TheDailyCalls.com Notebook¶

SPY Sectors Charts¶

This notebook is updated three times daily. Cheers.

In [1]:
import pandas as pd
import numpy as np
import yfinance as yf
import mplfinance as mpf
from datetime import datetime
from wallstreet import get_moving_averages, get_sp500_sector_components, get_daily_returns
In [2]:
n=50
In [3]:
# Parameters
n = 50
In [4]:
n=n*-1
sectors = get_sp500_sector_components()
In [5]:
datetime.now()
Out[5]:
datetime.datetime(2024, 9, 6, 15, 7, 5, 839648)
In [6]:
s = [i['symbol'] for i in sectors]
daily_returns = get_daily_returns(s)
In [7]:
pd.options.display.float_format = '{:.2f}'.format
daily_returns.sort_values(by='percent change',ascending=False).set_index('ticker').transpose()
Out[7]:
ticker xlre xlp xlv xlu xli xle xlb xlf xlc xly xlk
name
previous_close 43.63 83.16 154.48 76.64 127.18 87.10 91.04 44.95 85.56 187.13 209.35
current_price 43.63 82.98 153.99 75.94 125.91 86.02 89.89 44.31 83.76 182.40 203.99
percent change 0.00 -0.22 -0.32 -0.91 -1.00 -1.24 -1.26 -1.43 -2.10 -2.53 -2.56
today_volume 6.65 11.87 7.57 9.63 9.47 17.76 5.22 50.71 4.37 3.84 6.10
previous_volume 5.54 12.78 7.25 7.77 8.04 12.50 3.79 39.52 3.56 3.63 4.44
In [8]:
pd.options.display.float_format = '{:.2f}%'.format
for sector in sectors:
    df = yf.download(sector['symbol'])
    mav = get_moving_averages(sector['symbol'])
    mas = [mpf.make_addplot(mav[n:]['SMA8'], color='green', linestyle='dashed', width=1),
           mpf.make_addplot(mav[n:]['SMA21'], color='blue', linestyle='dashed', width=1),
           mpf.make_addplot(mav[n:]['SMA30'], color='orange', linestyle='dashed', width=1),
           mpf.make_addplot(mav[n:]['SMA200'], color='red', linestyle='dashed', width=1),
           ]
    current_price = mav[-1:]['Close'][0]
    current_sector = daily_returns[daily_returns['ticker']==sector['symbol']]
    current_percent_change = current_sector['percent change'].iloc[0]
#     print(current_percent_change)
    mpf.plot(df[n:],type='candle',style='yahoo',title='\n{} - {:.2f} ({:.2f}%)\n'.format(sector['name'], current_price, current_percent_change),addplot=mas,volume=True)

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