Research Review | 13 Aug 2015 | Portfolio Management

Momentum and Markowitz: A Golden Combination
Wouter J. Keller, Adam Butler, and Ilya Kipnis
May 16, 2015
Mean-Variance Optimization (MVO) as introduced by Markowitz (1952) is often presented as an elegant but impractical theory. MVO is “an unstable and error-maximizing” procedure (Michaud 1989), and “is nearly always beaten by simple 1/N portfolios” (DeMiguel, 2007)… In our opinion, MVO is a great concept, but previous studies were doomed to fail because they allowed for short-sales, and applied poorly specified estimation horizons… In this paper we apply short lookback periods (maximum of 12 months) to estimate MVO parameters in order to best harvest the momentum factor. In addition, we will introduce common-sense constraints, such as long-only portfolio weights, to stabilize the optimization. We also introduce a public implementation of Markowitz’s Critical Line Algorithm (CLA) programmed in R to handle the case when the number of assets is much larger than the number of lookback periods. We call our momentum-based, long-only MVO model Classical Asset Allocation (CAA) and compare its performance against the simple 1/N equal weighted portfolio using various global multi-asset universes over a century of data (Jan 1915-Dec 2014). At the risk of spoiling the ending, we demonstrate that CAA always beats the simple 1/N model by a wide margin.

A Practitioner’s Defense of Return Predictability
Blair Hull and Xiao Qiao
July 22, 2015
Revisiting the issue of return predictability, we show there is substantial predictive power in combining forecasting variables. We apply correlation screening to combine twenty variables that have been proposed in the return predictability literature, and demonstrate forecasting power at a six-month horizon. We illustrate the economic significance of return predictability through a walk-forward simulation, which takes positions in SPY proportional to the model forecast equity risk premium. The simulated strategy yields annual returns more than twice that of the buy-and-hold strategy, with a Sharpe ratio four times as large. To eliminate look-ahead bias, we perform additional simulations including variables only as they are discovered in the literature. Results show similar annual returns and Sharpe ratios. While a market-timing strategy outperforms the market, it is difficult to implement.

Factor-Based v. Industry-Based Asset Allocation: The Contest
Marie Briere and Ariane Szafarz
July 2015
Factor investing has emerged as the new paradigm for long-term investment. Applied to equities, factor investing is probably the most serious contender to the classical industry-based approach to asset allocation. By organizing a multi-trial contest opposing factor investing and sector investing, we address two questions: 1) Are the excess returns of factor investing offset by higher risks, and if so, are factor-specific risks eliminable by means of factor diversification? 2) How does factor investing perform during crisis times? Our results suggest that this form of investing is the best strategy when short sales are permitted. It also outperforms industry-based allocation during expansion and bull periods. In contrast, sector investing offers defensive opportunities to asset managers since it delivers better risk-return trade-offs for long-only portfolios during recessions and bear periods. Overall, factor investing keeps its promises, but it still has a long way to go before it can oust sector investing.

Tactical Alpha: A Quantitative Case for Active Asset Allocation
Adam Butler, et al.
September 3, 2014
Grinold linked investment alpha and Information Ratio to the breadth of independent active bets in an investment universe with his Fundamental Law of Active Management. Breadth is often misinterpreted as the number of eligible securities in a manager’s investment universe, but this ignores the impact of correlation. When correlation is considered, a small universe of uncorrelated assets may explain more than half the breadth of a large stock universe. Given low historical correlations between global asset classes in comparison with individual securities in a market, we make the case that investors may be well served by increasing allocations to Tactical Alpha strategies in pursuit of higher Information Ratios. This hypothesis is validated by a novel theoretical analysis, and bolstered by two empirical examples applied to a global asset class universe and U.S. stock portfolios.

Factor Investing Revisited
David Blitz
July 3, 2015
This paper takes another look at the recommendation of Blitz [2012] to allocate strategically to the value, momentum and low-volatility factor premiums in the equity market. Five years of fresh data shows that such a factor investing strategy continued to deliver out-of-sample. The potential added value of the two new factors in the Fama-French 5-factor model, operating profitability and investment, is investigated and found to depend critically on the performance metric that is considered most important. The paper also reviews the role of small-cap stocks, factor timing, long-only versus long-short portfolio construction, international evidence and factor investing beyond equities.

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