标题： 白皮书声明能否预测市场行为？ 来自加密货币因子分析的证据 显示英文标题

标题： Do Whitepaper Claims Predict Market Behavior? Evidence from Cryptocurrency Factor Analysis

摘要： 加密货币项目通过白皮书阐述价值主张，就功能和技术能力做出声明。 本研究调查这些叙述是否与观察到的市场行为一致。 我们构建了一个管道，结合零样本NLP分类（BART-MNLI）与CP张量分解，以比较三个空间：（1）来自24份白皮书的声明矩阵，涵盖10个语义类别，（2）49种资产两年的每小时数据的市场统计数据，以及（3）张量分解的潜在因素（秩为2，解释方差为92.45%）。 使用Procrustes旋转和Tucker的相似性系数，我们在23个共同实体上测试对齐情况。 结果表明对齐较弱：声明-统计数据（phi=0.341，p=0.332），声明-因素（phi=0.077，p=0.747），以及统计数据-因素（phi=0.197，p<0.001）。 统计数据-因素的显著性验证了我们的方法，确认当存在关系时，该管道能够检测到。 使用DeBERTa-v3进行的模型间验证显示32%的精确一致，但67%的前三名一致。 横截面分析揭示了异质性贡献：NEAR、MKR、ATOM显示出正对齐，而ENS、UNI、比特币偏离最多。 排除比特币证实结果不是由市场主导地位驱动的。 我们将发现解释为白皮书叙述与市场因子结构之间的弱对齐。 有限的功率（n=23）无法区分弱对齐与无对齐，但可以自信地拒绝强对齐（phi>=0.70）。 讨论了对叙述经济学和投资分析的含义。 显示英文摘要

摘要： Cryptocurrency projects articulate value propositions through whitepapers, making claims about functionality and technical capabilities. This study investigates whether these narratives align with observed market behavior. We construct a pipeline combining zero-shot NLP classification (BART-MNLI) with CP tensor decomposition to compare three spaces: (1) a claims matrix from 24 whitepapers across 10 semantic categories, (2) market statistics for 49 assets over two years of hourly data, and (3) latent factors from tensor decomposition (rank 2, 92.45% variance explained). Using Procrustes rotation and Tucker's congruence coefficient, we test alignment across 23 common entities. Results show weak alignment: claims-statistics (phi=0.341, p=0.332), claims-factors (phi=0.077, p=0.747), and statistics-factors (phi=0.197, p<0.001). The statistics-factors significance validates our methodology, confirming the pipeline detects relationships when present. Inter-model validation with DeBERTa-v3 yields 32% exact agreement but 67% top-3 agreement. Cross-sectional analysis reveals heterogeneous contributions: NEAR, MKR, ATOM show positive alignment while ENS, UNI, Bitcoin diverge most. Excluding Bitcoin confirms results are not driven by market dominance. We interpret findings as weak alignment between whitepaper narratives and market factor structure. Limited power (n=23) precludes distinguishing weak from no alignment, but strong alignment (phi>=0.70) can be confidently rejected. Implications for narrative economics and investment analysis are discussed.