CodeAlong3_Performance_Analysis_shell

library(tidyverse)

## Warning: package 'ggplot2' was built under R version 4.4.3

## Warning: package 'lubridate' was built under R version 4.4.3

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   3.5.2     ✔ tibble    3.2.1
## ✔ lubridate 1.9.4     ✔ tidyr     1.3.1
## ✔ purrr     1.0.4     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(tidyquant)

## Warning: package 'tidyquant' was built under R version 4.4.3

## Registered S3 method overwritten by 'quantmod':
##   method            from
##   as.zoo.data.frame zoo

## Warning: package 'xts' was built under R version 4.4.3

## Warning: package 'zoo' was built under R version 4.4.3

## Warning: package 'quantmod' was built under R version 4.4.3

## Warning: package 'PerformanceAnalytics' was built under R version 4.4.3

## ── Attaching core tidyquant packages ─────────────────────── tidyquant 1.0.11 ──
## ✔ PerformanceAnalytics 2.0.8      ✔ TTR                  0.24.4
## ✔ quantmod             0.4.27     ✔ xts                  0.14.1
## ── Conflicts ────────────────────────────────────────── tidyquant_conflicts() ──
## ✖ zoo::as.Date()                 masks base::as.Date()
## ✖ zoo::as.Date.numeric()         masks base::as.Date.numeric()
## ✖ dplyr::filter()                masks stats::filter()
## ✖ xts::first()                   masks dplyr::first()
## ✖ dplyr::lag()                   masks stats::lag()
## ✖ xts::last()                    masks dplyr::last()
## ✖ PerformanceAnalytics::legend() masks graphics::legend()
## ✖ quantmod::summary()            masks base::summary()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

1 Get stock prices and convert to returns

Ra <- c("AAPL", "GOOG", "NFLX") %>%
  tq_get(get = "stock.prices",
         from = "2010-01-01",
         to = "2015-12-31") %>%
  group_by(symbol) %>%
  tq_transmute(select = adjusted,
               mutate_fun = periodReturn,
               period = "monthly",
               col_rename = "Ra")

2 Get baseline and convert to returns

Rb <- "XLK" %>%
  tq_get(get = "stock.prices",
         from = "2010-01-01",
         to = "2015-12-31") %>%
  tq_transmute(select = adjusted,
               mutate_fun = periodReturn,
               period = "monthly",
               col_rename = "Rb")

3 Join the two tables

RaRb <- left_join(Ra, Rb, by = "date")

4 Calculate CAPM

RaRb_capm <- RaRb %>%
    tq_performance(Ra = Ra,
                   Rb = Rb,
                   performance_fun = table.CAPM)

## Registered S3 method overwritten by 'robustbase':
##   method          from     
##   hatvalues.lmrob RobStatTM

RaRb_capm

## # A tibble: 3 × 18
## # Groups:   symbol [3]
##   symbol ActivePremium  Alpha AlphaRobust AnnualizedAlpha  Beta `Beta-`
##   <chr>          <dbl>  <dbl>       <dbl>           <dbl> <dbl>   <dbl>
## 1 AAPL           0.119 0.0089      0.0095           0.112 1.11    0.578
## 2 GOOG           0.034 0.0028     -0.0005           0.034 1.14    1.39 
## 3 NFLX           0.447 0.053       0.0439           0.859 0.384  -1.52 
## # ℹ 11 more variables: `Beta-Robust` <dbl>, `Beta+` <dbl>, `Beta+Robust` <dbl>,
## #   BetaRobust <dbl>, Correlation <dbl>, `Correlationp-value` <dbl>,
## #   InformationRatio <dbl>, `R-squared` <dbl>, `R-squaredRobust` <dbl>,
## #   TrackingError <dbl>, TreynorRatio <dbl>