library(tidyverse)
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library(rvest)
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library(quantmod)
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library(ggplot2)
library(xts)
library(dplyr)
tesla_url <- "https://finviz.com/quote.ashx?t=TSLA"
tesla_page <- read_html(tesla_url)
tesla_data <- tesla_page %>%
html_nodes("table.snapshot-table2") %>%
html_table(fill = TRUE)
tesla_fins <- as.data.frame(tesla_data[[1]])
print(tesla_fins)
## X1 X2 X3 X4 X5 X6
## 1 Index NDX, S&P 500 P/E 128.87 EPS (ttm) 2.04
## 2 Market Cap 844.88B Forward P/E 68.55 EPS next Y 3.83
## 3 Income 7.13B PEG 4.77 EPS next Q 0.53
## 4 Sales 97.69B P/S 8.65 EPS this Y 19.21%
## 5 Book/sh 22.67 P/B 11.59 EPS next Y 32.83%
## 6 Cash/sh 11.52 P/C 22.80 EPS next 5Y 27.04%
## 7 Dividend Est. - P/FCF 235.93 EPS past 5Y -
## 8 Dividend TTM - Quick Ratio 1.61 Sales past 5Y 34.02%
## 9 Dividend Ex-Date - Current Ratio 2.02 EPS Y/Y TTM -52.81%
## 10 Employees 125665 Debt/Eq 0.19 Sales Y/Y TTM 0.95%
## 11 Option/Short Yes / Yes LT Debt/Eq 0.14 EPS Q/Q -71.01%
## 12 Sales Surprise -5.69% EPS Surprise -5.72% Sales Q/Q 2.15%
## 13 SMA20 -17.36% SMA50 -29.34% SMA200 -6.59%
## X7 X8 X9 X10 X11
## 1 Insider Own 12.91% Shs Outstand 3.22B Perf Week
## 2 Insider Trans -0.23% Shs Float 2.80B Perf Month
## 3 Inst Own 48.26% Short Float 2.19% Perf Quarter
## 4 Inst Trans 4.14% Short Ratio 0.71 Perf Half Y
## 5 ROA 6.24% Short Interest 61.50M Perf Year
## 6 ROE 10.52% 52W Range 138.80 - 488.54 Perf YTD
## 7 ROI 8.56% 52W High -46.23% Beta
## 8 Gross Margin 17.86% 52W Low 89.24% ATR (14)
## 9 Oper. Margin 7.94% RSI (14) 26.76 Volatility
## 10 Profit Margin 7.30% Recom 2.58 Target Price
## 11 Payout 0.00% Rel Volume 1.18 Prev Close
## 12 Earnings Jan 29 AMC Avg Volume 86.40M Price
## 13 Trades Volume 102,369,640 Change
## X12
## 1 -10.35%
## 2 -30.54%
## 3 -25.25%
## 4 19.72%
## 5 45.33%
## 6 -34.96%
## 7 2.60
## 8 19.24
## 9 6.73% 5.76%
## 10 378.39
## 11 263.45
## 12 262.67
## 13 -0.30%
getSymbols("TSLA", src = "yahoo", from = "2020-01-01", to = Sys.Date())
## [1] "TSLA"
tesla_prices <- Cl(TSLA)
autoplot(tesla_prices) + ggtitle("Tesla Stock Prices")

tesla_returns <- dailyReturn(TSLA, type = "log")
ggplot(data = as.data.frame(tesla_returns), aes(x = index(TSLA), y = coredata(tesla_returns))) +
geom_line() +
ggtitle("Tesla Daily Log Returns") +
xlab("Date") +
ylab("Log Returns")

pe_ratio <- tesla_fins[tesla_fins$X1 == "P/E", "X2"]
debt_eq_ratio <- tesla_fins[tesla_fins$X1 == "Debt/Eq", "X2"]
roe <- tesla_fins[tesla_fins$X1 == "ROE", "X2"]
print(paste("P/E Ratio:", pe_ratio))
## [1] "P/E Ratio: "
print(paste("Debt/Equity Ratio:", debt_eq_ratio))
## [1] "Debt/Equity Ratio: "
print(paste("Return on Equity:", roe))
## [1] "Return on Equity: "