Momentum based strategies, in which both trend-following and relative strength techniques are grouped, have been applied as investment strategies for over a century, and no doubt, momentum is one of the most widely discussed and researched investment strategies. There are various ways how to utilize this anomaly for the profit; a simple one is based on using momentum filter separately in each asset class and then combining asset classes into the one portfolio (as it is done in the “#1 – Asset Class Trend Following” strategy).
However, another way is to use the rotational momentum trading system, in search of the best asset class at the time of the investment. There is a simple way how to achieve that; the rotational momentum system compares the performance of all asset classes. It picks only the best-performing assets from the investment universe into the investor’s portfolio. The results showed robust performance across measurement periods as well as over the past eight decades. Yet, the trading rule is simple, same as the execution: the portfolio is rebalanced every month, and the portfolio’s holdings are rotated so that only the best-performing assets are held – there comes the name “rotational system“. Various assets could be used in this system, for it to be more precise: equities, bonds, commodities, and REITs.
We present Mebane Faber’s rotational system as a source paper (and his asset choices in it); however, the basic principle is verified by many other academics. For example, Kessler and Scherer in “Macro Momentum and the Economy” have found strong evidence for momentum across various asset classes. Their investment strategy that simultaneously looks at relative momentum between currencies, equities, real estate, commodities, and equities leads to stable and robust outperformance that survives both transaction costs as well as various stability tests. There are many other variants we would like to recommend to review, and those strategies can be found in the “Related papers” section.

Fundamental reason

No doubt, momentum is widely accepted among the vast majority of academic researchers as one of the strongest return generating factor. Moreover, this anomaly is still receiving a lot of attention from the academic world. As a result, a potential investor can find a lot of momentum-based strategies; however, it might be worth considering whether the strategy would work in the future. The reason to rotate various asset classes is simple; everything is based on the fact that various asset classes have a different sensibility to business cycles (likewise stocks from different industry sectors also have different sensitivity). Therefore it is possible to rotate between asset classes and hold only asset classes with the highest probability of returns and the lowest probability of losses.
According to the Kessler and Scherer, and their work “Macro Momentum and the Economy”, the success of the rotational strategy can be attributed to predictable variations in the investment opportunity set where excess returns can be interpreted as payoffs for rational investors hedging against predictable changes in investment opportunity set. Last but not least, the applicability of this strategy is ensured by the fact that the practitioner today can choose from thousands of mutual funds, ETFs, or closed-end funds. Many of these funds can be traded for $8 a trade or less, and many mutual funds and ETFs are now commission-free at some online brokers.

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Markets Traded
bonds, commodities, equities, REITs

Financial instruments
CFDs, ETFs, funds, futures

Confidence in anomaly's validity
Strong

Backtest period from source paper
1973-2009

Notes to Confidence in Anomaly's Validity

Indicative Performance
14.49%

Period of Rebalancing
Monthly

Notes to Indicative Performance

per annum, data from exhibit 10.6 – strategy using top 3 asset classes


Notes to Period of Rebalancing

Estimated Volatility
11%

Number of Traded Instruments
5

Notes to Estimated Volatility

data from exhibit 10.6 – strategy using top 3 asset classes


Notes to Number of Traded Instruments

5 (in our example), usually under 10


Maximum Drawdown
39.84%

Complexity Evaluation
Simple strategy

Notes to Maximum drawdown

data from exhibit 10.6 – strategy using top 3 asset classes


Notes to Complexity Evaluation

Sharpe Ratio
0.78

Simple trading strategy

The investment universe consists of 5 ETFs (SPY – US stocks, EFA – foreign stocks, BND – bonds, VNQ – REITs, GSG – commodities). Pick 3 ETFs with the strongest 12-month momentum into your portfolio and weight them equally. Hold for one month and then rebalance.

Hedge for stocks during bear markets

Partially - Tactical asset allocation strategy like the one proposed by Mebane Faber in his famous paper “A Quantitative Approach to Tactical Asset Allocation” usually contains equity-like risk assets, and the TAA strategy tries to rotate out of them during the time of stress. Therefore the proposed strategy isn’t mainly used as an add-on to a portfolio to hedge equity risk directly. Still, it is more an overlay that can be used to manage the percentual representation of equities (or “equity-like assets”) in a portfolio. The tactical asset allocation framework can decrease the overall risk of equities in a portfolio, and it can improve the risk-adjusted returns.

Source paper
Strategy's implementation in QuantConnect's framework (chart+statistics+code)
Other papers

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