MBA 728 – Fall AP1 2021 Project 2 Due: Sunday, September 26, 11:59 PM CST ※ Using the R script, answer the following questions. Please show all works for full credit. ※ Please install and load the following package as follows. install.packages("astsa") library(astsa) 1. Run the following code: set.seed(150) x <- arima.sim(model="list(ar" =="" c(0.4,="" 0.35),="" ma="c(0.5," 0.7)),="" mean="0," n="150)" a)="" [3="" points]="" what="" model="" is="" this="" simulation="" about?="" (that="" is,="" what="" are="" p,="" d,="" and="" q="" in="" arima(p,="" d,="" q)?="" )="" b)="" [2="" points]="" show="" the="" first="" five="" rows="" of="" ‘x’.="" c)="" [2="" points]="" plot="" the="" series="" ‘x’="" you="" obtained="" from="" the="" simulation.="" d)="" [3="" points]="" plot="" the="" sample="" autocorrelation="" function="" (acf)="" and="" the="" sample="" partial="" autocorrelation="" function="" (pacf).="" explain="" how="" they="" look="" like.="" 2.="" consider="" ‘x’="" you="" have="" obtained="" in="" previous="" question.="" suppose="" that="" you="" do="" not="" know="" what="" model="" the="" data="" ‘x’="" were="" generated="" from.="" after="" looking="" at="" acf="" and="" pacf,="" you="" decided="" to="" try="" to="" fit="" the="" following="" models="" to="" ‘x’="" :="" ar(1),="" ar(2),="" ma(1),="" ma(2),="" arma(1,="" 1),="" arma(1,="" 2),="" arma(2,="" 2),="" and="" arma(2,="" 3).="" a)="" [5="" points]="" fit="" each="" model="" you="" have="" decided="" to="" run.="" find="" the="" best="" model="" in="" terms="" of="" aic="" and="" bic="" criteria.="" b)="" [5="" points]="" explain="" about="" the="" significance="" of="" coefficients="" for="" all="" models.="" is="" the="" best="" model="" you="" selected="" in="" part="" a)="" reconciled?="" b)="" [5="" points]="" check="" the="" residual="" plots="" of="" the="" best="" model="" you="" chose="" in="" part="" a).="" explain="" all="" the="" plots.="" are="" the="" residuals="" white="" noise="" or="" not?="" this="" material="" is="" only="" for="" the="" use="" of="" students="" enrolled="" in="" mba="" 728="" for="" purposes="" associated="" with="" the="" course="" and="" may="" not="" be="" retained="" or="" further="" disseminated.="" all="" information="" in="" this="" material="" is="" proprietary="" to="" dr.="" sung="" ik="" kim.="" scanning,="" copying,="" posting="" to="" a="" website="" or="" reproducing="" and="" sharing="" in="" any="" form="" is="" strictly="" prohibited.="" 3.="" [25="" points]="" please="" use="" the="" following="" instructions.="" -="" find="" any="" stock="" you="" want="" to="" research.="" you="" can="" find="" ticker="" symbol="" from="" google,="" yahoo!="" finance,="" msn="" money,="" and="" so="" on="" (i.e.="" the="" ticker="" symbol="" of="" apple="" inc.="" is="" “aapl”).="" -="" run="" the="" following="" steps.="" 1)="" install="" package="" ‘quantmod’="" and="" load="" it.="" install.packages("quantmod")="" library(quantmod)="" 2)="" from="" yahoo!="" finance,="" download="" daily="" prices="" of="" the="" stock="" (from="" jan.="" 1,="" 2005="" to="" dec,="" 2019)="" you="" selected="" to="" research.="" you="" can="" run="" the="" following="" codes="" to="" download="" daily="" prices="" of="" the="" stock="" if="" you="" chose="" apple="" inc="" (the="" ticker="" symbol:="" aapl).="" getsymbols("aapl",="" src="yahoo" ,="" from='2005-01-01' ,="" to='2019-12-31' )="" please="" note="" that="" you="" have="" full="" length="" of="" daily="" prices.="" if="" not,="" consider="" other="" stock.="" 3)="" obtain="" monthly="" log="" stock="" returns.="" for="" instance,="" if="" you="" decide="" to="" do="" research="" on="" apple="" inc.="" whose="" ticker="" is="" “aapl”,="" then="" you="" will="" need="" to="" run="" the="" following:="" aapl.rtn=""><- monthlyreturn(aapl$aapl.adjusted,="" subset="NULL," type='log' ,="" leading="TRUE)" 4)="" change="" the="" data="" type="" to="" ts.="" again,="" for="" example,="" if="" you="" decide="" to="" do="" research="" on="" apple="" inc.,="" rtn=""><- ts(aapl.rtn, frequency = 12, start = c(2005,1)) - using monthly time series data rtn you obtained above, find a best model for the series. for example, ar(1), ar(2), ma(3), arma(2, 3), arima(2, 1, 4), or wahtever. justify your selection for a best model, using all knowledge you have learned so far in this course. ts(aapl.rtn,="" frequency="12," start="c(2005,1))" -="" using="" monthly="" time="" series="" data="" rtn="" you="" obtained="" above,="" find="" a="" best="" model="" for="" the="" series.="" for="" example,="" ar(1),="" ar(2),="" ma(3),="" arma(2,="" 3),="" arima(2,="" 1,="" 4),="" or="" wahtever.="" justify="" your="" selection="" for="" a="" best="" model,="" using="" all="" knowledge="" you="" have="" learned="" so="" far="" in="" this="">