Exploring Dual Momentum Strategies

Dual Momentum Investing

Gary Antonacci‘s forthcoming book Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk (New York: McGraw-Hill, 2014) is currently Amazon.com’s top-ranked book for “momentum investing”. Antonacci’s 2013 paper ‘Risk Premia Harvesting Through Dual Momentum’ (PDF) contains a preview – including a great opening discussion of why the momentum anomaly exists in the stockmarket and why behavioural finance factors are likely to be involved.


Antonacci distinguishes between two types of mometum strategies: (1) cross-sectional / relative momentum — used in long-short and index tracking strategies, and in the Relative Strength Indicator in ‘chartist’ technical analysis; and (2) absolute momentum – a time series phenomena where an asset’s prior price helps to determine its current price – used in trend-following.


Antonacci’s dual mometum framework combines both types of momentum to extract alpha from volatile asset classes. He uses a modular approach to portfolio construction. Treasury bills provide an initial hurdle rate for relative momentum, with a 12 month lookback period. Antonacci then uses absolute return increase the basis point return, whilst decreasing the portfolio’s volatility and maximum drawdown. He has tested the dual momentum strategy in fixed income, equity, and real estate REIT asset classes, and with other market factors such as credit risk and economic volatility.


The paper’s final paragraph summarises Antonacci’s dual momentum strategy:


The combination of relative and absolute momentum makes diversification more efficient by selectively utilizing assets only when both their relative and absolute momentum are positive, and these assets are more likely to appreciate. A dual momentum approach bears market risk when it makes the most sense, i.e., when there is positive absolute, as well as relative, momentum. Module-based dual momentum, serving as a strong alpha overlay, can help capture risk premia from volatile assets, while at the same time, defensively adapting to regime change. [emphasis added]


Dual momentum investing is thus an alpha extracting strategy that combines two different forms of momentum to diversify the portfolio, and to lower volatility. The two different forms of momentum identify a set of market assets that are highly probable to appreciate in value in the near-term, particularly in periods of economic volatility.


I suggest that momentum investors adapt to these market changes by possibly buying from distressed debt value investors near market lows that show signs of recent asset appreciation – and through identifying herding and overshoot conditions – selling to trend-following, news effect, and late-coming retail investors or mutual / pension fund managers. Thus, an understanding of game theoretic reasoning – as argued by the late trading psychologist Ari Kiev whilst at the hedge fund SAC – and population ecology models applied to market microstructure – might be helpful to momentum investors.

19th June 2013: The SmallCap Value Premia

Richard C. Marston‘s Portfolio Design: A Modern Approach to Asset Allocation (Hoboken, NJ: John Wiley & Sons, 2011) is my work commute read for this week. Wiley has excerpts here.


Portfolio Design focuses on return drivers and risk premia for the major asset classes used to allocate assets in diversified portfolios. The ‘modern approach’ includes a focus on data analytics and the available evidence base; a review of recent (Fama-French-influenced) quantitative finance studies; and insights on index benchmarks and portfolio construction.


I’m a couple of chapters in: Marston focuses on smallcap and value return drivers, in contrast to largecap and growth stocks. Although he doesn’t explore this Marston’s insights in his opening chapters are also relevant to two other areas:


  • Penny stick promoters rely on ‘crowded trades’ and rational herding: this is often what the ‘free’ investment newsletters and watchlists are for, to create drawdown market dynamics in relatively illiquid stocks.
  • Venture capital’s asymmetric returns can have large payoffs if opportunity evaluation screening works, and if stage one financing backs a break-out company that creates a new, large market or is a successful disruptive entrant into existing markets.


It’s interesting to see how an experienced, endowment investment adviser handles index benchmarks, portfolio construction, and specific return drivers. Since he is also on Yale’s investment committee Portfolio Design also makes an interesting counterpart to the influential Yale Swensen model detailed in Swensen’s Pioneering Portfolio Management: An Unconventional Approach to Institutional Investment (rev ed.) (New York: The Free Press, 2009).

Errors In Quantitative Models & Forecasting

Could the roots of the 2007 subprime crisis in collateralised debt obligations (CDOs) and residential mortgage-backed securities (RMBS) lie in financial analysts who all used similar assumptions and forecasts in their quantitative models?

Barron’s Bill Alpert argues so
, pointing to a shift of investment styles after the 2000 dotcom crash from sector-specific, momentum and growth stocks to value investing.  Investment managers who prefer the value approach then constructed their portfolios with ‘stocks that were cheap relative to their book value.’  In other words, the value investors exploited several factors — the gaps in asset valuation, asymmetries in public and private information sources, price discovery mechanisms and market participants — which contributed to mispriced stocks compared to their true value.

However, the value investing strategy had a blindspot: many of the stocks selected for investment portfolios also had a high exposure to credit and default risk.  The 2007 subprime crisis exposed this blindspot, which adversely affected value investors whose portfolios had stocks with a high degree of positive covariance.

Alpert quotes hedge fund manager Rick Bookstaber who believes that financial engineers have accelerated crises and systemic risks via the complex dynamics of new futures contracts, exotic options and swaps.  These new financial instruments create interlocking markets (capital, commodities, debt, equity, treasuries) which have the second-order effects of larger yield curve spreads and trading volatility.  Alpert and Bookstaber’s views echo Susan Strange‘s warnings a decade ago of ‘casino capitalism’  and ‘mad money’ as unconstrained forces in the international political economy.

Quantitative models also failed to foresee the 2007 subprime crisis due to excessive leverage, difficulties to achieve ‘alpha’ or above-market returns in market volatility, and the separation of risk management from the modelling process and testing.  Other commentators have raised the first two errors, which have led to changes in portfolio construction and market monitoring.  Nassim Nicholas Taleb has built a second career on the third error, with his Black Swan conjecture of high-impact events, randomness and uncertainty (see Taleb’s Long Now Foundation lecture The Future Has Always Been Crazier Than We Thought).

Alpert hints that these three errors may lead to several outcomes: (1) a new ‘arms race’ between investment managers to find the new ‘factors’ in order to construct resilient investment portfolios; (2) the integration of Taleb’s second-order creative thinking and risk management in the construction of financial models, in new companies and markets such as George Friedman’s risk boutique Stratfor; and (3) a new ‘best of breed’ manager who can make investment decisions in a global and macroeconomic environment of correlated and integrated financial markets.