This is a summary of links featured on Quantocracy on Wednesday, 01/27/2021. To see our most recent links, visit the Quant Mashup. Read on readers!
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The Correct Vectorized Backtest Methodology for Pairs Trading [Hudson and Thames]Whilst backtesting architectures is a topic on its own, this article dives into how to correctly backtest a pairs trading investment strategy using a vectorized (quick methodology) rather than the more robust event-driven architecture. This is a technique that is very common amongst analysts and is rather straightforward for long-only portfolios, however, when you start to construct long-short
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Infrastructure of algorithmic trading systems [Trade With Science]A development processs infrastructure can be understood as a step-by-step guide when working on a trading project. Every developer has a bit different approaches, but the skeleton of the process is usually the same. This article is an introduction to building your trading system from scratch. Each topic is crucial and contains steps you should not forget to do. Depending on your previous
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A Review of Ben Graham s Famous Value Investing Strategy: “Net-Nets” [Alpha Architect]Benjamin Graham, often considered a strong candidate for the the father of quantitative value investing, developed an investment strategy that involved purchasing securities for less than their current-asset value, a rough index of the liquidating value. We uncovered ten research papers that examined the returns achieved by investing in such securities which were conducted over a
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Fundamental and Sentiment analysis with different data sources [Quant Insti]Technical analysis of price and volume history wont cut it alone nowadays. When we want to perform value investing and/or measure a securitys intrinsic value, we need to make a fundamental analysis of the security. To perform fundamental analysis we need data, lots of data. We want fundamental data in the form of ratios, financial statements, earnings, etc. On top of that we can also use