从基本面判断到量化策略:金融知识图谱如何进入科技股投资
AlphaMap 白皮书先导篇|面向全球科技股趋势成长与轮动的中低频策略研究
Read the Chinese whitepaper prologue →FINLLM-KG → TRADABLE QUANT FACTORS
ALPHAMAP WHITEPAPERS / 01
The central question has moved beyond entity and triple extraction: what economic meaning the graph carries, how time and state transitions are modeled, and which excess-return mechanism the graph ultimately represents.
AlphaMap 白皮书先导篇|面向全球科技股趋势成长与轮动的中低频策略研究
Read the Chinese whitepaper prologue →DOI EMPIRICAL STUDIES / 02
The DOI series moves from the single-vintage projection diagnostic in #000 to a full graph-factor test in #001: 91 candidates, 266 dated documents and 85 mature weekly cross-sections. Predictive network alpha is still not established after controls.
Across 91 candidate companies, 266 dated SEC documents and 85 mature weekly tests, the raw IC of 0.0779 falls to 0.0072744 under full controls. Predictive network alpha is not established.
Read the DOI empirical study →An exploratory methods study from AI-industry semantics to cross-sectional stock rankings, beginning with the mechanical content written into scores by graph construction.
Read the DOI empirical study →The public surface provides citable methods research and its limitations. It does not provide live signals, production portfolio weights, trading instructions or return promises. Machine-readable Research Objects and continuous research are delivered by use case and license.
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