How Counter Trend Models Can Adapt to Changing Market Environments
Trend following methodologies attempt to buy into market strength and sell into market weakness. Counter trend methodologies do the opposite, buying into market weakness and selling into market strength. Trend following works under the premise that investments tend to trend over time and works best over intermediate term time frames (1-6 months). Counter trend models work under the premise that over shorter time periods (daily to weekly) markets are dominated by noise, fear, and greed, causing them to overshoot to the upside and downside before snapping back to equilibrium.
Counter trend models can add needed diversification to tactical portfolios dominated by trend following models. Trend following works extremely well in straight up or down markets, but doesn't work is well in choppy markets or equity peaks. Trend following models also can't participate in bear market rallies. Counter trend models don't work as well in straight up or down markets but do very well in choppy markets and equity peaks. They can also participate in bear market rallies.
The basic idea behind counter trend models is to use some measure to determine whether a market is oversold, overbought, or at equilibrium. These could be static models that perhaps buy on n day lows and sell on n day highs or they could use some sort of dynamic logic. Because markets are dynamic I have not seen static counter trend models work well over long periods of time. Dynamic models are usually a much better option.
There are two market factors that will determine how a counter trend model will react and perform, noise and volatility. Noise is a measure of whether the market has a direction or not, while volatility measures the extent of up and down moves. Market noise will determine how well a counter trend model will perform while volatility will determine what types of market moves a counter trend model will need for it to determine whether a market is overbought or oversold. Counter trend models tend to work best in markets that are noisy and volatile. They tend to work worst in markets that have low noise and high volatility (trend following models work best in this environment).
So far in 2015 we have had an extremely noisy market with no direction, but volatility has been low. In this environment---high noise, low volatility---an adaptive counter trend model wouldn't need large moves to determine whether the market is overbought or oversold and it could move in and out of noisy markets very frequently. This is what we have seen in our counter trend models this year. In a high volatility market, adaptive models would need larger changes to move in and out of markets.
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