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DrChandrakantDrChandrakant
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Golden Cross Over
Use Scatter addplot Color change 100SMA Line after Cross Over
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‎examples/Indicator_golden_cross_over.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "821ec5c5",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"import mplfinance as mpf\n",
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"import matplotlib.dates as mdates\n",
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"import numpy as np"
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]
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},
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{
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"cell_type": "markdown",
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"id": "b32a433d",
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"metadata": {},
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"source": [
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"# Read in daily data for NSE TCS"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "a410f0a2",
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"metadata": {},
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"outputs": [],
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"source": [
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"infile = 'data/t_data.csv'\n",
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"df = pd.read_csv(infile, index_col=0, parse_dates=True)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "7c9783ef",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Formula For Simple Moving Average\n",
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"# df['SMA21'] = df['Close'].rolling(window=21).mean()\n",
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"# df['SMA100'] = df['Close'].rolling(window=100).mean()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "1e3a3f0a",
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"metadata": {},
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"outputs": [],
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"source": [
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"#Function For Color Coding Golden Crossover\n",
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"def color(goldencrossover):\n",
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" UP = []\n",
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" DOWN = []\n",
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" for i in range(len(goldencrossover)):\n",
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" if goldencrossover['SMA100'][i] < goldencrossover['SMA21'][i]:\n",
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" UP.append(int(goldencrossover['SMA100'][i]))\n",
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" DOWN.append(np.nan)\n",
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" elif goldencrossover['SMA100'][i] > goldencrossover['SMA21'][i]:\n",
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" DOWN.append(int(goldencrossover['SMA100'][i]))\n",
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" UP.append(np.nan)\n",
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" else:\n",
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" UP.append(np.nan)\n",
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" DOWN.append(np.nan)\n",
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" goldencrossover['up'] = UP\n",
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" goldencrossover['down'] = DOWN\n",
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" return goldencrossover"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "d2a8c7ff",
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"metadata": {},
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"outputs": [],
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"source": [
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"def golden_cal(df):\n",
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" goldenSignal = []\n",
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" deathSignal = []\n",
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" position = False\n",
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" for i in range(len(df)):\n",
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" if df['SMA21'][i] > df['SMA100'][i]:\n",
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" if position == False :\n",
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" goldenSignal.append((df['SMA100'][i]-df['SMA100'][i]*0.01))\n",
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" deathSignal.append(np.nan)\n",
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" position = True\n",
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" else:\n",
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" goldenSignal.append(np.nan)\n",
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" deathSignal.append(np.nan)\n",
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" elif df['SMA21'][i] < df['SMA100'][i]:\n",
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" if position == True:\n",
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" goldenSignal.append(np.nan)\n",
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" deathSignal.append((df['SMA100'][i]+df['SMA100'][i]*0.01))\n",
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" position = False\n",
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" else:\n",
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" goldenSignal.append(np.nan)\n",
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" deathSignal.append(np.nan)\n",
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" else:\n",
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" goldenSignal.append(np.nan)\n",
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" deathSignal.append(np.nan)\n",
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" df['GoldenCrossOver'] = goldenSignal\n",
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" df['DeathCrossOver'] = deathSignal"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "3de60151",
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"metadata": {},
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"outputs": [],
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"source": [
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"golden_cal(df)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "d0043a96",
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"metadata": {},
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"outputs": [],
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"source": [
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"#Fuction Color Applied And Df Generated \n",
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"goldencrossover = color(df)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "84416a60",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Data Extracted And New Variable Applied\n",
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"up_sma100 = goldencrossover[['up']]\n",
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"down_sma100 = goldencrossover[['down']]\n",
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"up_sma21 = goldencrossover[['SMA21']]\n",
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"dco = goldencrossover[['GoldenCrossOver']]\n",
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"gco = goldencrossover[['DeathCrossOver']]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "3cc8fd1f",
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"metadata": {},
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"outputs": [],
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"source": [
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"ic = [\n",
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" #Golden Crossover\n",
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" mpf.make_addplot(up_sma100,color = 'green',panel=0,),\n",
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" mpf.make_addplot(down_sma100,color = '#FF8849',panel=0,),\n",
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" mpf.make_addplot(up_sma21,color = '#0496ff',panel=0,linestyle='dashdot'),\n",
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" mpf.make_addplot(gco,type='scatter',markersize=200,marker='v',color='red',panel=0),\n",
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" mpf.make_addplot(dco,type='scatter',markersize=200,marker='^',color='green',panel=0),\n",
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"]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "236c94af",
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"metadata": {},
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"outputs": [],
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"source": [
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"mpf.plot(\n",
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" df,\n",
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" volume=True,\n",
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" type=\"candle\", \n",
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" style=\"yahoo\",\n",
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" addplot=ic,\n",
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" figscale=1.2,\n",
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" #fill_between = [fill_between_up,fill_between_down],\n",
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" figsize=(36,16,)\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "c2401f98",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "c77f6ac7",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.7"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

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