Moving averages, Breakout strategies, etc. are no match for the Dow Theory
No new from the markets. Primary and secondary trends unchanged. And hence, I will further cogitate about the Dow Theory. Such moments of market lull are good to rethink one’s premises.
The more I know the entrails of the Dow Theory, the more fascinated I am about it. Clearly, Charles Dow was a genius, since mere chance cannot devise such a perfect way to determine the trend. And due credit should be given to Rhea and Schannep whose work has further streamlined Dow's insights.
When Dow Theorists appraise secondary reactions (hereinafter, “secondaries”), we routinely mention the “time” (at least 10 calendar days) and “extend”(at least 3% move) requirements. We are so used to it that we don’t give it a second thought.
However, by bringing together the time and extent element, the Dow Theory has nothing to do with its two closest competitors: Moving averages and sheer momentum (be it relative or absolute measured as a percentage change).
To begin with, the extent and duration requirements used by the Dow Theory to appraise secondaries are both non parametric. And this is a very good thing.
If we want to determine the trend using a moving average, we are just using the duration (time series) element, but have no regard to the underlying extent of the move (hence false signals on week trends and multiple moving average crossovers). A moving average is blind to the previous price structure (i.e. whether there was big momentum before the crossover, weak momentum, how many days of big momentum, how many days of vanishing momentum, etc.). Furthermore, a moving average is the best example of a parametric system. Parametric systems, as I have explained here and here, are undependable and highly unstable.
Sheer momentum strategies have no regard to time element and focus blindly on the “extent” element. Thus, a stock that may have been languishing for 11 months, suddenly rockets in month 12, and suddenly ranks among, i.e. top 1 percent. However, sheer magnitude without regard to the time elements (what did the stock do in the 11 preceding months) can be misleading and prone to false signals too. Furthermore, if we demand a determined percentage change threshold (i.e. it must be up 30% in the last 12 months), we are again toying with parameters, which may backfire in real life. As an aside, my personal take, is that the best way to use momentum is as relative strength, that is, by just taking the top “x” percent of a given universe, irrespective of their individual percentage gain. By doing this, we try to get rid of parameters as much as possible, being the only “weak” parameter the ranking percentage. In a future post of this Dow Theory blog I will write about “strong” parameters (dangerous, as they are prone to “overfitting” and share all the flaw of parametric systems) and “weak” parameters (which, are less dangerous, and less prone to over fitting). To say that I will select the top 10% high relative stocks of the S&P 500 is much less dangerous than selecting the stocks that gained more than 26.58% in the last 12 months.
Lack of distinction between “safe” and “unsafe” parameters misleads many system testers. For many years, I erroneously thought that any parameter was bringing my system closer and closer to curve fitting. This is not so. Thus, even if we considered the 3% minimum extent requirement of the Dow Theory as a “parameter”, we can see that it is a very “safe” one. You can successfully apply the Dow Theory, if in instead of 3% you take 3.5%, 4% or 5% as your definition of minimum movement...You just will get less secondaries and fewer signals (and more ample initial stops) but the system will perform roughly equally well. You will stand to lose a little bit more on some (not all) losing trades, but you will be less whipsawed. This proves that the 3% requirement is not a “parameter” or, if you deem it to be, a quite harmless one. Mutatis mutandis we can say the same of the “time” extend for a secondary to be appraised.
So both momentum and moving averages have two salient flaws.
a) Tend to be quite “parametric” (the worst offender are moving averages).
b) Each ignores the complementary element which would confirm (time should confirm extent, and extent should confirm time).
The Dow theory is non parametric. The time requirement (i.e. 10 days for sec reaction) and minimum extent (3%) are just this: minimum requirements to weed out noise. Called them if you want “weak, harmless, parameters”. However, there is no preset level of what constitutes the time and extent element of a secondary reaction which is the cornerstone of the Dow Theory (as primary bull and bear market signals depend on the breakup or breakdown of the highs and lows of secondaries and hence it is vital to properly ascertain them). You can have secondaries with just 4% downward movement and 20 days formation period , or with just 10 days and a 7% decline, all combinations are possible, and hence we see the beauty of the Dow Theory that it adapts to market conditions unlike inflexible moving averages. As an aside, the Dow Theory stops (secondary reaction lows) are not set at arbitrary levels (i.e. 20 days lows) but rather correspond with market action. A 20 days lows stop can be too narrow if the market has been raging of late (or too wide, if the market underwent a huge rally), whereas the Dow Theory stop based on the lows of the secondary reaction "adapts" to recent market action. And hence it can be larger or narrower depending precisely on market action.
Therefore, the net superiority of the Dow Theory is built in into the system: We depend on two non parametric variables: time and extent. So minimum time should confirm minimum extent and viceversa….So we can find the principle of confirmation even inside the entrails of the Dow Theory. If you add “external confirmation” (the classic rule “two indices” should confirm) with the “internal” one (“time and extent” should confirm), then you have in your hands, what I think is the most reliable tool to gauge the trend and keep whipsaws to an absolute minimum.
All in all, the Dow Theory:
a) Is non parametric.
b) Relies on “internal” confirmation: Time and Extent should confirm each other.
c) Relies on “external” confirmation. Indices should confirm each other.
Now go to my post analyzing the Dow Theory performance. It should not surprise you that ca. 70% of the trades are winners (something unknown in other trend following systems) with a remarkable win to lose ratio. Something unknown in typical trend following systems (we were taught that you either have a high batting average with a poor win/lose ration, or vice versa, but you cannot have both; well the Dow Theory proves this is simple wrong).
If you further cogitate, you will start to see that the Dow Theory is also clearly superior to traditional “breakout” systems (i.e., buy if today’s close is higher than the highest high of the last 50 days). Do such breakout systems include an “extent” element? Do such systems contain a dynamic exit point adapted to previous market action (as secondary reactions are)? Or they just have dummy parametric set stoplosses? Although, this is the subject of a future post, I can loudly say that I am not a turtle, as such systems are parametric flawed, and disregard the “extent” element, and hence the scares they give to their practitioners every now and then (and huge drawdowns which very few investors have the stomach to digest)
Once this post soaks in, you’ll have your “aha” moment.
The Dow Theorist
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