What Drives the Excess Bond Premium?

The Excess Bond Premium (EBP – the portion of corporate bond spreads not explained by default risk), a key metric in quantitative finance for gauging credit spreads, has long been a subject of intense scrutiny. Recent research sheds new light on its dynamics, moving beyond traditional macroeconomic factors to explore the role of information flow. By analyzing news attention across 180 topics, a significant portion of the EBP’s variation can be explained, offering a novel lens to understand its fluctuations and predictive power.

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Using Inflation Data for Systematic Gold and Treasury Investment Strategies

Inflation significantly impacts the prices of gold and treasury bonds through various mechanisms. Gold is often viewed as a hedge against inflation, while treasury bonds exhibit a more complex relationship influenced by interest rates and investor behavior. This relationship between inflation, gold, and treasuries is well understood, but the real question is whether we can systematically capitalize on it. In this article, we explore how inflation data can be used to build trading strategies—and as our findings suggest, the answer is a definite yes.

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Overnight Reversal Effects in the High-Yield Market

High-yield bond ETFs represent a unique financial vehicle: they are highly liquid instruments that hold inherently illiquid securities, creating a fertile ground for predictable market behaviors. Our latest research uncovers an intriguing anomaly within these ETFs, similar to those observed in the stock market: overnight returns are systematically higher than intraday returns. This overnight anomaly in high-yield bonds is not only prevalent but also exhibits a distinct seasonal pattern, primarily from Monday’s close to Tuesday’s open and from Tuesday’s close to Wednesday’s open. Additionally, this anomaly displays a reversal characteristic, where overnight performance is typically more robust following a negative close-to-close performance in the preceding period. These findings reveal potential opportunities for trading strategies that leverage these consistent overnight return patterns, offering new insights into high-yield bond trading dynamics.

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How to Construct a Long-Only Multifactor Credit Portfolio?

There exist two most common techniques for constructing multifactor portfolios. The mixing approach creates single-factor portfolios and then invests proportionally in each to build a multifactor portfolio. The integrated approach combines single-factor signals into a multifactor signal and then constructs a multifactor portfolio based on that multifactor signal. Which methodology is better? It is hard to tell, and numerous papers show each method’s pros and cons. The recent paper from Joris Blonk and Philip Messow explores this question from the standpoint of the credit fixed-income portfolio manager and offers their analysis, which shows that an integrated approach is probably better in this particular asset class.

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Corporate Bond Factors: Replication Failures and a New Framework

The replication crisis in social sciences (and, of course, finance) is an often covered topic (see also our articles How do Investment Strategies Perform After Publication and In-Sample vs. Out-of-Sample Analysis of Trading Strategies). In vs. out-of-sample tests are usually performed on equity factors as data are available. However, the Copenhagen Business Schools, in close cooperation with AQR Capital Management, went in a different direction and built a database of realistic corporate bond data and took a closer look at the precision of corporate bonds forecasting methodologies. We applaud them for that, as working with the corporate bond data is challenging, and their work sheds a little light on this important part of the financial markets.

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The Hidden Costs of Corporate Bond ETFs

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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Extending Historical Daily Bond Data to 100 Years

Finding a good data source with quality data and long history is one of the greatest challenges in quantitative trading. There definitely are some data sources with very long histories. However, they tend to be on the more expensive side. On the other hand, cheap or free data usually lacks quality and/or has shorter time frames.

This article explains how to combine multiple data sources to create a 100-year daily data history for US 10-year bonds. Having a 100-year history of daily data can be very beneficial to understanding the market patterns and analyzing history and extending backtests to arrive at a new source of out-of-sample data.

Furthermore, suppose you want to examine how your portfolio would have performed during various historical events or to backtest a strategy during multiple market phases. In that case, the long history provides more opportunities. Besides, investors are always on the run to better understand the market. So, having substantial knowledge of history is crucial.

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How News Move Markets?

Nobody would argue that nowadays, we live in an information-rich society – the amount of available information (data) is constantly rising, and news is becoming more accessible and frequent. It is indisputable that this evolvement has also affected financial markets. Machine learning algorithms can chew up big chunks of data. We can analyze the sentiment (which is frequently related to the news). Big data does not seem to be a problem anymore, and high-frequent trading algorithms can react almost instantly. But how important is the news? Kerssenfischer and Schmeling (2021) provide several answers by studying the impact of scheduled and unscheduled news (frequently omitted in other news-related studies) in connection with high-frequency changes in bond yields and stock prices in the EU and US as well. The research points out that the effect is tremendous and significant.

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Hunt for Yield

Thanks to quantitative easing, we see record-low interest rates. While yields for short to intermediate maturities in the US are lower than the inflation but still positive, other developed markets such as Japan or European countries even have bond yields negative. Still, it does not implicate that investors have withdrawn from the fixed income markets. Both individual and institutional investors still participate in bond trading. However, the critical question is how these conditions influence the investors. Does their behavior change? Do they reach for yield and prefer riskier bonds in the search for (positive) real yields? In this blog post, we present three novel research papers that offer insights into this topic.

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ESG Investing in Fixed Income

Corporate bonds and equities of the same firm should share the same fundamentals, but does this preposition hold for the ESG scores and their implications? In the equity market, there is convincing literature that states that ESG scores lower risks or even can improve the performance of portfolios. However, it was shown that the ESG implications could not be universally applied to all countries and their markets. Novel research by Slimane et al. (2020) examines the role of the ESG in the fixed market. The paper shows that the fixed income market is probably some years behind the equity market, but the ESG is also emerging in the fixed income. The performance of ESG outperformers compared to underperformers is continually rising. In Europe, the difference is already economically significant; the rest of the world seems to lag a little. Therefore, the ESG might have a bright future also in the corporate bond market. So far, the results are promising…

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