Last Updated on 10 February, 2024 by Rejaul Karim
In their research paper “Betting Against Betting Against Beta,” Robert Novy-Marx and Mihail Velikov delve into the complexities of the BAB factor, which has gained attention for its impressive performance and influential implications.
Frazzini and Pedersen’s BAB factor, similar to Black’s beta-arbitrage, has sparked considerable interest in the financial community. However, Novy-Marx and Velikov shed light on the non-standard methods used in its construction, revealing predictable biases that raise questions about its underlying performance.
The non-transparent equal weighting of stock returns and the non-standard beta estimation procedure have generated debate, given that its performance may not align with the theory it claims to support. With a focus on factor models, beta-arbitrage, and asset pricing, this study delves into the perplexing complexities of BAB and its implications in the realm of defensive equity and non-standard methods.
Abstract Of Paper
Frazzini and Pedersen’s (2014) Betting Against Beta (BAB) factor is based on the same basic idea as Black’s (1972) beta-arbitrage, but its astonishing performance has generated academic interest and made it highly influential with practitioners. This performance is driven by non-standard procedures used in its construction that effectively, but non-transparently, equal weight stock returns. For each dollar invested in BAB, the strategy commits on average $1.05 to stocks in the bottom 1% of total market capitalization. BAB earns positive returns after accounting for transaction costs, but earns these by tilting toward profitability and investment, exposures for which it is fairly compensated. Predictable biases resulting from the paper’s non-standard beta estimation procedure drive results presented as evidence supporting its underlying theory.
Original paper – Download PDF
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Simon Business School, University of Rochester; National Bureau of Economic Research (NBER)
Pennsylvania State University
In conclusion, the study of Frazzini and Pedersen’s Betting Against Beta (BAB) factor, as presented by Novy-Marx and Velikov, brings into question the foundations of its impressive performance.
The non-transparent equal weighting of stock returns, driven by non-standard procedures, and the predictable biases resulting from non-standard beta estimation procedures have called into doubt the credibility of BAB’s underlying theory. While BAB earns positive returns after factoring in transaction costs, it appears to do so by tilting toward profitability and investment, rather than through the strategy it purports to employ.
This raises concerns about the alignment between BAB’s performance and the theoretical principles it claims to uphold. By shedding light on these complexities, this study presents vital considerations for practitioners and academics engaged in factor models, beta-arbitrage, defensive equity, non-standard methods, and asset pricing.
What is the main focus of the paper “Betting Against Betting Against Beta” by Novy-Marx and Velikov?
The main focus of the paper is to critically examine Frazzini and Pedersen’s Betting Against Beta (BAB) factor, which has gained significant attention in both academic and practitioner circles due to its impressive performance. The authors specifically investigate the non-standard methods used in constructing the BAB factor and raise questions about its underlying performance.
What key issues with the BAB factor do the authors highlight in their research?
The authors highlight several key issues with the BAB factor, including the non-standard procedures used in its construction. They draw attention to the non-transparent equal weighting of stock returns and the non-standard beta estimation procedure, which they argue may introduce biases and question the credibility of BAB’s underlying theory. The study suggests that BAB’s performance may not align with the theory it claims to support.
What is the significance of the non-standard procedures in the construction of the BAB factor?
The non-standard procedures in the construction of the BAB factor, such as non-transparent equal weighting of stock returns and non-standard beta estimation, are considered significant because they may introduce biases. The authors argue that these biases, along with predictable biases resulting from the beta estimation procedure, raise concerns about the reliability and alignment of BAB’s performance with its underlying theoretical principles.