目前，关于传统产业链上下游股票价格传导机制的研究文献较为稀少，而已有的文献大多以宏观层面的产业链上下游关系为研究主要内容，旨在说明有产业链相关的股票投资组合比没有产业链相关的股票投资组合收益率更高。而相关的价格传导机制的研究文献，又集中于研究农业、重金属、期货等传统行业，并且传统行业的产业链细分市场相对单一。本文将以新能源汽车产业链上下游股票价格为研究对象，做垂直产业链上下游的研究、及新兴市场产业链的研究，因为垂直产业链上下游更能说明相关关系的紧密度，以及展示新兴市场产业链细分市场在不断完善过程中发展壮大的相互影响。本文后续以格兰杰因果检验、VAR模型、VEC修正为统计分析方法，对产业链上下游股票价格传导机制的原因做研究。 本文选取2017-2023年在A股上市的43家公司作为样本，筛选其中主营业务占比超过40%属于新能源汽车产业链上下游的企业，以7年内的股票周收盘价作为基础数据，在经过对数处理、等市值加权处理后，构建行业内各细分市场的指数，再进一步通过格兰杰因果检验、VAR模型和VEC修正寻找引起产业链上下游股票价格传导机制的原因。 研究发现，产业链上游对下游有成本关系的、以及下游对上游有需求关系的会有显著影响；且上游对下游有成本关系的脉冲响应更为显著，方差分解中贡献度的强弱也进一步说明它的重要性，这符合市场中上游成本价格影响下游成品利润的基本逻辑。可以为后续构建投资组合打下基础。

Currently, there is a scarcity of research literature on the price transmission mechanism of stocks in the traditional industry supply chain, and existing literature mostly focuses on the macro-level relationships within the industry supply chain. The aim is to demonstrate that portfolios related to industry supply chains yield higher returns compared to portfolios unrelated to industry supply chains. The research literature on relevant price transmission mechanisms is concentrated on traditional industries such as agriculture, heavy metals, and futures, and the sub-markets within traditional industries are relatively singular. This study will focus on the stock prices of companies in the new energy vehicle industry supply chain, conducting research on both the vertical relationships within the industry supply chain and the emerging industry supply chain. This is because vertical relationships within the industry supply chain can better illustrate the closeness of related relationships and demonstrate the mutual impact of developing sub-markets within emerging industry supply chains. Subsequently, this paper will use Granger causality tests, VAR models, and VEC correction as statistical analysis methods to study the reasons behind the price transmission mechanism of stocks in the industry supply chain. This study selects 43 companies listed on the A-share market from 2017 to 2023 as samples, filtering those where the proportion of their main business exceeds 40% in the new energy vehicle industry supply chain. Weekly closing stock prices for seven years are used as the basic data. After logarithmic transformation and equal market value weighting, indices for various sub-markets within the industry are constructed. Further analysis is conducted using Granger causality tests, VAR models, and VEC correction to identify the factors causing the price transmission mechanism in the industry supply chain. The research findings indicate that there is a significant impact from the cost relationship between the upstream and downstream sectors in the industry supply chain, as well as the demand relationship from the downstream to the upstream. Moreover, the pulse response from the upstream‘s cost relationship to the downstream is more pronounced. The strength of their contributions in the variance decomposition further underscores their importance. This aligns with the fundamental logic in the market where upstream cost prices have a substantial influence on downstream product profits. These findings can provide a foundation for constructing investment portfolios in the future.