This is a summary of links featured on Quantocracy on Monday, 02/25/2019. To see our most recent links, visit the Quant Mashup. Read on readers!
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Developing a Trading Strategy using Volume Data [Quant News]Traders and market analysts use volume data, which is the amount of buying and selling of an instrument over a given time period, to gauge the strength of an existing trend or identify a reversal. The back-and-forth movement between buyers and sellers for the best available price allows us to analyze volume to confirm trends and predict reversals. Generally, volume tends to increase as a trend
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Low Volatility Can Be Low Turnover [Alpha Architect]Low volatility strategies have garnered a fair amount of popularity and a growing body of supporting research. Studies have shown risk reduction levels of 25%, while turnover has varied from 20% to 120%. However, higher turnover produces higher costs of trading, such that the excess return obtained with low volatility products may actually be subsumed by those same trading costs. The authors of
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Three Applications of Trend Equity [Flirting with Models]Trend equity strategies seek to meaningfully participate with equity market growth while side-stepping significant and prolonged drawdowns. These strategies aim to achieve this goal by dynamically adjusting market exposure based upon trend-following signals. A nave example of such a strategy would be a portfolio that invests in U.S. equities when the prior 1-year return for U.S. equities is
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Minimum Variance Versus Low Volatility [Factor Research]The largest smart beta Low Volatility ETF is technically a Minimum Variance strategy Low Volatility and Minimum Variance have comparable and attractive characteristics However, both currently feature a high sensitivity to interest rates INTRODUCTION The Low Volatility factor was the best performing factor in 2018, which few investors expected at the beginning of the year. Central banks across the