Research Library研究资料库

When market consensus concentrates on one direction, how do you systematically examine the fundamental changes consensus has obscured? Four cases (energy storage, non-ferrous metals, innovative pharma, and non-bank financials) build a cross-dimensional cross-validation research framework.

Applying the Three-Layer Signal framework to the AI industry: supply signals remain tight, capital signals are accelerating expansion, and earnings signals are improving but not yet mature. Currently in the transition from investment phase to delivery phase.

Frameworks tell you what to look at, but they cannot guarantee that what you see is real. Three cognitive biases (availability bias, confirmation bias, and herding) can distort the input, execution, and output of analytical frameworks.

From supply constraints to commercial deployment: building a research framework for studying technology revolutions, using the AI industry as a case study. Find supply constraints, observe capital investment, wait for earnings delivery.

K-shaped divergence is not a random fluctuation. It is the result of three long-term economic forces working together: supply constraints in the AI industry, transformation of the macro policy framework, and restructuring of the global industrial division of labor.

What changes is statistical regularity; what remains constant is the logic of earnings-driven patterns. AI supply rigidity, misaligned capital structure, and policy framework shifts have together triggered a fundamental restructuring of the market.