# 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("AMZN", "MSFT", "TSLA")

prices <- tq_get (x     = symbols,
                  get   = "stock.price",
                 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)

weights <- c(0.3, 0.3, 0.4)
weights
## [1] 0.3 0.3 0.4
w_tbl <- tibble(symbols, weights)
w_tbl
## # A tibble: 3 × 2
##   symbols weights
##   <chr>     <dbl>
## 1 AMZN        0.3
## 2 MSFT        0.3
## 3 TSLA        0.4

4 Build a 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: 20 × 2
##    date       portfolio.returns
##    <date>                 <dbl>
##  1 2013-03-28          0.0861  
##  2 2013-06-28          0.488   
##  3 2013-09-30          0.262   
##  4 2013-12-31          0.00993 
##  5 2014-03-31          0.109   
##  6 2014-06-30          0.0532  
##  7 2014-09-30          0.0358  
##  8 2014-12-31         -0.0439  
##  9 2015-03-31         -0.0490  
## 10 2015-06-30          0.213   
## 11 2015-09-30          0.0214  
## 12 2015-12-31          0.139   
## 13 2016-03-31         -0.0556  
## 14 2016-06-30          0.00358 
## 15 2016-09-30          0.0686  
## 16 2016-12-30          0.0102  
## 17 2017-03-31          0.175   
## 18 2017-06-30          0.147   
## 19 2017-09-29         -0.000558
## 20 2017-12-29          0.0653

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(label = scales::percent_format()) +

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

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

Returns are relatively flat but do have an uptick around the 5% to 8% range so I would expect this to be the range of a typical quarterly return.