# load packages
library(tidyverse)
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## ✔ lubridate 1.9.4 ✔ tidyr 1.3.1
## ✔ purrr 1.1.0
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library(tidyquant)
## Registered S3 method overwritten by 'quantmod':
## method from
## as.zoo.data.frame zoo
## ── Attaching core tidyquant packages ─────────────────────── tidyquant 1.0.11 ──
## ✔ PerformanceAnalytics 2.0.8 ✔ TTR 0.24.4
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## ✖ 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("stock.prices",
from = "10-01-01",
to = "2015-12-31") %>%
group_by("symbol") %>%
tq_transmute(select = adjusted,
mutate_fun = periodReturn,
period = "monthly",
col_rename = "Ra")
Ra
## # A tibble: 421 × 3
## # Groups: "symbol" [1]
## `"symbol"` date Ra
## <chr> <date> <dbl>
## 1 symbol 1980-12-31 0.187
## 2 symbol 1981-01-30 -0.172
## 3 symbol 1981-02-27 -0.0619
## 4 symbol 1981-03-31 -0.0755
## 5 symbol 1981-04-30 0.158
## 6 symbol 1981-05-29 0.167
## 7 symbol 1981-06-30 -0.215
## 8 symbol 1981-07-31 -0.0385
## 9 symbol 1981-08-31 -0.195
## 10 symbol 1981-09-30 -0.242
## # ℹ 411 more rows
2 Get basline and convert to returns
Rb <- c("XLK") %>%
tq_get("stock.prices",
from = "10-01-01",
to = "2015-12-31") %>%
group_by("symbol") %>%
tq_transmute(select = adjusted,
mutate_fun = periodReturn,
period = "monthly",
col_rename = "Rb")
Rb
## # A tibble: 205 × 3
## # Groups: "symbol" [1]
## `"symbol"` date Rb
## <chr> <date> <dbl>
## 1 symbol 1998-12-31 0.0180
## 2 symbol 1999-01-29 0.159
## 3 symbol 1999-02-26 -0.0992
## 4 symbol 1999-03-31 0.0743
## 5 symbol 1999-04-30 0.00598
## 6 symbol 1999-05-28 0.00340
## 7 symbol 1999-06-30 0.0960
## 8 symbol 1999-07-30 -0.0116
## 9 symbol 1999-08-31 0.0351
## 10 symbol 1999-09-30 -0.00415
## # ℹ 195 more rows
3 Join the two tables
RaRb <- left_join(Ra, Rb, by = c("date" = "date"))
RaRb
## # A tibble: 421 × 5
## `"symbol".x` date Ra `"symbol".y` Rb
## <chr> <date> <dbl> <chr> <dbl>
## 1 symbol 1980-12-31 0.187 <NA> NA
## 2 symbol 1981-01-30 -0.172 <NA> NA
## 3 symbol 1981-02-27 -0.0619 <NA> NA
## 4 symbol 1981-03-31 -0.0755 <NA> NA
## 5 symbol 1981-04-30 0.158 <NA> NA
## 6 symbol 1981-05-29 0.167 <NA> NA
## 7 symbol 1981-06-30 -0.215 <NA> NA
## 8 symbol 1981-07-31 -0.0385 <NA> NA
## 9 symbol 1981-08-31 -0.195 <NA> NA
## 10 symbol 1981-09-30 -0.242 <NA> NA
## # ℹ 411 more rows
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: 1 × 17
## ActivePremium Alpha AlphaRobust AnnualizedAlpha Beta `Beta-` `Beta-Robust`
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 0.408 0.0473 0.0363 0.742 0.910 1.21 1.03
## # ℹ 10 more variables: `Beta+` <dbl>, `Beta+Robust` <dbl>, BetaRobust <dbl>,
## # Correlation <dbl>, `Correlationp-value` <dbl>, InformationRatio <dbl>,
## # `R-squared` <dbl>, `R-squaredRobust` <dbl>, TrackingError <dbl>,
## # TreynorRatio <dbl>