# Load packages

# Core
library(tidyverse)
library(tidyquant)

Goal

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

five stocks: “IVV”, “VOO”, “VTSAX”, “VSMPX”

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

1 Import stock prices

symbols <- c("IVV", "VOO", "VTSAX", "VSMPX", "FBGRX")

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

2 Convert prices to returns

asset_returns_tbl <- prices %>%
    
    group_by(symbol) %>%
    
    tq_transmute(select = adjusted,
                 mutate_fun = periodReturn,
                 period = "monthly", 
                 type = "log") %>%
    
    slice(-1) %>%
    
    ungroup() %>%

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

3 Assign a weight to each asset

#symbols
symbols <- asset_returns_tbl %>% distinct(asset) %>% pull() 
symbols
## [1] "FBGRX" "IVV"   "VOO"   "VSMPX" "VTSAX"
#weights
weights <- c(0.25, 0.25, 0.2, 0.2, 0.1)
weights
## [1] 0.25 0.25 0.20 0.20 0.10
w_tbl <- tibble(symbols, weights)
w_tbl
## # A tibble: 5 × 2
##   symbols weights
##   <chr>     <dbl>
## 1 FBGRX      0.25
## 2 IVV        0.25
## 3 VOO        0.2 
## 4 VSMPX      0.2 
## 5 VTSAX      0.1

4 Build a portfolio

# ?tq_portfolio

portfolio_returns_tbl <- asset_returns_tbl %>%
    
    tq_portfolio(assets_col = asset,
                 returns_col = returns, 
                 weights = w_tbl,
                 rebalance_on = "quarters")

portfolio_returns_tbl
## # A tibble: 60 × 2
##    date       portfolio.returns
##    <date>                 <dbl>
##  1 2013-01-31            0.0388
##  2 2013-02-28            0.0104
##  3 2013-03-28            0.0280
##  4 2013-04-30            0.0143
##  5 2013-05-31            0.0242
##  6 2013-06-28           -0.0133
##  7 2013-07-31            0.0460
##  8 2013-08-30           -0.0198
##  9 2013-09-30            0.0303
## 10 2013-10-31            0.0347
## # ℹ 50 more rows

5 Plot

Histogram

portfolio_returns_tbl %>%
    
    ggplot(mapping = aes(x = portfolio.returns)) +
    geom_histogram(fill = "goldenrod4", binwidth = 0.01, color = "tomato4") +
    
    labs(x = "returns",
         title = "Portfolio Returns Distribution")

Histogram and Density

portfolio_returns_tbl %>%
    
    ggplot(mapping = aes(x = portfolio.returns)) +
    geom_histogram(fill = "goldenrod4", binwidth = 0.01,) +
    geom_density() +
    
    # Formatting
    scale_x_continuous(labels = scales::percent_format()) + 
    
    labs(x = "returns",
         y = "distribution",
         title = "Histogram & Density")

What Return Should You Exoect in a Typical Quarter

You should expect about a 2% return from this portfolio in a typical quarter.