This is a summary of links featured on Quantocracy on Wednesday, 04/20/2016. To see our most recent links, visit the Quant Mashup. Read on readers!
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Kaufman’s Market Efficiency Model [Milton FMR]The trend following model by Kaufman says that trading by the direction of the trend is a conservative approach to the markets. Kaufmans Market Efficient Model states that longer trends are the most reliable but they respond rather slowly to changing market conditions. The main argument of the Market Efficiency Model is that an adaptive method must be applied to the markets for proper trend
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CAPE 10 Ratio In Need Of Context [Larry Swedroe]The Shiller cyclically adjusted (for inflation) price-to-earnings ratioreferred to as the CAPE 10 because it averages the last 10 years earnings and adjusts them for inflationis a metric used by many to determine whether the market is undervalued, fairly valued or overvalued. Employing a 10-year average for earnings, instead of the most current 12-month earnings, was first suggested by
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Information Content of Pre- and Post-Market Trading Sessions [Jonathan Kinlay]I apologize in advance for this rather "wonkish" post, which is aimed chiefly at the high frequency fraternity, or those at least who trade intra-day, in the equity markets. Such minutiae are the lot of those engaged in high frequency trading. I promise that my next post will be of more general application. Pre- and Post Market Sessions The pre-market session runs from 8:00 AM ET, while
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What is the difference between Bagging and Boosting? [Quant Dare]Bagging and Boosting are both ensemble methods in Machine Learning, but what is the key behind them? Bagging and Boosting are similar as they are both ensemble techniques, where a set of weak learners are combined to create a strong learner that obtains better performance than a single one. So, lets start from the beginning: What is an ensemble method? Ensemble is a Machine Learning concept in
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Analysis of US Dollar Carry Trades in the Era of ‘Cheap Money’ [Quantpedia]In this paper, we employ a unique dataset of actual US dollar (USD) forward positions against a number of currencies taken by so-called Commodity Trading Advisors (CTAs). We investigate to what extent these positions exhibit a pattern of USD carry trading or other patterns of currency trading over the recent period of the ultra-loose US monetary policy. Our analysis indeed shows that USD positions