# Load packages

# Core
library(tidyverse)
library(tidyquant)

Goal

Visualize and examine changes in the underlying trend in the performance of your portfolio in terms of Sharpe Ratio.

Choose your stocks.

from 2012-12-31 to present

1 Import stock prices

symbols <- c("AAPL", "MSFT", "JNJ", "MMM", "AGG")

prices <- tq_get(x    = symbols,
                 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() %>%
    
    set_names(c("asset", "date", "returns"))

3 Assign a weight to each asset

# symbols
symbols <- asset_returns_tbl %>% distinct(asset) %>% pull()
symbols
## [1] "AAPL" "AGG"  "JNJ"  "MMM"  "MSFT"
# 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 AAPL       0.25
## 2 AGG        0.25
## 3 JNJ        0.2 
## 4 MMM        0.2 
## 5 MSFT       0.1

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 = "months", 
                 col_rename = "returns")

portfolio_returns_tbl
## # A tibble: 60 × 2
##    date        returns
##    <date>        <dbl>
##  1 2013-01-31 -0.0112 
##  2 2013-02-28  0.0126 
##  3 2013-03-28  0.0220 
##  4 2013-04-30  0.0229 
##  5 2013-05-31  0.0170 
##  6 2013-06-28 -0.0342 
##  7 2013-07-31  0.0569 
##  8 2013-08-30  0.00369
##  9 2013-09-30  0.00765
## 10 2013-10-31  0.0550 
## # … with 50 more rows

5 Calculate Sharpe Ratio

# Define risk free rate
rfr <- 0.0003

portfolio_SharpeRatio_tbl <- portfolio_returns_tbl %>%
    
    tq_performance(Ra = returns, 
                   performance_fun = SharpeRatio, 
                   Rf = rfr,
                   FUN = "StdDev")

portfolio_SharpeRatio_tbl
## # A tibble: 1 × 1
##   `StdDevSharpe(Rf=0%,p=95%)`
##                         <dbl>
## 1                       0.430

6 Plot

Rolling 24-Month Sharpe Ratio

# Create a custom function to calculate a rolling SR
Calculate_rolling_SharpeRatio <- function(data) {
    
    rolling_SR <- SharpeRatio(R = data, Rf = rfr, FUN = "StdDev")
    
    return(rolling_SR)
}

# Define window
window <- 24

# Transform data: calculate rolling sharpe ratio
rolling_sr_tbl <- portfolio_returns_tbl %>%
    
    tq_mutate(select = returns, 
              mutate_fun = rollapply, 
              width = window,
              FUN = Calculate_rolling_SharpeRatio, 
              col_rename = "rolling_sr") %>%
    
    select(-returns) %>%
    na.omit()

rolling_sr_tbl
## # A tibble: 37 × 2
##    date       rolling_sr
##    <date>          <dbl>
##  1 2014-12-31      0.587
##  2 2015-01-30      0.601
##  3 2015-02-27      0.638
##  4 2015-03-31      0.546
##  5 2015-04-30      0.520
##  6 2015-05-29      0.517
##  7 2015-06-30      0.529
##  8 2015-07-31      0.469
##  9 2015-08-31      0.357
## 10 2015-09-30      0.340
## # … with 27 more rows
rolling_sr_tbl %>%
    
    ggplot(aes(x = date, y = rolling_sr)) +
    geom_line(color = "cornflowerblue") +
    
    #Labeling
    labs(x = NULL, y = "rolling sharpe ratio") +
    
    annotate(geom = "text",
             x = as.Date("2016-06-01"), y = 0.5,
             label = "This portfolio has done quite well since around December 2016.",
             color = "red",
             size = 5)

How has your portfolio performed over time? Provide dates of the structural breaks, if any. The Code Along Assignment 9 had one structural break in November 2016. What do you think the reason is?

Over time my portfolio has done both well and not so well it started out very good and then got worse until very late 2016, I think this could be related to the election and since Trump won and he was lowering the corporate tax rate and doing other things that benefits businesses. In addition to that the risk free rate was going up in 2015 which is not helpful for my my sharpe ratio. Then from the time Trump was elected my portfolio started doing well again.