Global Assets Enter Bear Market Cycle: How Wave Theory Quantifies Market Corrections

As major global assets such as gold, silver, and A-shares enter correction phases, does this mean we are already in a bear market? This question has sparked widespread market discussion since mid-March. Recent market observations show that global assets indeed exhibit typical bear market characteristics, affecting not only traditional assets but also spilling over into the cryptocurrency sector.

To understand the essence of the current bear market, it is necessary to approach from a technical analysis perspective, using quantitative tools rather than subjective judgment to identify market cycles.

Scientific Definition of Bear Markets: From Narrow to Broad Classifications

There are various opinions in the market regarding the understanding of bear markets. Some say, “No matter how high the position, if you can make money in the long run, it’s a bull market; no matter how low, if you can lose money in the long run, it’s a bear market”—this description is vivid but lacks quantitative standards.

Wave theory provides a more precise definition system. Narrowly, a bear market refers to a correction phase that occurs after a five-wave upward impulse at wave degree of large wave or above. However, in practical application, we need to understand a broader classification with four levels:

• Deep Bear: A correction after a five-wave upward impulse at the cycle wave level or above, representing the longest cycle of bear markets.
• Major Bear: A correction after an upward impulse at a large wave level.
• Medium Bear: A correction after an upward impulse at a medium wave level.
• Small Bear: The shortest cycle correction.

Based on this framework, current assets like the Peter Index, gold, and silver are in a deep bear phase; while high-quality stocks (like leading US tech stocks) and high-valuation A-shares are in a major bear phase. This indicates significant differences in the depth of bear markets across various assets.

Three Stages of Bear Markets and Trading Strategies

Bear markets are not static; they can be divided into three distinct stages over time, each with unique characteristics.

• Early Stage: Characterized by limited declines in indices, while small-cap assets experience sustained, significant corrections. This marks the beginning of market divergence—large-cap stocks resist declines, small-cap stocks lead the downturn.
• Mid Stage: The trend reverses, with indices falling sharply and small-cap assets also declining significantly, leading to a resonant market downturn.
• Late Stage: The most confusing phase—indices slow their decline and enter bottoming consolidation, while small-cap assets show divergence—some stabilize with the index, others continue to drift downward.

This three-stage model provides direct guidance for trading strategies. Recent short-selling records show that accurately identifying the bear market stage can lead to very high success rates. Short positions on assets like XAU (gold), XAG (silver), Pixel, DEGO, Kite, Pippin, Resolv, Lyn, Power, Enso, ZEC—totaling 11 instruments—have achieved full success. Except for Resolv, which was slightly above the top due to position adjustments, all others were shorted near their peaks, resulting in perfect records.

Predicting Turning Points: Gann’s Time Law

Technical analysis not only focuses on price but also emphasizes time. Gann theory highlights the regularity of market turning points in time. After analysis, the next critical turning point is expected around March 21, 2026, followed by a second resonance point between March 26-27, 2026. The significance of these dates lies in their typical association with key trend reversals.

Bitcoin and Ethereum Wave Patterns in the Bear Market

Within the current bear market framework, observing cryptocurrency performance is quite meaningful. Bitcoin traded at $70,510 on March 24, 2026, up 3.30% in the past 24 hours. According to the latest wave analysis, the targets of $73,925 on March 13 and $74,482 on March 16 have been achieved, demonstrating the short-term predictive accuracy of wave theory. These achieved targets serve as reference points for subsequent analysis.

Ethereum traded at $2,140, up 4.04% in 24 hours. Similar wave validation shows that the predicted targets of $22.04 on March 13 and $23,116 on March 16 have also been met. This indicates that, even in a bear wave, technical patterns remain highly regular.

Commodities and A-shares Bear Market Progress

Recent wave analysis of gold shows that the rebound target predicted last week precisely matched the second-highest top, confirming the limited nature of rebounds in a bear market. Silver also achieved the predicted secondary top rebound on March 10, then resumed downward movement. These precious metals’ performances validate the characteristic limited rebounds during the early stage of a bear market.

Regarding A-shares, the wave analysis of the Shanghai Composite Index indicated at the start of the year that a “golden pit” would appear in March-April, a forecast later confirmed by market movements. This pre-forecast realization demonstrates the effectiveness of technical analysis in large-cycle judgment.

Divergent Performance of Small-Cap Assets

ZEC (a major altcoin) is currently quoted at $226.74, up 3.14% in 24 hours, with its wave pattern also following the segmented characteristics of a bear market. Additionally, assets across different sectors—such as Huahong Semiconductor, BlueFocus, Leo Holdings, and Lead Intelligent—show varied performance during the bear phase.

Particularly noteworthy is Huahong Semiconductor, which was predicted last week to rebound between $75.4 and $81.85, with the lowest rebound point at $80.4—both of which have been realized. The cumulative success rate of such predictions approaches nearly 100%. These successful cases demonstrate that even in a bear environment, applying wave theory for detailed analysis can yield high success rates.

Applying and Learning Technical Analysis Frameworks

In a bear market, the key is to avoid being swayed by market sentiment and instead use quantitative analysis frameworks to understand market structure. Tools like wave theory and Gann theory, when properly applied, can transform subjective judgment into a verifiable prediction system.

From the global asset bear market phenomenon, it is clear that the market does not decline chaotically but follows a clear wave structure. Recognizing your current bear market stage, predicting turning points, and understanding the differences among various assets are essential for risk management and opportunity seeking in a bear environment.

By systematically learning these analytical tools and cultivating independent market judgment, you can maintain clarity and rationality in decision-making amid complex bear markets.