This is a summary of links featured on Quantocracy on Wednesday, 09/14/2022. To see our most recent links, visit the Quant Mashup. Read on readers!
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NEW Contributor: Multivariate GARCH with Python and Tensorflow [Sarem Seitz]In an earlier article, we discussed how to replace the conditional Gaussian assumption in a traditional GARCH model. While such gimmicks are a good start, they are far from being useful for actual applications. One primary limitation is the obvious restriction to a single dimensional time-series. In reality, however, we are typically dealing with multiple time-series. Thus, a multivariate GARCH
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Optimal Allocation to Cryptocurrencies in Diversified Portfolios [Artur Sepp]Cryptocurrencies have been acknowledged as an emerging asset class with a relatively low correlation to traditional asset classes. One of the most important questions for allocators is how much to allocate to Bitcoin and to a portfolios cryptocurrency assets within a broad portfolio which includes equities, bonds, and other alternatives. I wrote a research paper addressing this questions. I will
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Analyzing U.S. election cycle seasonality in the S&P 500 [Quant Dare]Everyone is aware of the importance of the U.S. elections and we take it for granted that, like many other things, financial markets will end up being affected in some way. But have you ever wondered if there is any seasonality throughout those elections that we can take advantage of when making investment decisions? Lets find out! Introduction The following charts show the historical evolution
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Momentum – a separate factor or does it subsume stock risk? [Alpha Architect]Breaking new ground, the authors present a novel view on the nature and source of momentum that differs from our current understanding of momentum, whether it be industry momentum, residual, or any other version of momentum. Explanations of the source of profitability for momentum strategies have traditionally relied on behavioral biases on the part of investors, time-varying risk premiums,