A New Solution to Market Cycle Prediction from a Dynamic Probability Perspective

Written by: NingNing

As of 2025, we have experienced less than four complete four-year cycles. However, basic statistical knowledge tells us that any conclusions drawn from extremely small statistical sample sizes (only three valid data points) require careful verification, rather than simple blind faith.

In predicting large market cycles with small samples, the Bayesian probability method's derivation of the correlation between 25Q4 and 19Q4 is more valuable than the four-year cycle theory.

The 25Q4-to-19Q4 criterion is transformed into Bayesian formula notation: P(Bear Market | Merrill Lynch Clock Stagflation/Recession) = [P(Bear Market) / P(Merrill Lynch Clock Stagflation/Recession)] * (P(Merrill Lynch Clock Stagflation/Recession | Bear Market)). Bayesian probability parameter estimation: P(Bear Market) - Prior Probability. Since 1929: The S&P 500 has experienced 27 bear markets. Average frequency: once every 3.5 years. Annual probability: approximately 28.6%. Quarterly probability (Q4-Q1 span): Approximately 15-20% Conservative estimate: P(Bear Market) ≈ 18% P(Stagflation → Recession) - Merrill Lynch Clock Conversion Probability Historically, the conversion probability of "Stagflation → Recession": 1970s Stagflation: Ultimately led to three recessions in 1973-74, 1980, and 1981-82. 2000-2001: Tech bubble burst, mild recession. 2007-2008: Financial crisis, deep recession. 2011-2012: European debt crisis, not a complete recession (avoided) 2018-2019: Trade war concerns, successful soft landing Statistical estimates: Approximately 6 "stagflation → recession" scenarios in the past 50 years Of these, 4 turned into recession (66%) 2 resulted in soft landings (34%) Current environment adjustments: Fed proactive interest rate cuts (vs 1970s passive interest rate hikes) Labor market resilience (vs 2008 financial systemic risk) Tariff policy uncertainty Global de-dollarization pressure

Estimation: P(Stagflation → Recession) ≈ 40-50% (median 45%)

P(Stagflation → Recession | Bear Market) - Likelihood Probability

Probability of experiencing "Stagflation → Recession" under the condition of a bear market:

Historical bear market classification:

Recession-type bear markets (12 times): 1929, 1937, 1973-74, 1980, 1981-82, 1990, 2000-02, 2007-09, 2020, 2022

Non-recession-type bear markets (15 times)

Non-recession-type bear markets (15 times)

(Times): Other technical adjustments

In 12 recession-type bear markets:

Experienced stagflation phase: 1973-74, 1980, 1981-82, 2007-08 (approximately 4 times)

Non-stagflation: 1929 (deflation), 2020 (pandemic shock), 2022 (pure inflation)

Estimation: P(Stagflation→Recession|Bear Market) ≈ 33%

Bayesian calculation

Standard formula:

P(Bear Market|Stagflation→Recession) = P(Stagflation→Recession|Bear Market) × P(Bear Market) / P( Stagflation → Recession) 0.33 × 0.18 / 0.45 0.0594 / 0.45 0.132 = 13.2% Scenario Analysis Matrix Key Difference Analysis: Why is the Probability Low? [Image URL: https://img.foresightnews.pro/202511/842-1762760309358.jpeg?x-oss-process=style/scale70] Overall Conclusion: P(25Q4-26Q1 Bear Market) ≈ 15-20% Confidence Interval: Lower Bound (Optimistic): 12% Median (Benchmark): 17% Upper Bound (Pessimistic): 25% Strategy: Tactical defense is needed, not strategic retreat.