Finance/technical_indicators/relative_volatility_index.py at main · catinthecode/Finance · GitHub

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# 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 * 2)
end = dt.date.today()

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

n = 14  # Number of period
change = df["Adj Close"].diff(1)
df["Gain"] = change.mask(change < 0, 0)
df["Loss"] = abs(change.mask(change > 0, 0))
df["AVG_Gain"] = df.Gain.rolling(n).std()
df["AVG_Loss"] = df.Loss.rolling(n).std()
df["RS"] = df["AVG_Gain"] / df["AVG_Loss"]
df["RVI"] = 100 - (100 / (1 + df["RS"]))

from mplfinance.original_flavor import candlestick_ohlc

fig = plt.figure(figsize=(14, 7))
ax1 = plt.subplot(2, 1, 1)
ax1.plot(df["Adj Close"])
ax1.set_title("Stock " + symbol + " Closing Price")
ax1.set_ylabel("Price")

ax2 = plt.subplot(2, 1, 2)
ax2.plot(df["RVI"], label="Relative Volatility Index")
ax2.text(s="Overbought", x=df.RVI.index[30], y=60, fontsize=14)
ax2.text(s="Oversold", x=df.RVI.index[30], y=40, fontsize=14)
ax2.axhline(y=60, color="red")
ax2.axhline(y=40, color="red")
ax2.grid()
ax2.set_ylabel("Volume")
ax2.set_xlabel("Date")
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=(14, 7))
ax1 = plt.subplot(2, 1, 1)
candlestick_ohlc(ax1, dfc.values, width=0.5, colorup="g", colordown="r", alpha=1.0)
ax1.set_title("Stock " + symbol + " Closing Price")
ax1.set_ylabel("Price")
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")

ax2 = plt.subplot(2, 1, 2)
ax2.plot(df["RVI"], label="Relative Volatility Index")
ax2.text(s="Overbought", x=df.RVI.index[30], y=60, fontsize=14)
ax2.text(s="Oversold", x=df.RVI.index[30], y=40, fontsize=14)
ax2.axhline(y=60, color="red")
ax2.axhline(y=40, color="red")
ax2.grid()
ax2.set_ylabel("Volume")
ax2.set_xlabel("Date")
ax2.legend(loc="best")
plt.show()