# Load Packages
library(tidyverse)
## ── 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()
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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 1.0.11 ──
## ✔ 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 & Convert To Returns
Ra <- c("ATCO-A.ST", "SINCH.ST", "INVE-B.st", "SSAB-B.ST", "SAAB-B.ST", "AXFO.ST", "VOLCAR-B.ST", "NDA-SE.ST", "ERIC-B.ST", "CAST.ST", "ORRON.ST", "AZN.ST") %>%
tq_get(get = "stock.prices",
from = "2025-03-01",
to = Sys.Date()) %>%
group_by(symbol) %>%
tq_transmute(select = adjusted,
mutate_fun = periodReturn,
period = "weekly",
col_rename = "Ra")
Ra
## # A tibble: 144 × 3
## # Groups: symbol [12]
## symbol date Ra
## <chr> <date> <dbl>
## 1 ATCO-A.ST 2025-03-07 0.0116
## 2 ATCO-A.ST 2025-03-14 -0.0338
## 3 ATCO-A.ST 2025-03-21 -0.0564
## 4 ATCO-A.ST 2025-03-28 -0.0191
## 5 ATCO-A.ST 2025-04-04 -0.126
## 6 ATCO-A.ST 2025-04-11 0.0366
## 7 ATCO-A.ST 2025-04-17 0.00539
## 8 ATCO-A.ST 2025-04-25 0.0405
## 9 ATCO-A.ST 2025-05-02 -0.0121
## 10 ATCO-A.ST 2025-05-09 -0.00296
## # ℹ 134 more rows
2 Get Baseline & Convert To Returns
Rb <- "^OMXSPI" %>%
tq_get(get = "stock.prices",
from = "2025-03-01") %>%
tq_transmute(select = adjusted,
mutate_fun = periodReturn,
period = "weekly",
col_rename = "Rb")
Rb
## # A tibble: 12 × 2
## date Rb
## <date> <dbl>
## 1 2025-03-07 -0.0165
## 2 2025-03-14 -0.0140
## 3 2025-03-21 -0.0130
## 4 2025-03-28 -0.0315
## 5 2025-04-04 -0.0908
## 6 2025-04-11 -0.0111
## 7 2025-04-17 0.0339
## 8 2025-04-25 0.0339
## 9 2025-05-02 0.0191
## 10 2025-05-09 -0.00381
## 11 2025-05-16 0.0326
## 12 2025-05-21 -0.00111
3 Join the two tables
RaRb <- left_join(Ra, Rb, by = c("date" = "date"))
RaRb
## # A tibble: 144 × 4
## # Groups: symbol [12]
## symbol date Ra Rb
## <chr> <date> <dbl> <dbl>
## 1 ATCO-A.ST 2025-03-07 0.0116 -0.0165
## 2 ATCO-A.ST 2025-03-14 -0.0338 -0.0140
## 3 ATCO-A.ST 2025-03-21 -0.0564 -0.0130
## 4 ATCO-A.ST 2025-03-28 -0.0191 -0.0315
## 5 ATCO-A.ST 2025-04-04 -0.126 -0.0908
## 6 ATCO-A.ST 2025-04-11 0.0366 -0.0111
## 7 ATCO-A.ST 2025-04-17 0.00539 0.0339
## 8 ATCO-A.ST 2025-04-25 0.0405 0.0339
## 9 ATCO-A.ST 2025-05-02 -0.0121 0.0191
## 10 ATCO-A.ST 2025-05-09 -0.00296 -0.00381
## # ℹ 134 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: 12 × 18
## # Groups: symbol [12]
## symbol ActivePremium Alpha AlphaRobust AnnualizedAlpha Beta `Beta-`
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 ATCO-A.ST -0.0682 0.0001 0.0001 0.0044 1.23 1.40
## 2 SINCH.ST 0.743 0.0209 0.0197 1.93 1.98 2.55
## 3 INVE-B.st -0.0705 -0.0019 -0.004 -0.0941 0.994 1.08
## 4 SSAB-B.ST -0.075 0.0013 0.0012 0.0683 1.37 1.55
## 5 SAAB-B.ST 2.37 0.025 0.025 2.61 0.302 0.627
## 6 AXFO.ST 1.77 0.0189 0.0205 1.64 0.136 -0.281
## 7 VOLCAR-B.ST -0.228 -0.0069 0.0014 -0.304 0.888 1.04
## 8 NDA-SE.ST 0.214 0.0061 0.0127 0.373 1.14 1.09
## 9 ERIC-B.ST 0.170 0.0054 -0.0029 0.326 1.19 1.01
## 10 CAST.ST 0.255 0.002 -0.0025 0.112 0.350 -0.241
## 11 ORRON.ST -0.328 -0.0104 -0.0098 -0.421 0.930 0.0612
## 12 AZN.ST -0.262 -0.0099 -0.0039 -0.405 0.691 0.300
## # 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>
5 Which stock has a positively skewed distribution of returns?
RaRb_capm <- RaRb %>%
tq_performance(Ra = Ra,
Rb = Rb,
performance_fun = VolatilitySkewness)
RaRb_capm
## # A tibble: 12 × 2
## # Groups: symbol [12]
## symbol VolatilitySkewness.1
## <chr> <dbl>
## 1 ATCO-A.ST 1.15
## 2 SINCH.ST 2.22
## 3 INVE-B.st 0.0121
## 4 SSAB-B.ST 1.29
## 5 SAAB-B.ST 24.1
## 6 AXFO.ST 13.7
## 7 VOLCAR-B.ST 1.57
## 8 NDA-SE.ST 2.44
## 9 ERIC-B.ST 2.62
## 10 CAST.ST 1.01
## 11 ORRON.ST 4.79
## 12 AZN.ST 0.618