Tradologics & The Future of Trading
An introduction to the Trading revolution: How to deploy a trading strategy with Tradologics - using Tradelets, Tradehooks, Pipelines, and the Universal API.
Algo Trading in the Cloud
What if there was a way for traders to focus only on the trading logic – without worrying about stuff like broker connectivity, data management, or infrastructure? Now there is...
It's time for a modern, standardized trading interface, suitable for the web-age
In this post, I share my vision for an Open Trading standard for communicating with online brokers using modern technologies.
Is this the world's best (and laziest) trading strategy?
Can you regularly beat the market, cut volatility by 40% and max drawdown by 70% with only four trades a year, or is this too good to be true?
Downloading option chain and fundamental from Yahoo! Finance with Python
The recently updated yfinance added a lot more capabilities to this already popular library. You can now download fundamental data, including company financials, balance sheet and cashflow, as well as option chain data. Here's how...
The Future of QTPyLib
I released the first version of QTPyLib, my Python library for algo traders, in 2016. If you had told me then that I would still be working on it three years later, I probably wouldn't have believed you. But guess what? That's precisely where I'm doing :)
Reliably download historical market data from Yahoo! Finance with Python
Ever since Yahoo! Finance decommissioned their historical data API, Python developers looked for a reliable workaround. As a result, my library, yfinance, gained momentum and was downloaded over 100,000 acording to PyPi.
Machine Learning for Trading (with Python): Webinar Recording, Slides and Notebook (IV)
I had a great time presenting yesterday's webinar about Live Trading with Python... This was the fourth and the final part of my webinar series on Treading With Python for futures.io's members.
Fast Data Store for Pandas Time-Series Data using PyStore
As algorithmic traders, we need a lot of data to test and optimize our strategy ideas. Over time, the amount of data adds up and the search for a reliable, efficient and easy-to-use storage solution begins.
Volatility Index for Crypto Currency
The CBOE Volatility Index (Ticker: VIX) is a well known measure of the stock market's expectation of volatility implied by S&P 500 index options.
My Bitcoin Scalping Strategy
Bitcoin has seen a tremendous growth in both price an trading volume this year. Noticing that, I’ve backtested a scalping strategy I normally use to trade interest rate futures on Bitcoin, and... it worked great with very minor modifications.
Live Trading with Python: Webinar Recording, Slides and Notebook (III)
I had a great time presenting yesterday's webinar about Live Trading with Python... This was the third out of a four-part webinar series on Treading With Python for futures.io's members.
Backtesting Trading Strategies with (pure) Python: Webinar Recording, Slides and Notebook (II)
On wednsday, I gave the second out of a four-part webinar series on Treading With Python for futures.io's members. Here's the webinar's recording, slides, and Jupyter notebook.
You can still download Yahoo! Finance data using Pandas Datareader using this quick hack
As you may have heard, Yahoo! finance has decommissioned its historical data API, causing many programs that relied on it to stop working. However...
Live Plotting in Python using Matplotlib and ZeroMQ
While working on a new dashboard for QTPyLib I needed to get a Matplotlib plot to refresh and update based on data coming from a ZeroMQ stream.
Prototyping Trading Strategies with Python - Slides, Notebook and Webinar Recording (I)
Last week I had my first out of four webinars with futures.io about Prototyping Trading Strategies with Python and people seem to enjoy it :) I thought I'd share the webinar's slides, notebook and webinar recording here.
Analyzing Twitter Sentiment with Python
I've recently launched a Twitter bot that posts a daily sentiment analysis for the S&P500 Stock Market Index, and thought I'd share the gist of the code here.
I was thinking going back to blogging for a while, but...