Research On The Stock Selection Strategy And Product Design Of Private Equity Funds With The Theme Of Software Services

Software service industry as the token and characteristic of the new generation of information technology revolution is the inevitable choice for China to build a new global competitive advantage and seize the commanding heights of the new industrial revolution.In order to implement the 13th Five-Year Plan Outline of National Economic and Social Development of the People's Republic of China and Made in China 2025 and promote the development of software and information technology services,the Ministry of Industry and Information Technology compiled the Development Plan of Software and Information Technology Services(2016-2020).The listed companies of software services have more opportunities for great development.However,we notice that the A-share market is highly volatile and has a high systemic risk.According to the statistics of China Securities Corporation,the annual income of Shanghai and Shenzhen 300 reached 89.83%in 2015,29%in 2018,and only 1.01%in 2016-2018;the total software and services index(H30182)rose 95.41%in 2015,and showed a downturn in 2018,with a decline of 28.75%,16.73%in 2016-2018,and only-1.23%in five years.This paper tries to differentiate the advantages and disadvantages of software service companies listed in A-share market through stock selection strategy,build up winner portfolio and loser portfolio,and realize positive returns of fund products through hedging strategy.We strive to surpass Software Service industry's China Securities Index or Shanghai-Shenzhen 300 Index in terms of long-term annualized earnings and volatility risk.This paper mainly applies empirical methods to carry out research:data selection,using the data of 11 years(2007-2018)listed circulation enterprises in the software service sector as the research sample;methodologically,on the basis of GSCORE growth scoring model,combining with the financial characteristics of China's local high-tech companies,the paper establishes a"growth scoring model"suitable for the A-share software service industry.In the strategy test,the classical risk factors are used as control variables to test the validity and robustness of the scoring factors.In the process of measurement and simulation,we use the five-year market data from 2014 to 2018 to simulate the return of products.We calculate the annual return,volatility and Sharp ratio of products,and compare them with the Shanghai-Shenzhen 300 index and the China Stock Exchange Industry Index to evaluate the performance of products.This paper also examines the effectiveness of GSCORE theory and method by using China local stock market data of software and service industry and tries to build up a strategy to earn excess returns.Strategies formed in this paper not only based on the well documented traditional fundamental figures,such as return of assets(ROA),cash ratio and R&D expenditure,but also combines the industrial figures,referring to assets structure and cost composition.This paper draws the following conclusions through empirical research:the performance of the High GSCORE firms is better than Low GSCORE firms' in one-year return from 2014 to 2018.Although the buy-and-hold strategy relied on winners(High sores portfolio)achieved significant excess returns in year of 2014 and 2015,but failed in long-term compound yield.On the contrast,A long-short hedging strategy formed in this paper can't surpass the market returns in every single year,but achieved significant excess returns in long-term yield,with 7.27%in 3-year compound yield and 9.92%in 5-year compound yield,compared to CSI 300 index and industry index returns.From the perspective of risk,monthly return standard deviation of hedging strategy is 5.35%,Sharp ratio is 0.19,and maximum withdrawal is 13.75%.These risk indicators are better than the return of Shanghai-Shenzhen 300 index and industry index,showing outstanding performance.Finally,the factor variable GSCORE formed in this paper is still keeping robust and persists after controlling three classical risk factors,such as book-to-market,size and momentum.Apparently,most of return in the long-short strategy comes from short side.This conclusion is similar with the result drawn by Professor Mohanram in the year of 2002,although the fundamental figures applied in both experiments are partly different.