Machine Learning Execution Time in Asset Pricing

16.January 2024

Machine Learning will quite certainly continue to be a hot topic in 2024, and we are committed to bringing you new developments and keeping you in the loop. Today, we will review original research from Demirbaga and Xu (2023) that highlights the critical role of machine learning model execution time (combination of time for ML training and prediction) in empirical asset pricing. The temporal efficiency of machine learning algorithms becomes more pivotal, given the necessity for swift investment decision-making based on the predictions generated from a lot of real-time data. Their study comprehensively evaluates execution time across various models and introduces two time-saving strategies: feature reduction and a reduction in time observations. Notably, XGBoost emerges as a top-performing model, combining high accuracy with relatively low execution time compared to other nonlinear models.

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Pragmatic Asset Allocation Model for Semi-Active Investors

11.January 2024

The primary motivation behind our study stems from an observation of the Global Tactical Asset Allocation (GTAA) strategies throughout the existing papers – the majority of them require relatively frequent rebalancing from the point of view of the ordinary investor. Portfolio rebalancing is usually done on a weekly or monthly basis, and while this period may seem overly boring and slow for the majority of traders (who like to trade on intraday or daily basis), fans of GTAA strategies are not traders; they are investors. Of course, some like to follow the ebbs and flows of the market. But a lot of investors just want to have a life. The financial market is not their hobby. However, on the other hand, they also do not want to hold just the passive buy & hold portfolio. Recognizing the demand for the semi-active strategy, we introduce our novel Pragmatic Asset Allocation.

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Quantpedia’s Research in 2023

8.January 2024


Dear readers & clients,

As we celebrate the dawn of another year, it’s a great occasion to reflect on Quantpedia’s journey in the previous 12 months. While 2023 certainly had its own share of challenges, luckily, the movements in financial markets were not as seismic as during the events that unfolded in 2022. As always, I am really proud of my whole team for their work as we continue fulfilling our primary mission to process academic research related to quant & algo trading to a more user-friendly form.

So, what are the main highlights?

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Why Do US Stocks Outperform EM and EAFE Regions?

5.January 2024

Investing in emerging markets (EM) or developed markets (DM) outside of the United States tends to follow cyclical trends. At times, it becomes popular and crowded to focus solely on U.S. stocks, while in other periods, the trend shifts to favor everything except U.S. equities. This inclination often relies on historical and past performance data, although it doesn’t guarantee identical outcomes in the future. But what drives these periods of popularity? When do U.S. markets outperform Emerging Markets or other Developed Markets? When do large-cap stocks outperform small-cap stocks, and when do growth stocks outperform value stocks? Are those ebbs and flows in the performance of major thematic investments somehow interlinked, and can we uncover some insights into why this occurs? Those are the questions we will try to answer in the following analysis.

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Top Ten Blog Posts on Quantpedia in 2023

27.December 2023

As usual, at this time of the year, let us do a short recapitulation of posts on our blog in the previous 12 months. We have published over 75 short analyses of academic papers and our own research articles on this blog in 2023. We want to use this opportunity to summarize 10 of them, which were the most popular (based on the Google Analytics tool). The top 10 is really diverse; maybe you will be able to find something you have not read yet …

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What’s the FED Perspective on Inflation Surprises and Equity Returns

21.December 2023

The period of high inflation in the 1970s prompted researchers to carefully examine the relationship between inflation and stock returns and to look for ways to avoid unexpected inflation. The year 2022 brought back inflationary pressures to the U.S. economy not seen in more than 40 years, and this has spurred new efforts to answer long-standing questions about inflation and asset prices. Authors from the Board of Governors of the Federal Reserve System (2023) bring a fresh perspective on this topic, and their paper allows us to get a FED insider’s view on the ageless question of how inflation affects equity returns.

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