I just finished writing my latest book, Algorithmic Trading with Python. When writing the chapter on performance metrics, I was consistently surprised with the simplicity of the pandas code. If you, as a developer, resolve to only work with datetime-indexed pd.Series objects, the resulting code is really clean and easy. Simulating Data For those unfamiliar […]
Moving from Single-Asset to Multi-Asset Algorithmic Trading
In my latest book, Algorithmic Trading with Python (2020), readers work through the process of developing a trading strategy, simulator, and optimizer against a portfolio of 100 assets. Each asset has 10 years of end-of-day data, creating about 2,500 data points per asset, totaling 250,000 data points. A lot of similar work in this field […]
Alteryx for Good Teams Up with University of Virginia to Support New Class: STAT 4559
I’d like to give a big “thanks” to Alteryx and DataMeaning for hosting Big Data & Self-Service Analytics at the Jack Rose Saloon in Washington D.C. I met a lot of great professionals, and learned a ton about the rise of self-service analytics. Before discussing the partnership, I would like to share some of my […]
The Best Language for XYZ: Answered Empirically
One of the biggest jobs of CTOs and Technical Project Managers is to answer: What is the best software stack for building XYZ? On the web… Internet forums like Quora and Stack Overflow are littered with these kinds of questions. This is understandable, because committing to the wrong software stack can be deadly in the […]
Download Historical Stock Data with R and Python
Update #2: Track this Issue Here Updates to this post are more about which API’s are still supported than how to access them with R, Python, or any other language. Follow the hilarious change history of EOD stock data API’s at my other post: https://chrisconlan.com/download-daily-data-every-sp-500-stock-r/. Update: Using Quandl’s API Because everything I write about breaks, […]
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