Week 4: Apply 3

# Load packages
library(tidyverse)

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
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## ✔ lubridate 1.9.5     ✔ tidyr     1.3.2
## ✔ purrr     1.2.2     
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## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(tidyquant)

## Registered S3 method overwritten by 'quantmod':
##   method            from
##   as.zoo.data.frame zoo 
## ── Attaching core tidyquant packages ─────────────────────── tidyquant 1.0.12 ──
## ✔ PerformanceAnalytics 2.1.0      ✔ TTR                  0.24.4
## ✔ quantmod             0.4.29     ✔ xts                  0.14.2── 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()
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## ✖ 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

Get stock prices and convert to returns

Ra <- c("MU", "CRWD", "PANW") %>%
    tq_get(get  = "stock.prices",
           from = "2026-01-01") %>%
    group_by(symbol) %>%
    tq_transmute(select     = adjusted, 
                 mutate_fun = periodReturn, 
                 period     = "monthly", 
                 col_rename = "Ra")

## Warning: There were 2 warnings in `dplyr::mutate()`.
## The first warning was:
## ℹ In argument: `nested.col = purrr::map(...)`.
## ℹ In group 1: `symbol = "CRWD"`.
## Caused by warning in `to_period()`:
## ! missing values removed from data
## ℹ Run `dplyr::last_dplyr_warnings()` to see the 1 remaining warning.

Ra

## # A tibble: 27 × 3
## # Groups:   symbol [3]
##    symbol date             Ra
##    <chr>  <date>        <dbl>
##  1 MU     2026-01-30  0.315  
##  2 MU     2026-02-27 -0.00605
##  3 MU     2026-03-31 -0.180  
##  4 MU     2026-04-30  0.531  
##  5 MU     2026-05-29  0.878  
##  6 MU     2026-06-30  0.189  
##  7 MU     2026-07-31 -0.287  
##  8 MU     2026-08-31  0.165  
##  9 MU     2026-09-22  0.143  
## 10 CRWD   2026-01-30 -0.0268 
## # ℹ 17 more rows

Get baseline and convert to returns

Rb <- "^IXIC" %>%
    tq_get(get  = "stock.prices",
           from = "2026-01-01") %>%
    tq_transmute(select     = adjusted, 
                 mutate_fun = periodReturn, 
                 period     = "monthly", 
                 col_rename = "Rb")

## Warning in to_period(xx, period = on.opts[[period]], ...): missing values
## removed from data

Rb

## # A tibble: 9 × 2
##   date             Rb
##   <date>        <dbl>
## 1 2026-01-30  0.00973
## 2 2026-02-27 -0.0338 
## 3 2026-03-31 -0.0475 
## 4 2026-04-30  0.153  
## 5 2026-05-29  0.0836 
## 6 2026-06-30 -0.0281 
## 7 2026-07-31 -0.0320 
## 8 2026-08-31  0.0393 
## 9 2026-09-21  0.0285

Join the two tables

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

## # A tibble: 27 × 4
## # Groups:   symbol [3]
##    symbol date             Ra       Rb
##    <chr>  <date>        <dbl>    <dbl>
##  1 MU     2026-01-30  0.315    0.00973
##  2 MU     2026-02-27 -0.00605 -0.0338 
##  3 MU     2026-03-31 -0.180   -0.0475 
##  4 MU     2026-04-30  0.531    0.153  
##  5 MU     2026-05-29  0.878    0.0836 
##  6 MU     2026-06-30  0.189   -0.0281 
##  7 MU     2026-07-31 -0.287   -0.0320 
##  8 MU     2026-08-31  0.165    0.0393 
##  9 MU     2026-09-22  0.143   NA      
## 10 CRWD   2026-01-30 -0.0268   0.00973
## # ℹ 17 more rows

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 MU              4.09 0.124       0.123             3.05  4.27   12.1 
## 2 CRWD            1.63 0.0713      0.0317            1.29  1.97   -2.47
## 3 PANW            1.41 0.0725      0.0685            1.32  1.45    1.21
## # 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>

Which stock has a positively skewed distribution of returns?

RaRb_capm <- RaRb %>%
    tq_performance(Ra = Ra, 
                   Rb = Rb, 
                   performance_fun = SkewnessKurtosisRatio)
RaRb_capm

## # A tibble: 3 × 2
## # Groups:   symbol [3]
##   symbol SkewnessKurtosisRatio.1
##   <chr>                    <dbl>
## 1 MU                       0.205
## 2 CRWD                     0.317
## 3 PANW                     0.300