This is a summary of links featured on Quantocracy on Friday, 09/16/2016. To see our most recent links, visit the Quant Mashup. Read on readers!
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Factor Investing: Buyer Beware [Dual Momentum]A highlight of the 2016 Morningstar ETF Conference was the keynote address by the former leader of U.S. Navy Seal Team Six, Rob ONeill. Chief ONeill shared some stories about his training and operations as an elite Navy Seal. The take away lessons from his talk were the importance of preparation, discipline, and keeping the mission goal in mind. Overriding all this is the importance of
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Average TAA Allocation by Month [Allocate Smartly]We delayed adding the latest strategy to our site (GestaltUs Adaptive Asset Allocation) for a week due to technical hurdles running the minimum variance component of the strategy in near real-time for members. Historical results on GestaltUs strategy are exceptional though, and we plan to have the kinks with real-time worked out shortly. In the meantime, I thought the following chart
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Was the Financial Crisis Really a Valuation Crisis? [Alpha Architect]Most people look back at the dot-com bubble and acknowledge valuations were elevated far above historical norms. Investors ignored historically useful fundamentals, such as earnings and book value, and started relying on measures like eyeballs and clicks. Investors really started to believe, This time its different, the four most dangerous words in investing according to Sir John
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A Persistent Kind Of Momentum [Larry Swedroe]Time-series momentum examines the trend of an asset with respect to its own past performance. This is very different than cross-sectional momentum (often referred to as Carhart momentum), which compares the performance of an asset with respect to the performance of another asset. Ian DSouza, Voraphat Srichanachaichok, George Jiaguo Wang and Chelsea Yaqiong Yao, who authored the 2016 study
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Loading and Manipulating Historical Data From .csv Files [Dekalog Blog]In my last post I said I was going to look at data wrangling my data, and this post outlines what I have done since then. My problem was that I have numerous csv files containing historical data with different date formats and frequency, e.g. tick level and hourly and daily OHLC, and in the past I have always struggled with this. However, I have finally found a solution using the R quantmod