ETF Liquidity

3.September 2020

Exchange-traded funds (ETFs) have become popular and important investment vehicles in the financial markets. However, that is not a shock given the numerous benefits connected with ETFs. Naturally, they have caught the interest of academics, and there is plenty of literature about strategies on ETFs. While the profits and trading strategies are probably the most important research topics for practitioners, liquidity in the financial markets is almost equally important. Concerning liquidity in the ETFs, novel research by Pham et al. shows when exactly are ETFs the most liquid. Looking on the spreads, they are the lowest at market close. Such a finding can be an essential part of an optimal trading position making, where the aim is to minimize the trading costs.

Authors: Pham, Son Duy and Marshall, Ben R. and Nguyen, Nhut (Nick) Hoang and Visaltanachoti, Nuttawat 

Title: Predicting ETF Liquidity

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Quantpedia in August 2020

1.September 2020

Once again, welcome to our summary of Quantpedia’s research. Ten 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 15 new backtests written in QuantConnect code. Our database currently contains over 340 strategies with out-of-sample backtests/codes.

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

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Pre-Announcement Returns

26.August 2020

Earnings announcement days are really important dates in a usual yearly corporate routine. The stock market usually reacts sharply on earnings announcement news and stocks on average earn statistically significant return excess of the market over the short window centred around the announcements. But how does the movement of stocks look before earnings announcement? The recent research paper written by Gao, Hu, and Zhang analyzes price action before and after earnings announcement and shows that a majority of the announcement month premium is realized during the pre-announcement period. Stocks with higher levels of uncertainty (stocks are sorted based on their option implied volatilities) experience larger pre-announcement returns and more uncertainty resolution during the pre-announcement period…

Authors: Gao, Chao and Hu, Grace Xing and Zhang, Xiaoyan.

Title: Uncertainty Resolution Before Earnings Announcements

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Multi-Asset Skewness Trading Strategy

19.August 2020

The best course of action for every quant researcher is to try to fundamentally understand anomalies and explore their functioning besides the original scope of the academic research papers. The goal of this article was to look for inspiration and further explore the Skewness affect – the tendency of assets with the lowest skewness to outperform assets with the highest skewness. It seems that this anomaly is present not only in commodities but also in currencies, fixed income and equities. Trading strategy that exploits the effect of skewness in the multi-asset setting would earn an annual return of 7.67% when leveraged to the 15% volatility.

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Implied Equity Duration as a Measure of Pandemic Shutdown Risk

14.August 2020

Some companies have relatively more of their value in near-term cash flow (for ex. General Motors Corporation). Others (for ex. Tesla), are growth stocks, with a greater proportion of their market value based on long-term expected future cash flow. It seems that coronavirus pandemic has hit mainly the first group, the “low equity duration” companies. A new academic research paper written by Dechow, Erhard, Sloan, and Soliman explains how the equity duration factor can be used to assess how are companies exposed to short-term unexpected macroeconomic events (like COVID-19 pandemic), and how equity duration sensitivity can also explain relative underperformance of value vs growth stocks during the last bear market.

Authors: Dechow, Patricia and Erhard, Ryan and Sloan, Richard G. and Soliman, Mark T.

Title: Implied Equity Duration: A Measure of Pandemic Shutdown Risk

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