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Mar 23, 2026 03:40
The central dilemma of investment theory is that no deterministic causal relationship exists between analytical inputs and profit-loss outputs, yet the investor cannot bypass analytical frameworks to access results directly. Starting from this fundamental contradiction, this essay proposes market activity as the primary screening indicator, establishes a binary classification discipline for stock selection, discusses the application of various technical standards within this framework, and introduces the problem of false breakout filtration as the next critical challenge.
I. No Deterministic Relationship Exists Between Analytical Inputs and Profit-Loss Outputs
The final result of any investment reduces to exactly two outcomes: profit or loss. Every investment theory system — whether founded on fundamental analysis, technical analysis, capital flow analysis, or sentiment analysis — is, at its core, attempting to control some category of analytical input so as to eliminate loss from the set of possible outputs. This means that the logical precondition of all investment theories necessarily rests upon an implicit assumption: that a deterministic causal chain connects analytical input to profit-loss output.
This assumption, however, does not hold in any rigorous sense. Companies with excellent fundamentals can see their stock prices decline persistently over extended periods. Technically perfect breakout patterns can be invalidated as false breakouts within a single trading session. A market environment flush with liquidity can reverse instantaneously upon the arrival of an unforeseen event. No analytical framework can provide a guaranteed mapping from input to output. In the domain of investment, there exist no causal relationships in the sense of sufficient conditions — no proposition of the form “if condition A is satisfied, result B necessarily follows” can be sustained.
Yet upon recognizing this, a common erroneous reaction is to swing to the opposite extreme: since no analytical framework can provide certainty, one should simply discard all frameworks and attempt to grasp the market’s pulse through raw “intuition” or “instinct.” This posture appears liberated, but in reality it merely elevates some unexamined implicit assumption to the status of ultimate truth. Every investment action must necessarily be conducted in some manner, and behind every manner there necessarily stands some theory or belief, whether or not the actor is consciously aware of it. Investors who claim to rely on no theory whatsoever are typically mistaking some crude rule of thumb or emotional impulse for a transcendent “intuition” that supersedes theory.
The correct epistemic stance, therefore, is neither to fetishize the certainty of any single analytical framework nor to deny the utility of all frameworks, but rather to compare and evaluate the relative merits of different frameworks under the explicit acknowledgment that none possesses certainty. The sole criterion for judging the quality of an investment theory is not the elegance of its logical premises, nor the sophistication of its analytical procedures, but whether it can, in a probabilistic sense, deliver a positive expectancy of profit over loss. The value of any analytical framework can ultimately be validated only through actual profit-and-loss outcomes.
II. Market Activity as the Primary Screening Indicator
Having established the epistemic framework above, an immediate operational question arises: among the multitude of potential investment targets, which merit attention and which should be excluded? On this point, the essay proposes a primary screening principle: market activity.
Market activity, as used here, refers to the signs of trend initiation and the energy of price movement exhibited by a market or an individual stock. A market or stock that has remained in prolonged stagnation — with persistently shrinking volume and directionless oscillation within a narrow range — does not possess investment value and should not enter the investor’s field of attention. The logical basis for this principle is straightforward: the precondition for investment profit is directional price movement, and the precondition for directional movement is the presence of market activity. A market devoid of activity is a body of still water from which no profit can be extracted, regardless of how much analytical effort is invested.
The characteristic error of a large proportion of retail investors consists precisely in violating this principle. Driven by fear of risk, they gravitate toward markets and stocks exhibiting prolonged stagnation and minimal volatility, equating low volatility with low risk and therefore with safety. However, the other side of low volatility is low or negative returns. On a target with no directional movement, the investor consumes time cost and opportunity cost, both of which carry especially severe penalties in a bull market environment. More dangerously, investors who have waited for extended periods on low-activity targets often swing to the opposite extreme once their patience is exhausted: they rush indiscriminately into any target displaying violent movement, entering at elevated prices and subsequently suffering significant losses.
Within the global universe of markets, there is never a shortage of markets and instruments displaying nascent activity. The investor’s primary task is not to labor fruitlessly within a dormant market but to direct attention toward those directions showing early signals of trend activation. Only when a market or stock displays such early activation signals does it merit entry into the investor’s candidate universe. Otherwise, regardless of how attractive its fundamental data or how low its valuation metrics, it should be resolutely excluded.
III. Binary Classification of Stocks and Classification Standards
Building upon the market activity screen, the more granular operational layer requires the establishment of a system for dynamically classifying individual stocks. The core logic of this classification system is extremely concise: at any given moment, all stocks can and should be divided into exactly two categories — actionable and non-actionable. The investor’s operational scope must be strictly confined within the actionable category, with no exceptions permitted for any reason.
The specific criteria for classification may vary from investor to investor, depending on capital scale, operating timeframe, and technical proficiency, but the underlying logical framework is consistent. Several commonly used classification standards are described below.
The first category of standards is based on long-term moving average breakouts. The most canonical example is the breakout above the 250-day moving average (annual line). When a stock breaks above the 250-day moving average on elevated volume, it signals the termination of its long-term downtrend and the establishment of a new uptrend, thereby transferring the stock from the non-actionable category to the actionable category. Similarly, a breakout above the volume-defined resistance line on the weekly chart can serve as a classification signal of equivalent significance. For investors with smaller capital pools and competent short-term technical skills, the moving average parameter may be shortened to 70 days, 35 days, or even the corresponding moving averages on the 30-minute chart, in order to capture shorter-cycle trading opportunities.
The second category of standards applies to recently listed stocks. Because such stocks lack sufficient trading history to form effective long-term moving averages, their classification criterion can substitute the highest price recorded on the first day of trading. When a recently listed stock breaks above its first-day high on elevated volume, it signifies that all participants who purchased on the listing day are now in profit, the overhead resistance from trapped positions has been entirely dissolved, and the stock thereby enters the actionable category.
The third category of standards involves the safety margin of special instruments. For example, in prior installments of this series, for underlying stocks accompanied by put warrants, a safety margin line can be calculated based on the put warrant’s exercise price. When the underlying price approaches this safety margin line, the downside risk is constrained by the warrant hedge while the upside remains open, creating an entry condition with an exceptionally favorable risk-reward ratio.
The fourth category represents a more advanced standard involving the identification of bear traps. A bear trap occurs when the market, within a declining trend, fabricates the appearance of an accelerating breakdown, inducing concentrated panic selling, only to reverse sharply upward immediately thereafter. The ability to accurately identify bear traps and initiate contrarian positions within them constitutes a highly efficient method, though one that demands considerable screen-reading experience and is suitable only for technically proficient investors.
Regardless of which classification standard is adopted, the core discipline is identical: stocks that do not satisfy the actionable condition must not be engaged under any circumstances whatsoever. Only when a stock automatically transitions from the non-actionable category to the actionable category by meeting a preset standard does it acquire eligibility for inclusion in the operational universe. The rigor with which this discipline is maintained directly determines the investor’s probability of survival.
IV. The Conflict Between Greedy Impulse and Classification Discipline
The binary classification principle described above is logically transparent, yet in practice it constitutes an enormous challenge to human nature. The overwhelming majority of investors, even those who intellectually endorse the principle without reservation, prove unable to adhere to it at the operational level. The root cause is a deeply ingrained psychological impulse toward greed — an irrational desire to capture every available opportunity.
The characteristic manifestation of this greedy impulse is as follows: when an investor observes a stock outside their actionable classification surging in price, an almost irresistible urge to chase arises. At that moment, classification discipline is abandoned and replaced by self-deceptive rationalizations such as “this time is different” or “this one is special.” Once the chase is executed, it typically coincides with the stock’s short-term peak, resulting in a loss. Worse still, on those occasions when the violation of discipline is coincidentally rewarded (the stock does continue to rise after the chase entry), positive psychological reinforcement is established, inducing the investor to violate discipline with increasing frequency in the future, until one catastrophic loss wipes out all the accumulated accidental profits in a single stroke.
In investment markets, the behavioral pattern of indiscriminate pursuit — lunging at every perceived opportunity without discrimination — inevitably produces catastrophic results. Opportunities in the market are infinite, but the investor’s capital and attention are finite. The attempt to capture all opportunities guarantees the capture of none. The essence of discipline is not the restriction of profit but the restriction of loss — by voluntarily forgoing a large number of uncertain opportunities, finite resources are concentrated on the few opportunities with higher probability of success. This ostensibly conservative strategy, over a sufficiently long statistical horizon, will invariably outperform the aggressive strategy of indiscriminate action.
V. False Breakout Filtration — The Next Core Challenge
After narrowing the investment target universe to the actionable category through activity screening and binary classification, a new and more intractable problem emerges: among all stocks satisfying the actionable criteria, a substantial proportion will ultimately prove to be false breakouts. These stocks briefly advance after meeting the classification standard, then rapidly retrace, failing to sustain a valid trend continuation.
The incidence rate of this phenomenon correlates closely with the overall market environment. In bear market conditions, the false breakout ratio is extremely high, reaching 80% or more — meaning that in a bear market, out of every ten stocks satisfying breakout criteria, more than eight will ultimately prove to be bull traps. In bull market conditions, the false breakout ratio drops substantially to approximately 30% — the systemic upward momentum of the bull market provides structural support for individual stock breakouts, significantly raising the probability that any given breakout is genuine.
The task of further filtering out false breakouts from among stocks that have already satisfied the classification criteria constitutes the single most important and most difficult element of investment operations. Many investors who perform well on classification discipline nevertheless suffer major losses at precisely this juncture. They select stocks strictly according to their criteria, only to find that the stock reverses shortly after entry, the breakout is invalidated, the stop-loss is triggered, and after several such occurrences, both confidence and capital are eroded. The specific methods and technical standards for false breakout filtration — involving the comprehensive analysis of volume-price relationships, temporal structure, trend momentum, and other multidimensional indicators — will be addressed in dedicated subsequent analysis.
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