HW 8

library(tidyquant)

## Registered S3 method overwritten by 'quantmod':
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##   as.zoo.data.frame zoo

## ── Attaching core tidyquant packages ─────────────────────── tidyquant 1.0.11 ──
## ✔ PerformanceAnalytics 2.0.8      ✔ TTR                  0.24.4
## ✔ quantmod             0.4.28     ✔ xts                  0.14.1
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## ✖ PerformanceAnalytics::legend() masks graphics::legend()
## ✖ quantmod::summary()            masks base::summary()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(dplyr)

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## ######################### Warning from 'xts' package ##########################
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## # The dplyr lag() function breaks how base R's lag() function is supposed to  #
## # work, which breaks lag(my_xts). Calls to lag(my_xts) that you type or       #
## # source() into this session won't work correctly.                            #
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## # Use stats::lag() to make sure you're not using dplyr::lag(), or you can add #
## # conflictRules('dplyr', exclude = 'lag') to your .Rprofile to stop           #
## # dplyr from breaking base R's lag() function.                                #
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## # Code in packages is not affected. It's protected by R's namespace mechanism #
## # Set `options(xts.warn_dplyr_breaks_lag = FALSE)` to suppress this warning.  #
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## Attaching package: 'dplyr'
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## The following objects are masked from 'package:xts':
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## The following objects are masked from 'package:stats':
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## The following objects are masked from 'package:base':
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##     intersect, setdiff, setequal, union

library(tidyr)
library(ggplot2)

tickers <- c("AAPL", "AMD", "MU", "NIO", "NVDA", "PRPL", "SNAP", "TSLA")

stock_data <- tq_get(tickers,
                     from = "2016-01-01",
                     to   = "2024-12-31",
                     get  = "stock.prices")

stock_prices <- stock_data %>%
  select(date, symbol, close)

ggplot(stock_prices, aes(x = date, y = close)) +
  geom_line(color = "black") +
  facet_wrap(~ symbol, scales = "free_y") +
  labs(title = "",
       x = "Date",
       y = "Closing prices") +
  theme_minimal(base_size = 14) +
  theme(strip.background = element_rect(fill = "lightgray"))

normalized_prices <- stock_prices %>%
  group_by(symbol) %>%
  mutate(norm_price = close / first(close))

ggplot(normalized_prices, aes(x = date, y = norm_price, color = symbol)) +
  geom_line() +
  labs(title = "Normalized Stock Prices (2016–2024)",
       x = "Date",
       y = "Normalized price (Base = $1)") +
  theme_minimal(base_size = 14) +
  theme(legend.title = element_blank())