Abstract
We propose a single factor mixed effects panel data model to compose an arbitrage portfolio identifying differences in firm-level latent fundamentals. Furthermore, we show that even though the characteristics that affect returns are unknown variables, it is possible to identify the strength of the combination of these fundamentals for each stock by following a simple approach using historical data. As a result, a trading strategy that buys the stocks with the best fundamentals (strong fundamentals portfolio) and sells the stocks with the worst ones (weak fundamentals portfolio) realized significant risk-adjusted returns for the period between July 1986 and June 2008. In this case, this arbitrage portfolio generated a significant monthly risk-adjusted return of 2.42% considering the Carhart (1997) 4-factor model and presented a market sensibility (CAPM Beta) of 0.14. For robustness we performed sub period and seasonal analyses as well as an adjustment by trading costs. Finally, we find further empirical evidence to profit from the usage of a simple investment rule identifying fundamentals from structure of pass returns.
Highlights
One of the major issues in investment management is the quest for an efficient securities selection criterion that can distinguish prospective winners from losers
We found empirical evidence that a zero net investment portfolio, structured with a long position in a portfolio composed of stocks with the best combination of the N latent fundamental factors and a short position in a portfolio composed of stocks with the worst combination of the N fundamental factors, generated positive and statistically significant risk-adjusted returns, considering the Carhart (1997) 4-factor model
We argue that the unrestricted model for the structure of stock returns is given by the market variable and N firm-specific latent fundamentals characteristics
Summary
One of the major issues in investment management is the quest for an efficient securities selection criterion that can distinguish prospective winners from losers. The value and growth investing principles are based on well-known deviations that persist in the U.S as well as in international markets; attracting a great deal of academic empirical research (Chan & Lakonishok, 2004). Fama & French (1992, 1996) argue that the market is efficient and that value investing has better performance because value stocks are riskier. Another explanation is offered by Lakonishok et al (1994), who explain the value premium anomaly by arguing that investors’ cognitive biases and the agency costs of professional investment lead individuals and institutional investors to prefer growth stocks and dislike value stocks
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
