# Load packages

# Core
library(tidyverse)
library(tidyquant)

Goal

Collect individual returns into a portfolio by assigning a weight to each stock

five stocks: “SPY”, “EFA”, “IJS”, “EEM”, “AGG”

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

1 Import stock prices

symbol <- c("SPY", "EFA", "IJS", "EEM", "AGG")

prices <- tq_get(x = symbol,
                 get = "stock.prices",
                 from = "2012-12-31",
                 to = "2017-12-31")

2 Convert prices to returns

asset_returns_tbl <- prices %>%
    
    group_by(symbol) %>%
    
    tq_transmute(select = adjusted,
                 mutate_fun = periodReturn,
                 period = "monthly",
                 type = "log") %>%
    slice(-1) %>%
    
    ungroup()

3 Assign a weight to each asset

symbols <- asset_returns_tbl %>% distinct(symbol) %>% pull()
symbols
## [1] "AGG" "EEM" "EFA" "IJS" "SPY"
weight <- c(0.25,0.25,0.2,0.2,0.1)
weight
## [1] 0.25 0.25 0.20 0.20 0.10
w_tbl <- tibble(symbols, weight)

4 Build a portfolio

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

##5 Plot

Scatterplot

portfolio_returns_tbl %>%
    
    ggplot(mapping = aes(x = date, y = portfolio.returns)) +
    geom_point(color = "cornflowerblue") +
    
    # formatting
    scale_x_date(date_breaks = "1 year", 
                 date_labels = "%Y") +
    
    #labeling
    labs(y     = "monthly returns",
         x     = NULL,
         title = "Portfolio Returns Scatter")

histogram

portfolio_returns_tbl %>%
    
    ggplot(mapping = aes(x = portfolio.returns)) +
    geom_histogram(fill = "cornflowerblue", binwidth = 0.005) +
    
    labs(x = "returns",
         title = "portfolio Returns Distribution")

Histogram & Destiny Plot

portfolio_returns_tbl %>%
    
    ggplot(mapping = aes(x = portfolio.returns)) +
    geom_histogram(fill = "cornflowerblue", binwidth = 0.01) +
    geom_density() +
    
    # Formatting
    scale_x_continuous(labels = scales::percent_format()) +
    
    labs(x = "returns",
         y = "disribution",
         title = "portfolio Returns Distribution")