This is a summary of links featured on Quantocracy on Monday, 11/20/2017. To see our most recent links, visit the Quant Mashup. Read on readers!
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Risk Parity: How Much Data Should We Use When Estimating Volatilities and Correlations? [Flirting with Models]Risk parity portfolios attempt to diversify across asset classes and strategies by risk contribution as opposed to dollar allocation. Implementing a risk parity strategy requires making a number of important construction decisions. A key question we have to answer is How are we going to measure risk? One approach is to use historical data to estimate risk. When using this approach, we have
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Sector Rotation with Fama-French Alphas [Allocate Smartly]Allocate Smartly tests and tracks asset allocation strategies sourced from books, academic papers and other publications. Most of the strategies that we test though never make it on to this site. There are a variety of reasons that might be, but often its simply because theyre not very good. Usually we just let those strategies slip gently into the good night, but this one took a lot of work
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Candlestick Plotting Function for Octave [Dekalog Blog]I have long been frustrated by the lack of an "out of the box" solution for plotting OHLC candlestick charts natively in Octave, the closest solution I know being the highlow plot function from the financial package ( which does not yet implement a candle function ) over at Octave Sourceforge. This being the case, I decided to write my own candlestick plotting functions, the codes for
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Quant Strategies in the Cryptocurrency Space [Factor Research]The year 2017 might be regarded as the year where cryptocurrencies became mainstream. Investment funds focused on cryptocurrencies were launched, the CBOE announced Bitcoin futures for the end of the year and some everyday expenses like booking flights at Expedia can be paid in Bitcoins. Institutional investors have been cautious entering the space, but are slowly getting more active given that