# 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("NFLX", "AAPL", "JPM", "NVDA", "WMT")

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()
symbols
## [1] "AAPL" "JPM"  "NFLX" "NVDA" "WMT"
weights <- c(0.3, 0.15, 0.2, 0.2, 0.15)
weights
## [1] 0.30 0.15 0.20 0.20 0.15
w_tbl <- tibble(symbols, weights)
w_tbl
## # A tibble: 5 × 2
##   symbols weights
##   <chr>     <dbl>
## 1 AAPL       0.3 
## 2 JPM        0.15
## 3 NFLX       0.2 
## 4 NVDA       0.2 
## 5 WMT        0.15

4 Build a portfolio

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

portfolio_returns_tbl
## # A tibble: 20 × 2
##    date       portfolio.returns
##    <date>                 <dbl>
##  1 2013-03-28           0.127  
##  2 2013-06-28           0.0269 
##  3 2013-09-30           0.153  
##  4 2013-12-31           0.122  
##  5 2014-03-31           0.00594
##  6 2014-06-30           0.103  
##  7 2014-09-30           0.0419 
##  8 2014-12-31           0.0155 
##  9 2015-03-31           0.0767 
## 10 2015-06-30           0.0842 
## 11 2015-09-30          -0.00385
## 12 2015-12-31           0.0724 
## 13 2016-03-31           0.00833
## 14 2016-06-30           0.0153 
## 15 2016-09-30           0.153  
## 16 2016-12-30           0.178  
## 17 2017-03-31           0.117  
## 18 2017-06-30           0.0761 
## 19 2017-09-29           0.116  
## 20 2017-12-29           0.110

5 Plot: Portfolio Histogram and Density

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

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

I expect between a 7.5% and 12.5% return from my portfolio in a typical quarter