Contributed so kindly by Joe Wojniak It may seem obvious, but financial research requires data — and a lot of it. If financial research isn’t your day job, it can be surprisingly difficult to come by. Here are some suggestions for acquiring data to use in your financial research project. Data Sources Every project has […]
70+ Code Profiles of Common Python Algorithms
I just released my latest book, Fast Python: Master the Basics to Write Faster Code. In it, you will find a blend of academic discussion of algorithms and a pragmatic optimizations of computation time. Whether or not you are interested in buying the book, I wanted to share some free resources from the accompanying GitHub […]
Calculating Financial Performance Metrics in Pandas
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 […]
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