This is a summary of links featured on Quantocracy on Monday, 04/20/2020. To see our most recent links, visit the Quant Mashup. Read on readers!
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One Factor World [Two Centuries Investments]For the past decade, asset managers have been educating clients about factor investing as it became the new norm. And yet after all these years, portfolios are still composed of one factor: Equity Beta. Among many questionable assertions and assumptions behind factor investing (our thoughts here, here and here), there is one that remains true: Equity Beta is the most significant Risk Factor in
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Estimating Pandemic Economic Costs for “Face-to-Face” Businesses [Alpha Architect]To describe the impact of social distancing, a theory of communication is developed and described comprehensively in this article. The focus is on the relative importance of worker interactions, the cost of those interactions and their impact on the size of wage subsidies intended as compensation for the disruption due to social distancing. The authors develop a model of communication whereby the
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Smart Beta Fixed Income ETFs [Factor Research]Factor investing in fixed income has been heralded as the next frontier in asset management Smart beta fixed income ETFs in the US manage only slightly more than $2 billion of assets Defensive strategies reduced drawdowns during the ongoing coronavirus crisis INTRODUCTION Investing is becoming more scientific over time as technology continues to advance, but it will never be a hard science like
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Well, you No, you gotta do more than that. [Flirting with Models]Since 2009, any decision to de-risk in a trend equity portfolio has largely been the wrong decision. At the time of writing, we implement a 1-month tranching process in most of our trend mandates, which has the effect of dollar-cost averaging signal changes over a 1-month period. We adopted this approach for a number of reasons, including: (1) to align our rebalance frequency with what we believe
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Dual Momentum & Rate of Change: Trading Strategy Review [Oxford Capital]Concept: Dual momentum trading strategy based on Rate of Change (ROC). Research Goal: Performance verification of dual momentum signals. Specification: Table 1. Results: Figure 1-2. Trade Filter: Long Filter: Slow Rate of Change (ROC1) is above zero. Short Filter: Slow Rate of Change (ROC1) is below zero. Trade Setup: Long Setup: Fast Rate of Change (ROC2) is above zero. Short Setup: Fast Rate of