The mechanism of politically-connected managers on technological innovation for small and medium high-tech enterprises - empirical evidence from listed firms in Chinese SMEs stock market

Author(s):  
Zhenyi Wang ◽  
Jinjian Yang ◽  
Huqin He ◽  
Li Su
2014 ◽  
Vol 30 (4) ◽  
pp. 1211
Author(s):  
C. Catherine Chiang ◽  
Yilun Shi ◽  
Lin Zhao

In this paper, we investigate the relation between stock returns and R&D spending under different market conditions. Our empirical evidence suggests that investors response to R&D activities varies according to stock market status. Following the conventional definitions of markets, we first categorize the market into four different states: slightly up (up by 0-20%), bull (up by more than 20%), slightly down (down by 0-20%), and bear (down by more than 20%). Using firms in high-tech industries from 1992 to 2009 as our sample, we show that investors value R&D spending consistently positively only when the market (proxied by the S&P 500) is up. R&D is valued less in the downward market and R&D response coefficients even turn negative during bear markets. However, earnings response coefficients are consistently positive regardless of market status. The results remain unchanged after we control for beta, bankruptcy risk, size, and different measuring windows. Our findings cannot be explained by risk-based hypothesis. The study advances our understanding of the relation between stock returns and R&D activities by empirically documenting its variations in market valuation across different market states; particularly, we found empirical evidence that R&D response coefficients in the down markets are negative. The study also provides additional input to the ongoing debate on finding the appropriate accounting treatment for intangible assets.


2017 ◽  
Vol 33 (2) ◽  
pp. 391-408
Author(s):  
Sun Min Kang

This research investigates the attributes of firms that choose to voluntarily delist in Korea, including the evolution of firms after delisting, using performance indicators such as total assets, revenue, and net income. Empirical evidence suggests that the higher the shareholding ratio of the largest shareholder and the higher the growth prospects and liquidity, the greater the incentive for voluntary delisting. In addition, firms in non-high-tech industries choose to delist more often than those in high-tech industries. Further, firms that have delisted show lower total assets, revenues, and net incomes than listed firms, and these gaps increase over time.


2019 ◽  
Vol 12 (3) ◽  
pp. 125-133
Author(s):  
S. V. Shchurina ◽  
A. S. Danilov

The subject of the research is the introduction of artificial intelligence as a technological innovation into the Russian economic development. The relevance of the problem is due to the fact that the Russian market of artificial intelligence is still in the infancy and the necessity to bridge the current technological gap between Russia and the leading economies of the world is coming to the forefront. The financial sector, the manufacturing industry and the retail trade are the drivers of the artificial intelligence development. However, company managers in Russia are not prepared for the practical application of expensive artificial intelligence technologies. Under these circumstances, the challenge is to develop measures to support high-tech projects of small and medium-sized businesses, given that the technological innovation considered can accelerate the development of the Russian economy in the energy sector fully or partially controlled by the government as well as in the military-industrial complex and the judicial system.The purposes of the research were to examine the current state of technological innovations in the field of artificial intelligence in the leading countries and Russia and develop proposals for improving the AI application in the Russian practices.The paper concludes that the artificial intelligence is a breakthrough technology with a great application potential. Active promotion of the artificial intelligence in companies significantly increases their efficiency, competitiveness, develops industry markets, stimulates introduction of new technologies, improves product quality and scales up manufacturing. In general, the artificial intelligence gives a new impetus to the development of Russia and facilitates its entry into the five largest world’s economies.


2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Shahid Rasheed ◽  
Umar Saood ◽  
Waqar Alam

This study aims to examine the momentum effect presence in selected stocks of Pakistan stock market using data from Jan 2007 to Dec 2016. This study constructed the strategies includes docile, equal weighted and full rebalancing techniques. Data was extracted from the PSX – 100 index ranging from 2007 to 2016. STATA coding ASM software was used for calculating momentum portfolios, finally top 25 stocks were considered as a winner stocks and bottom 25 stocks were taken as a loser stocks. In conclusion, the results of the study found a strong momentum effect in Pakistan stock exchange PSX 100- index. As by results it has been observed that a substantial profit can earn by the investors or brokers in constructing a portfolio with a short formation period of three months and hold for 3, 6 and 12 months. There is hardly a study is present on the same topic on Pakistan Stock Exchange as preceding studies were only conducted on individual stock markets before merger of stock markets in Pakistan while this study leads the explanation of momentum phenomenon in new dimension i.e. Pakistan Stock Exchange. Keywords: Momentum, Portfolio, Winner Stocks, Loser Stocks


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