# load packages
library(tidyverse)
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library(tidyquant)
## Registered S3 method overwritten by 'quantmod':
## method from
## as.zoo.data.frame zoo
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## ✔ PerformanceAnalytics 2.0.4 ✔ TTR 0.24.4
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## 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("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")
Ra
## # A tibble: 216 × 3
## # Groups: symbol [3]
## symbol date Ra
## <chr> <date> <dbl>
## 1 AAPL 2010-01-29 -0.103
## 2 AAPL 2010-02-26 0.0654
## 3 AAPL 2010-03-31 0.148
## 4 AAPL 2010-04-30 0.111
## 5 AAPL 2010-05-28 -0.0161
## 6 AAPL 2010-06-30 -0.0208
## 7 AAPL 2010-07-30 0.0227
## 8 AAPL 2010-08-31 -0.0550
## 9 AAPL 2010-09-30 0.167
## 10 AAPL 2010-10-29 0.0607
## # ℹ 206 more rows
2 Get baseline and convert to returns
Rb <- "TSLA" %>%
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 = "Rb")
3 join the two tables
RaRb <- left_join(Ra, Rb, by = c("date" = "date"))
RaRb
## # A tibble: 216 × 5
## symbol.x date Ra symbol.y Rb
## <chr> <date> <dbl> <chr> <dbl>
## 1 AAPL 2010-01-29 -0.103 <NA> NA
## 2 AAPL 2010-02-26 0.0654 <NA> NA
## 3 AAPL 2010-03-31 0.148 <NA> NA
## 4 AAPL 2010-04-30 0.111 <NA> NA
## 5 AAPL 2010-05-28 -0.0161 <NA> NA
## 6 AAPL 2010-06-30 -0.0208 TSLA -0.00251
## 7 AAPL 2010-07-30 0.0227 TSLA -0.163
## 8 AAPL 2010-08-31 -0.0550 TSLA -0.0231
## 9 AAPL 2010-09-30 0.167 TSLA 0.0477
## 10 AAPL 2010-10-29 0.0607 TSLA 0.0701
## # ℹ 206 more rows
4 calculate CAPM
RaRb_capm <- RaRb %>%
tq_performance(Ra = Ra,
Rb = Rb,
performance_fun = table.CAPM)
RaRb_capm
## # A tibble: 1 × 12
## ActivePremium Alpha AnnualizedAlpha Beta `Beta-` `Beta+` Correlation
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 NA 0.0263 NA 0.0717 -0.0366 -0.0123 0.0961
## # ℹ 5 more variables: `Correlationp-value` <dbl>, InformationRatio <dbl>,
## # `R-squared` <dbl>, TrackingError <dbl>, TreynorRatio <dbl>