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The general effect of quantitative analysis of the markets is to enforce randomness. Suppose a strategic quant finds a predictable pattern where a stock always rises on Tuesdays. His institution will commence buying the stock every Monday, and selling on Tuesday. The trading itself pushes the stock price up on Monday and down on Tuesday (in general), so if ...


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You have started a huge job, an enormous number of anomalies have been reported. The web site quantpedia.com has a list, here for example is their writeup on momentum effect in stocks


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The best overview I have seen so far is this paper which lists 214 (!) factors (or anomalies if you like) on over one hundred (!) pages: …and the Cross-Section of Expected Returns by Harvey, C. et al., Feb. 2015: Abstract: Hundreds of papers and hundreds of factors attempt to explain the cross-section of expected returns. Given this extensive ...


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There are different methodologies to detect a change in the market efficiency, both in the market and firm-specific cases. In the FIRM-SPECIFIC case, the most common procedure is the event study methodology; you can find how to construct an event-study case explained in Kothari & Warner (2006), who collected all the event study methodology implemented ...


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More measurable effects to add to your list: "window dressing" - returns of the fourth quarter or 12th month (i.e. year-end) are higher on average than oher returns; the same to returns of 4th months (qtr-end) vs. others; "herding": changes in asset-classes shares of "big" funds (whatever you define "big") granger-cause changes in asset-classes shares of ...



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