This is a summary of links featured on Quantocracy on Wednesday, 03/29/2017. To see our most recent links, visit the Quant Mashup. Read on readers!
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Podcast: Trading technology, alternative data, and originality w/ Manoj Narang [Chat With Traders]High-speed trading veteran, Manoj Narang, originally worked on Wall St for the likes of Credit Suisse and Goldman Sachs prior to founding Tradeworx, which became one of the larger trading firms in the U.S. (in terms of volume). Hes since parted ways with Tradeworx to start MANA Partnersan innovative quant fund which raised almost one billion dollars for its launch in January this year
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How to use bootstrapping in Portfolio Management [Quant Dare]Faced with growing uncertainty in financial markets, investors are worried about the future of their investments. Travelling in time to check the future reality is not yet a possibility. For that reason, we use techniques and create measures to gain confidence in our investments future behaviour. Bootstrapping is a financial technique that allows us to get a return confidence interval for a
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Podcast w/ @GaryAntonacci: You Get a Synergy That Happens When You Use Dual Momentum [Meb Faber]Gary has over 40 years experience as an investment professional focusing on underexploited investment opportunities. Since receiving his MBA degree from the Harvard Business School, Gary has concentrated on researching, developing, and applying innovative investment strategies that have their basis in academic research. His innovative research on momentum investing was the first-place winner in
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A More Complex View On Value [Larry Swedroe]Eugene Fama and Kenneth Frenchs 1992 paper, The Cross-Section of Expected Stock Returns, resulted in the development of the FamaFrench three-factor model. This model added the size and value factors to the market beta factor. As my co-author, Andrew Berkin, and I demonstrate in Your Complete Guide to Factor-Based Investing: The Way Smart Money Invests Today, the value premium has
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The Case For Using Random Benchmarks In Portfolio Analysis [Capital Spectator]Benchmarks are indispensable for investment analytics. The challenge is picking a relevant one. The stakes are high because the wrong benchmark can be worse than none at all. The good news is that the potential for error can be dramatically reduced by choosing a set of random benchmarks that are generated from a portfolios holdings. As an example, consider a money manager with a mandate to beat