Refkexiones de Hussman. La próxima semana volvemos.

“The most useful part of Dow Theory, and the part that must never be forgotten

for even a day, is the fact that no price movement is worthy of consideration unless the movement is confirmed by both averages. Many who claim an understanding of the Theory consider only the movements of the Industrial stock average if they happen to be trading in industrials. Some even chart only the one average and profess to be able to interpret the movements correctly. It is true that there are times when such conclusions seem justified, but over any extended period such procedure inevitably results in disaster… When the Averages disagree, it’s usually a sign of distribution.”

I’ll add as a side note that veteran Dow Theorist Richard Russellexpresses enormous concerns today about market action, partly (though certainly not entirely) because of the joint breakdown in the Industrials and the Transports a few months ago, and the subsequent failure of the Dow Transports to confirm the rally in the Dow Industrials since then. Price-volume behavior is also problematic here. As William Hamilton observed a century ago, a market that becomes “dull on rallies and active on declines” should not be trusted. From that standpoint, the wholesale collapse of trading volume in recent weeks is almost creepy.

Based on a century of historical data, the multiple-sensor approach is what turns out to be most effective in our own work. In that sort of analysis, concepts like “breakout” and “crossover” turn out to be far less useful than concepts like “uniformity” and “divergence.” While our broad measures of market action have been unfavorable for some time as stocks have played hot potato between periods of overbought froth and periods of ragged market internals, we now see an unusual combination of both. Even the best trend-following measures we track broke down in mid-April as a result of clear deterioration in market internals (see No, Stop, Don’t), and we have not yet observed a recovery on that front.

So for those who have asked whether we can reduce the extent of our hedging until the trend-following components of market action turn negative, the simple answer is that they’ve already done so. Moreover, I should note that even very popular trend-following approaches such as the 200-day moving average, the “Golden cross” (50-day vs. 200-day), the 34-week crossover, the 55-week crossover and others, have produced flat or negative total returns – even before transaction costs – since the April 2010 market peak. Saying that some trend-following measures are “positive” is much different than saying that they are promising.

Still, it’s worth repeating that we addressed a more general trend-following issue earlier this year, in order to reduce our use of actual put options in a world where monetary policies make investors believe that free ones can be taken for granted. Consistent with the analysis above, historical tests indicated that it would be unprofitable to simply remove hedges whenever the trend components are favorable. A strategy like that has no exit criteria other than a trend breakdown, and when stocks are severely overbought, the required decline can be very steep and incur a great deal of loss before establishing a hedge.

Still, that fact suggested its own solution, which was to allow sufficiently overbought conditions to act as an alternate exit criterion. That approach turned out to be very effective, particularly in reducing the frequency of “staggered strike” hedges without reducing their long-term benefit. Accordingly, we added criteria earlier this year to restrict the use of “staggered strike” positions, requiring not only a very negative return/risk estimate, but also either negative trend-following measures or the presence of hostile indicator syndromes (e.g. “overvalued, overbought, overbullish” conditions). The limited set of instances that survive those criteria are historically associated with average market losses on the order of between -25% to -50% at an annual rate, depending on the particular set of syndromes involved. There’s not a chance that I would ignore that data here.