# 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

symbol <- c("AMZN", "BIG", "TSLA", "WM", "PLUG")

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

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

symbols <- asset_returns_tbl %>% distinct(symbol) %>% pull()
symbols
## [1] "AMZN" "BIG"  "PLUG" "TSLA" "WM"
weight <- c(0.2,0.2,0.2,0.2,0.2)
weight
## [1] 0.2 0.2 0.2 0.2 0.2
w_tbl <- tibble(symbols, weight)

4 Build a portfolio

portfolio_returns_tbl <- asset_returns_tbl %>%
    tq_portfolio(assets_col = symbol,
                 returns_col = quarterly.returns,
                 weights = w_tbl,
                 rebalance_on = "quarter")

5 Compute Standard Deviation

portfolio_sd_tq_builtin_percent <- portfolio_returns_tbl %>%
    tq_performance(Ra = portfolio.returns,
                   performance_fun = table.Stats) %>%
    select(Stdev) %>%
    mutate(tq_sd = round(Stdev, 4))
portfolio_mean_sd_tq_builtin_percent <- mean(portfolio_returns_tbl$portfolio.returns)
sd_mean_tbl <- asset_returns_tbl %>%
    group_by(symbol) %>%
    tq_performance(Ra = quarterly.returns,
                   performance_fun = table.Stats) %>%
    select(Mean = ArithmeticMean, Stdev) %>%
    ungroup() %>% 
        add_row(tibble(symbol = "Portfolio",
                       Mean = portfolio_mean_sd_tq_builtin_percent,
                       Stdev = portfolio_sd_tq_builtin_percent$tq_sd))
sd_mean_tbl <- asset_returns_tbl %>%
    group_by(symbol) %>%
    tq_performance(Ra = quarterly.returns,
                   performance_fun = table.Stats) %>%
    select(Mean = ArithmeticMean, Stdev) %>%
    ungroup() %>% 
        add_row(tibble(symbol = "Portfolio",
                       Mean = portfolio_mean_sd_tq_builtin_percent,
                       Stdev = portfolio_sd_tq_builtin_percent$tq_sd))

6 Plot: Expected Returns versus Risk

sd_mean_tbl <- asset_returns_tbl %>%
    group_by(symbol) %>%
    tq_performance(Ra = quarterly.returns,
                   performance_fun = table.Stats) %>%
    select(Mean = ArithmeticMean, Stdev) %>%
    ungroup() %>% 
        add_row(tibble(symbol = "Portfolio",
                       Mean = portfolio_mean_sd_tq_builtin_percent,
                       Stdev = portfolio_sd_tq_builtin_percent$tq_sd))
sd_mean_tbl %>%
    ggplot(aes(x = Stdev, y = Mean, color = symbol)) +
    geom_point() +
    ggrepel::geom_text_repel(aes(label = symbol))

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.
If I was to invest in this portfolio I would most likely put higher weights in PLUG and TSLA as they outperform the portfolio. I would also stay invested in the other stocks because of the lowered risk that is offered by these stocks. The return of some stocks (TSLA,Plug) is higher but the risk also tends to follow and be higher than the portfolios.