The impact of patent citation information flow regarding economic innovation on common stock returns: Volume vs. patent citations

摘要

This study examines whether the number of forward patent citations (along with alternative patent data)—when used as a proxy for the mixing variable—could infer the aggregate amount of economic-innovation information arriving at the New York Stock Exchange (NYSE) in the United States. The results show that the number of forward patent citations, when used as a mixing variable, fails to eliminate total volatility persistence in the conditional variance equation of the exponential generalized autoregressive conditional heteroscedastic (EGARCH) model. However, the trading volume successfully eliminates total volatility persistence, thus confirming the validity of the framework used. When the volatility is modeled with an expectation of mean return, the persistence of conditional variance is deterministically increased, and the sum of the volatility coefficients exceeds unity. The inclusion of trading volume with a time trend in the variance equation rectifies the deterministic increase in the conditional volatility. These findings suggest that the form of heteroscedasticity (i.e., as per the autoregressive conditional heteroscedastic model, ARCH model) in NYSE portfolio returns is based on the type of shocks to volatility (e.g., deterministic vs . stochastic), which manifests as news arrivals (i.e., new information arrivals proxied by trading volume) at the stock market. The volume therefore reflects the time dependence in the innovations to the ARCH error generation process. The response of volatility to volume persists over time when the volatility estimates are derived from the EGARCH model with an expectation for the mean of return. Backward patent citations, patent applications, and patents issued have been found to interact somewhat with trading volume, suggesting that each of these variables could play the role of an absorptive capacity variable as the new information flow associated with economic innovation (i.e., flow of firms’ stock of new knowledge) could be picked up by the trading volume.