# Load packages

# Core
library(tidyverse)
library(tidyquant)

Goal

Collect individual returns into a portfolio by assigning a weight to each stock

Choose your stocks.

from 2012-12-31 to 2017-12-31

1 Import stock prices

symbols <- c("AAPL", "BA", "DIS", "NKE")

prices <- tq_get(x = symbols,
get = "stock.prices",
from = "2012-12-31",
to = "2017-12-31")

2 Convert prices to returns (quarterly)

asset_returns_tbl <- prices %>%

group_by(symbol) %>%
tq_transmute(select = adjusted,
mutate_fun = periodReturn,
period = "quarterly",
type = "log") %>%
slice(-1) %>%
ungroup() %>%
set_names(c("asset", "date", "returns"))

3 Assign a weight to each asset (change the weigting scheme)

symbols <- asset_returns_tbl %>% distinct(asset) %>% pull()

w <- c(0.30,
0.25,
0.20,
0.15)

w_tbl <- tibble(symbols, w)

4 Build a portfolio

portfolio_returns_rebalanced_monthly_tbl <- asset_returns_tbl %>%

tq_portfolio(assets_col = asset,
returns_col = returns,
weights = w_tbl,
col_rename = "returns",
rebalance_on = "quarters")

portfolio_returns_rebalanced_monthly_tbl
## # A tibble: 20 × 2
##    date       returns
##    <date>       <dbl>
##  1 2013-03-28  0.0277
##  2 2013-06-28  0.0475
##  3 2013-09-30  0.117 
##  4 2013-12-31  0.138 
##  5 2014-03-31 -0.0306
##  6 2014-06-30  0.0857
##  7 2014-09-30  0.0565
##  8 2014-12-31  0.0607
##  9 2015-03-31  0.103 
## 10 2015-06-30  0.0140
## 11 2015-09-30 -0.0511
## 12 2015-12-31  0.0232
## 13 2016-03-31 -0.0316
## 14 2016-06-30 -0.0485
## 15 2016-09-30  0.0419
## 16 2016-12-30  0.0723
## 17 2017-03-31  0.131 
## 18 2017-06-30  0.0279
## 19 2017-09-29  0.0534
## 20 2017-12-29  0.115
# write_rds(portfolio_returns_rebalanced_monthly_tbl,
#"00_data/Ch03_portfolio_returns_rebalanced_monthly_tbl.rds")

5 Plot: Portfolio Histogram and Density

portfolio_returns_rebalanced_monthly_tbl %>%

ggplot(aes(x = date, y = returns)) +
geom_point(color = "cornflower blue") +

# Formatting
scale_x_date(breaks = scales::breaks_pretty(n = 6)) +

labs(title = "Portfolio Returns Scatter",
y = "quarterly return")

portfolio_returns_rebalanced_monthly_tbl %>%

ggplot(aes(returns)) +
geom_histogram(fill = "cornflower blue",
binwidth = 0.005) +

labs(title = "Portfolio Returns Distribution",
y = "count",
x = "returns")

portfolio_returns_rebalanced_monthly_tbl %>%

ggplot(aes(returns)) +
geom_histogram(fill = "cornflower blue",
binwidth = 0.01) +
geom_density(aes(returns)) +

labs(title = "Portfolio Histogram and Density",
y = "distribution",
x = "quarterly returns")

What return should you expect from the portfolio in a typical quarter?

The data shows that the longer the stocks are held the better the benefit. the stocks are very volatile but if held and sold proprerly they have potential.