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1 Get stock prices and convert to returns

Ra <- c("MSFT", "GOOG", "DELL") %>%
    tq_get(get  = "stock.prices",
           from = "2022-01-01") %>%
    group_by(symbol) %>%
    tq_transmute(select     = adjusted, 
                 mutate_fun = periodReturn, 
                 period     = "monthly", 
                 col_rename = "Ra")
Ra
## # A tibble: 87 × 3
## # Groups:   symbol [3]
##    symbol date             Ra
##    <chr>  <date>        <dbl>
##  1 MSFT   2022-01-31 -0.0710 
##  2 MSFT   2022-02-28 -0.0372 
##  3 MSFT   2022-03-31  0.0319 
##  4 MSFT   2022-04-29 -0.0999 
##  5 MSFT   2022-05-31 -0.0181 
##  6 MSFT   2022-06-30 -0.0553 
##  7 MSFT   2022-07-29  0.0931 
##  8 MSFT   2022-08-31 -0.0667 
##  9 MSFT   2022-09-30 -0.109  
## 10 MSFT   2022-10-31 -0.00331
## # ℹ 77 more rows

2 Get baseline and convert to return

Rb <- "^IXIC" %>%
    tq_get(get  = "stock.prices",
           from = "2022-01-01") %>%
    tq_transmute(select     = adjusted, 
                 mutate_fun = periodReturn, 
                 period     = "monthly", 
                 col_rename = "Rb")
Rb
## # A tibble: 29 × 2
##    date            Rb
##    <date>       <dbl>
##  1 2022-01-31 -0.101 
##  2 2022-02-28 -0.0343
##  3 2022-03-31  0.0341
##  4 2022-04-29 -0.133 
##  5 2022-05-31 -0.0205
##  6 2022-06-30 -0.0871
##  7 2022-07-29  0.123 
##  8 2022-08-31 -0.0464
##  9 2022-09-30 -0.105 
## 10 2022-10-31  0.0390
## # ℹ 19 more rows

3 Join the two tables

RaRb <- left_join(Ra, Rb, by = c("date" = "date"))
RaRb
## # A tibble: 87 × 4
## # Groups:   symbol [3]
##    symbol date             Ra      Rb
##    <chr>  <date>        <dbl>   <dbl>
##  1 MSFT   2022-01-31 -0.0710  -0.101 
##  2 MSFT   2022-02-28 -0.0372  -0.0343
##  3 MSFT   2022-03-31  0.0319   0.0341
##  4 MSFT   2022-04-29 -0.0999  -0.133 
##  5 MSFT   2022-05-31 -0.0181  -0.0205
##  6 MSFT   2022-06-30 -0.0553  -0.0871
##  7 MSFT   2022-07-29  0.0931   0.123 
##  8 MSFT   2022-08-31 -0.0667  -0.0464
##  9 MSFT   2022-09-30 -0.109   -0.105 
## 10 MSFT   2022-10-31 -0.00331  0.0390
## # ℹ 77 more rows

4 Calculate CAPM

RaRb_capm <- RaRb %>%
    tq_performance(Ra = Ra, 
                   Rb = Rb, 
                   performance_fun = VolatilitySkewness)
RaRb_capm
## # A tibble: 3 × 2
## # Groups:   symbol [3]
##   symbol VolatilitySkewness.1
##   <chr>                 <dbl>
## 1 MSFT                   1.69
## 2 GOOG                   1.46
## 3 DELL                  10.2

Which stock has a positively skewed distribution of return?

All three stocks have positively skewed distribution of return however DELL is the greatest with 10.2