# Load packages

# Core
library(tidyverse)
library(tidyquant)

Goal

Visualize expected returns and risk to make it easier to compare the performance of multiple assets and portfolios.

Choose your stocks.

Stocks : “MSFT”, “AAPL”, “F”, “JPM”, “SBUX”

from 2012-12-31 to 2017-12-31

1 Import stock prices

symbols <- c("MSFT", "AAPL", "F", "JPM", "SBUX")

prices <- tq_get(x    = symbols,
                 from = "2012-12-31",
                 to   = "2017-12-31")

2 Convert prices to returns (monthly)

asset_returns_tbl <- prices %>%
    
    group_by(symbol) %>%
    
    tq_transmute(select     = adjusted,
                 mutate_fun = periodReturn,
                period.     = "quarters",
                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" "F"    "JPM"  "MSFT" "SBUX"
# weights
weights <- c(0.3, 0.2, 0.2, 0.15, 0.15)
weights
## [1] 0.30 0.20 0.20 0.15 0.15
w_tbl <- tibble(symbols, weights)

4 Build a portfolio

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

portfolio_returns_tbl
## # A tibble: 60 × 2
##    date       portfolio.returns
##    <date>                 <dbl>
##  1 2013-01-31         -0.000198
##  2 2013-02-28         -0.00101 
##  3 2013-03-28          0.0157  
##  4 2013-04-30          0.0584  
##  5 2013-05-31          0.0743  
##  6 2013-06-28         -0.0273  
##  7 2013-07-31          0.0580  
##  8 2013-08-30         -0.00318 
##  9 2013-09-30          0.0245  
## 10 2013-10-31          0.0460  
## # ℹ 50 more rows

5 Compute Standard Deviation

portfolio_sd_tidyquant_builtin_percent <- portfolio_returns_tbl %>%
    
    tq_performance(Ra = portfolio.returns, 
                   performance_fun = table.Stats) %>%
    
    select(Stdev) %>%
    mutate(tq_sd = round(Stdev, 4))

portfolio_sd_tidyquant_builtin_percent
## # A tibble: 1 × 2
##    Stdev  tq_sd
##    <dbl>  <dbl>
## 1 0.0368 0.0368
# Mean of Portfolio Returns 
portfolio_mean_tidyquant_builtin_percent <- mean(portfolio_returns_tbl$portfolio.returns)

portfolio_mean_tidyquant_builtin_percent
## [1] 0.0141496

6 Plot: Expected Returns versus Risk

# Expected Returns vs Risk
sd_mean_tbl <- asset_returns_tbl %>%
    
    group_by(asset) %>%
    tq_performance(Ra = returns,
                   performance_fun = table.Stats) %>%
    
    select(Mean = ArithmeticMean, Stdev) %>%
    ungroup() %>%
  
    # Add portfolio sd
    add_row(tibble(asset = "Portfolio",
               Mean = portfolio_mean_tidyquant_builtin_percent,
               Stdev = portfolio_sd_tidyquant_builtin_percent$tq_sd))

sd_mean_tbl
## # A tibble: 6 × 3
##   asset       Mean  Stdev
##   <chr>      <dbl>  <dbl>
## 1 AAPL      0.015  0.0695
## 2 F         0.0031 0.0545
## 3 JPM       0.017  0.0556
## 4 MSFT      0.0216 0.0589
## 5 SBUX      0.0139 0.0458
## 6 Portfolio 0.0141 0.0368
sd_mean_tbl %>%
    
    ggplot(aes(x = Stdev, y = Mean)) +
    geom_point() +
    ggrepel::geom_text_repel(aes(label = asset))

24 Month Rolling Volitility

rolling_sd_tbl <- portfolio_returns_tbl %>%
    tq_mutate(select = portfolio.returns,
              mutate_fun = rollapply,
              width = 24,
              FUN = sd,
              col_rename = "rolling_sd") %>%
    
    na.omit() %>%
    select(date, rolling_sd)
rolling_sd_tbl %>%
    
    ggplot(aes(x = date, y = rolling_sd)) +
    geom_line(color = "cornflowerblue") +
    
    # Formatting
    scale_y_continuous(labels = scales::percent_format()) +
    
    # Labeling
    labs(x = NULL,
         y = NULL,
         title = "24 Month Rolling Volitility") +
    theme(plot.title = element_text(hjust = 0.5))

How should you expect your portfolio to perform relative to its assets in the portfolio? Would you invest all your money in any of the individual stocks instead of the portfolio? Discuss both in terms of expected return and risk.

The portfolio offers higher expected returns than any individual stock but comes with more risk (standard deviation). However, it’s still a better choice since it diversifies risk across assets. Investing all your money in one stock could expose you to more volatility and lower returns. In short, the portfolio provides a better balance of risk and return.