# 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("MSFT", "NFLX", "AAPL", "AMD", "DELL")
prices <- tq_get(x = symbols,
                 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
symbols <- asset_returns_tbl %>% distinct (asset) %>% pull()
symbols
## [1] "AAPL" "AMD"  "DELL" "MSFT" "NFLX"
#weights
weight <- c(0.5,0.2,0.2,0.05,0.05)
weight
## [1] 0.50 0.20 0.20 0.05 0.05
w_tbl <- tibble(symbols,weight)
w_tbl
## # A tibble: 5 × 2
##   symbols weight
##   <chr>    <dbl>
## 1 AAPL      0.5 
## 2 AMD       0.2 
## 3 DELL      0.2 
## 4 MSFT      0.05
## 5 NFLX      0.05

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          -0.0374 
##  2 2013-06-28           0.0575 
##  3 2013-09-30           0.0993 
##  4 2013-12-31           0.102  
##  5 2014-03-31          -0.00933
##  6 2014-06-30           0.120  
##  7 2014-09-30           0.00848
##  8 2014-12-31          -0.0146 
##  9 2015-03-31           0.0663 
## 10 2015-06-30           0.0112 
## 11 2015-09-30          -0.123  
## 12 2015-12-31           0.0979 
## 13 2016-03-31           0.0132 
## 14 2016-06-30           0.0464 
## 15 2016-09-30           0.156  
## 16 2016-12-30           0.157  
## 17 2017-03-31           0.202  
## 18 2017-06-30          -0.0338 
## 19 2017-09-29           0.101  
## 20 2017-12-29           0.0258

5 Plot: Portfolio Histogram and Density

portfolio_returns_tbl %>%
    
    ggplot(mapping = aes(x = portfolio.returns)) +
    geom_histogram(fill = "violet", binwidth = 0.01) +
    geom_density() +
    
    #formatting
    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? #This portfolio should return 2-3% in a typical quarter