How to acquire free historical Tick and Bar data for algo trading and backtesting in 2020! [Stocks, Forex, and Crypto Currency]

jack · Nov 18, 2019

I noticed that many guides or lists of tick data sources were out of date, broken, or otherwise not working, so I decided to make an updated list with modern sources for use as a resource with the algo trading community. I will also keep this up to date as new sources appear and old sources break.

Below are the guides for downloading tick or bar level data for various markets which can be used for backtesting and analysis.

Note: Typical format for tick and bar data is in CVS files. You might need to adjust or re-arrange said files as needed to fit into your desired analytics and/or backtesting program.

Table of Contents:

Stocks (this post)
Forex (Darwinex, Pepperstone / TrueFX, Dukascopy)
Crypto [part 1] (Binance)
Crypto [part 2] (BitMEX)

--------------------------

Stocks [Daily Bars]

Yahoo Finance - US and International stock exchanges - On a stock by stock basis, you can download decades of historical daily bar data by doing the following steps:

Go to https://finance.yahoo.com
In the search field, type in your desired symbol or company name and select the appropriate result
Click the 'Historical Data' tab
Set the date range to 'MAX'
Hit the 'Apply' button
Click the 'Download Data' link just below the 'Apply' button
Enjoy your daily bar data

Google Finance - Rest in peace..

Google nuked their finance site back to the stone age many years ago so this service is pretty useless now (Honestly Google, what were you thinking? Google Finance was awesome back in 2012 and prior.) Google also used to have an API but that too got turned off. I included an entry for Google here because many people will be searching around the net and find references to using Google Finance's API but be unsure why it's not working as expected.

Cautious mention - QuantConnect - tick and minute bar data on stocks and forex. I'm currently reviewing QuantConnect as a potential source. They do offer a lot of free data but since their ecosystem was built around offering up crowd sourced strategies to prop firms I'm hesitant to recommend them until I've wrapped my head around their offering and can say I trust their platform.

jack · Nov 18, 2019

Forex [Tick Data] (Since tick data is available from multiple sources without cost, I will only mention bar data at the end.*)

Darwinex -

Darwinex is easy but you'll need to have a live account. Anyone can signup for an account (live) and head over to this page here once logged in: Historical Tick Data Download. From there, just click the "Request FTP Access" button to have your FTP login details generated for you. Darwinex provides tick level data all major and minor currency pairs, as well as index and commodity CFDs, with most of them going back to mid-late 2017. You don't need to deposit to have a live account at Darwinex, you just need to have a verified account with them, so there's little downside to enabling access to this high quality source of tick data. (As a side benefit, you can also get access to historical price data of their Darwin Exchange, so you can model investing in other traders and model their strategy returns, which is pretty cool.)

Pepperstone / Integral / TrueFX -

Pepperstone relies on price feeds and liquidity very similar to Integral's offering, so similar that for a while Pepperstone used to publish Integral's data on their own FTP for easy customer access. Unfortunately, they stopped offering this FTP access some time ago (thus why most online tutorials referencing them are out of date) and the source of data that Pepperstone currently recommends is Integral's TrueFX data service offering. A free account at TrueFX.com will get you access to tick data on most major and minor currency pairs from the past year only (Currently only 2019 YTD is available for free.) I encouraged Pepperstone to bring back their historical data access to regain access to years prior to 2019 and if they ever open back up then I'll update this spot here with access info.

Dukascopy -

This source is a staple in the forex tick data world. Dukascopy Bank has been around for a long time and has offered historical tick data on their products with dates going back into the mid-early 2000's. Like the other sources, you'll need signup to their site, but they do not require a live account to access data. To access, all you need to do is visit the Dukascopy Bank Historical Data Feed page, and use the historical download tool provided (with registering or logging in when prompted before it will let you download.) The download tool makes it easy to select what data you want, but note that all non-forex listings here (like stocks) are CFDs on Duka's platform, NOT the underlying stock data that trades on a stock exchange. (If you're interested in Dukascopy but need to trade under Euro zone regulations, you can find their Europe subsidiary here with different trading conditions.)

*Regarding Bar type data - Downscale it from the tick data above as needed. However, if you really only want daily bar data, you can find it from Oanda's website, or others pretty easily.

jack · Nov 21, 2019

Crypto

Binance - One of the top exchanges by volume with easily one of the largest collections of crypto pairs to trade. Binance is very API friendly, and is structured in a way that even trading smaller amounts can be done efficiently. Recently, Binance opened up trading on leveraged products (spot, and futures,) as well as started offering options.

You're going to need an account, which is free to get started, so if you don't already have an account you can register here.

From your account page, then you'll need to generate API keys to access the API and pull down data:

On the following page, find the create field and enter any nick name you want:

Hit the create button. You'll likely have to authenticate or verify via email that you want to generate an API key, but once done you will see the generated API key itself, and the API secret code as well. Save these somewhere secure and safe.

Next up we need to setup Python on our system to do the leg work of downloading data. Head over to https://python.org and grab the latest version of Python 3 for your OS. Install said package.

Once installed we will add the python-binance and pandas packages to access the Binance API from within Python and to save the resulting data to a CSV file.

To do this, open a Open a CMD (Command Line) window as Administrator on Windows (or the appropriate terminal in Linux / OSX..) and run the following commands:

Code:

pip install python-binance

Code:

pip install pandas

Once that's done, copy the code below to a new python file and save it somewhere handy:

Python:

import pandas as pd
from binance.client import Client
import datetime

# YOUR API KEYS HERE
api_key = ""    #Enter your own API-key here
api_secret = "" #Enter your own API-secret here

bclient = Client(api_key=api_key, api_secret=api_secret)

start_date = datetime.datetime.strptime('1 Jan 2016', '%d %b %Y')
today = datetime.datetime.today()

def binanceBarExtractor(symbol):
    print('working...')
    filename = '{}_MinuteBars.csv'.format(symbol)

    klines = bclient.get_historical_klines(symbol, Client.KLINE_INTERVAL_1MINUTE, start_date.strftime("%d %b %Y %H:%M:%S"), today.strftime("%d %b %Y %H:%M:%S"), 1000)
    data = pd.DataFrame(klines, columns = ['timestamp', 'open', 'high', 'low', 'close', 'volume', 'close_time', 'quote_av', 'trades', 'tb_base_av', 'tb_quote_av', 'ignore' ])
    data['timestamp'] = pd.to_datetime(data['timestamp'], unit='ms')

    data.set_index('timestamp', inplace=True)
    data.to_csv(filename)
    print('finished!')


if __name__ == '__main__':
    # Obviously replace BTCUSDT with whichever symbol you want from binance
    # Wherever you've saved this code is the same directory you will find the resulting CSV file
    binanceBarExtractor('BTCUSDT')

Where you see the api_key, and api_secret variables near the beginning of the file, you will add the generated API key and API secret from your binance account BETWEEN the quotes.

Finally, at the bottom on the last line, change the 'BTCUSDT' to whichever crypto pair you desire to extract from Binance... browse around Binance's exchange to see all your options.

Run the code... the script will write a CSV file to the same directory you saved the code in, and these files will be ~100-200mb in size depending on how far back their history goes. As for timing, for BTCUSDT it takes my connection about 10-12 minutes to grab minute bar data going all the way back to ~2017.. so don't hold your breath. This is because Binance rate limits their historical data requests.

Done! Enjoy a few million lines of 1m data per symbol on any crypto currency pair that binance has listed! Enjoy!:

jack · Nov 24, 2019

Crypto [part 2]

[EDIT: Bitmex removed as they are no longer a supported option.]

ciskeceli · Feb 27, 2020

hi, thanks for the great article.

well, i' ve downloaded phyton and opened cmd, typed in "pip install bitmex" and got the error below.

'pip' is not recognized as an internal or external command,
operable program or batch file.

can you help me?

jack · Feb 27, 2020

ciskeceli said:
hi, thanks for the great article.

well, i' ve downloaded phyton and opened cmd, typed in "pip install bitmex" and got the error below.

'pip' is not recognized as an internal or external command,
operable program or batch file.

can you help me?

Sounds like you might have unchecked adding python to your system's PATH during the installation. Try uninstalling Python, then reinstall making sure to "install for all users" and "add to PATH" when given the options.

redstripe2 · Apr 20, 2020

Hi, thanks for the help!

I see BTCUSD listed on Binance but it's only letting me pull BTCUSDT, it says that BTCUSD is an invalid symbol. Any idea how to fix this issue? Thanks!

j1v32r · Jun 17, 2020

Hi Jack,

thank you very much for the information, really useful!

I have a question: do you know how I can extract the full symbols list from Yahoo finance in order to avoid downloading stock info one by one? I would like to backtest the European market and I didn't find a way to obtain the ticker list from every european market.

Thanks in advance and good luck with the trading!

LYERO · Aug 7, 2020

Thanks you man for the information!

LYERO · Aug 8, 2020

is there a way to get binance futures data ?

MettoCHief · Apr 30, 2021

Hey Jack, is it possible to change the tick data into daily data? Thank you!

jack · May 17, 2021

MettoCHief said:
Hey Jack, is it possible to change the tick data into daily data? Thank you!

Yes, it's possible to do this via Pandas (that the script already uses.) After the line that sets the timestamp as your index you'd then use a resample function.

Read up on how to use panda's resample function in the official pandas docs. It includes examples. Link here:

pandas.DataFrame.resample — pandas 2.2.3 documentation

pandas.pydata.org

Good luck.

MettoCHief · May 17, 2021

jack said:
Yes, it's possible to do this via Pandas (that the script already uses.) After the line that sets the timestamp as your index you'd then use a resample function.

Read up on how to use panda's resample function in the official pandas docs. It includes examples. Link here:

pandas.DataFrame.resample — pandas 2.2.3 documentation

pandas.pydata.org

Good luck.

Thanks! Going try it out! Do you know if and how it is possible to get historical data of orderbooks? Like bid and ask prices

BR

AlexeyYa · May 18, 2021

Jack, thanks a lot. Everything worked out. Very useful!!!

MettoCHief · Jun 7, 2021

jack said:
Yes, it's possible to do this via Pandas (that the script already uses.) After the line that sets the timestamp as your index you'd then use a resample function.

Read up on how to use panda's resample function in the official pandas docs. It includes examples. Link here:

pandas.DataFrame.resample — pandas 2.2.3 documentation

pandas.pydata.org

Good luck.

Hey Jack, I was not able to get it done. Maybe u could help me out one more time.
Thanks!
BR

jack · Jun 7, 2021

MettoCHief said:
Hey Jack, I was not able to get it done. Maybe u could help me out one more time.
Thanks!
BR

Where are you getting stuck? It's a well documented process .. like an extra line or two. What did you try?

MettoCHief · Jun 17, 2021

jack said:
Where are you getting stuck? It's a well documented process .. like an extra line or two. What did you try?

Sorry I'm not so familiar with scripting in Python...newbie on that. Tried data.resample('1140ms').sum()
getting error that Im using a Range Index instead of datetimeindex

jack · Jun 18, 2021

Are you calling resample after the 'set index' line?

jack · Jun 18, 2021

MettoCHief said:
Sorry I'm not so familiar with scripting in Python...newbie on that. Tried data.resample('1140ms').sum()
getting error that Im using a Range Index instead of datetimeindex

I believe in teaching, and encourage people to figure it out themselves after pointing them in the right direction.. but that said, this one turns out to be more than just an extra line given you gotta declare a conversion key for the aggregate. So harder than the 'one liner' I suggested earlier.

Here's an edited script that will work for converting to "daily" bars, what you first asked.

Python:

import pandas as pd
from binance.client import Client
import datetime
import os

# YOUR API KEYS HERE
api_key = ""    #Enter your own API-key here
api_secret = "" #Enter your own API-secret here

bclient = Client(api_key=api_key, api_secret=api_secret)

start_date = datetime.datetime.strptime('1 Mar 2021', '%d %b %Y')
today = datetime.datetime.today()

conversion = {'open' : 'first', 'high' : 'max', 'low' : 'min', 'close' : 'last', 'volume' : 'sum'}

def binanceBarExtractor(symbol):
    print('working on: {}'.format(symbol))
    filename = '{}_MinuteBars.csv'.format(symbol)

    klines = bclient.get_historical_klines(symbol, Client.KLINE_INTERVAL_1MINUTE, start_date.strftime("%d %b %Y %H:%M:%S"), today.strftime("%d %b %Y %H:%M:%S"), 1000)
    data = pd.DataFrame(klines, columns = ['timestamp', 'open', 'high', 'low', 'close', 'volume', 'close_time', 'quote_av', 'trades', 'tb_base_av', 'tb_quote_av', 'ignore' ])
    data['timestamp'] = pd.to_datetime(data['timestamp'], unit='ms')
    data['volume'] = pd.to_numeric(data['volume'], errors='coerce')
    
    data.set_index('timestamp', inplace=True)

    data = data.resample('D').agg(conversion)
    
    data.to_csv(filename)
    print('finished!')


if __name__ == '__main__':
    for sym in ['BTCUSDT',]:
        binanceBarExtractor(sym)

MettoCHief · Jun 19, 2021

jack said:

I believe in teaching, and encourage people to figure it out themselves after pointing them in the right direction.. but that said, this one turns out to be more than just an extra line given you gotta declare a conversion key for the aggregate. So harder than the 'one liner' I suggested earlier.

Here's an edited script that will work for converting to "daily" bars, what you first asked.

Python:

import pandas as pd
from binance.client import Client
import datetime
import os

# YOUR API KEYS HERE
api_key = ""    #Enter your own API-key here
api_secret = "" #Enter your own API-secret here

bclient = Client(api_key=api_key, api_secret=api_secret)

start_date = datetime.datetime.strptime('1 Mar 2021', '%d %b %Y')
today = datetime.datetime.today()

conversion = {'open' : 'first', 'high' : 'max', 'low' : 'min', 'close' : 'last', 'volume' : 'sum'}

def binanceBarExtractor(symbol):
    print('working on: {}'.format(symbol))
    filename = '{}_MinuteBars.csv'.format(symbol)

    klines = bclient.get_historical_klines(symbol, Client.KLINE_INTERVAL_1MINUTE, start_date.strftime("%d %b %Y %H:%M:%S"), today.strftime("%d %b %Y %H:%M:%S"), 1000)
    data = pd.DataFrame(klines, columns = ['timestamp', 'open', 'high', 'low', 'close', 'volume', 'close_time', 'quote_av', 'trades', 'tb_base_av', 'tb_quote_av', 'ignore' ])
    data['timestamp'] = pd.to_datetime(data['timestamp'], unit='ms')
    data['volume'] = pd.to_numeric(data['volume'], errors='coerce')
   
    data.set_index('timestamp', inplace=True)

    data = data.resample('D').agg(conversion)
   
    data.to_csv(filename)
    print('finished!')


if __name__ == '__main__':
    for sym in ['BTCUSDT',]:
        binanceBarExtractor(sym)

Wow amazing! Thank you for your help! I appreciate it!
Best Regards!

How to acquire free historical Tick and Bar data for algo trading and backtesting in 2020! [Stocks, Forex, and Crypto Currency]

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