代做Prices of TESLA stock代写C/C++语言

Assignment 1

The files TESLA.xlsx txt (excel format)  and TESLA.txt (tex format) contain daily data on prices of TESLA stock from 2019/01/02 to 2021/12/30.  Use the SAS code provided for Assignment 1 or your own code to perform. the following analysis.

Examine the daily close prices and answer the following questions:

1.   Define the random walk process.

2.   Does the time series of daily TESLA prices display a trend?

3.   Given your answer to the first question, do TESLA prices behave like a stationary process or rather like a random walk?

4.   Does the return series, defined as return(t) = log p(t)–log p(t-1) have a trend?

5.   What are the differences between the behavior. of prices and returns?

6.   Define “volatility clustering” .

7.   Comment on the patterns in return and prices between 2020/01/29 and 2020/03/13

– what do you observe?

8.   Are the TESLA returns normally distributed? Explain and describe all evidence from the output provided by the summary statistics and figures (histogram, qq-  plot, quantiles)

9.   Write the formula of the AR(1) process.

10. Explain the computer output and describe all evidence along the following lines:

10.1 what are the estimated marginal mean and variance of returns? Is the mean return statistically significant? – write the statistic for testing the hypothesis: “mean return = 0”

10.2 Are the returns serially correlated? Is the autoregressive coefficient of the estimated AR(1) model statistically significant? What is the estimated variance of the error term of the AR(1) model?

10.3 What is the efficient market hypothesis?

10.4 Is your AR(1) estimation result consistent with the efficient market hypothesis? Explain why yes or not.