This is a summary of links featured on Quantocracy on Monday, 03/25/2019. To see our most recent links, visit the Quant Mashup. Read on readers!
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AI and Alternative Data in Investing – Hype or Reality? [Two Centuries Investments]Having just attended a great AI conference in New York, here are some observations: First about AI Most quants prefer the term Machine Learning (ML) instead of AI. Questions still remain of where AI (ML) adds value in a quant investment process. For example, Mans CIO Sandy Rattray said that it works well for the execution of trades but is not that helpful in forecasting returns (see here). He
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Time Dilation [Flirting with Models]Information does not flow into the market at a constant frequency or with constant magnitude. By sampling data using a constant time horizon (e.g. 200-day simple moving average), we may over-sample during calm market environments and under-sample in chaotic ones. As an example, we introduce a highly simplified price model and demonstrate that trend following lookback periods should be a
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Seasonality May Again Flip This Week To Bullish [Quantifiable Edges]With regards to seasonality, we are in an interesting period right now. The last couple of weeks the market played out well according to seasonal patterns. We saw March opex week put in nice gains as it often does. And then we saw the week after Quad-witching suffer losses this past week. Interestingly, the week after the 4th Friday in March has been a strong one over the last 21 years. (Not as
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Black Swans, Major Events and Factor Returns [Factor Research]It is questionable if investors should prepare for catastrophic events Factor returns are almost random after black swan and major events Simple diversification is likely the best option for the expected and unexpected INTRODUCTION Investors fear black swan events, although it can be argued that this fear is irrational. The black swan theory is a metaphor that describes a surprise event that has a
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Signaling systemic risk [SR SV]Systemic financial crises arise when vulnerable financial systems meet adverse shocks. A systemic risk indicator tracks the vulnerability rather than the shocks (which are the subject of stress indicators). A systemic risk indicator is by nature slow-moving and should signal elevated probability of financial system crises long before they manifest. A recent ECB paper proposed a practical