The Hidden Costs of Corporate Bond ETFs

28.September 2022

Exchange-traded funds (ETFs) have been recently booming in popularity and enjoy great praise for their flexibility and accessibility in terms of liquidity. They allow investors convenient exposure to less liquid assets such as corporate bonds. But liquid ETF instrument based on illiquid assets is a recipe for a lot of hidden problems (and sometimes disasters), especially in such a turbulent period on fixed income markets as it’s now. There are various certain specifics which come with creation of new ETFs and problems for buying of underling prospects to match the fund’s NAV. Chris Reilly’s paper (2022) revolves around the point that ETF managers encourage Authorized Participants (APs) to more aggressively arbitrage tracking errors to the benefit of ETF investors while simultaneously allowing APs to interact strategically with ETF portfolios at the expense of ETF investors. Underlying asset liquidity is a first-order determinant of optimal security design for ETFs. While these ETFs do underperform their benchmark by greater than their stated net expense ratios (as much as claimed 48 bps p.a.), they still offer a liquid alternative for investors that do not have the resources to manage their own fixed income portfolio. This summary could be taken as a good reminder that investors’ expenses to obtain liquidity in the fixed income space are often quite substantial.

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Overnight Sentiment and the Intraday Return Dynamics

24.September 2022

Overnight and seasonality effects or analysis of sentiment are favorite themes in quantitative academic research. Novel and very recent research from Baoqing Gan, Vitali Alexeev, and Danny Yeung (August 2022) presents us with an opportunity to discover new findings related to both these phenomena. The main takeaway is that the accumulated sentiment from the overnight non-trading period can predict the next period’s intraday stock return.

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How Common is Insider Trading? Evidence from the Options Market

20.September 2022

Trading on non-public information has been very profitable in the past (and probably still is). Prominent insiders use their knowledge and share it with influential, wealthy institutional investors who earn money in an illegal way. And especially, options provide attractive leverage and relatively viable ways to “hide” sources of this illegal advantage. But after several big scandals, the resurgence of some forms of insider trading was stopped in 2009 after a trial with hedge fund superstar Raj Rajaratnam. The question is: What is the situation now?

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Investing in Deflation, Inflation, and Stagflation Regimes

16.September 2022

Investing has been a reliable way to compound one’s inheritance over ages known throughout human history. But different monetary and fiscal situations, especially during times of uncertainty and extreme stress, force both individuals and institutions to adjust their financial habits. A recent research paper written by Guido Baltussen, Laurens Swinkels, and Pim van Vliet analyzed large samples of data starting from the 19th century and brought unique perspectives on how various asset classes perform during “quiet, good” periods and, on the other side, economic turmoil. Research summarized very actual topics of investing during those different cycles and what inflation does to returns across equities, bonds, and cash.

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A Study on How Algorithmic Traders Earn Money

13.September 2022

Our mission here at Quantpedia is to provide both retail and institutional investors with ideas for trading strategies that are easily understandable while based on and backed by quantitative academic research. Today, we present you with the results from a study that we came across. Although it’s not quantitative, but qualitative, it has really held our interest. The paper does not provide any images or figures; it is a study made from various types of surveys with answers from professionals concluded with an attention-grabbing summary table. 

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Quantpedia in August 2022

7.September 2022

Hello all,

What have we accomplished in the last month?

– A new Automatic Trading Edge Analysis report
– 9 new Quantpedia Premium strategies have been added to our database
– 10 new related research papers have been included in existing Premium strategies during the last month
– Additionally, we have produced 9 new backtests written in QuantConnect code
– And finally, 2+4 new blog posts that you may find interesting have been published on our Quantpedia blog in the previous month

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