stratFaber: Faber market timing strategy
In cloudcell/quantstrat: Quantitative Strategy Model Framework

Description Usage Details Indicators Signals Rules Notes References

The Faber(2007) article proposes a very simple quantitative market-timing model. They test the model in sample on the US stock market since 1900 before testing it out-of-sample in twenty other markets.

1	data('stratFaber')

The Faber(2007) article discusses a 200-day simple moving average, which is proposed in Jeremy Seigel's book "Stocks for the Long Run" (1994) for timing the DJIA. He concludes that a simple market timing strategy improves the absolute and risk adjusted returns over a buy-and-hold strategy. After all transaction costs are included, the timing strategy falls short on the absolute return, but still provides a better risk-adjusted return. Siegel also tests timing on the Nasdaq composite since 1972 and finds better absolute and risk adjusted returns.

The article implements a simpler version of the 200-day SMA, opting for a 10-month SMA. Monthly data is more easily available for long periods of time, and the lower granularity should translate to lower transaction costs.

The rules of the system are relatively simple:

Buy when monthly price > 10-month SMA
Sell and move to cash when monthly price < 10-month SMA
All entry and exit prices are on the day of the signal at the close.
All data series are total return series including dividends, updated monthly. For the purposes of this demo, we only use price returns.
Cash returns are estimated with 90-day commercial paper. Margin rates for leveraged models are estimated with the broker call rate. Again, for the purposes of this demo strategy, we ignore interest and leverage (though these can be modeled in the framework).
commissions, and slippage are excluded (though they can be modeled in the framework).
taxes are excluded.

This simple strategy is different from well-known trend-following systems in three respects. First, there's no shorting. Positions are converted to cash on a 'sell' signal, rather than taking a short position. Second, the entire position is put on at trade inception. No assumptions are made about increasing position size as the trend progresses. Third, there are no stops. If the trend reverts quickly, this system will wait for a sell signal before selling the position.

This strategy uses only a single indicator, comprised of the TTR function SMA. Parameters for this indicator include only the number of MA periods.

The Faber strategy depends on two crossover events (signals) around the SMA.

Cl.gt.SMA: type sigCrossover, if the Close price is greater than the SMA value.
Cl.lt.SMA: type sigCrossover, if the Close price is less than the SMA value.

In this strategy, each signal has a corresponding entry or exit rule.

enter: type ruleSignal, enter a buy order at market when the price crosses above the SMA using the Cl.gt.SMA signal.
exit: type ruleSignal, enter a sell order at market when the price crosses below the SMA using the Cl.lt.SMA signal.

This strategy may be improved in practice by:

utilizing trailing entry or exit orders
using a different smoothing mechanism other than SMA
the addition of stop-loss rules
the addition of some other indicator of value

Faber, Mebane T., "A Quantitative Approach to Tactical Asset Allocation." Journal of Risk Management (Spring 2007).

Siegel, Jeremy J. Stocks for the Long Run : The Definitive Guide to Financial Market Returns and Long-Term Investment Strategies (4th ed.). 436 pp. McGraw-Hill. 2007. ISBN 9780071494700. (earlier editions 1994, 1998, 2002)

cloudcell/quantstrat documentation built on May 13, 2019, 8:03 p.m.