# 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("NVDA", "AAPL", "NFLX", "MSFT", "TSLA")
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
symbol <- asset_returns_tbl %>% distinct(asset) %>% pull()
symbols
## [1] "NVDA" "AAPL" "NFLX" "MSFT" "TSLA"
# Weights
weights <- c(0.3, 0.3, 0.25, 0.25, 0.2)
weights
## [1] 0.30 0.30 0.25 0.25 0.20
w_tbl <- tibble(symbols, weights)
w_tbl
## # A tibble: 5 × 2
##   symbols weights
##   <chr>     <dbl>
## 1 NVDA       0.3 
## 2 AAPL       0.3 
## 3 NFLX       0.25
## 4 MSFT       0.25
## 5 TSLA       0.2

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 = "months")

portfolio_returns_tbl
## # A tibble: 20 × 2
##    date       portfolio.returns
##    <date>                 <dbl>
##  1 2013-03-28          0.182   
##  2 2013-06-28          0.282   
##  3 2013-09-30          0.295   
##  4 2013-12-31          0.0855  
##  5 2014-03-31          0.102   
##  6 2014-06-30          0.161   
##  7 2014-09-30          0.0617  
##  8 2014-12-31         -0.0300  
##  9 2015-03-31          0.0365  
## 10 2015-06-30          0.199   
## 11 2015-09-30          0.0359  
## 12 2015-12-31          0.152   
## 13 2016-03-31          0.000393
## 14 2016-06-30         -0.0145  
## 15 2016-09-30          0.207   
## 16 2016-12-30          0.229   
## 17 2017-03-31          0.186   
## 18 2017-06-30          0.155   
## 19 2017-09-29          0.143   
## 20 2017-12-29          0.0849

5 Plot: Portfolio Histogram and Density

portfolio_returns_tbl %>% 
    
    ggplot(mapping = aes(x = portfolio.returns)) +
    geom_histogram(fill = "cornflowerblue", binwidth = 0.015) + 
    geom_density() + 
    
    # Formatting 
    scale_x_continuous(labels = scales::percent_format()) + 

    labs(x = "returns",
         y = "distribution", 
         title = "Portfolio Returns Distribution")

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

Based off of the chart it seems I should expect a typical quarter return of 15%. The bar is the highest around there, and we see the line in peaked out around 15% as well.