有限关注度下科技关联的定价作用 (The Role of Technological Links in Asset Pricing Under Limited Attention Assumption)
26 Pages Posted: 21 Nov 2019
Date Written: June 1, 2019
Chinese Abstract: 本文探讨了当投资者具有有限关注度时，因科技价值信息的延迟扩散带来的投资机会。在有限关注度假设下，投资者倾向于忽略企业间的科技关联，导致科技价值在同类科技公司中的传递产生延迟，从而带来投资机会。然而，在我国股票收益率受非理性因素影响过多，不适合用作科技溢出效应的代理变量。本文首次提出，分析师一致盈余预测修正比股票收益率更适合用来衡量上市公司的科技价值。本文根据上市公司持有的专利计算了不同公司间的科技关联，并结合分析师一致盈余预测修正设计了“科技修正因子”。通过该因子构建的套利组合可以获得1.00%的月均收益。本文不仅验证了科技关联在我国股票市场的信息传递能力，而且深入探讨了投资者有限关注度在此过程中起到的作用。本文发现科技修正因子的投资价值一方面来源于其能够预测未来的分析师一致盈余预测修正，一方面来源于其能够预测公司未来的盈余变化。本文首次将分析师行为信息与上市公司间的科技关联结合起来运用，该思路不仅有助于增加投资者对科技关联的应用，而且有助于更加充分地挖掘分析师行为信息的价值。
English Abstract: This paper investigates the investment opportunities from the delayed information diffusion through technological links among firms. Under the assumption of limited attention, investors tend to neglect the technological linkages among firms, resulting in delayed information diffusion among technological peers, thus bringing investment opportunities. However, the stock return is affected by too many irrational factors in China, which makes it unsuitable to be treated as proxy for the spillover effect of technology development. This paper proposes for the first time that analyst consensus earnings forecast revision is more suitable than stock return to measure technology value of listed companies. Using analyst consensus earnings forecast revision, this paper proposes the TechRev factor. Then the roles of technological links and limited attention in asset pricing are investigated.
Firstly, this paper defined the technological correlation between firms based on the patents belonging to the focal firm. Then the TechRev for the focal firm can be calculated by averaging the analyst consensus earnings forecast revision of its technological peers, using the technological correlations as the weights. The empirical results show that: (1) the TechRev factor has significant investment value and the long-short strategy based on it yields monthly return of 100 basis points; (2) both portfolio test and the Fama-Macbeth regression verify that the investment value of TechRev is not derived from the well-known anomaly factors, but based on the specific information it contains essentially; (3) the TechRev factor is more efficient among the firms with stronger patent intensity or less analyst reports coverage, which means that the limited attention mechanism plays an important role; (4) the predictability of TechRev factor for the future stock return of the focal firm is derived from its predictability for the analyst consensus forecast revisions and the unexpected earnings of the focal firm; (5) the TechRev anomaly is more attributed to mispricing instead of risk premium.
Because of the huge difference between the stock markets of China and developed countries, many effective investment strategies in mature markets lose their effects in China. However, this does not mean that the operation mode of China's stock market does not conform to the basic economic or financial laws. At least, the limited attention paradigm embodies well in the markets of both China and the US. And the securities analysts play indispensable roles in the stock market, although the independence of China's securities analysts has been suspected for a long time. As the information medium between listed companies and investors, securities analysts can not only the transmit information among the market, but also provide deeper and more effective investment information for the majority of investors based on their professional investment knowledge. At present, the market still cannot make full use of the analyst behavior information. This paper opens a new perspective by combining the analyst behavior information with the technological linkages of the listed firms, which is not only conducive to providing investors with new investment strategies, but also conducive to improving the efficiency of the whole stock market in China.
Note: Downloadable document is in Chinese.
Keywords: Technological Links, Security Analysts, Trading Strategies, Limited Attention
JEL Classification: G11, G12, O30
Suggested Citation: Suggested Citation