# 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

# Choose stocks

symbols <- c("GM", "PLUG", "AAPL")

# Using tq_get() ----
prices <- tq_get(x = symbols,
                 get = "stock.prices",
                 from = "2002-12-31",
                 to = "2024-12-31")

2 Convert prices to returns (quarterly)

asset_returns_tbl <- prices %>%

    # Calculate monthly returns
    group_by(symbol) %>%
    tq_transmute(select = adjusted,
                 mutate_fun = periodReturn,
                 period = "quarterly",
                 type = "log") %>%
    slice(-1) %>%
    ungroup() %>%

    # remane
    set_names(c("asset", "date", "returns"))

# period_returns = c("yearly", "quarterly", "monthly", "weekly")

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

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

weights <- c(0.4, 0.35, 0.25)

w_tbl <- tibble(symbols, weights)

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: 88 × 2
##    date       returns
##    <date>       <dbl>
##  1 2003-03-31  0.0245
##  2 2003-06-30  0.0994
##  3 2003-09-30  0.0569
##  4 2003-12-31  0.0988
##  5 2004-03-31  0.110 
##  6 2004-06-30  0.0662
##  7 2004-09-30  0.0313
##  8 2004-12-31  0.191 
##  9 2005-03-31  0.122 
## 10 2005-06-30 -0.0403
## # ℹ 78 more rows
# 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 = "monthly 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 = "Quarterly 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? Quarterly returns can range from -37% to 42%. But, I expect the returns to be from -13% to 18%.