Frank Weikai Li (Singapore Management University), et al.
October 12, 2019
We document economically large momentum profits when sorting ETFs on returns over the past two to four years. A value-weighted, long-short strategy based on ETF momentum delivers Carhart (1997) four-factor alphas of up to 1.20% per month. Neither cross-sectional stock momentum nor co-variation with macroeconomic and liquidity risks can explain ETF momentum. Instead, the post-holding period returns are most consonant with the behavioral story of delayed overreaction. While ETF momentum survives multiple adjustments for transaction costs, it may be difficult to arbitrage as the profits are volatile and concentrated in ETFs with high idiosyncratic volatility or that hold low-analyst-coverage stocks.
The “In(de-)flated” Value Premium
Yulong Sun (Bocconi University)
September 1, 2019
The value premium has disappeared over the last decade and this paper provides a risk-based explanation for its disappearance. I document a positive linear relationship among the value premium and the expected inflation at both high frequency and lower business cycle frequency. A heterogeneous cash flow model featuring inflation non-neutrality is proposed to justify the observed pattern. The estimated results suggest that value firms are more exposed to high-frequency fluctuations in aggregate consumption growth but less exposed to the low-frequency consumption risk. This finding is consistent with the documented inflation-return relationship but it contrasts with the previous findings suggesting that value firms are more sensitive to long-run consumption risk. Simulation-based results show that the positive linear relationship among the value premium and the expected inflation can be recovered when inflation is non-neutral and the relationship turns into uncorrelated when inflation is neutral. Therefore we argue that inflation non-neutrality can justify the positive relationship among inflation and value premium. Meanwhile, value firms tend to under-perform growth firms when the inflation is in low range, and it leads to the disappearance of the value premium.
Correlations, Value Factor Returns, and Growth Options
Lorenzo Schoenleber (Frankfurt School of Finance & Management)
November 6, 2019
Ex ante (expected) average equity market correlation is linked to the differential correlation dynamics of growth and value firms, as well as the value premium. It predicts the value premium, returns of growth and value firms, and the level of growth options within an economy for horizons up to one year. A production-based asset-pricing model supports the existence of a homogeneous correlation among stocks with similar growth characteristics, depending on the prevailing idiosyncratic firm variance, increasing in the value of growth options and, hence, is connected to the value premium. Due to its link to growth options and the value premium, implied correlation serves as a leading procyclical state variable. Value Index-based implied correlations improve the predictability of value-related factors.
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Dynamic Risk Management of Equity Market Factors
Roger G. Clarke (Ensign Peak Advisors), et. al
November 11, 2019
Managing the inter-temporal risk of multi-factor portfolios adds to performance, in addition to the utility investors may derive from controlling how much risk they are exposed to over time. We derive a simple closed-form formula for security weights in optimal multi-factor portfolios with an active risk budget. We test the risk control of five factors; value, momentum, small size, low beta, and profitability, and the optimal multi-factor portfolio. Our empirical research on the large-cap U.S. equity market for the last 54 years (1966 to 2019) allows for transparent performance attribution and replication of the process in other markets and time periods. We conclude that for the U.S. equity market, more active factors are better than less if each factor sub-portfolio is pure and anchored to the passive benchmark, and that dynamic management of multi-factor portfolio exposures increases realized performance.
The Leverage Factor: Credit Cycles and Asset Returns
Josh Davis (PIMCO) and Alan M. Taylor (University of California, Davis)
Research finds strong links between credit booms and macroeconomic outcomes like financial crises and output growth. Are impacts also seen in financial asset prices? We document this robust and significant connection for the first time using a large sample of historical data for many countries. Credit boom periods tend to be followed by unusually low returns to equities, in absolute terms and relative to bonds. Return predictability due to this leverage factor is distinct from that of established factors like momentum and value and generates trading strategies with meaningful excess profits out-of-sample. These findings pose a challenge to conventional macro-finance theories.
Another Look on Choosing Factors: The International Evidence
Klaus Grobys (University of Vaasa)
October 9, 2019
Extending Fama and French’s (2018) study to international equity markets, we test nested and non-nested asset pricing models for North America, Europe, Asia (excluding Japan), and Japan. For testing non-nested models, we propose a new simulation methodology using a blocks bootstrap approach. Our approach, which accounts for factor dependencies, results in lower out-of-sample Sharpe ratios across all models and countries than Fama and French’s (2018) pairs bootstrap approach. While we confirm that the six-factor model that combines the market factor and size factor with the small stock spread factors for vlaue, profitability, investment and momentum, produces the highest maximum squared Sharpe ratio in most economies, we do not find such evidence for Asia (excluding Japan). Spanning regressions reveal that size does not matter in any of the international equity markets, whereas value matters in Europe, Asia (excluding Japan), and even in Japan.
How Smart Is the Real Estate Smart Beta? Evidence from Optimal Style Factor Strategies for REITs
Massimo Guidolin and Manuela Pedio (Bocconi University)
This paper has a twofold objective. First, we contribute to the stream of literature that investigates whether traditional asset pricing factors show any predictive power for the cross-section of Real Estate Investment Trust (REIT) returns. In particular, we investigate the existence of a premium associated to the Value, Size, Momentum, Investment, and Profitability factors over the period 1993-2018. We find support for all the pricing factors but for the Profitability one. Second, we investigate whether a set of smart beta strategies, based on the combination of the identified factors, may outperform similar allocation techniques that do not exploit factors. We find that all the proposed factor-based strategies display a higher risk-adjusted out-of-sample performance than a simple buy-and-hold investment in the real estate market (proxied by the FTSE NAREIT All REITs Index). In addition, we find that when factor-based strategies are implemented, REIT-only portfolios display risk-adjusted performances comparable to those of diversified portfolios that include equity, bond, and commodities.
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