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 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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Market Makers and Extreme Price Movements

5.December 2020

Often, this blog provides novel research that may not include the straightforward trading strategy, yet it is an interesting insight for portfolio managers, risk managers, investors or traders. Novel research of Brogaard et al. (2020) examines the crucial role of market makers during extreme price movements. According to the authors and the past literature, there are two competing theories of how the extreme price movements end, and both are related to the market makers. It is the constrained liquidity provision theory and the strategic liquidity provision. This research tests and explains these competing theories, with findings that are in line with the strategic liquidity provision. The results can be found particularly interesting during extreme price movements because the paper has shown that firstly, liquidity providers scale back and only interfere later. Market makers utilize price pressures in stressful times in a profitable way, since they profit from subsequent reversals.

Authors: Jonathan Brogaard, Konstantin Sokolov and Jiang Zhang

Title: How do Extreme Price Movements End?

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Quantpedia in November 2020

2.December 2020

Thirteen new Quantpedia Premium strategies have been added into our database, and eleven new related research papers have been included in existing Premium strategies during last month.

Additionally, we have produced 11 new backtests written in QuantConnect code. Our database currently contains over 370 strategies with out-of-sample backtests/codes.

Also, four new blog posts, that you may find interesting, have been published on our Quantpedia blog.

Plus we continue to re-run some of our codes on a monthly basis systematically, over 160 codes are at the moment part of this activity.

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