# 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("TSLA", "AMZN", "GOOG", "JNJ", "MSFT", "AAPL")
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"))

asset_returns_tbl    
## # A tibble: 120 × 3
##    asset date       returns
##    <chr> <date>       <dbl>
##  1 AAPL  2013-03-28 -0.178 
##  2 AAPL  2013-06-28 -0.103 
##  3 AAPL  2013-09-30  0.191 
##  4 AAPL  2013-12-31  0.169 
##  5 AAPL  2014-03-31 -0.0383
##  6 AAPL  2014-06-30  0.198 
##  7 AAPL  2014-09-30  0.0858
##  8 AAPL  2014-12-31  0.0956
##  9 AAPL  2015-03-31  0.124 
## 10 AAPL  2015-06-30  0.0122
## # … with 110 more rows

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

#Symbols
symbols <- asset_returns_tbl %>%
    distinct(asset) %>%
    pull()
symbols
## [1] "AAPL" "AMZN" "GOOG" "JNJ"  "MSFT" "TSLA"
#Weights
weights <- c(0.5, 0.1, 0.1, 0.1, 0.1, 0.1)
weights
## [1] 0.5 0.1 0.1 0.1 0.1 0.1
w_tbl <- tibble(symbols, weights)

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: 20 × 2
##    date       portfolio.returns
##    <date>                 <dbl>
##  1 2013-03-28          -0.0367 
##  2 2013-06-28           0.0923 
##  3 2013-09-30           0.164  
##  4 2013-12-31           0.127  
##  5 2014-03-31           0.0136 
##  6 2014-06-30           0.122  
##  7 2014-09-30           0.0574 
##  8 2014-12-31           0.0256 
##  9 2015-03-31           0.0519 
## 10 2015-06-30           0.0582 
## 11 2015-09-30          -0.0403 
## 12 2015-12-31           0.0588 
## 13 2016-03-31           0.00711
## 14 2016-06-30          -0.0539 
## 15 2016-09-30           0.120  
## 16 2016-12-30           0.0140 
## 17 2017-03-31           0.175  
## 18 2017-06-30           0.0592 
## 19 2017-09-29           0.0419 
## 20 2017-12-29           0.0899

5 Plot: Portfolio Histogram and Density

Portfolio Histogram and Density

portfolio_returns_tbl %>%
    
    ggplot(mapping = aes(portfolio.returns)) +
    geom_histogram(fill = "cornflowerblue", binwidth = 0.02) +
    geom_density() +
    
    #Formatting
        scale_x_continuous(labels = scales::percent_format()) +

    
    labs(x = "Returns",
         y = "Density",
         title = "Portfolio Histogram & Density")

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

In a typical quarter return I can expect between 5%-6% returns.