# 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("AMZN", "TSLA", "MSFT")
prices <- tq_get(x    = symbols, 
                 get = "stock.prices",
                 from = "2012-12-31",
                 to   = "2022-12-31")

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 <- asset_returns_tbl %>% distinct(asset) %>% pull()
symbols
## [1] "AMZN" "MSFT" "TSLA"
#Weights
weights <- c(0.3, 0.3, 0.4)
weights
## [1] 0.3 0.3 0.4
w_tbl <- tibble(symbols, weights)
w_tbl
## # A tibble: 3 × 2
##   symbols weights
##   <chr>     <dbl>
## 1 AMZN        0.3
## 2 MSFT        0.3
## 3 TSLA        0.4

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: 120 × 2
##    date       returns
##    <date>       <dbl>
##  1 2013-01-31  0.0660
##  2 2013-02-28 -0.0248
##  3 2013-03-28  0.0448
##  4 2013-04-30  0.171 
##  5 2013-05-31  0.273 
##  6 2013-06-28  0.0437
##  7 2013-07-31  0.0895
##  8 2013-08-30  0.0876
##  9 2013-09-30  0.0848
## 10 2013-10-31 -0.0117
## # ℹ 110 more rows

5 Compute Sharpe Ratio

rfr <- .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                       0.260

6 Plot: Rolling Sharpe Ratio

# Create 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 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: 97 × 2
##    date       rolling_sr
##    <date>          <dbl>
##  1 2014-12-31      0.504
##  2 2015-01-30      0.444
##  3 2015-02-27      0.486
##  4 2015-03-31      0.421
##  5 2015-04-30      0.420
##  6 2015-05-29      0.379
##  7 2015-06-30      0.360
##  8 2015-07-31      0.355
##  9 2015-08-31      0.262
## 10 2015-09-30      0.216
## # ℹ 87 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("2016-6-01"), y = .7, label = "Very Volatile Portfolio.", color = "purple", size = 4)

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 not performed very good. Especially at the beginning of 2022. It looks like there was a break in April or May of 2018, and another in February of 2022 which could be the result of Covid starting to slow down. Especially for Microsoft and Amazon Covid was huge for them and as it slowed down so did they.