How To Calculate Stocks Support And Resistance Using Clustering

How To Calculate Stocks Support And Resistance Using Clustering

In this notebook, I will show you how to calculate Stocks Support and Resistance using different clustering techniques.

Stock Data - I have stocks data in mongo DB. You can also get this data from Yahoo Finance for free.

MongoDB Python Setup

In [1]:

import pymongo
from pymongo import MongoClient
client_remote = MongoClient('mongodb://localhost:27017')
db_remote = client_remote['stocktdb']
collection_remote = db_remote.stock_data

Get Stock Data From MongoDB

I will do this analysis using last 60 days of Google data.

In [2]:

mobj = collection_remote.find({'ticker':'GOOGL'}).sort([('_id',pymongo.DESCENDING)]).limit(60)

Prepare the Data for Data Analysis

I will be using Pandas and Numpy for the data manipulation. Let us first get the data from Mongo Cursor object to Python list.

In [3]:

prices = []
for doc in mobj:
    prices.append(doc['high'])

Stocks Support and Resistance Using K-Means Clustering

In [4]:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.cluster import AgglomerativeClustering

For K means clustering, we need to get the data in

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