Managing risk via tactical asset allocation (TAA) offers a number of encouraging paths for limiting the hefty drawdowns that take a toll on buy-and-hold strategies. But what looks good on paper can get ugly in the real world. There’s a relatively easy fix, of course: consider the total number of trades associated with a strategy as another dimension of risk.

The dirty little secret is that many TAA backtests don’t survive the smell test after considering the impact of trading frictions—particularly for taxable accounts. Deciding where to draw the line for separating the practical from the ridiculous varies, based on the usual lineup of factors—an investor’s risk tolerance, time horizon, tax bracket, etc. But there’s an obvious place to start the analysis. Let’s kick the tires for some perspective using some toy examples.

An obvious way to begin is by using the widely cited TAA model outlined by Meb Faber in what’s become an staple in the literature for this corner of finance—“A Quantitative Approach to Tactical Asset Allocation”. The original 2007 paper studied the results of applying a simple system of moving averages across asset classes. The impressive results are generated by a model that compares the current end-of-month price to a 10-month average. If the end-of-month price is above the 10-month average, buy or continue to hold the asset. Otherwise, sell or hold cash for the asset’s share of the portfolio. The result? A remarkably strong return for the Faber TAA model over decades, in both absolute and risk-adjusted terms, vs. buying and holding the same mix of assets.

The question is whether running the Faber model as presented would be practical after deducting trading costs and any taxable consequences? Let’s ask the same question for two other simple strategies:

Percentile strategy: apply the rules in Faber but limit the buy/hold signal so that it only applies when the asset price is above the 70th percentile for the ratio of the price above the trailing 10-month average. The same logic applies in reverse for the sell signal: the asset price is below the 30th percentile for the ratio of price below the 10-month moving average. For signals between that 30th-70th percentile range, the previous signal remains in force.

Relative-strength strategy: apply the Faber rules but limit the buys to assets in the top half of the performance results for the target securities, based on the trailing 10-month results. The same rule applies in reverse for triggering a sell signal. In other words, sell only assets in the bottom half of the performance results via the trailing 10-month period if a sell signal applies.