moving_average_ribbon.py

# Import dependencies
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import yfinance as yf
import datetime as dt
yf.pdr_override()

# input
symbol = "AAPL"
start = dt.date.today() - dt.timedelta(days=180)
end = dt.date.today()

# Read data
df = yf.download(symbol, start, end)

df["MA10"] = df["Adj Close"].rolling(10).mean()
df["MA20"] = df["Adj Close"].rolling(20).mean()
df["MA30"] = df["Adj Close"].rolling(30).mean()
df["MA40"] = df["Adj Close"].rolling(40).mean()
df["MA50"] = df["Adj Close"].rolling(50).mean()
df["MA60"] = df["Adj Close"].rolling(60).mean()

import talib as ta

df["SMA5"] = ta.SMA(df["Adj Close"], timeperiod=5)
df["SMA15"] = ta.SMA(df["Adj Close"], timeperiod=15)
df["SMA25"] = ta.SMA(df["Adj Close"], timeperiod=25)
df["SMA35"] = ta.SMA(df["Adj Close"], timeperiod=35)
df["SMA45"] = ta.SMA(df["Adj Close"], timeperiod=45)

df["EMA5"] = ta.EMA(df["Adj Close"], timeperiod=5)
df["EMA15"] = ta.EMA(df["Adj Close"], timeperiod=15)
df["EMA25"] = ta.EMA(df["Adj Close"], timeperiod=25)
df["EMA35"] = ta.EMA(df["Adj Close"], timeperiod=35)
df["EMA45"] = ta.EMA(df["Adj Close"], timeperiod=45)

# Line Chart
df[["Adj Close", "MA10", "MA20", "MA30", "MA40", "MA50", "MA60"]].plot(figsize=(16, 8))
plt.title("Stock " + symbol + " Closing Price of MA")
plt.xlabel("Date")
plt.ylabel("Price")
plt.legend(loc="Best")
plt.show()

df[["Adj Close", "SMA5", "SMA15", "SMA25", "SMA35", "SMA45"]].plot(figsize=(16, 8))
plt.title("Stock " + symbol + " Closing Price of SMA")
plt.xlabel("Date")
plt.ylabel("Price")
plt.legend(loc="Best")
plt.show()

df[["Adj Close", "EMA5", "EMA15", "EMA25", "EMA35", "EMA45"]].plot(figsize=(16, 8))
plt.title("Stock " + symbol + " Closing Price of EMA")
plt.xlabel("Date")
plt.ylabel("Price")
plt.show()

from matplotlib import dates as mdates

dfc = df.copy()
dfc["VolumePositive"] = dfc["Open"] < dfc["Adj Close"]
# dfc = dfc.dropna()
dfc = dfc.reset_index()
dfc["Date"] = mdates.date2num(dfc["Date"].tolist())
from mplfinance.original_flavor import candlestick_ohlc

fig = plt.figure(figsize=(16, 8))
ax1 = plt.subplot(111)
candlestick_ohlc(ax1, dfc.values, width=0.5, colorup="g", colordown="r", alpha=1.0)
ax1.plot(dfc.Date, dfc[["EMA5", "EMA15", "EMA25", "EMA35", "EMA45"]])
ax1.xaxis_date()
ax1.xaxis.set_major_formatter(mdates.DateFormatter("%d-%m-%Y"))
ax1.grid(True, which="both")
ax1.minorticks_on()
ax1v = ax1.twinx()
ax1v.fill_between(dfc.Date, 0, dfc.Volume[0:], facecolor="#0079a3", alpha=0.4)
ax1v.axes.yaxis.set_ticklabels([])
ax1v.set_ylim(0, 3 * df.Volume.max())
ax1.set_title("Stock " + symbol + " Closing Price")
ax1.set_ylabel("Price")
plt.show()