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Research Review | 20 September 2019 | Factor Investing

Summary:
Momentum with Volatility Timing Yulia Malitskaia (VKY Analytics)July 9, 2019The growing adoption of factor investing simultaneously prompted the active topic of factor timing approaches for the dynamic allocation of multi-factor portfolios. The trend represents a natural development of filling the gap between passive and active management. The paper addresses this direction by introducing the volatility-timed winners approach that applies past volatilities as a timing predictor to mitigate momentum factor underperformance for time intervals spanning the market downturn and post-crisis period. The proposed approach was confirmed with Spearman rank correlation and demonstrated in relation to different strategies including momentum volatility scaling, risk-based asset allocation, time

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Momentum with Volatility Timing
Yulia Malitskaia (VKY Analytics)
July 9, 2019
The growing adoption of factor investing simultaneously prompted the active topic of factor timing approaches for the dynamic allocation of multi-factor portfolios. The trend represents a natural development of filling the gap between passive and active management. The paper addresses this direction by introducing the volatility-timed winners approach that applies past volatilities as a timing predictor to mitigate momentum factor underperformance for time intervals spanning the market downturn and post-crisis period. The proposed approach was confirmed with Spearman rank correlation and demonstrated in relation to different strategies including momentum volatility scaling, risk-based asset allocation, time series momentum and MSCI momentum indexes. The corresponding analysis generalized existing volatility scaling strategies and brought together the two branches of the smart-beta domain, factor investing and risk-based asset allocation.

Fama–French Factor Timing: The Long-Only Integrated Approach
Markus Leippold and Roger Rüegg (University of Zurich)
June 27, 2019
There is ample evidence that factor momentum exists in the standard long–short mixed approach to factor investing. However, the excess returns are put under scrutiny due to the high implementation costs. We present a novel real-life approach that relies on the long-only integrated approach to factor investing. Instead of exploiting the potential momentum in factor portfolios, our strategy builds on the momentum of the optimal factor score weights in the integrated approach, which allows us to additionally profit from the serial dependence in the factors’ interaction effects. One limitation of short-term timing strategies is their high turnover. By including the information of the covariance matrix and minimizing the strategy’s risk to the market portfolio, we can substantially reduce turnover. The resulting timing alpha remains significant even after transaction costs in a robust statistical test framework across the major stock markets.

Factors and Advisors Portfolios
Brian Lawler (BlackRock), et al.
July 15, 2019
In the approximately 10,000 advisor portfolios that we analyze at the security level, we find there are large common patterns and significant exposures to just a few factors. Advisor portfolios are heavily exposed to economic growth, which is mostly accessed through equities, and could obtain better factor balance by including other diversifiers. Within equities, the only significant style exposure is small size; advisors, in general, can potentially improve returns by harvesting other rewarded style factors. In fixed income, advisor portfolios veer towards shorter duration which can be lengthened in an effort to provide more resilience against economic downturns. Finally, the average advisor fee is 0.54% across all portfolios, but with a wide range from 0.14% to 0.96% at the 5th and 95th percentiles, respectively. These fees, however, do not correlate highly with absolute levels of risk, active risk, or the number of positions—implying large scope to obtain greater efficiencies in taking active risk within a given fee budget.

Performance Attribution for Factor Investing
Frederic Abergel (BNP Paribas)
September 9, 2019
Understanding and mastering factor investing requires an accurate and readable factor-based performance attribution. This note presents the cross-sectional approach to performance attribution. We show that the performances of multi-factor investment portfolios are well explained by the cross-sectional regression of asset returns onto their idiosyncratic characteristics. The methodology is applied to equity and credit portfolios, with some specificities highlighted.

The Volatility Effect Revisited
David Blitz (Robeco), et al.
August 26, 2019
High-risk stocks do not have higher returns than low-risk stocks in all major stock markets. This paper provides a comprehensive overview of this low-risk effect, from the earliest asset pricing studies in the nineteen seventies to the most recent empirical findings and interpretations since. Volatility appears to be the main driver of the anomaly, which is highly persistent over time and across markets, and which cannot be explained by other factors such as value, profitability, or exposure to interest rate changes. From a practical perspective we argue that low-risk investing requires little turnover, that volatilities are more important than correlations, that low-risk indices are suboptimal and vulnerable to overcrowding, and that other factors can be efficiently integrated into a low-risk strategy. Finally, we find little evidence that the low-risk effect is being arbitraged away, as many investors are either neutrally positioned, or even on the other side of the low-risk trade.

Decarbonization Factors
Alexander Cheema-Fox (State Street Associates)
August 20, 2019
In the face of accelerating climate change, investors are making capital allocations seeking to decarbonize portfolios by reducing the carbon emissions of their holdings. To understand the performance of portfolio decarbonization strategies and investor behavior towards decarbonization we construct decarbonization factors that go long low carbon intensity sectors, industries, or firms and short high carbon intensity. We consider several portfolio formation strategies and find strategies that lowered carbon emissions more aggressively performed better. Decarbonization factor returns are associated with contemporaneous institutional flows into the factors. Buying decarbonization factors when coincident flows are positive while selling when they are negative produces significantly positive alphas. Combining decarbonization factors that have positive contemporaneous flows would provide investors with significantly superior returns and continuous exposure to low carbon portfolios. The results are more pronounced in Europe relative to the US. Our results suggest that institutional investor flows contain information about anticipated fundamentals related to climate change developments.

A Factor-Based Approach to Diversifying Oil Exposure
Harald Lohre (Invesco), et al.
June 28, 2019
Institutional investors who are highly sensitive to oil price changes are keen to reduce their risk exposure without explicitly engaging in oil price hedging. We investigate a viable alternative that considers diversifying oil exposure by employing adequate market and style factors. In particular, we present a multi-asset multi-factor solution in which quality and low volatility style factors play a crucial role in mitigating oil risk exposure while increasing overall portfolio diversification.

James Picerno
James Picerno is a financial journalist who has been writing about finance and investment theory for more than twenty years. He writes for trade magazines read by financial professionals and financial advisers. Over the years, he’s written for the Wall Street Journal, Barron’s, Bloomberg Markets, Mutual Funds, Modern Maturity, Investment Advisor, Reuters, and his popular finance blog, The CapitalSpectator.

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