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(2022, 10, 4, 12, 7, 6, 855970)
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 xle xlb xlf xli xlk xly xlc xlv xlu xlre xlp
name Energy Select Sector SPDR Fund Materials Select Sector SPDR Fund Financial Select Sector SPDR Fund Industrial Select Sector SPDR Fund Technology Select Sector SPDR Fund Consumer Discretionary Select Sector SPDR Fund Communication Services Select Sector SPDR Fund Health Care Select Sector SPDR Fund Utilities Select Sector SPDR Fund The Real Estate Select Sector SPDR Fund Consumer Staples Select Sector SPDR Fund
previous_close 76.09 70.22 31.18 85.34 122.46 142.59 49.23 123.60 67.43 36.68 67.88
current_price 78.88 72.50 32.17 87.74 125.90 146.41 50.50 125.81 68.39 37.17 68.57
percent change 3.67 3.25 3.16 2.81 2.81 2.68 2.58 1.78 1.42 1.34 1.02
today_volume 18.49 6.19 25.62 5.18 4.76 4.31 4.71 7.34 9.49 4.58 7.07
previous_volume 34.76 9.93 47.08 8.61 8.66 8.65 5.78 9.33 25.45 11.62 12.70
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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