fundamental analysis

Out-of-Sample Test of Formula Investing Strategies

January 16, 2025

Can we simplify the complexities of the stock market and distill them into a simple set of quantifiable metrics? A lot of academic papers suggest this, and they offer formulas that should make the life of a stock picker easier. Some of the most compelling methodologies within this realm are the F-Score, Magic Formula, Acquirer’s Multiple, and the Conservative Formula. These quantitative strategies are designed to identify undervalued stocks with robust fundamentals and potential for high returns. But do they really work out-of-sample? A new paper by Marcel Schwartz and Matthias X. Hanauer tries to answer this interesting question…

Design Choices in ML and the Cross-Section of Stock Returns

December 17, 2024

For those who have not yet had the chance to read it, we recommend the latest empirical study by Minghui Chen, Matthias X. Hanauer, and Tobias Kalsbach, which shows that design choices in machine learning models, such as feature selection and hyperparameter tuning, are crucial to improving portfolio performance. Non-standard errors in machine learning predictions can lead to substantial portfolio return variations, and authors are highlighting the importance of robust model evaluation techniques.

Valuing Stocks With Earnings

October 1, 2024

Today, we will venture a little into the fundamental analysis corner, and we will give you a glimpse of an intriguing paper (Hillenbrand and McCarthy, 2024) that discusses the advantages of using ‘Street’ earnings over traditional GAAP earnings. The paper suggests that ‘Street’ earnings provide better valuation estimates and improved financial analysis. Is this a way how to improve the performance of the struggling equity value factor?

Payout-Adjusted CAPE

August 19, 2024

Professor Robert Shiller’s CAPE (cyclically adjusted price-to-earnings) ratio is well-known among the investment community. His methodology for assessing a valuation of the U.S. equity market is undoubtedly the most cited and discussed. Therefore, it’s not surprising that there exists quite a lot of papers that try to refine and expand the CAPE’s methodology. One such last attempt is the work of James White and Victor Haghani, whose research paper revolves around the use of a modified version of the Cyclically-Adjusted Price Earnings (CAPE) ratio, termed P-CAPE. Their methodology aims to improve the estimation of long-term expected real returns of the stock market by incorporating the dividend payout ratio into the traditional CAPE metric.

What’s the Key Factor Behind the Variation in Anomaly Returns?

October 13, 2023

In a game of poker, it is usually said that when you do not know who the patsy is, you’re the patsy. The world of finance is not different. It is good to know who your counterparties are and which investors/traders drive the return of anomalies you focus on. We discussed that a few months ago in a short blog article called “Which Investors Drive Factor Returns?“. Different sets of investors and their approaches drive different anomalies, and we have one more paper that helps uncover the motivation of investors and traders for trading and their impact on anomaly returns.

Performance of Factor Strategies in India

August 31, 2023

India is a big emerging market, actually the second biggest after China. We primarily look at developed markets, mostly the U.S. and Europe, and from Emerging Markets, China at most, and we are aware that we neglect this prospective country. We would like to correct this notion and give attention to a country that is (along with China) being cited as a new potential rising superpower and already looking to take the lead of Emerging Markets (EM) countries. Today, we would like to review the paper that analyzes the performance of main equity factors (with an emphasis on the Quality factor) and is a good starting point to understand the specifics of factor investing strategies in India.

Factor Trends and Cycles

May 30, 2023

Bearish trends or deep corrections in international equity markets starting in 2022 and rising interest rates worldwide brought investors’ attention back to not only once-proclaimed dead factor investing. From long-run and short run, during different market cycles, different factors behave differently. What’s fortunate is that it is pretty predictable to some extent. Andrew Ang, Head of Factor Investing Strategies at BlackRock, in his Trends and Cycles of Style Factors in the 20th and 21st Centuries (2022), used Hodrick-Prescott (HP) filter and spectral analysis to investigate different models to draw some general conclusions on most-widely used factors. We will take a look at a few of quite the most interesting ones of them.

How Often Should We Rebalance Equity Factor Portfolios?

May 10, 2022

Quantpedia has already covered a countless number of factor investing strategies and articles, from strategies in our Screener to multiple blog posts. Therefore, we can confidently say that we do like factor investing. However, there is always new research with a unique point of view. For example, we recently found a paper focused on the decay of the factor exposures of equity factor strategies. The study examines five factors: Value, Momentum, Quality, Investment, and Low Volatility, across 12 developed and emerging markets over a 20-year period. This research aims to find out how long it takes for a factor to decay after the portfolio is assembled. In other words, how often should the portfolio be rebalanced?

VIX-Yield Curve Cycles May Predict Recessions

January 21, 2022

Since recessions and bear markets come hand in hand for several asset classes, recession predictions have always been the foremost concern. The yield curve slope, defined as the difference between long and short-term rates, is the leading indicator backed by numerous research papers. Hansen (2021) builds on this theorem, but the author improves the recession prediction by his empirical observation that the VIX index (index of implied equity volatility or fear index) and the slope co-move in counterclockwise cycles, which align with business cycles.

How News Move Markets?

November 12, 2021

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.