Question 49) ListenThe misspecification of a structural population regression equation due to nonlinearities is a problem that generates inconsistency in the estimation of standarderrors.O TrueFalseQuestion 501) ListenThe Gauss-Markov assumption of zero conditional expectation of the error term in apopulation regression model implies the assumption of mean conditionalindependence.(Hint: the generalized Law of iterated expectations isE(Y | Z)=E(E(u | X, Z) | Z) for any Y, X, Z random variables)TrueFalse

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MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

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Question 17: A well-known brokerage firm executive claimed that 90% of investors are currently confident of meeting their investment goals. An XYZ Investor Optimism Survey, conducted over a two week period, found that in a sample of 100 people, 81% of them said they are confident of meeting their goals.Test the claim that the proportion of people who are confident is smaller than 90% at the 0.05 significance level.The null and alternative hypothesis would be: H0:p≤0.9H0:p≤0.9H1:p>0.9H1:p>0.9 H0:μ≤0.9H0:μ≤0.9H1:μ>0.9H1:μ>0.9 H0:μ≥0.9H0:μ≥0.9H1:μ<0.9H1:μ<0.9 H0:μ=0.9H0:μ=0.9H1:μ≠0.9H1:μ≠0.9 H0:p=0.9H0:p=0.9H1:p≠0.9H1:p≠0.9 H0:p≥0.9H0:p≥0.9H1:p<0.9H1:p<0.9 The test is: two-tailed right-tailed left-tailed The test statistic is: (to 3 decimals)The p-value is: (to 4 decimals)Based on this we: Fail to reject the null hypothesis Reject the null hypothesis
Question 2 Ignore the term "maximum likelihood"
Question 9 A well-known brokerage firm executive claimed that 60% of investors are currently confident of meeting their investment goals. An XYZ Investor Optimism Survey, conducted over a two week period, found that in a sample of 100 people, 61% of them said they are confident of meeting their goals.Test the claim that the proportion of people who are confident is larger than 60% at the 0.10 significance level.The null and alternative hypothesis would be: H0:μ≤0.6H0:μ≤0.6H1:μ>0.6H1:μ>0.6 H0:p≥0.6H0:p≥0.6H1:p<0.6H1:p<0.6 H0:p≤0.6H0:p≤0.6H1:p>0.6H1:p>0.6 H0:μ≥0.6H0:μ≥0.6H1:μ<0.6H1:μ<0.6 H0:μ=0.6H0:μ=0.6H1:μ≠0.6H1:μ≠0.6 H0:p=0.6H0:p=0.6H1:p≠0.6H1:p≠0.6 The test is: left-tailed right-tailed two-tailed The test statistic is: (to 2 decimals)The p-value is: (to 4 decimals)Based on this we: Fail to reject the null hypothesis Reject the null hypothesis
Question 6 Having studied Fixed Income Securities, you are now working as an analyst for a well known bond fund. Your manager asks you to replicate the JP Morgan T-Bond Index using a tracking error minimization approach. You are to replicate this index as closely as possible using a medium duration Treasury bond (M-BOND) and a long duration Treasury bond (L-BOND). These expire in approximately 7.15 years’ and 29.25 years’ time respectively. The following variance-covariance matrix, based on daily returns over the preceding six months, is given to you to use in your replication: Note: As usual, variances are given on the diagonal, e.g. the variance of M-BOND is 0.0042%. As usual, covariances appear in the non-diagonal elements, e.g. the covariance of M-BOND and L-BOND is 0.0057%. (a) Suppose the optimal weights for M-BOND and L-BOND are 0.7 and 0.3. Calculate the expected tracking error of the portfolio and explain how you interpret this number. (b) Calculate the correlation matrix…
1. What are time-series research designs, and how are they used to learn about changes in behavior over time? 2. What types of independent variables can be used in participant-variable research designs, and what conclusions can and cannot be drawn from their use? 3. What are single-participant research designs? When are they used, and what are their limitations?
In Australia, 16% of the adult population is nearsighted.17 If three Australians are chosen at random, what is the probability that two are nearsighted and one is not? 2.state each of the ﬁve assumptions of the classical regression model (OLS) and give an intuitive explanation of the meaning and need for each of them.
D & R A1 10 - 7 Question 10. Minimum Variance Commodity Hedge Choc Full of Good Inc., a producer of powdered hot chocolate, has just received a large order that will require the purchase of 800 metric tons of cocoa in 3 months. The current spot price of cocoa is US $3,055 per metric ton. The standard deviation of the change in spot cocoa price is 0.2. Mr. Dulce, the CFO of Choc Full, is considering a minimum-variance hedge of this future cocoa purchase using the three-month cocoa futures contract. The contract size is 10 metric tons. The standard deviation of the change in cocoa futures price is 0.25. The covariance between the change in the spot and futures cocoa price is 0.035. The annually compounded interest rate faced by the company is 5%, the three-month storage cost is $2.5 per metric ton, and the convenience yield is $0.5 per metric ton. What is the correlation of the change in the spot and futures cocoa price?
In a simple regression analysis for a given data set, if the null hypothesis β = 0 is rejected, then the null hypothesis ρ = 0 is also rejected. This statement is ___________ true.
D & R A1 10 - 3 Question 10. Minimum Variance Commodity Hedge Choc Full of Good Inc., a producer of powdered hot chocolate, has just received a large order that will require the purchase of 800 metric tons of cocoa in 3 months. The current spot price of cocoa is US $3,055 per metric ton. The standard deviation of the change in spot cocoa price is 0.2. Mr. Dulce, the CFO of Choc Full, is considering a minimum-variance hedge of this future cocoa purchase using the three-month cocoa futures contract. The contract size is 10 metric tons. The standard deviation of the change in cocoa futures price is 0.25. The covariance between the change in the spot and futures cocoa price is 0.035. The annually compounded interest rate faced by the company is 5%, the three-month storage cost is $2.5 per metric ton, and the convenience yield is $0.5 per metric ton. Compute the minimum-variance hedge ratio.
QUESTION 12 Historically, the proportion of people who trade in their old car to a car dealer when purchasing a new car is 48%. Over the previous 6 months, in a sample of 115 new-car buyers, 46 have traded in their old car. To determine (at the 10% level of significance) whether the proportion of new-car buyers that trade in their old car has statistically significantly decreased, what can you conclude concerning the null hypothesis?
Cinema HD an online movie streaming service that offers a wide variety of award-winning TV shows, movies, animes, and documentaries, would like to determine the mathematical trend of memberships in order to project future needs. Year 2013 2014 2015 2016 2017 2018 2019 2020 2021 Membership 17 16 16 21 20 20 23 25 24 Use the following time series data, to develop a regression equation relating memberships to time. Forecast 2023 membership Assuming the COVID-19 pandemic comes to an end in 2021, in your opinion, how will this affect membership? Why? How will this affect your prediction? What are the issues associated with qualitative forecasting, and how are these overcome? Provide an example of qualitative forecasting and explain the shortcomings.
In the simple linear regression model , the Gauss Markov ( classical ) assumptions guarantee that the OLS estimator of the unknown parameters is BLUE. Among those assumptions , in order to have consistency of the OLS estimator we need ( this is a question on the necessary condition ): Question 4Select one: a. we need that the errors are not correlated with each others and that they have zero mean b. we need that the errors are homoscedastic ( all have the same variance) c. we need that the residuals are not correlated with the explanatory variables and that the residuals have zero mean d. we need that the errors have zero mean and that they are not correlated with the regressors ( no endogeneity) e. we need that the errors are homoscedastic ( all have the same variance) and not correlated with each others ( no serial correlation)

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The misspecification of a structural population regression equation due to non linearities is a problem that generates inconsistency in the estimation of standard errors. True False