Systematic analysis reads a bull market by comparing what prices are embedding with what the wider information environment is showing. The key signals include market breadth, sentiment, volatility and the prevailing market regime.

This framework fits readers who want a structured way to examine late-cycle conditions without relying only on the headline index or the prevailing market narrative. In the 2021 advance, warning signals appeared in parts of the data before the S&P 500 reached its January 2022 peak.

This article is based on the source's systematic reading of the post-March 2020 bull market, using breadth, sentiment, volatility-adjusted signals, market regime and the Noise Threshold.

1. Define the bull market and its prevailing regime

A bull market is conventionally defined as a sustained rise of 20% or more in a major market index from a recent low, persisting for at least several months. After the March 2020 pandemic trough, the S&P 500 rose from approximately 2,200 to more than 4,700 by January 2022, a gain of more than 110%.

During the 2021 advance, the Signal Stack showed a sustained positive trend across major equity indices. Strong sentiment readings from earnings communications and constructive macro data supported a Market Regime classification of firmly trending positive.

This is the starting point for systematic analysis. Quantitative systems read constructive conditions as constructive conditions rather than imposing pessimism on a rising market.

2. Separate genuine deterioration from bull-market noise

Extended bull markets generate repeated potential warning signals. Breadth can deteriorate briefly and recover, sentiment can reach extremely positive readings while prices continue rising, and volatility can spike without producing a regime change.

Apply the Noise Threshold

The Noise Threshold is the level above which a quantitative signal represents a genuine regime change rather than normal variation within the prevailing trend. It is not fixed. A meaningful divergence in a high-volatility environment differs from a meaningful divergence in a low-volatility trending environment.

Repeated false signals can condition market participants to discount later warnings, including signals that precede an actual transition. A systematic reading therefore considers the prevailing noise floor before assigning weight to an indicator.

3. Check for divergence across the data

The central late-cycle question is whether the advance remains supported across the market and information environment, or whether prices are continuing higher while supporting signals weaken.

Review sentiment around rate sensitivity

In the autumn and winter of 2021, sentiment in interest-rate-sensitive communications began to shift towards caution. The areas included mortgage market commentary, housing sector analyst reports and corporate issuance language. The change coincided with inflation data exceeding Federal Reserve projections.

The Sentiment Layer was registering a change in the information environment around rate sensitivity that was not yet reflected in the broad equity index-level advance.

Measure market breadth

The percentage of S&P 500 constituents trading above their 200-day moving averages peaked in mid-2021 and declined gradually through the second half of the year. The index continued making new highs, driven by a concentrated group of large-capitalisation names.

This narrowing of participation is a classic late-cycle breadth pattern. The advance can continue at index level while fewer constituents support it.

Adjust trend signals for volatility

By late 2021, Volatility Adjusted Signals for high-multiple growth stocks and long-duration technology names were showing reduced confidence scores. This reflected the elevated noise floor as volatility increased in those rate-sensitive segments.

The same trend signal carries less information in a higher-volatility environment than in a lower-volatility one. Reading the signal without its volatility context can therefore obscure the quality of the information.

4. Compare the systematic reading with the market narrative

The emotional experience of a bull market peak is often confidence and momentum. The quantitative reading is the accumulation of inconsistencies between price and data.

During the 2021 advance, previous warning signals had resolved without consequence. This experience encouraged market participants to treat new warnings as potential buying opportunities. The result was a continuing advance narrative even as breadth deteriorated and sentiment shifted.

A quantitative model evaluates current data against its trained parameters rather than changing its response because earlier warning signals produced false positives. This is the source's concept of the Emotionless Edge.

5. Read the regime transition before index-level confirmation

Across bull market cycles, the source identifies a recurring sequence in the data. Breadth peaks before the index, sentiment diverges before the trend reverses, and volatility begins to rise in the most rate-sensitive or extended segments before the broad market confirms a regime change.

The Opes Borsa Signal Stack monitors these dimensions simultaneously and provides a live read of where the current market environment sits within its historical pattern. It is described as a systematic framework for reading current conditions, not a prediction engine.

The durable lesson is that a bull market can enter late-cycle conditions in the data before the transition becomes visible in the headline index. Systematic analysis focuses on how the signals evolve rather than on the narrative alone.

Common pitfalls when reading a bull market

• Treating one temporary breadth decline as proof of a regime change.

• Ignoring the Noise Threshold and the prevailing volatility environment.

• Reading positive sentiment as confirmation that all parts of the market remain healthy.

• Focusing only on the headline index while participation narrows among its constituents.

• Giving later warning signals less weight solely because earlier warnings resolved without consequence.

• Treating the Signal Stack as a prediction engine rather than a framework for reading current conditions.

Frequently asked questions

What is the main warning sign before a bull market ends?

The main warning pattern is a divergence between rising prices and weakening supporting data, including deteriorating breadth, shifting sentiment and higher volatility in rate-sensitive segments.

What did the data show before the January 2022 peak?

Before the January 2022 peak, breadth declined, rate-sensitive sentiment shifted towards caution and Volatility Adjusted Signals for high-multiple growth stocks and long-duration technology names showed reduced confidence scores.

What is breadth deterioration?

Breadth deterioration is the narrowing proportion of market constituents participating in an index-level advance.

Why is volatility important when reading a trend signal?

Volatility affects the signal's information value because the same trend signal carries less information in a higher-volatility environment than in a lower-volatility one.

What is the Noise Threshold?

The Noise Threshold is the level above which a quantitative signal represents a genuine regime change rather than normal variation within the prevailing trend.

Is the Opes Borsa Signal Stack a prediction engine?

No. The source describes it as a systematic framework for reading current market conditions, updated continuously.

Key terms

• Bull Market: A sustained increase of 20% or more in a major market index from a recent low, typically persisting for several months to years.

• Late-Cycle Conditions: A phase in which the advance narrows, breadth deteriorates and valuation assumptions begin to diverge from the data environment.

• Volatility-Adjusted Signal: A Trend Signal calibrated for the prevailing volatility environment, with confidence scores adjusted downward during high-volatility periods.

• Noise Threshold: The level above which a quantitative signal represents a genuine regime change rather than normal variation within the prevailing trend.

• Breadth Deterioration: The narrowing proportion of market constituents participating in an index-level advance.

• Signal Stack: The Opes Borsa framework for monitoring multiple market dimensions, including trend, sentiment, breadth and volatility.