| EX4.STOCKS | R Documentation |
Stock data for Exercise 2 in Chapter 4
data("EX4.STOCKS")
A data frame with 216 observations on the following 41 variables.
AAa numeric vector
AAPLlag2a numeric vector
AXPlag2a numeric vector
BAlag2a numeric vector
BAClag2a numeric vector
CATlag2a numeric vector
CSCOlag2a numeric vector
CVXlag2a numeric vector
DDlag2a numeric vector
DISlag2a numeric vector
GElag2a numeric vector
HDlag2a numeric vector
HPQlag2a numeric vector
IBMlag2a numeric vector
INTClag2a numeric vector
JNJlag2a numeric vector
JPMlag2a numeric vector
KOlag2a numeric vector
MCDlag2a numeric vector
MMMlag2a numeric vector
MRKlag2a numeric vector
MSFTlag2a numeric vector
PFElag2a numeric vector
PGlag2a numeric vector
Tlag2a numeric vector
TRVlag2a numeric vector
UNHlag2a numeric vector
VZlag2a numeric vector
WMTlag2a numeric vector
XOMlag2a numeric vector
Australialag2a numeric vector
Copperlag2a numeric vector
DollarIndexlag2a numeric vector
Europelag2a numeric vector
Exchangelag2a numeric vector
GlobalDowlag2a numeric vector
HongKonglag2a numeric vector
Indialag2a numeric vector
Japanlag2a numeric vector
Oillag2a numeric vector
Shanghailag2a numeric vector
The goal is to predict the closing price of Alcoa stock (AA) from the closing prices of other stocks and commodities two days prior (IMBlag2, HongKonglag2, etc.). If this were possible, and if the association between the prices continued into the future, it would be possible to use this information to make smart trades.
Compiled from various sources on the internet, e.g., Yahoo historical prices.
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