| dc.description.abstract | This study incorporates innovation efficiency factor proposed by Hirshleifer et al. (2013) into the three-factor asset pricing model to capture both input and output of innovation in boosting the explanatory power of how innovation efficiency affects the return of listed companies in the Taiwan electronics industry. Employing single-factor, three-factor, and four-factor asset pricing models, this study applies panel data analysis to investigate the effect of market risk factor (〖MKT〗_t) , size factor (〖SMB〗_t) , value factor (〖HML〗_t) , and innovation efficiency factor (〖EMP〗_t) on the stock returns of listed companies in the electronics industry from July 2010 to June 2021.
The empirical results show that the monthly average returns of a market portfolio comprised of listed companies in the electronics industry of Taiwan outperform those of risk-free assets, a finding that corroborates the Capital Asset Pricing Model (CAPM). Additionally, the size factor (SMB) and the value factor (〖HML〗_t) explain the cross-sectional stock returns well, where small-sized investment portfolios yield higher monthly average returns compared to large-sized investment portfolios, and investment portfolios with high book-to-market ratios deliver higher monthly average returns than those with lower book-to-market ratios, thus confirming the findings of Fama & French (1992).
Furthermore, innovation efficiency factor (〖EMP〗_t) also holds explanatory power for the overall electronics industry, consistent with the findings of Hirshleifer et al. (2013), suggesting that stocks with higher innovation efficiency tend to yield higher returns compared to those with lower innovation efficiency. Specifically, the high innovation efficiency investment portfolio′s monthly average annualized return outperforms the low innovation efficiency investment portfolio by 0.9642%. Further heterogeneity analysis reveals that the innovation efficiency factor (〖EMP〗_t) lacks explanatory power in the optoelectronics, telecommunications, and computer peripherals industries. However, it is significant at a 10% level in other electronic industries, at a 5% level in the electronic distribution and electronic components industry, and a 1% level in the semiconductor industry. This illustrates the varying degree of impact of innovation efficiency across sub-industries, thus calling for fund managers to thoroughly consider the differential impact of innovative activities on stock returns when selecting investment targets and optimizing the timing of buying and selling within the electronics industry. | en_US |