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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import datetime as dt\n",
"import yfinance as yf\n",
"\n",
"ticker = 'TSLA'\n",
"period_start = dt.datetime.now() - dt.timedelta(weeks=8)\n",
"try:\n",
" print(f'Fetching price data for {ticker}')\n",
" data = yf.download(\n",
" ticker,\n",
" start=period_start,\n",
" end=dt.datetime.now(),\n",
" interval='1d'\n",
" )\n",
"except Exception as e:\n",
" print(f'Error fetching price data for {ticker}: {str(e)}')\n",
"\n",
"data.head()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# get rid of the redundant ticker column\n",
"df= data.copy()\n",
"df.columns = df.columns.droplevel('Ticker')\n",
"df.head()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"import matplotlib.dates as mdates\n",
"\n",
"def plot_stock_metrics_ax(\n",
" ax,\n",
" dataset,\n",
" df,\n",
" colstoplot):\n",
" print(f'plotting {colstoplot} in {dataset}')\n",
" colorcycle = ['black', 'blue', 'red', 'green', 'orange']\n",
" for i, col in enumerate(colstoplot):\n",
" ax.plot(\n",
" df.index,\n",
" df[col],\n",
" color=colorcycle[i],\n",
" label=col,\n",
" linewidth=2)\n",
" # Format major ticks with year\n",
" # Set major ticks (every Monday with labels)\n",
" ax.xaxis.set_major_locator(mdates.WeekdayLocator(byweekday=mdates.MO))\n",
" ax.xaxis.set_major_formatter(mdates.DateFormatter('%b %d'))\n",
" # Set minor ticks (every day, but without labels)\n",
" ax.xaxis.set_minor_locator(mdates.DayLocator())\n",
" \n",
" ax.set_title(dataset)\n",
" ax.set_xlabel('Date')\n",
" ax.set_ylabel(dataset)\n",
" if len(colstoplot) > 1:\n",
" ax.legend()\n",
" if dataset in ['Index', 'Indices']:\n",
" ax.set_ylim([0, 100])\n",
" # Add a transparent shaded region between y=30 and y=70\n",
" ax.fill_between(df.index, 30, 70, color='gray', alpha=0.3)\n",
" if dataset in ['Price', 'Prices']:\n",
" # Add a transparent shaded region between y=30 and y=70\n",
" ax.fill_between(df.index, df['Low'], df['High'], color='gray', alpha=0.3)\n",
" ax.grid(True, linestyle='--', alpha=0.7)\n",
"\n",
"def plot_stock_metrics(\n",
" df,\n",
" datasets={\n",
" 'Volume': ['Volume'],\n",
" 'Price': ['Close'] # 'High','Low'\n",
" }\n",
" ):\n",
" numax = len(datasets)\n",
" fig, axes = plt.subplots(\n",
" nrows=numax,\n",
" ncols=1,\n",
" figsize=(10, 5*numax))\n",
" for i, ax in enumerate(axes.flat):\n",
" dataset = list(datasets.keys())[i]\n",
" colstoplot = datasets[dataset]\n",
" plot_stock_metrics_ax(\n",
" ax,\n",
" dataset,\n",
" df,\n",
" colstoplot)\n",
" plt.tight_layout()\n",
" plt.show()\n",
"plot_stock_metrics(df)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from ta.volume import volume_weighted_average_price\n",
"from ta.momentum import RSIIndicator, StochasticOscillator\n",
"from ta.trend import MACD \n",
"\n",
"# Price Indicators\n",
"# Volume-Weighted Average Price (VWAP)\n",
"# https://chartschool.stockcharts.com/table-of-contents/technical-indicators-and-overlays/technical-overlays/volume-weighted-average-price-vwap\n",
"df['VWAP'] = volume_weighted_average_price(\n",
" high=df['High'],\n",
" low=df['Low'],\n",
" close=df['Close'],\n",
" volume=df['Volume'],\n",
")\n",
"\n",
"# Indices\n",
"# RSI:\n",
"# https://www.investopedia.com/terms/r/rsi.asp\n",
"df['RSI'] = RSIIndicator(\n",
" df['Close'],\n",
" window=14).rsi()\n",
"# Stochastic Oscillator: \n",
"# https://chartschool.stockcharts.com/table-of-contents/technical-indicators-and-overlays/technical-indicators/stochastic-oscillator-fast-slow-and-full\n",
"df['StochOsc'] = StochasticOscillator(\n",
" df['High'],\n",
" df['Low'],\n",
" df['Close'],\n",
" window=14).stoch()\n",
"\n",
"# Trend signals\n",
"# Moving Average Convergence Divergence (MACD):\n",
"# https://chartschool.stockcharts.com/table-of-contents/technical-indicators-and-overlays/technical-indicators/macd-moving-average-convergence-divergence-oscillator\n",
"macd = MACD(\n",
" df['Close'],\n",
" window_slow=26,\n",
" window_fast=12,\n",
" window_sign=9)\n",
"df['MACD'] = macd.macd()\n",
"df['MACDsig'] = macd.macd_signal()\n",
"df['MACDdif'] = macd.macd_diff()\n",
"\n",
"plot_stock_metrics(\n",
" df,\n",
" datasets={\n",
" 'Volume': ['Volume'],\n",
" 'Prices': ['Close', 'VWAP'], # 'High','Low', \n",
" 'Indices': ['RSI', 'StochOsc'],\n",
" 'Trend': ['MACD', 'MACDsig', 'MACDdif']}\n",
" )"
]
}
],
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