This is a summary of links featured on Quantocracy on Wednesday, 07/11/2018. To see our most recent links, visit the Quant Mashup. Read on readers!
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Excerpt, Part II: Quantitative Investment Portfolio Analytics In R [Capital Spectator]A couple of weeks back I published the first part of a full-chapter excerpt from my new book, Quantitative Investment Portfolio Analytics In R: An Introduction To R For Modeling Portfolio Risk and Return. Heres the second half of this two-part excerpt of Chapter 5, which reviews the basics for factor analysis via R code. The chapter sample below focuses on additional analytics, including a
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Our Conversation with Adam Butler [Flirting with Models]This post is the first of a series where we will be providing some of our own thoughts and commentary the conversations we had in the first season of our new podcast. This post covers our conversation with Adam Butler, which you can listen to here. 1:57 – Corey introduces Adam via a blog post Adam wrote about his experience with the emerging market and commodity super cycle theory of the early
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Multiple Managers vs A Single Manager: Return Predictability [Rayner Gobran]This is the seventh in my Hedge Fund Hacks series. It is a natural follow-up to my sixth hack on Hedge Fund Return Predictability in which I identified the following conundrum: You need a track record of 8+ years of monthly data to have reasonable confidence in a managers expected returns. The longer the track record you demand, the fewer managers you will have to choose from. A long track
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Hierarchical Risk Parity [Quant Dare]Building profitable portfolios has been giving investment managers headaches for decades. Many approaches have been used up until now, some of the most well-known being Markowitzs Efficient Frontier and Risk Parity. Today, we are presenting a brand new approach to this recurrent problem developed by Dr. Marcos Lpez de Prado applying Modern Graph Theory and Machine Learning techniques. Lpez
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Impact of Single Stocks On Factor Returns [Factor Research]Factor portfolios are typically created by equal weighting stocks The impact of single stocks is therefore reduced compared to market-cap weighted indices The FAANG stocks impacted factors differently INTRODUCTION The famous FAANG quintet of Facebook, Amazon, Apple, Netflix, and Google has driven much of the performance of the Nasdaq 100 in 2018 and currently accounts for approximately 35% of the
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Double Gaps and Hens Teeth [Throwing Good Money]I looked at the chart for SPY just now, and thought, Huhtwo days in a row that have gapped up. Wonder if thats significant in any way? By gap, I mean that todays low was higher than yesterdays high. When this happens two days in a row, does it mean we should use quintuple leverage to buy everything we can? Sell at the opening bell and hide under a rock? Something else?