# 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("WMT", "TGT", "AMZN")

prices <- tq_get(x    = symbols,
                 get  = "stock.prices",
                 from = "2012-12-31",
                 to   = "2022-11-03")

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] "AMZN" "TGT"  "WMT"
# weights
weights <- c(0.25, 0.2, 0.1)
weights
## [1] 0.25 0.20 0.10
w_tbl <- tibble(symbols, weights)
w_tbl
## # A tibble: 3 × 2
##   symbols weights
##   <chr>     <dbl>
## 1 AMZN       0.25
## 2 TGT        0.2 
## 3 WMT        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: 119 × 2
##    date        returns
##    <date>        <dbl>
##  1 2013-01-31  0.0208 
##  2 2013-02-28  0.00943
##  3 2013-03-28  0.0250 
##  4 2013-04-30 -0.00233
##  5 2013-05-31  0.00955
##  6 2013-06-28  0.00544
##  7 2013-07-31  0.0317 
##  8 2013-08-30 -0.0457 
##  9 2013-09-30  0.0301 
## 10 2013-10-31  0.0443 
## # … with 109 more rows

5 Compute 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                       0.212

6 Plot: Rolling Sharpe Ratio

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

#Define window
window <- 24

# Transform date: 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: 96 × 2
##    date       rolling_sr
##    <date>          <dbl>
##  1 2014-12-31      0.197
##  2 2015-01-30      0.203
##  3 2015-02-27      0.225
##  4 2015-03-31      0.200
##  5 2015-04-30      0.230
##  6 2015-05-29      0.220
##  7 2015-06-30      0.217
##  8 2015-07-31      0.240
##  9 2015-08-31      0.272
## 10 2015-09-30      0.235
## # … with 86 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 been shakey since 2016, and plummeted from 2021 and on",
             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?

My portfolio has been very shakey overtime since 2016, constantly having spikes and plummets. However, since 2021 my portfolio has plummeted drastically. There has been 4 structural breaks, 1 in 2017, 1 in 2019, another at the beginning of 2021, and another at the beginning of 2022 before plummeting. The reason why I think these happened and why my portfolio has plummeted is due to the Covid-19 Pandemic. Due to being in a global pandemic we were on lock down for almost 2 years not allowing us to leave our homes in fear of the virus. With corporations not being completely prepared for this a lot of issues with production and sales arose for each company.