This is a summary of links featured on Quantocracy on Friday, 01/12/2024. To see our most recent links, visit the Quant Mashup. Read on readers!
-
Pragmatic Asset Allocation Model for Semi-Active Investors [Quantpedia]The primary motivation behind our study stems from an observation of the Global Tactical Asset Allocation (GTAA) strategies throughout the existing papers the majority of them require relatively frequent rebalancing from the point of view of the ordinary investor. Portfolio rebalancing is usually done on a weekly or monthly basis, and while this period may seem overly boring and slow for the
-
A Short Take on Real-World Pairs Trading [Robot Wealth]In textbooks, one often sees pairs trading algorithms start by regressing prices of Asset A on Asset B to calculate a hedge ratio. Ive rarely seen anyone actually do this in the real world. Thats because it is a very unstable thing especially for a pair of volatile assets, and especially over a large amount of data. The basic pairs trading algorithm which you see out in the real world
-
Peer-Reviewed Theory and Expected Stock Returns [Alpha Architect]As professor John Cochrane observed, the literature on investment factors now fills a veritable factor zoo, with hundreds of options. How do investors select from among this huge array of possibilities? In order to minimize the risk that outcomes result from data mining, in our book Your Complete Guide to Factor-based Investing, Andrew Berkin and I established six criteria for a factor
-
Research Review | 11 January 2024 | Fat Tail Distributions [Capital Spectator]Optimal Portfolio Choice with Fat Tails and Parameter Uncertainty Raymond Kan (U. of Toronto) and Nathan Lassance (LFIN/LIDAM) December 2023 Existing portfolio combination rules that optimize the out-of-sample performance under estimation risk are calibrated assuming multivariate normally distributed returns. In this paper, we show that this assumption is not innocuous because fat tails in returns