The size effect assumes a negative relationship between average stock returns and firm size. In other words, it states that low capitalization stocks outperform stocks with large capitalization. Although generally accepted, the size effect keeps being challenged. Researchers have been asking how important the firm size characteristic actually is, and whether it is possible to replace the traditional size factor of Fama and French asset pricing model (1993) with more accurate factor. Recently, one potential challenger has emerged – so-called takeover factor, employed by Easterwood et al. (2022). In their study, they work on the assumption that small firms are often targets of takeovers, which gives us a different perspective on merger and acquisition news in regards to size effect. Their results show that M&A component of average returns explains the size premium entirely.

The CAPM model was a breakthrough for asset pricing, but the times where the market factor was most widely used are long gone. Nowadays, if we exaggerate a bit, we have as many factors as we want. Therefore, it might not be straightforward which factor model should be used. 

Hanauer et al. (2021) provide several insights into factor models. The authors postulate that the factor models should be examined in the international samples since this can be understood as a test for asset pricing models. The domestic Chinese A-shares stock market seems to be an excellent “playground” for the factors models, given the size of the Chinese stock market, but mainly because of its uniqueness. The paper compares the models (and factors) based on various methods (performance, data-driven asset pricing framework, test assets, turnovers and even transaction costs). Apart from valuable insights into the several less-known factors, the key takeaway message could be that the “US classic” Fama-French factor models perform poorly in China. The modified Fama-French six-factor model or q-factor is better, but overall, it seems that factor models designed for China, such as the model of Liu, Stambaugh and Yuan (2019), are the best.

Every week, through these posts, we point to interesting academic research papers. This week´s blog is slightly different, yet no less engaging. This blog includes numerous interesting charts from more than hundred charts in the CUSTOM REPORT: U.S. LARGE INDEX by the PHILOSOPHICAL ECONOMICS using OSAM Research Database. The report consists of the visually presented analysis of the U.S. Large index. The analysis includes the composition, returns, individual stocks, sector and factor allocations, and six fundamentals. The report contains comprehensive information about the large caps in the U.S. market from 1963 to 2020 and is worthy of a look.

We wish you all Merry Christmas …

The bear markets were and surely would be present in the equities in the future. While many fear them, experienced investors accept that the growth of the equity market cannot be constant and that inherent equity risk often manifests as a painful market drawdown. When someone designs a strategy, it is a general practice to check its performance during such downturns. Therefore, we can recommend an interesting novel research paper by Paul Geertsema and Helen Lu. The selected paper analyzes the risk of the most common equity factors and plots their over- or under-performance during multiple crisis periods since the Vietnam war until the COVID-19.

Authors: Paul Geertsema, Helen Lu

Title: The Risk in Risk Factors