This is a summary of links featured on Quantocracy on Tuesday, 05/19/2020. To see our most recent links, visit the Quant Mashup. Read on readers!
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Implied risk premia [OSM]In our last post, we applied machine learning to the Capital Aset Pricing Model (CAPM) to try to predict future returns for the S&P 500. This analysis was part of our overall project to analyze the various methods to set return expectations when seeking to build a satisfactory portfolio. Others include historical averages and discounted cash flow models we have discussed in prior posts. Our
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Prospect Theory Helps Explain Return Anomalies [Alpha Architect]The field of behavioral finance provides us with fascinating insights into individual investor behavior, including how individuals view risk, as well as the impact of those views on asset prices. Prospect theory plays a major role in explaining investor behavior. The theory, formulated in 1979 by Amos Tversky and Daniel Kahneman, describes how individuals make choices between probabilistic
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Using Digital Signal Processing in Quantitative Trading Strategies [Robot Wealth]In this post, we look at tools and functions from the field of digital signal processing. Can these tools be useful to us as quantitative traders? Whats a Digital Signal? A digital signal is a representation of physical phenomena created by sampling that phenomena at discrete time intervals. If you think about the way we typically construct a price chart, there are obvious parallels: we sample
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Trend Following the S&P 500? Some Practical Advice [Alpha Architect]Now that market volatility is back, tail risk management strategies are gaining some attention. A lot of investors are dipping their toe into the water and exploring trend-following strategies on the S&P 500 arguably the most popular U.S. stock market index.This paper explores multiple trend following signals (TF) with various degrees of complexity, frequency, and trading (they also check
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Periodically Rebalanced Static Allocation ‘Buy and Hold’ Strategies in QSTrader [Quant Start]For those systematic traders who are considering a long-term investment horizon one of the most common forms of generating a portfolio involves static proportional capital allocation amongst a collection of (hopefully) diversifying asset classes, which is periodically rebalanced to maintain the allocation. Such portfolios are often termed 'buy and hold' despite the fact that the
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Profiling S&P 500 Drawdowns Since 1871 [Capital Spectator]Longer is better for analyzing the stock market, which is why Professor Robert Shillers data set (with an 1871 starting date) is one of the great free resources on the internet for studying the history of US equities. With that in mind, lets review how the current drawdown for the S&P 500 compares over the past century and a half. First, a few housekeeping notes. Shillers data is
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A Volume Profile With Levels Chart [Dekalog Blog]Just a quick post to illustrate the latest of my ongoing chart iterations which combines a levels chart, as I have recently been posting about, but with the addition of a refined methodology of creating the horizontal histograms to more clearly represent the volumes over distinct periods. The main change is to replace the use of the Octave barh function with the fill function. A minimal working