# 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("L", "Dell", "HAL", "TSM", "HMC")

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


## 2 Convert prices to returns (quarterly)

``` r
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)

``` r
# symbols
symbols <- asset_returns_tbl %>% distinct(asset) %>% pull()
symbols
## [1] "Dell" "HAL"  "HMC"  "L"    "TSM"
# weights
weights <- c(0.25, 0.25, 0.2, 0.2, 0.1)
weights
## [1] 0.25 0.25 0.20 0.20 0.10
w_tbl <- tibble(symbols, weights)
w_tbl
## # A tibble: 5 × 2
##   symbols weights
##   <chr>     <dbl>
## 1 Dell       0.25
## 2 HAL        0.25
## 3 HMC        0.2 
## 4 L          0.2 
## 5 TSM        0.1


## 4 Build a portfolio

``` r
# ?tq_portfolio

portfolio_returns_tbl <- asset_returns_tbl %>%

tq_portfolio(assets_col = asset,
             returns_col = returns,
             weights = w_tbl, rebalance_on = "quarter")

portfolio_returns_tbl
## # A tibble: 20 × 2
##    date       portfolio.returns
##    <date>                 <dbl>
##  1 2013-03-28           0.0630 
##  2 2013-06-28           0.0126 
##  3 2013-09-30           0.0477 
##  4 2013-12-31           0.0402 
##  5 2014-03-31           0.00235
##  6 2014-06-30           0.0531 
##  7 2014-09-30          -0.0409 
##  8 2014-12-31          -0.139  
##  9 2015-03-31           0.0495 
## 10 2015-06-30          -0.0175 
## 11 2015-09-30          -0.0846 
## 12 2015-12-31           0.0265 
## 13 2016-03-31          -0.00253
## 14 2016-06-30           0.0650 
## 15 2016-09-30           0.0424 
## 16 2016-12-30           0.105  
## 17 2017-03-31           0.0373 
## 18 2017-06-30          -0.0563 
## 19 2017-09-29           0.105  
## 20 2017-12-29           0.0730


## 5 Plot: Portfolio Histogram and Density
Scatterplot

``` r
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 & Density 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 = "distribution",
        title = "Portfolio Histogram & Density")

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

I would say that I can expect a fairly high return within a typical quarter, because of the volatility between the stocks.