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String of Pearls


...along the way I gathered up a dozen or so pearls which I found to have lasting value.


Editor's Note: Minyanville would like to introduce Jess Thompson, the newest professor to our community! Get to know Jess and join us in welcoming him to the 'Ville.

During an interview, comedian Steve Martin said that (paraphrase) over the span of their careers they (comedians) collect jokes and bits that are strung like pearls to form routines and acts.

As a wide-eyed stock & futures broker in 1978, I stumbled upon a set of Trendline stock charts and became quickly fascinated that the endless stream of transactions swish-swishing across our boardroom's Trans-Lux ticker could be condensed haiku-like into a series of price bars. I also discovered an oddball group of market watchers called "technicians" who were allegedly making meaningful investment decisions based on relationships among those bars.

At the time, technical analysis was akin to practicing voodoo while personal computers were being newly hatched by Jobs and Wozniack in a garage in what was to later become Silicon Valley. So technical analysis largely involved updating charts by hand and drawing lots of lines. From that point forward, I spent the next three decades discovering 10,000 things that do not work in technical analysis; but along the way I gathered up a dozen or so pearls which I found to have lasting value.

Strung together, those pearls inoculate me (most, but not all of the time) from the thought contagion that sweeps markets on a regular basis. And those same pearls form a touchstone for developing and adapting technical strategies and tactics which are robust because they're grounded in market principles.

Here's a handful of those pearls. I hope they can provide context for observations which I'll be soon also contributing to the Buzz & Banter in the Minyan soup.

Pearl #1: Time conditions the potency of all price movement.

This pearl is priceless. For example, trends comprised of intraday or daily swings (small slices of time) tend to to be abortive when they run counter to higher timeframe trends comprised of monthly or weekly structures (large slices of time). So it's time which allows us to establish a hierarchy among a constellation of trends and determine which is dominant (potent).
As another example, imagine that price swings up to test an important top, the potency of that swing (the ability to sustain directional bias) is a function of the amount of time (or price acceptance) which builds above that old top.

Conversely, a rejection of price (a lack of time and non-price acceptance) after thrusting above that same top reveals a lack of potency in that price movement and increases the probability of a relapse back into a trading range.

Pearl #2: Positive trade expectation occurs when the perception of the probability of a market event diverges from the actual probability.

This is just another way of describing the pre-conditions for variant perception among traders acting on information extracted from different timeframes.

We can port this into a technical analysis framework by describing a situation where momentum traders are piling into a rally driving prices ever higher. If this occurs in a context where a more dominant downtrend is already established, the rally will at some point reach a critical juncture where momentum traders are caught assigning a higher probability to trend continuation up than the actual probability based on the higher timeframe downtrend reasserting its dominance. That point is where one form of variant perception occurs in technical analysis and defines strategic inflection points.

Pearl #3: The absolute value of a price pattern is the product of the intrinsic value of that pattern modified by context.

There are myriad price patterns that occur in markets that have some degree of intrinsic value, meaning they exhibit tendencies for price continuation or reversal. The absolute value of a price pattern is what we're really after and that's exploited by pairing a pattern of known intrinsic value with a higher timeframe in market contexts.

For example, a breakout of a period of range contraction has intrinsic value as an expression of price moving from random (congestion) to non-random (trend), but when paired with a market context sensitive to a higher timeframe reversal the absolute value of range contraction becomes magnified.

Pearl #4: Play Tight in A Loose Market; Loose in a Tight Market.

This pearl suggests how money management tactics might be linked to the character of the price action.

Tight markets are well-bid markets with an order flow imbalance. They tend to exhibit tight sloping channels with smallish ranges and appear on a day-to-day basis to be relatively dull. But, tightness is often a marker of trending (non-random) price movement; so in a tight market, profits are generally maximized by using wide stops and letting the trend run.

Loose markets, on the other hand, have wider spreads between dominant bids and offers and tend to be mean-reverting and exhibit wide-swinging trading range-like behavior. Profits tends to be transient in loose markets and they demand more aggressive profit-taking tactics.

Part of the purpose of technical analysis should be to monitor for changes in market character to adapt more dynamic processes for altering money management tactics.

Pearl #5: Markets are either readable or reliable.

When information traders act on either fundamental or technical information, they are trying to exploit inefficiencies in the propagation of information. If that information is already impounded into price when a trader initiates, then the trader is trading on noise as if it were information.

There is a perpetual trade-off between readability in a market and reliability of trade decision-making. Conventional technical analysis has high readability because the tools are easily understood, they appeal to our pattern-loving minds and they are widely dispersed -- they are available at practically little or no cost on most trading platforms. But, the information being extracted from conventional analysis is so widely-propagated, that the reliability (utility) of that information is low which is why technical analysis is often frustrating to its practitioners.

In kind, fundamentals or market events which are announced and widely distributed across financial media certainly have high readability, yet buying or selling on news is unreliable as a tactic. Again the propagation of that information is generally efficient enhancing readability, but the trade-off is lower reliability.
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