One of my passions is analyzing stock and option data. Although I love trading, I find looking for an edge in the data to be the most fun part of the game (besides making money, of course). Since I learned about using API’s in the Data Analysis class in which I’m currently enrolled, I decided to flex my new skills and connect to a broker’s API so I can start collecting more data for my first trading algorithm.
For anyone interested using the Ally Financial API to collect and analyze data, I have put together a brief cheat sheet to help you get started making the API calls and outputting the data to a Pandas’ dataframe.
It contains the following examples:
- Time and Sales for Stocks
- Options Market Depth
- Options Extended Quote
Click here to check out my Ally Financial API Cheat Sheet on my github. It is written for Python 3
#!/usr/bin/env python
# coding: utf-8
# # Ally Financial API Cheat Sheet
# * Refer to the documentation for additional routes:
# * https://www.ally.com/api/invest/documentation/getting-started/
import requests
from requests_oauthlib import OAuth1
from config import (api_key, secret, oath_token, oath_secret)
import pandas as pd
import sqlalchemy
import numpy as np
import sqlite3
from sqlite3 import Error
import matplotlib.pyplot as plt
import datetime as dt
#authentication
auth = OAuth1(api_key, secret, oath_token, oath_secret)
# # Time and Sales for Stocks Example
# * documentation: https://www.ally.com/api/invest/documentation/market-timesales-get/
# * base url: https://api.tradeking.com/
# * route: v1/market/timesales.json
# * query: ?symbols=MSFT&startdate=2019-05-03&interval=1min
#url
url = 'https://api.tradeking.com/v1/market/timesales.json?symbols=MSFT&startdate=2019-05-03&interval=1min'
#api request
response = requests.get(url, auth = auth).json()
#send to data frame and format data types
df = pd.DataFrame(response["response"]["quotes"]["quote"])
df = df.sort_values(['datetime'], ascending = False)
df['date'] = pd.to_datetime(df['date'])
df['datetime'] = pd.to_datetime(df['datetime'], utc=False).dt.tz_convert('US/Central')
df['hi'] = df["hi"].astype(float)
df['incr_vol'] = df["incr_vl"].astype(float)
df['last'] = df["last"].astype(float)
df['lo'] = df["lo"].astype(float)
df['opn'] = df["opn"].astype(float)
df['vl'] = df['vl'].astype(float)
df.head()
#resample the time value to be greater than 1 min as needed. Example: 30 min resample for last price
df.set_index(df['datetime'], inplace = True)
df.head()
df_resample30 = df.resample(rule = '30min', label = 'right').last()
df_resample30.head()
# # Options Search Example
# * Provides market depth for options
# * Documentation: https://www.ally.com/api/invest/documentation/market-options-search-get-post/
# * base url: https://api.tradeking.com/
# * route: v1/market/timesales.json
# * query: ?symbol=MSFT&query=xyear-eq%3A2019%20AND%20xmonth-eq%3A06%20AND%20strikeprice-eq%3A140
#
#
# * Query breakdown:
# * exipiration year equals 2019:
# * xyear-eq%3A 2019
#
# * and:
# * %20AND%20
#
# * expiration month equals 06:
# * xmonth-eq%3A 06
#
# * and strike price equals 140:
# * %20AND%20 strikeprice -eq%3A 140
#
#
# * Operators:
# * lt : less than
# * gt : greater than
# * gte : greater than or equal to
# * lte : less than or equal to
# * eq : equal to
url = 'https://api.tradeking.com/v1/market/options/search.json?symbol=MSFT&query=xyear-eq%3A2019%20AND%20xmonth-eq%3A06%20AND%20strikeprice-eq%3A140'
response = requests.get(url, auth = auth).json()
df = pd.DataFrame(response["response"]["quotes"]["quote"])
df
# # Extended Quote Example (Option)
# * Works for stocks too
# * Documentation: https://www.ally.com/api/invest/documentation/market-ext-quotes-get-post/
# * base url: https://api.tradeking.com/
# * route: v1/market/ext/quotes.json
# * query: ?symbols=MSFT190607C00140000
#
# * Option Symbol naming convention:
# * Underlying symbol - MSFT
# * 2 digit expiration year - 19
# * 2 digit expiration month - 06
# * 2 digit expiration day - 07
# * "C" for Call or "P" for Put - C
# * 8 digit strike price - 00140000
#
#
# * Specify desired fields in the query as needed using fids:
# * i.e. fids=ask,bid,vol
url = 'https://api.tradeking.com/v1/market/ext/quotes.json?symbols=MSFT190607C00140000'
response = requests.get(url, auth = auth).json()
df = pd.DataFrame(response["response"]["quotes"]["quote"], index = [0])
df
Eric Kleppen Wins 