# 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.

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

1 Import stock prices

symbols <- c ("MSFT", "NVDA", "JPM", "MS", "GS")

prices <- tq_get(x = symbols,
                 get = "stockprices",
                 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 = "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] "GS"   "JPM"  "MS"   "MSFT" "NVDA"
# weights
weights <- c(0.2, 0.2, 0.2, 0.2, 0.2)
weights
## [1] 0.2 0.2 0.2 0.2 0.2
w_tbl <- tibble(symbols, weights)
w_tbl
## # A tibble: 5 × 2
##   symbols weights
##   <chr>     <dbl>
## 1 GS          0.2
## 2 JPM         0.2
## 3 MS          0.2
## 4 MSFT        0.2
## 5 NVDA        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 = "quarters")

portfolio_returns_tbl
## # A tibble: 20 × 2
##    date       portfolio.returns
##    <date>                 <dbl>
##  1 2013-03-28            0.0999
##  2 2013-06-28            0.108 
##  3 2013-09-30            0.0424
##  4 2013-12-31            0.112 
##  5 2014-03-31            0.0358
##  6 2014-06-30            0.0165
##  7 2014-09-30            0.0656
##  8 2014-12-31            0.0633
##  9 2015-03-31           -0.0427
## 10 2015-06-30            0.0735
## 11 2015-09-30           -0.0534
## 12 2015-12-31            0.134 
## 13 2016-03-31           -0.0773
## 14 2016-06-30            0.0517
## 15 2016-09-30            0.177 
## 16 2016-12-30            0.295 
## 17 2017-03-31            0.0177
## 18 2017-06-30            0.0787
## 19 2017-09-29            0.0998
## 20 2017-12-29            0.101

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 0.0826 0.0826
# Mean of portfolio returns
portfolio_mean_tidyquant_builtin_percent <- mean(portfolio_returns_tbl$portfolio.returns)

portfolio_mean_tidyquant_builtin_percent
## [1] 0.06992572

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 GS        0.0379 0.120 
## 2 JPM       0.0511 0.0843
## 3 MS        0.0544 0.122 
## 4 MSFT      0.0648 0.0855
## 5 NVDA      0.141  0.134 
## 6 Portfolio 0.0699 0.0826
sd_mean_tbl %>%
  
  ggplot(aes(x = Stdev, y = Mean, color = asset)) +
  geom_point() +
  ggrepel::geom_text_repel(aes(label = asset))

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.

My portfolio has an expected quarterly return of 6.99% and a risk (standard deviation) of 8.26%. Compared to the individual stocks, my portfolio has a good balance of return and risk. NVDA has the highest expected return at 14.1%, but it also has the highest risk at 13.4%. My portfolio has lower risk than every individual stock because it is diversified across five companies. I would not invest all my money in just one stock. Even though NVDA has a higher expected return, it also comes with more risk. I would rather invest in the portfolio because spreading my money across different stocks reduces risk while still providing a solid expected return.