YATIRIM İŞLEMLERİNİN DİJİTALLEŞMESİNİN PORTFÖY YÖNETİM ŞİRKETLERİ PERFORMASINA ETKİSİ VARMIDIR?

Öz

Bu çalışmanın amacı, dijital yatırım işlemlerinin bankaların portföy yönetim şirketleri işlem hacmine ve kârlarına etkisini araştırmaktır. Çalışmadaki değişkenlere ait gözlemler 9 adet banka için 2015 1.çeyrek dönemi ile 2023 1.çeyrek dönemi arasında eksiksiz olarak derlenerek 297 adet gözlem içeren dengeli bir panel veri seti oluşturulmuştur. Çalışmada Panel ARDL modeli, eş bütünleşme anali ve korelasyon analizlerinden faydalanılmıştır. Çalışmada betimsel istatistikler ve normal dağılım istatistiklerine göre, Toplam İşlem Hacmi değişkeninin normal dağılım gösterdiği, Portföy Yönetim Şirketi Kâr Tutarı, Tahvil İşlem Hacmi, Hisse Senedi İşlem Hacmi ve VİOP İşlem Hacmi değişkenlerinin normal değil fakat normale yakın dağılım gösterdiği tespit edilmiştir. CD Yatay Kesit Bağımlılık Testi bulgularına göre; Toplam İşlem Hacmi ve Portföy Yönetim Şirketi Kâr Tutarı değişkenleri için yatay kesit bağımlılığın olduğu ve diğer değişkenlerin birimlere göre değişmediği tespit edilmiş. Yatay kesit bağımlılık özelliği gösteren Toplam İşlem Hacmi ve Portföy Yönetim Şirketi Kâr Tutarı değişkenleri için yapılan IPS (2003), LLC (2002) ve CADF (2007) 2.nesil panel birim kök testi bulgularına göre, araştırmanın bağımlı değişkenlerinin düzeyde durağan olmayan ve birinci devresel farkında durağanlaşan değişkenler oldukları tespit edilmiştir (Toplam İşlem Hacmi, Portföy Yönetim Şirketi Kâr Tutarı). Birim sabiti ve zaman değişkeni olan değişkenler için 1.nesil panel birim kök testlerinden Breitung (1991) ve Harris-Tzavalis (1999) birim kök testi bulgularına göre, modellerdeki birim sabiti ve zaman değişkeni olan Tahvil İşlem Hacmi, Hisse Senedi İşlem Hacmi, VİOP İşlem Hacmi ve Yatırım Fonu İşlem Hacmi değişkenlerinin düzeyde durağan olmayan fakat birinci devresel farkında durağanlaşan değişkenler oldukları tespit edilmiştir. Değişkenler arasındaki korelasyon analizi bulgularına göre, Toplam İşlem Hacmi ile Tahvil İşlem Hacmi, VİOP İşlem Hacmi ve Yatırım Fonu İşlem Hacmi arasında %1 anlamlılık düzeyinde istatistiksel olarak anlamlı, orta düzeyde ilişki tespit edilmiştir. Toplam İşlem Hacmi ile Hisse Senedi İşlem Hacmi arasında ise istatistiksel olarak anlamlı bir ilişkisi saptanmamıştır. Portföy Yönetim Şirketi Kâr Tutarı değişkeni ile ise Tahvil İşlem Hacmi, Yatırım Fonu İşlem Hacmi ve Yatırım Fonu İşlem Hacmi arasında %1 anlamlılık düzeyinde istatistiksel olarak anlamlı düşük ve orta düzey arasında değişen pozitif ilişkileri söz konusu iken, Portföy Yönetim Şirketi Kâr Tutarı ile Hisse Senedi İşlem Hacmi arasında istatistiksel olarak anlamlı bir ilişkisi tespit edilmemiştir. Bağımsız değişkenler arası ilişkiler incelendiğinde ise, Tahvil İşlem Hacmi ile VİOP İşlem Hacmi ve Yatırım Fonu İşlem Hacmi arasında %1 anlamlılık düzeyinde istatistiksel olarak anlamlı ve oldukça yüksek bir ilişki tespit edilmiştir.

Anahtar Kelimeler

• Dijitalleşme
• Dijital Yatırımlar
• Portföy Yönetim Şirketleri.

DOES THE DIGITALIZATION OF INVESTMENT TRANSACTIONS HAVE AN EFFECT ON THE PERFORMANCE OF PORTFOLIO MANAGEMENT COMPANIES?

Öz

The purpose of this study is to investigate the impact of digital investment transactions on the trading volume and profitability of banks' asset management companies. The observations of the variables in the study are compiled for 9 banks between the 1st quarter of 2015 and the 1st quarter of 2023, and a balanced panel data set containing 297 observations is formed. Panel ARDL model, cointegration analysis and correlation analysis are utilized in the study. According to descriptive statistics and normal distribution statistics, Total Trading Volume variable is normally distributed, while Asset Management Company Profit Amount, Bond Trading Volume, Equity Trading Volume and VIOP Trading Volume variables are not normally distributed but close to normal. According to the findings of the CD Horizontal Cross-Section Dependence Test, it is determined that there is horizontal cross-section dependence for Total Trading Volume and Asset Management Company Profit Amount variables and other variables do not vary across units. According to the findings of the IPS (2003), LLC (2002) and CADF (2007) 2nd generation panel unit root tests for the variables Total Trading Volume and Portfolio Management Company Profit Amount, the dependent variables of the study were found to be non-stationary at the level and stationary at the first cyclical difference (Total Trading Volume, Portfolio Management Company Profit Amount). According to the findings of Breitung (1991) and HarrisTzavalis (1999) unit root tests, which are among the first generation panel unit root tests for variables with unit constant and time variables, the variables with unit constant and time variables in the models, namely Bond Trading Volume, Equity Trading Volume, VIOP Trading Volume and Mutual Fund Trading Volume, are found to be non-stationary in level but stationary in first-cycle difference. According to the findings of the correlation analysis between variables, there is a statistically significant, moderate relationship between Total Trading Volume and Bond Trading Volume, VIOP Trading Volume and Mutual Fund Trading Volume at the 1% significance level. There is no statistically significant relationship between Total Trading Volume and Equity Trading Volume. While there are statistically significant low to medium positive relationships between Asset Management Company Profit Amount variable and Bond Trading Volume, Mutual Fund Trading Volume and Mutual Fund Trading Volume at 1% significance level, there is no statistically significant relationship between Asset Management Company Profit Amount and Equity Trading Volume. When the relationships between independent variables are analyzed, there is a statistically significant and quite high relationship between Bond Trading Volume and VIOP Trading Volume and Mutual Fund Trading Volume at the 1% significance level.

Anahtar Kelimeler

• Digitalization
• Digital Investments
• Asset Management Companies.

Kaynakça

1. Asongu, S. A. (2018). Conditional determinants of mobile phones penetration and mobile banking in sub-Saharan Africa. The Journal of the Knowledge Economy, 9(1) 81–135.
2. Baltagi, B. H. (2005). Econometric Analysis of Panel Data. New Delhi: John WileyveSons Ltd.
3. Barber, B. M., ve Odean, T. (2001). “The internet and the investor”. Journal of Economic Perspectives, 15(1), 41-54.
4. Bhandarkar, V. V., Bhandarkar, A. A., ve Shiva, A. (2019). “Digital stocks using blockchain technology the possible future of stocks?”. International Journal of Management (IJM), 10(3), 44-49
5. Bildik, D. (2022). Finansal yenilikler ve Türkiye'deki ticari bankaların performasına etkileri (Yüksek Lisan Tezi), Hitit Üniversitesi Lisansüstü Eğitim Enstitüsü. Çorum.
6. Blackburne, E. F., ve Frank, M. W. (2007). “Estimation of Nonstationary Heterogeneous Panels”. Stata Journal, 197-208.
7. Buckley, R., Arner, D., ve Barberis, J. (2016). “The Evolution of Fintech: A New Post-Crisis Paradigm?”, Georgetown Journal of International Law, 47(4), 1271-1319.
8. Cankat, F., & Taşseven, Ö. (2023). Fıntech’lere Yapılan Yatırımların Bankaların Hisse Senedi Getirileri Üzerindeki Etkisi: Türkiye Örneği. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi, 45(1), 21-46.

9. Capgemini., ve Efma. (2016). World retail banking report. Retrieved October 2018, https://www.febelfin.be/sites/default/files/InDepth/worldretailbankingreport2015.pdf (09.08.2023).
10. Cenni, S., Monferrà, S., Salottic, V., Sangiorgid, M., & Torluccio, G. (2015). Credit rationing and relationship lending. Does frm size matter? Journal of Banking & Finance, 53, 249–265.
11. Chhaidar, A., Abdelhedi, M., & Abdelkafi, I. (2022). The effect of financial technology investment level on european banks’ profitability. Journal of the Knowledge Economy, 1-23.
12. Cho, T. Y., & Chen, Y. S. (2021). The impact of financial technology on China’s banking industry: An application of the metafrontier cost Malmquist productivity index. The North American Journal of Economics and Finance, 57.
13. Chuen, K., Lee, D., ve Teo, E.G.S., (2015). “Emergence of FinTech and the LASIC Principles”. Journal of Financial Perspectives. EY Global FS Institute, 3(3), 24-36.
14. Çil, N. (2018). Finansal Ekonometri. İstanbul: DER yayınları.
15. Darolles, S. (2016). The rise of fntechs and their regulation. Financial Stability Review, Banque De France, 20, 85–92
16. Deloitte Center for Financial Industry. (2017). Fintech by the numbers. Retrieved November 2018, https://www2.deloitte.com/content/dam/Deloitte/tr/Documents/financial-services/dcfs-fintech-by-the-numbers.pdf (05.08.2023).
17. Ertuğrul, H. M., Özün, A., & Kartal, M. T. (2021).Blokzincir Teknolojisinin Türk Bankacılık Sektörüne Etkileri: Halka Açık Mevduat Bankalarının Maddi Özsermaye Karlılığı Üzerine Bir İnceleme. İktisadî Araştırmalar Vakfı İktisadi İşletmesi Yayınları, İstanbul.
18. EY. (2018). Global Banking Outlook 2018. Retrieved November 2018, https://www.ey.com/Publication/vwLUAssets/ey-global-banking-outlook-2018/$File/ey-global-bankingoutlook-2018.pdf (06.08.2023).
19. Gomber, P., Koch, J. A., ve Siering, M. (2017). “Digital Finance and FinTech: current research and future research directions”. Journal of Business Economics, 87, 537-580.
20. Granger, C., ve P.Newbold. (1977). Forecasting Economik Time Series. London: Academik Press.
21. Harris, R., ve Sollis, R. (2003). Applied Time Series. John Wiley ve Sons.
22. Im, K., ve Pesaran, M. (2003). On the Panel Unit Roots Testin Using Nonlinear Instrumental Variables.
23. Juengerkes, B. E. (2016). FinTechs and Banks – Collaboration is Key. In S. Chishti, ve J. Barberis, The FinTech Book: The Financial Technology Handbook for Investors, Entrepreneurs and Visionaries (p. 179-182). London: Wiley.
24. Jun, J., ve Yeo, E. (2016). “Entry of FinTech Firms and Competition in the Retail Payments Market”. Asia-Pacific Journal of Financial Studies, 45(2), 159-184.
25. Kou, G., Olgu Akdeniz, Ö., & Dinçer, H. (2021). Fintech investments in European banks: A hybrid IT2 fuzzy multidimensional decision-making approach. Financial Innovation, 7, 39.
26. KPMG. (2018). The Pulse of Fintech:Biannual global analysis of investment in fintech. Retrieved February 2019, https://home.kpmg/content/dam/kpmg/xx/pdf/2018/07/h1-2018-pulse-of-fintech.pdf (08.08.2023).
27. Le, T., & Ngo, T. (2020). The determinants of bank proftability: A cross-country analysis. Central Bank Review, 20, 65–73.
28. Lee, I., ve Shin, Y. J. (2018). “Fintech: Ecosystem, business models, investment decisions, and challenges”. Business horizons, 61(1), 35-46.
29. Levin, A., Lin, C., ve Chu. (2002). “Unit Root Test in Panel Data: Asympotic and Finite-Sample Properties”. Journal of Econometrics, s. 1-24.
30. Li, Y., Spigt, R., ve Swinkels, L. (2017). “The impact of Fintech startups on incumbent retail banks’ share prices. Rotterdam: Erasmus University Rotterdam. Springer Link”. Journal of Financial Innovation. 26(3), 1-16.
31. Liberti, J. M., & Peterson, M. (2019). Information: Hard and soft. The Review of Corporate Finance Studies, 8(1), 1–41
32. Loayza, N., ve Ranciere, R. (2006). “Financial Development, Financial Fragility, and Growth”. Journal of Money, Credit and Banking, s. 1051-1076.
33. Madsen, E. (2008). “Unit root inference in panel data models where the time-series dimension is fixed: a comparison of different tests”. The Econometrics Journal, 63-94.
34. Medyawati, H., Yunanto, M., & Hegarini, E. (2021). Financial Technology as Determinants of Bank Profitability. Journal of Economics, Finance and Accounting Studies, 3(2), 91-100.
35. Miller, D., ve Liu, K. (2014). Creative Destruction: Evidence From Initial Public Offerings. In Academy of Management Proceedings (Vol. 2014, No. 1, p. 17308). Briarcliff Manor, NY 10510: Academy of Management.
36. Mire, S. (2018). Blockchain for stock markets: 11 possible use cases.
37. Naimi-Sadigh, A., Asgari, T., & Rabiei, M. (2021). Digital transformation in the value chain disruption of banking services. Journal of the Knowledge Economy, 13, 1-31.
38. Navaretti, G. B., Calzolari, G., Mansilla-Fernandez, J. M., ve Pozzolo, A. F. (2017). Fintech and banking. Friends or foes?. Friends or Foes.
39. Ningsi, E. H., Manurung, L., Ardillah, Y., ve Ramadhani, S. (2022). “Good Corporate Governance Model on Corporate Financial Performance in the Era of the Digital Revolution on the Indonesia Stock Exchange”. Journal of Economics, Finance And Management Studies, 5(08), 2182-2190.
40. Omarini, A. (2015). Retail banking: business transformation and competitive strategies for the future. New York: Palgrave Macmillan.
41. Pesaran, M. (2007). “A Simple Panel Unit Root Test in the Presence of Cross Section Dependence”. Journal of Applied Econometrics, 265-312.
42. Pesaran, M. H. (2004). General Diagnostic Test for Cross Section Dependence in Panels. Cambridge: Cambridge Working Papper.
43. Peters, G. W., & Panayi, E. (2015). Understanding Modern Banking Ledgers through Blockchain Technologies: Future of Transaction Processing and Smart Contracts on the Internet of Money. Social Science Research. 239-279.
44. PwC. (2018). Digital Banking Survey 2018. Retrieved December 2018, https://www.pwc.com/id/en/publications/assets/financialservices/digital-banking-survey-2018-pwcid.pdf (04.08.2023).
45. Romānova, I., and Kudinska, M. (2016). “Banking and Fintech: A Challenge or Opportunity?”. In: Contemporary Issues in Finance: Current Challenges from Across Europe, 98, 21-35.
46. Sahi, H. (2017). Studying market reactions to Fintech companies-Acquisitions and initial public offerings in OECD Countries. Master’s Thesıs, Lappeenranta Unıversıty Of Technology
47. Saidi, A. M. (2018). E-Payment technology efect on bank performance in emerging economies–evidence from Nigeria. Journal of Open Innovation: Technology, Market and Complexity, 4(4), 43.
48. Samargand, N., Fidrmuc, J., ve Ghosh, S. (2014). Is the Relationship between Financial Development and Economic Growth Monotonic? Evidence from a Sample of Middle Income Countries. Munich: Leibniz Institute for Economic Research at the University of Munich.
49. Scott, S. V., Reenen, J. V., & Zachariadis, M. (2017). The long-term efect of digital innovation on bank performance: An empirical study of SWIFT adoption in fnancial services. Research Policy, 46, 984– 1004
50. Sheng, T. (2021). The efect of fntech on banks’ credit provision to SMEs: Evidence from China. Finance Research Letters, 39(C
51. Song, T., Cai J., & Le, L. (2021). Towards smart cities by Internet of Things (IoT)-A silent revolution in China. The Journal of the Knowledge Economy, 12(2), 1–17.
52. Sood, A., ve Tellis, G. J. (2009). “Do innovations really pay off? Total stock market returns to innovation”. Marketing Science, 28(3), 442-456.
53. Sorrentino, F. (2015). Millennials ve FinTech are top of mind for traditional banks. Forbes. Retrieved September 2018, https://www.forbes.com/sites/franksorrentino/2015/11/20/heard-at-the-2015-aba-national-convention/#34e0886465cb (09.08.2023).
54. Sucipto. 2018. Financial Performance Assessment. Medan: Usu Digital Library
55. Tatoğlu, F. Y. (2018). Panel Zaman Serileri Analizi. İstanbul: Beta.
56. Treleaven, P., Brown, R. G., ve Yang, D. (2017). “Blockchain technology in finance”. Computer, 50(9), 14-17.
57. Tunay, K. B., Tunay, N., & Akhisar, İ. (2015). Interaction between Internet banking and bank performance: The case of Europe. Procedia - Social and Behavioral Sciences, 195, 363–368
58. Ulusoy, A. (2022). Türk Bankacılık Sisteminde Dijitalleşme-Kârlılık Etkileşimi. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 40(1), 184-200.
59. Wang, Y., Xiuping, S., & Zhang, Q. (2021). Can fintech improve the efficiency of commercial banks?—An analysis based on big data. Research in international business and finance, 55.
60. Wood, G., & Buchanan, A. (2015). Advancing Egalitarianism. In: D.L.K. Chuen (ed.), Handbook of Digital Currency: Bitcoin, Innovation, Financial Instruments, and Big Data. London: Elsevier.
61. Zhang, M., & Yang, J. (2019). Research on fnancial technology and inclusive fnance development. In 2018 6th international conference on economics, social science, arts, education and management engineering. Atlantis Press