients death time if the patient relapsed. Construct the likelihood for theta and alpha based on this truncated sample
A theoretical justification based on a certain material failure mechanism underlies the assumption that ductile strength X of a material has a lognormal distribution. Suppose the parameters are μ = 4.8 and σ = 0.11. What is the value of median ductile strength? (Round your answer to three decimal places.) If ten different samples of an alloy steel of this type were subjected to a strength test, how many would you expect to have strength of at least 125? If the smallest 5% of strength values were unacceptable, what would the minimum acceptable strength be?
find the expected value of Y and the variance of Y to three decimal places where appropriate
If the expected return on the market is 8% and the risk for your rate is 4%. What is the expected return for a stock with a beta equal to 2.00?