This is a summary of links featured on Quantocracy on Friday, 08/17/2018. To see our most recent links, visit the Quant Mashup. Read on readers!
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A Review of Quantitative Investment Portfolio Analytics in R by @JPicerno [QuantStrat TradeR]This is a review of James Picernos Quantitative Investment Portfolio Analytics in R. Overall, its about as fantastic a book as you can get on portfolio optimization until you start getting into corner cases stemming from large amounts of assets. Heres a quick summary of what the book covers: 1) How to install R. 2) How to create some rudimentary backtests. 3) Momentum. 4) Mean-Variance
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Consistent Momentum on the JSE [Sutherland Research]In my last post we explored a momentum strategy applied to the USA markets that was provided to us from the good guys over at www.quantpedia.com. One of my readers set about quantifying the same strategy on the JSE and shared their results with me. With permission and thanks, I pass along their fine work for your benefit. As reference, Chris Muller employed his style engine to quantify the
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Long Memory and Regime Shifts in Asset Volatility [Jonathan Kinlay]This post covers quite a wide range of concepts in volatility modeling relating to long memory and regime shifts and is based on an article that was published in Wilmott magazine and republished in The Best of Wilmott Vol 1 in 2005. A copy of the article can be downloaded here. One of the defining characteristics of volatility processes in general (not just financial assets) is the tendency for
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Accruals Momentum as an Investment Strategy [Alpha Architect]Accruals are a part of any companys financial reporting. For those unfamiliar with accrual accounting, a simple explanation is that accruals are adjustments made for (1) revenue that has been earned but not received and (2) costs that have been incurred but have not been paid. In short, one should assume that all publicly traded companies have accruals.(1) Given that accruals are common-place,