When Does Cap-Weighting Outperform? Factor-Based Explanations
Roger G Clarke (Ensign Peak Advisors), et al.
May 1, 2018
Equity mutual fund performance can be partially explained by commonly-followed equity market factors, and the proposition that fund managers in the aggregate have more equally-weighted positions that the capitalization weighted market. Currently, the aggregate mutual fund’s active return is positively associated with the performance of pure Momentum, Small Size, and Profitability factors, and negatively associated with the performance of pure Value and Low Beta factors.
Analysing the Exposure of Low-Volatility Equity Strategies to Interest Rates
Lauren Stagnol and Bruno Taillardat (Amundi Asset Management)
November 9, 2017
At the dawn of a potential rise in rates triggered by Central Banks in both Europe and the United States, doubts are being raised about the ability of low-volatility portfolios to continue to deliver robust performance. We quantify this latent performance lag and provide empirical explanations, distinguishing parallel moves from non-parallel distortions in the yield curve. More specifically, we evaluate the implications from the low-volatility screening on the portfolio’s industrial breakdown. The conclusion shows that the overweighting of defensive industries is the main source of underperformance in a risk-on environment. However, these bets happen to be the ones that allow the strategy to outperform over a full economic cycle. Therefore, we propose a method to control the low-volatility exposure to changes in interest rates, which should be of interest to benchmarked portfolio managers.
Do Smart Beta ETFs Capture Factor Premiums? A Bayesian Perspective
Alexandre Rubesam (IESEG) and Soosung Hwang (Sungkyunkwan U.)
May 28, 2018
This paper investigates which factors matter to explain the returns of smart beta as well as conventional ETFs using a Bayesian variable selection method. Our results show different factors for these two groups of ETFs. Smart beta ETFs are well explained by the market and size factors, with weaker evidence for the betting-against-beta factor of Frazzini & Pedersen (2014), whereas conventional ETFs are well explained by a model including the market, the quality-minus- junk factor of Asness et al. (2017), and the alternative value factor of Asness & Frazzini (2013). Smart beta ETFs may benefit from their exposure to the betting-against-beta factor, but the benefit is offset by their negative alphas, while the factor exposure of conventional ETFs is purely detrimental. The performance of the models identified with the Bayesian approach are very similar to that of a benchmark model that includes several other factors in terms of alphas and R2s. Overall, our results suggest investors should be skeptical about the ability of smart beta ETFs to capture factor premiums.
Factor Performance Across Market-Driven Scenarios
Robert Bass (BlackRock), et al.
May 11, 2018
We develop a methodology to model factor returns in scenarios which are yet to occur or do not correspond to past market conditions. We infer factor performance conditional on hypothetical market-driven scenarios, which are determined by a parsimonious number of underlying policy shocks. We derive regime-dependent corresponding security and asset class returns, which are functions of factors and policy drivers. The analysis is helpful in constructing robust portfolios designed for more stable performance across various scenarios, and can aid in framing and communicating portfolio risks.
Tailoring Multi-Asset Multi-Factor Strategies
Joo Hee Lee (Invesco), et al.
May 8, 2018
To sharpen the top-down allocation perspective of their investments, investors are keen to identify and manage the most salient drivers of risk and return. For many years, the focus was on traditional market risks, such as equity, duration or credit risk. This framework can be considerably advanced when examining a given investment through the factor investing lens, which accounts for style factors, such as carry, value, momentum and quality. We put forward a variety of approaches, ranging from the traditional multi-asset allocation to factor-based tail-hedging, factor completion and a fully diversified multi-asset multi-factor proposition.
Smart Equity Investing: Implementing Risk Optimization Techniques on Strategic Beta Portfolios
Boris Fays (University of Liege), at al.
January 1, 2018
We examine the performance of risk-optimization techniques on equity style portfolios. To form these portfolios, also called Strategic Beta factors by practitioners and data providers, we group stocks based on size, value and momentum characteristics through either independent or dependent sorting. Overall, performing risk-oriented strategies on style portfolios constructed with a dependent sort deliver greater abnormal returns. On average, we observe these strategies to significantly outperform 42% of the risk-oriented ETFs listed on US exchanges, compared to 31% when the risk-oriented strategies are performed on portfolios formed with an independent sort. We attribute the outperformance yielded by dependent sorting to the fact that it provides a better stratification of the set of stocks’ opportunity and diversification properties.
Are Exchange-Traded Funds Harvesting Factor Premiums?
David Blitz (Robeco Asset Management)
August 9, 2017
Some exchange-traded funds (ETFs) are specifically designed for harvesting factor premiums, such as the size, value, momentum, and low-volatility effects. Other ETFs, however, may implicitly go against these factors. This paper analyzes the factor exposures of U.S. equity ETFs and finds that, indeed, for each factor there are funds that offer a large positive exposure and also funds that offer a large negative exposure toward that factor. On aggregate, all factor exposures turn out to be close to zero, and plain market exposure is all that remains. This finding argues against the concern that factor premiums are being arbitraged away rapidly by investors in ETFs.
Thematic Indexing, Meet Smart Beta! Merging ESG into Factor Portfolios
Jennifer Bender (State Street Global Advisors), et al.
October 18, 2017
Many investors are starting to explore ways to integrate environmental, social and governance (ESG) considerations into their portfolios. Factor portfolios and indices which integrate ESG allow investors to capture both the long-term durable factor premia while allowing them to invest in companies with attractive ESG attributes. Traditional factors and ESG both have strong investment rationale for investors with long horizons. But how should blended ESG-factor portfolios be constructed? This paper discusses several ways in which to integrate ESG in factor portfolios. We show that the choice of which approach depends on the investor’s investment rationale behind integrating ESG, desired exposure, performance expectations, and preference for conceptual consistency.
A New Book From The Capital Spectator:
Quantitative Investment Portfolio Analytics In R:
An Introduction To R For Modeling Portfolio Risk and Return
By James Picerno