This is a summary of links featured on Quantocracy on Saturday, 05/20/2017. To see our most recent links, visit the Quant Mashup. Read on readers!
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How to Scrape and Parse 600 ETF Options in 10 mins with Python and Asyncio [Black Arbs]This is Part 1 of a new series I'm doing in semi real-time to build a functional options data dashboard using Python. There are many underlying motivations to attempt this, and several challenges to implementing a tool like this from scratch. Where to get the data? Is it affordable? Easily accessible? API? How to parse the results? How to aggregate and organize the data for analysis? How to
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Solved: Errors Downloading Stock Price Data from Yahoo Finance [Robot Wealth]Recently, Yahoo Finance a popular source of free end-of-day price data made some changes to their server which wreaked a little havoc on anyone relying on it for their algos or simulations. Specifically, Yahoo Finance switched from HTTP to HTTPS and changed the data download URLs. No doubt this is a huge source of frustration, as many backtesting and trading scripts that relied on such
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Yahoo is dead, long live Yahoo! [Trading with Python]On 18 May 2017 the ichart data api of yahoo finance went down, without any notice. And it does not seem like it is coming back. This has left many (including me) with broken code and without a descent free end-of-day data source. Something needs to be done. Now. Apparently Yahoo! does not want us to download free data automatically, but it is still possible to download it by hand, clicking the
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An Example of Trading Model Design by Richard Olsen (Founder of @OANDA) [Quantpedia]We introduce a new approach to algorithmic investment management that yields profitable automated trading strategies. This trading model design is the result of a path of investigation that was chosen nearly three decades ago. Back then, a paradigm change was proposed for the way time is defined in financial markets, based on intrinsic events. This definition lead to the uncovering of a large set