Top Ten Blog Posts on Quantpedia in 2020

1.January 2021

Once again, let us use the turn of the year for a short recapitulation of posts on our blog. Apart from other things we do (which we will summarize in our next blog post in a few days), we have published around over 50 short blog posts / recherches of academic papers on this blog during the last year. We want to use this opportunity to summarize 10 of them, which were the most popular (based on Google Analytics tool). Maybe you will be able to find something you have not read yet …

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Senators vs Santa’s Reindeer

29.December 2020

During the festive season, everything is more relaxed, and this week’s blog is no exception. The stock-picking abilities of animals are not the main research topic for most academics, yet the stock-picking skills, for example, of monkeys, were previously documented. To our best knowledge, the paper of Belmont et al. (2020) is the first that examines the stock-picking abilities of reindeer. Moreover, the performance of reindeer is compared to the US senators during 2020. Trading of US senators or congresspeople is particularly interesting since there are concerns about informed stock trading. Especially during the COVID pandemic, where the governments have a significant influence on the economies. The finding of the paper is that the performance of the senate is behind reindeer. However, the reindeer exhibit herding behaviour and momentum preferences. Perhaps, their abilities should be examined more deeply during a more extended period.

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Large Cap Analysis

23.December 2020

Every week, through these posts, we point to interesting academic research papers. This week´s blog is slightly different, yet no less engaging. This blog includes numerous interesting charts from more than hundred charts in the CUSTOM REPORT: U.S. LARGE INDEX by the PHILOSOPHICAL ECONOMICS using OSAM Research Database. The report consists of the visually presented analysis of the U.S. Large index. The analysis includes the composition, returns, individual stocks, sector and factor allocations, and six fundamentals. The report contains comprehensive information about the large caps in the U.S. market from 1963 to 2020 and is worthy of a look.

We wish you all Merry Christmas …

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ESG and CEO Turnover

19.December 2020

ESG scores are already well-established, and nobody doubts that the scores affect investors or companies. Investors seem to care more and more about the other aspects of the stocks and not just the profits – the human welfare, ecology or social aspects of our lives. Additionally, numerous researches point out that the the ESG scores can positively affect also the portfolios. However, the novel research by Colak et al. (2020), has examined other implications of the ESG scores: how the ESG affect the CEOs. To be more precise, how the adverse ESG events and subsequent negative media attention affects the longevity of the CEOs. The finding is that negative event significantly increase the probability of the CEO being replaced. Overall, the research paper highlights the importance of ESG scores in the corporate world.

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Trading Index (TRIN) – Formula, Calculation & Trading Strategy in Python

14.December 2020

Short-term mean reversion trading on equity indexes is a popular trading style. Often, price-based technical indicators like RSI, CCI are used to assess if the stock market is in overbought or oversold conditions. A new research article written by Chainika Thakar and Rekhit Pachanekar explores a different indicator – TRIN, which compares the number of advancing and declining stocks to the advancing and declining volume. TRIN’s advantage is that it’s cross-sectionally based and its calculation uses not only price but also volume information. Thakar& Pachanekar’s research paper is useful for fans of indicator’s based trading strategies and offers a short introduction to TRIN’s calculation together with an example of mean-reversion market timing strategy written in a python code.

Authors: Chainika Thakar, Rekhit Pachanekar

Title: Trading Index (TRIN) – Formula, Calculation & Strategy in Python

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The Active vs Passive: Smart Factors, Market Portfolio or Both?

11.December 2020

While there may be debates about passive and active investing, and even blogs about the numbers of active funds that were outperformed by the market, the history taught us that the outperformance of active or passive investing is cyclical. As a proxy for the active investing, the new Quantpedia’s research paper examines factor strategies and their smart allocation using fast or slow time-series momentum signals, the relative weights based on the strength of the signals and even blending the signals. While the performance can be significantly improved, using those smart approaches, the factors still got beaten by the market in both US and EAFE sample. However, the passive approach did not show to be superior. The factor strategies and market are significantly negatively correlated and impressively complement each other. The combined Smart Factors and market portfolio vastly outperforms both factors and market throughout the sample in both markets. With the combined approach, the ever-present market falls can be at least mitigated or profitable thanks to the factors.

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