بررسی عوامل تعیین کننده سرمایه گذاری مخاطره آمیز در بورس اوراق بهادار تهران

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری حسابداری دانشگاه ازاد اسلامی واحد زاهدان، زاهدان، ایران

2 استادیار دانشکده مدیریت و اقتصاد , دانشگاه سیستان و بلوچستان، زاهدان، ایران

10.22111/jmr.2021.35779.5222

چکیده

سرمایه‌گذاری‌های مخاطره‌آمیز نقش مهمی در اقتصاد ایفا می‌کنند. هدف مقاله حاضر بررسی عوامل تعیین‌کننده سرمایه‌گذاری مخاطره‌آمیز در شرکت‌های پذیرفته‌شده در بورس اوراق بهادار تهران است. پژوهش حاضر ازنظر هدف، کاربردی و ازنظر روش پژوهش توصیفی پیمایشی با رویکرد علی مقایسه‌ای است. 100شرکت حاضر در بورس اوراق بهادار ایران در سال‌های 1393 تا 1398 به‌عنوان نمونه انتخاب شد. داده‌ها از پایگاه‌های داده‌ای بانک مرکزی ایران، مرکز آمار ایران، وب‌سایت کدال، سایت سازمان بورس اوراق بهادار تهران و سایت WDI ( بانک جهانی) گردآوری و با استفاده از نرم‌افزارهای Excel و 9Eviews و matlab تجزیه‌وتحلیل شد. فرآیند انجام تحقیق به این صورت بود که عوامل تعیین‌کننده سرمایه‌گذاری مخاطره‌آمیز در بورس اوراق بهادار تهران (حجم سرمایه‌گذاری، میزان صادرات، مالیات شرکت، شاخص افشا، شاخص حاکمیت قانون، تنوع‌گرایی صنعت، تنوع‌گرایی مراحل چرخه عمر شرکت، نوع مالکیت، تعداد بخش‌ها و شرکت‌های تابعه، سرمایه‌گذاری شرکت ، اندازه شرکت و سن شرکت) با استفاده از مطالعه ادبیات پژوهش تعیین و با به‌کارگیری شبکه عصبی و منطق فازی به ایجاد یک مدل پیشگویانه برای تعیین ریسک سرمایه‌گذاری بر اساس شاخص‌های تعیین شده پرداخته شد. مدل دسته‌بندی بر اساس ترکیب خوشه‌بندی با استفاده از شبکه عصبی بدون نظارت SOM و انعطاف‌پذیری منطق فازی ارائه شد. پارامتر ارزیابی طرح، دقت دسته‌بندی ترکیبی ارائه‌شده، مقدار خطای میانگین مربعات و ضریب تبیین می‌باشد. نتایج شبیه‌سازی حاکی از آن بود که عملکرد طرح پیشنهادی نسبت به دسته‌بندی به روش شبکه عصبی MLP بهبود داشته و مدل پیشنهادی بر مبنای آموزش ارائه‌شده به مدل، با دقت مطلوبی به پیش‌بینی وضعیت سرمایه‌گذاری‌های انجام‌شده پرداخته است.

کلیدواژه‌ها


عنوان مقاله [English]

Determinants of Venture Capital on the Tehran Stock Exchange

نویسندگان [English]

  • Nahid Naeimi 1
  • Ramin Zeraatgari 2
1 PhD Student, Department of Accounting, Zahedan Branch, Islamic Azad University, Zahedan, Iran.
2 Professor of Accounting, University of Sistan and Baluchestan, Zahedan, Iran
چکیده [English]

Abstract
Venture capital plays a significant role in economy. Different types of companies involved in venture capital activities may face difficulty in financing. This study aimed to investigate the determinants of venture capital in the companies listed on the Tehran Stock Exchange.
 The present study was applied in terms of purpose and In terms of the descriptive research method, it is a survey with a comparative causal approach. A number of 100 companies listed on the Tehran Stock Exchange in 2014 to 2019 were selected as a sample. Data were collected from the databases of the Central Bank of Iran, Statistics Center of Iran, Codal website, and WDI website and Tehran Stock Exchange website, and then analyzed using Excel, 9Eviews, and Matlab software. In this study, the determinants of venture capital on the Tehran Stock Exchange (capital volume, export volume, company tax, disclosure index, rule of law index, industry diversity, diversity of company life cycle stages, type of property, number of divisions and subsidiaries, company capital, company, size and company age) By studying the research literature and using neural network and fuzzy logic, a predictive model was created to determine the investment risk based on the determined indicators.. The classification model was presented using neural network without SOM supervision and fuzzy logic flexibility. The evaluation parameters of design, accuracy of the proposed ensemble classifier, mean error of the squares, and coefficient of explanation. The simulation results indicated that the performance of the proposed design compared to the classification by MLP neural network method was improved and the presented model based on the training provided predicted the status of capital with good accuracy.
Introduction
Venture capital and its role in economy has been raised since the 1990s and includes not only financial capital but also non-financial capital. (Gompers and Lerner, 1998). Venture capital is described as a means of providing capital to the companies which may not use independent financial instruments and thus require external financing. Venture capital is a kind of active capital in the market in which some activities like monitoring and influencing the company's strategic decisions are performed using salary control and board seats. The abilities of an individual to participate in venture capital to add more value is reflected in the duration of the capital (Hain et al., 2018).
Materials and Method
The data set used in this simulation included capitals made by the companies listed on the stock exchange in 2014 to 2019, with a record of 500 capitals selected as a sample. Such data included two parts: training data and testing data to evaluate the accuracy of the model in forecasting. Of all the devices, 350 capitol records were used as training data and 150 capital data were as test datasets to evaluate project performance. Each capital record was assigned a numerical value as the amount of venture capital. The present study was applied in terms of purpose. The purpose of applied research is to develop applied knowledge in a specific field. In addition, the present study was descriptive-correlational in terms of method and nature. This study aimed to determine the relationship between variables. For this purpose, appropriate indicators were obtained based on the scale of measurement of variables. The study was conducted in form of inductive deduction and its information was expost facto. The present study was a thematic area in the field of finance with a focus on venture capital issues. Tehran Stock Exchange was selected as the spatial domain of the present study. Data were collected from the databases of the Central Bank of Iran, Statistics Center of Iran, Codal website, Tehran Stock Exchange website, and then analyzed using Excel, 9Eviews, and Matlab software. The research process was as follows: in the framework of developing economies, focusing on Iran, the determinants of venture capital on the Tehran Stock Exchange were identified. Then, a predictive model was created using neural network and fuzzy logic to determine venture capital based on extractive indicators. capital volume, export volume, company tax, disclosure index, rule of law index, industry diversity, diversity of life cycle stages of the company, type of property, number of divisions and subsidiaries, company capital, company size and age of the company were twelve factors determining venture capital on the Tehran Stock Exchange.
Hypothesis
1:  The investment volume of mergers and acquisitions has an effect on venture investment in the Tehran Stock Exchange.
2:  Exports have an effect on venture investment in Tehran Stock Exchange.
3:  Company tax has an effect on venture investment in Tehran Stock Exchange.
4: Disclosure index has an effect on venture investment in Tehran Stock Exchange.
5: The rule of law index has an effect on venture investment in the Tehran Stock Exchange.
6: Diversification of industry has an effect on venture investment in Tehran Stock Exchange.
7:  Diversification of different stages of the company's life cycle has an effect on venture investment in the Tehran Stock Exchange.
8: The type of ownership has an effect on venture investment in Tehran Stock Exchange.
9: The number of sections and subsidiaries has an effect on venture investment in Tehran Stock Exchange.
10: The company investment has an effect on venture investment in Tehran Stock Exchange.
11: Company size has an effect on venture investment in Tehran Stock Exchange.
12: The age of company has an effect on venture investment in the Tehran Stock Exchange.
Discussion and Results
 The design evaluation parameter was the mean square error (MSE) and the explanation index (R2) of the proposed ensemble classifier
In order to compare the proposed design with existing tools, it was necessary to determine the accuracy of these tools on their data set, so in this section, the MLP neural network was used first to predict venture capital. At this step, 12 features were proposed for corporate capital records as input neurons to the neural network. The output of the network was the amount of venture capital. Here, the neural network had the task to provide conditions in the model training phase by determining the weights, so that the predicted amount of venture capital had the least difference with their actual amount.
After training, the neural network was evaluated to test performance with testing data.
Conclusion
In the proposed design, to predict the initial clustering of data by SOM method, to calculate the centers of clusters, the innovative formula was used and combined with fuzzy logic of the second type was used.
In the current design, the researchers used the SOM neural network, which is an unsupervised learning method, along with logic flexibility, to decide on the amount of venture capital. The SOM network clusters the observed data and determines the centers of the clusters, then assigns a probabilistic value to each cluster in the range of zero and one, depending on the sample density in each cluster. After that, a model for labeling new samples based on the distance factor from the centers of the clusters was presented, which based on the second type fuzzy logic, the probability of each sample belonging to each class is determined. The simulation results indicate that the performance of the proposed design has improved compared to the classification by MLP neural network method and the proposed model based on the training provided to the model, has predicted the status of capitals with good accuracy.

کلیدواژه‌ها [English]

  • Venture capital
  • predictive model
  • neural network
  • fuzzy logic
  • Tehran Stock Exchange

منابع فارسی

اصغریان، احسان و سخدری، کمال و خدایی، هاینه (1395) " صنعت سرمایه­گذاری مخاطره آمیز (فرآیند سرمایه­گذاری و ابزار ارزیابی)"، کنفرانس ملی سرمایه­گذاری مخاطره­پذیر، سال 1395، دوره
عسکری ماسوله، سعید و افشار، مهدی (1395) "بررسی وضعیت امکان­پذیری صنعت سرمایه­گذاری­های مخاطره­پذیر در ایران: فرصت­ها، چالش­ها و آسیب شناسی"، نخستین کنفرانس بین­المللی پارادیم­های نوین مدیریت هوشمندی تجاری و سازمانی.
سجادی، سیدمجتبی و اسماعیل حافظی، محمد (1394) "بررسی راهکارهای تأمین سرمایه­گذاری مخاطره­پذیر به عنوان محرکی در رونق اکوسیستم کسب و کار"، اولین کنفرانس بین­المللی علوم انسانی با رویکرد بومی - اسلامی و با تاکید بر پژوهش­های نوین.
کریم‌خانی، مهرداد؛ پاکیزه، کامران؛ اخوان انوری، محمّدرضا. (1396). رتبه‌بندی عوامل اثرگذار بر نوآوری شرکت‌های سرمایه‌پذیر از منظر سرمایه‏­گذاران مخاطره­ پذیر (مورد مطالعه: صندوق‌های سرمایه‌گذاری مخاطره­پذیر و شتاب‌دهنده‌ها). فصلنامه علمی پژوهشی توسعه کارآفرینی، 10(4)
خطیب، محمود و محقق­نیا، محمدجواد و صادقی شاهدانی، مهدی و سرگلزایی، مصطفی،1400، شناسایی عوامل موثر برسرمایه­گذاری طرح­های فناورانه مرحله رشد شرکت­های دانش بنیان در نظام بانکی.
مشهدی، رضا و احمدیه، محمد امین،1397،ارائه مدل بکارگیری و توسعه صندوق های سرمایه گذاری خطرپذیر در اقتصاد ایران در راستای اقتصاد مقاومتی و مقابله با جنگ اقتصادی، فصلنامه اقتصاد دفاعی(19 )ص129-150.
حیدری، مهرناز؛ محمدی، پرستو. (1396). مسائل کارگزاری در سرمایه‌گذاری خطرپذیر و راهکارهای رفع آنها در مراحل مختلف رشد شرکت‌های نوآور در ایران. مدیریت نوآوری، 6(3)، 113-140.
پالیزدار، کاظم؛ مدنی، شیما؛ عسگری­نیا، محسن. (1397). بررسی عوامل رفتاری و محیطی مؤثر بر جذب سرمایه‌گذار خطرپذیر جهت سرمایه‌گذاری در شرکت‌های دانش‌بنیان (مطالعه موردی: صنعت بیوتکنولوژی ایران). تحلیل های اقتصادی توسعه ایران، 6(1)، 93-124.
احسنی زاد، سامان؛ پیشوایی، میرسامان؛ کریمی، امیر علی. (1395). رتبه­بندی طرح­های کسب وکار سرمایه­گذاری خطرپذیر با روش تحلیل پوششی داده­ها- مورد مطالعه: یک شرکت سرمایه­گذاری خطرپذیر ایرانی. مدیریت نوآوری، 5(2)، 87-108.
غضنفری، حسین؛ خداداد حسینی، سیدحمید؛ کردناییج، اسدالله؛ آذر، عادل. (1398). مدل سرمایه گذاری مخاطره­آمیز شرکتی در شرکت­های فناوری اطلاعات. اندیشه مدیریت راهبردی (اندیشه مدیریت)، 13(1)، 255-293.
رضایی، محسن و حیات الغیب مقدم، سیده نسیم و اسمعیلی زاده، اعظم،1396،نقش صندوق­های پژوهش و فناوری در افزایش سرمایه­گذاری خطرپذیر، هشتمین کنفرانس بین­المللی حسابداری و مدیریت با رویکرد علوم پژوهشی نوین، تهران.
سجادی، سید مجتبی و حافظی، محمد اسماعیل (1394) بررسی راهکارهای تأمین سرمایه­گذاری مخاطره­پذیر به عنوان محرکی در رونق اکوسیستم کسب و کار،اولین کنفرانس بین المللی علوم انسانی با رویکرد بومی - اسلامی و با تاکید بر پژوهش های نوین،ساری.
 
Refrences
Asgharian, E, Sakhdari, K. Khodaei, H. (2016). Venture capital industry Investment Process and Valuation Tools, National Conference on Venture Capital, 2016, Volume (In persina)
Askari Masoleh, S and Afshar, M, (2016). Investigating the feasibility of the venture capital industry in Iran: opportunities, challenges and pathologies, the first international conference on new paradigms of business and organizational intelligence management.
Bonini, S. Alkan, S. (2017).  The Macro and Political Determinants of Venture Capital Investments around the World., 16th November 2017
Bustamante, C. V., Mingo, S., & Matusik, S. F. (2021). Institutions and venture capital market creation: The case of an emerging market. Journal of Business Research, 127, 1-12.
Felix, R. A. (2007). Passing the burden: Corporate tax incidence in open economies (No. 468). LIS Working Paper Series
González, C., & Massieu, D. R. (2021). Universally-enabling and context-binding resources in new venture internationalization: Evidence from venture capital backed start-ups in an emerging market. International Business Review, 101851
Gazdar, K., & Cherif, M. (2015). Institutions and the finance–growth nexus: Empirical evidence from MENA countries. Borsa Istanbul Review, 15(3), 137-160.
Gompers, P., & Lerner, J. (1998). Venture capital distributions: Short‐run and long‐run reactions. The Journal of Finance, 53(6), 2161-2183
Hain, D. Johan, S. Wang, D (2018). Determinants of Cross-Border Venture Capital Investments in Emerging and Developed Economies. The Effects of Relational and Institutional Trust., Journal of Business Ethics, No. 2018, Vol, 138, Issue 4, PP. 743–764.
Hongtao, Y. (2020) Citation DataMicroprocessors and Microsystems, ISSN: 0141-9331, Page: 103457 Publication
KarimKhani, M. Pakizeh, K. Akhavananvari, M. (2017). Ranking the factors affecting the innovation of investable companies from the perspective of venture capitalists, Entrepreneurship Development, Vol. 10, No.4.655-674
Khatib, M. Mohaghnia., MJ. Shahdani, M. sargolzaee,   M.  (2021). Identifying the factors affecting the investment of technological projects in the growth stage of knowledge-based companies in the banking system. Business Management Quarterly. Vol. 50.239-250(In Persian)
Karim, M. (2019).  Determinants  of  Venture  Capital Investments:  A panel data analysis across regions in the United Kingdom., Bachelor Thesis
Within, Economics Nunber of Credits, Programme of Study, International Economics, 2019, Bachelor Thesis in Economics.
Mashhadi, R. Ahmadiieh, A. (2018). Provide a model for the use and development of venture capital funds In the Iranian economy in the direction of resistance economy and confrontation with war Economical. Defense Economics Quarterly.vol9.129-150(In Persian)
Mohammadi, P. Haidari, M. (2017). Brokerage issues in venture capital and solutions to eliminate them in different stages of growth of innovative companies in Iran.Innovation Management.vol3.113-140
Palizdar, K. Madani, Sh. Asgary Nia, M. (2018). Assessing behavioral and environmental factors affecting the attraction of venture capital for investing in Knowledge-based companies. Economic Development Policy, Vol. 6, Issue 1, 5-17(In Persian)
Pishvaee, M. Karimi, A. Ahsanizadeh, S. (2016). Ranking of venture capital business plans by data envelopment analysis. Innovation Management.vol2.78-108(In Persian)
Park, S., LiPuma, J.A. (2020) New venture internationalization: The role of venture capital types and reputation Journal of World Business, Volume 55, Issue 1.
Peter Groh, A. Wallmeroth, J. (2016). Determinants of venture capital investments in emerging markets., Emerging Markets Review, Vol. 29, December 2016, PP. 104-132.
Qazanfari, H. Khodadad Hosseini, H. Kordnaeij, A. Azar, A.(2019). Corporate Venture Capital (CVC) Model in ICT Companies. Strategic Management Thought, Vol.13, No.1.25(In Persian)
Rezaei, M.  Hayat al-Gheyb Moghadam, N. Esmailizadeh, A. (2017) "The role of research and technology funds in increasing venture capital", 8th International Conference on Accounting and Management with a New Research Sciences Approach. (In Persian)
Sajadi, M. Hafezi, M (2015) "Study of venture capitalstrategies as a stimulus for the prosperity of business ecosystem", the first international conference on humanities with a native-Islamic approach and emphasis on new research. (In persina)
Shao, Y., & Sun, L. (2021). Entrepreneurs’ social capital and venture capital financing. Journal of Business Research, 136, 499-512.
Tykvová, T. (2018). Legal framework quality and success of (different types of) venture capital investments. Journal of Banking & Finance, 87, 333-350.