(My observations, my experience, and my opinion — not advice.)
Market declines dominate headlines. They stir emotion, amplify fear, and often overshadow the quieter, more analytical signals that disciplined investors rely on. Yet for those who use structured systems—like my Median Averages and Standard Deviations within what I call the Augmented Income Strategy (AIS) and the Medeiros Alpha Strategy (MAS) these sharp declines often expose opportunity rather than danger.
Everything I describe in this writing reflects my own experience and my own opinion. I am not offering financial advice, and nothing here is a recommendation. This is simply how I see markets, how I trade them, and how I’ve built a rules-based approach that helps me stay disciplined when the headlines are loudest.
Recently, we’ve seen drastic shifts in both Median Averages and Standard Deviations. These are two of the most important barometers I use to understand where a stock sits relative to its recent behavior. When the market falls sharply, these averages compress and distort, creating conditions that often precede meaningful reversals.
This isn’t new. In 2008, the market collapsed under the weight of extreme pressure. Fuel prices surged to the highest levels I had ever seen—gas and diesel both reached records. Those increases acted like a tax on the entire economy. No one escapes higher fuel costs; they ripple through food, transportation, construction, and manufacturing. Today’s environment isn’t identical, but it carries familiar echoes. And just as in 2008, the decline itself is not the whole story. What matters is how individual equities behave relative to their own history.
Most trading strategies seek reversion
In my opinion, the majority of trading strategies... whether simple or sophisticated... are built on the idea of reversion. Prices stretch too far in one direction, sentiment overshoots, and eventually the pendulum swings back. While only the most advanced and sophisticated traders should pursue downward-gaining strategies (because they have no mercy toward losses), an upward strategy focuses on stocks that are declining but likely to rebound. After a sale, a repurchase might be sought at a decline.
This is where disciplined accumulation matters. I believe it is reasonable to dollar-cost average into a stock that is falling if the underlying metrics suggest it is approaching a reversion point. My system is designed to identify those points with precision, using moving averages, standard deviations, and structured profit targets.
Watching the 30-day and 90-day averages
When a stock falls below both its 30-day and 90-day moving averages, it enters a zone that deserves closer attention. I’ve been told many times that “the market can’t be timed,” but that isn’t entirely true. It can’t be predicted, but it can be measured. And measurement reveals patterns.
One of those patterns is the sequence of recovery:
- First, the stock re-prices its 30-day moving average.
- It often remains below the 90-day for a time.
- That gap... 30-day regained, 90-day still overhead... is often the earliest sign of a rebound forming.
News flow often aligns with this shift: upgrades, easing macro pressures, or simply a change in sentiment. I don’t trade the news, but I do notice when the technical structure and the narrative start to rhyme.
A visual metaphor for standard deviation declines
The way I visualize standard deviation declines is simple: I picture a staircase descending into a valley.
- Each step downward represents another standard deviation decline.
- Each step is deeper, darker, and more uncomfortable than the last.
- But each step also represents a stronger potential rebound.
When the stock eventually climbs back up, it doesn’t always just return to the previous step—it can overshoot, because the market tends to overcorrect in both directions. The deeper the valley, the more dramatic the climb can be.
So when I see standard deviation expanding to the downside, I don’t just see “pain.” I see a staircase that, if the company survives and fundamentals hold, can eventually lead to meaningful upside.
How I scale shares as standard deviations decline
This part is purely my opinion and my personal method. I'm borderline of sharing my code...
With each standard deviation decline, I increase the number of shares I buy. The number of shares purchased at each level helps set the profit I seek for that trade-iteration. As the stock declines from the previous target... what I think of as “tuple 1” in a pair of prices... I increase the gain I’m aiming for on the next move up "tuple 2".
In other words:
- Each lower level = more shares.
- More shares = a higher absolute profit target for that specific iteration. Rather than 2%, 2.5% for example. Dividends also influence my calculations.
- The deeper the decline, the more the system expects the rebound to compensate.
This process can take years to complete. But in my experience, it often generates gains in the middle too, long before the full rebound occurs. Partial rebounds, dividend payments, and intermediate exits can all contribute to the overall result.
MAS vs. AIS: two engines, two purposes
I use two distinct strategies, each with its own logic and purpose. They are not interchangeable, and I don’t treat them as such.
AIS — Augmented Income Strategy
AIS is built for what I consider income-focused tickers—names where yield and cash flow matter. Its purpose is to extract income and amplify returns through disciplined accumulation and structured exits.
In my opinion, AIS has these characteristics:
- Standard deviation and moving averages help define buy zones.
- Dividend yield and timing matter.
- Reversion is expected, but I’m also being paid to wait.
- The augmentor plays a major role in setting future profit targets.
- Gains often come from both price movement and dividends.
AIS is the strategy I use, as it implies, to augment income and capture gains.
MAS — Medeiros Alpha Strategy
MAS is built for what I view as quality, compounding, capital-appreciation tickers. Its purpose is to accumulate shares of strong companies during volatility and trim them during strength.
In my opinion, MAS has these characteristics:
- Standard deviation and longer moving averages (like 90-day) matter more than yield.
- Dividend timing is irrelevant or secondary.
- Momentum and business quality matter.
- Reversion is expected but not guaranteed.
- Gains come primarily from price movement and long-term compounding.
- The candidates are among the top of the S&P 500 by Market Cap.
MAS is the strategy I use when I want the stock to grow, not necessarily pay. I have made more from this than other strategies but also paid more taxes...
Together, AIS and MAS form a dual-engine system for me: one engine focused on income, the other on appreciation. Both rely on structure, standard deviation, and reversion—but they express those ideas differently.
How I see myself as a trader
I’ve been told I’m a “Quant,” and I’m not sure I fully agree with that label, mostly because I don’t live inside the world of academic quant trading, Monte Carlo simulations, or machine learning models. I don’t pretend to understand every nuance of what professional quant funds do.
But I do trade quantitatively. I use numbers, rules, and structure to guide my decisions. I don’t trade on vibes or headlines; I trade on measurements.
If I had to define myself, based on how I actually operate, I’d say this:
I am a disciplined, quantitative reversion trader who uses structured scaling, standard deviation logic, and iterative profit targets to turn market declines into long-arc opportunities.
I’m not a pure quant in the Wall Street sense. I don’t build complex statistical models or fully automated black-box systems. Instead:
- I use quantitative inputs.
- I follow rules that I’ve defined in advance.
- I execute those rules with human judgment and patience.
I’m not trying to predict the market. I’m trying to prepare for what it does, using structure instead of emotion.
A real example: Hershey
Hershey is one of my favorite stocks. It has declined for years. I was very heavily invested during that period, and I continued to accumulate as it fell through multiple standard deviation levels and below key moving averages.
Today, I hold fewer than ten shares because the rebound is finally occurring. Along the way, I enjoyed an ample amount of qualified dividends. That’s the kind of long-arc payoff that reinforces my belief in reversion-based, rules-driven strategies.
And a humbling example: Big Lots
On the other hand, NEVER ask me about Big Lots. Just know that I have been wrong, and I know it too. No system is perfect, and no trader is immune to misjudgment. That’s part of the journey.
I include this not as a punchline, but as a reminder—to myself as much as anyone else—that discipline does not guarantee perfection. It simply improves the odds of surviving long enough to learn.
Appendix: the augmentor explained (non-technical)
The augmentor is one of the quieter but more important concepts in my system. I don’t present it as something others should use; I share it because it explains how I think about building on previous trades. It is in a formula I labeled, "Appreciated Aggregation".
As I recall and currently use it, the augmentor is the percentage of the profit from the previous trade-iteration that is effectively “carried forward” into the next iteration’s gain target.
In simple terms:
- A trade occurs and is expected to generate a profit.
- I take a percentage of that profit, this is the augmentor.
- That percentage is added to the next trade’s expected gain.
- The deeper the decline and the more iterations, the more the augmentor can amplify the next target.
So if the previous trade seeks to earn a certain amount, the next trade, triggered if the stock declines, doesn’t just aim for the same gain it aims slightly higher, because a portion of the prior target is being layered into the new target. This is very complex, I've been told.
It’s not magic. It’s not predictive. It’s simply a disciplined way of saying:
“If I took risk at a lower level/higher price, I expect a stronger reward at the next level.”
That’s all the augmentor is, a structured way to respect past risk and past success when setting future expectations with greater probability.
Opportunity exists on both sides of the averages
Market declines are uncomfortable, but they are also clarifying. They strip away excess, reset expectations, and reveal which companies are resilient enough to re-price their way back through the averages. For traders who rely on structured systems rather than emotion, these periods are not just survivable—they are actionable.
Below the averages, there may be a turnaround forming. Above the averages, momentum may be building. And in the middle—those stocks drifting out of sight—I may continue to accumulate if they once earned my attention and still fit my rules.
Declines are not the enemy. For a structured, reversion-based trader, they are the environment in which the system does its best work.
