speed_resistance_lines.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=365)
end = dt.date.today()

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

df["Middle_Line"] = df["Low"] + (df["High"] - df["Low"]) * 0.667
df["Lower_Line"] = df["Low"] + (df["High"] - df["Low"]) * 0.333

plt.figure(figsize=(14, 7))
plt.plot(df["Adj Close"])
plt.plot(df["Middle_Line"], color="orange", label="Middle Line")
plt.plot(df["Lower_Line"], color="red", label="Lower Line")
plt.legend(loc="best")
plt.title("Stock of Midpoint Method")
plt.xlabel("Date")
plt.ylabel("Price")
plt.show()

def connectpoints():
    x1, x2 = (
        df["Low"].loc["2019-01-01":].idxmin(),
        df["Adj Close"].loc["2019-01-01":].idxmax(),
    )
    y1, y2 = (
        df["Low"].loc["2019-01-01":].min(),
        df["Adj Close"].loc["2019-01-01":].max(),
    )
    plt.plot([x1, x2], [y1, y2], "y-")
    return

def connectpoints2():
    x1, x2 = (
        df["Low"].loc["2019-01-01":].idxmin(),
        df["Adj Close"].loc["2019-01-01":].idxmax(),
    )
    y1, y2 = (
        df["Low"].loc["2019-01-01":].min(),
        df["Middle_Line"].loc["2019-01-01":].max(),
    )
    plt.plot([x1, x2], [y1, y2], "g-")
    return

def connectpoints3():
    x1, x2 = (
        df["Low"].loc["2019-01-01":].idxmin(),
        df["Adj Close"].loc["2019-01-01":].idxmax(),
    )
    y1, y2 = (
        df["Low"].loc["2019-01-01":].min(),
        df["Lower_Line"].loc["2019-01-01":].max(),
    )
    plt.plot([x1, x2], [y1, y2], "r-")
    return

# Connect the points
plt.figure(figsize=(20, 8))
plt.plot(
    df["Low"].loc["2019-01-01":].idxmax(),
    df["Adj Close"].loc["2019-01-01":].max(),
    "yo",
    label="Highest Point",
)
plt.plot(
    df["Low"].loc["2019-01-01":].idxmin(),
    df["Adj Close"].loc["2019-01-01":].min(),
    "bo",
    label="Lowest Point",
)
plt.plot(
    df["Low"].loc["2019-01-01":].idxmax(),
    df["Middle_Line"].loc["2019-01-01":].max(),
    "go",
    label="Middle Line",
)
plt.plot(
    df["Low"].loc["2019-01-01":].idxmax(),
    df["Lower_Line"].loc["2019-01-01":].max(),
    "ro",
    label="Lower Line",
)
plt.plot(df["Adj Close"], color="blue")
connectpoints()
connectpoints2()
connectpoints3()
plt.title("Stock Price")
plt.xlabel("Date")
plt.ylabel("Price")
plt.legend(loc="best")
plt.show()

# ## Candlestick wtih Speed Resistance Lines
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=(14, 7))
ax1 = plt.subplot(2, 1, 1)
candlestick_ohlc(ax1, dfc.values, width=0.5, colorup="g", colordown="r", alpha=1.0)
ax1.plot(
    df["Low"].loc["2019-01-01":].idxmax(),
    df["Adj Close"].loc["2019-01-01":].max(),
    "yo",
    label="Highest Point",
)
ax1.plot(
    df["Low"].loc["2019-01-01":].idxmin(),
    df["Adj Close"].loc["2019-01-01":].min(),
    "bo",
    label="Lowest Point",
)
ax1.plot(
    df["Low"].loc["2019-01-01":].idxmax(),
    df["Middle_Line"].loc["2019-01-01":].max(),
    "go",
    label="Middle Line",
)
ax1.plot(
    df["Low"].loc["2019-01-01":].idxmax(),
    df["Lower_Line"].loc["2019-01-01":].max(),
    "ro",
    label="Lower Line",
)
connectpoints()
connectpoints2()
connectpoints3()
ax1.xaxis_date()
ax1.xaxis.set_major_formatter(mdates.DateFormatter("%d-%m-%Y"))
ax1.grid(True, which="both")
ax1.minorticks_on()
ax1v = ax1.twinx()
colors = dfc.VolumePositive.map({True: "g", False: "r"})
ax1v.bar(dfc.Date, dfc["Volume"], color=colors, 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")
ax1.set_xlabel("Date")
ax1.legend(loc="best")
plt.show()