# Load packages

# Core
library(tidyverse)
library(tidyquant)

Goal

Visualize and compare skewness of your portfolio and its assets.

Choose your stocks.

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

1 Import stock prices

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

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 = "monthly", 
               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] "BAC"  "GS"   "JPM"  "MS"   "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 BAC         0.2
## 2 GS          0.2
## 3 JPM         0.2
## 4 MS          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",
               col_rename = "returns")

portfolio_returns_tbl
## # A tibble: 60 × 2
##    date        returns
##    <date>        <dbl>
##  1 2013-01-31  0.0750 
##  2 2013-02-28  0.0147 
##  3 2013-03-28  0.00152
##  4 2013-04-30  0.0245 
##  5 2013-05-31  0.105  
##  6 2013-06-28 -0.0500 
##  7 2013-07-31  0.0814 
##  8 2013-08-30 -0.0468 
##  9 2013-09-30  0.0273 
## 10 2013-10-31  0.0150 
## # ℹ 50 more rows

5 Compute Skewness

portfolio_skew_tidyquant_builtin_percent <- portfolio_returns_tbl %>%
  
  tq_performance(Ra = returns, 
                 performance_fun = table.Stats) %>%
  
  select(Skewness)
  

portfolio_skew_tidyquant_builtin_percent
## # A tibble: 1 × 1
##   Skewness
##      <dbl>
## 1   0.0445

6 Plot: Skewness Comparison

Is any asset in your portfolio more likely to return extreme positive returns than your portfolio collectively? Discuss in terms of skewness. You may also refer to the distribution of returns you plotted in Code along 4.

My portfolio has a skewness of 0.0445, which means it has a slightly positive skew. This suggests that the portfolio has a small tendency to produce extreme positive returns rather than extreme negative returns. The skewness is very close to zero, so the returns are relatively balanced. Some individual stocks may have higher positive skewness than the overall portfolio. This shows how diversification can help balance the returns of individual assets and reduce the impact of extreme movements in one stock.