RESEARCH ON RISK MEASUREMENT OF SUPPLY CHAIN FINANCE BASED ON FRACTAL THEORY


Liu X., Peng X., Stuart M.

FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY, cilt.28, sa.8, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 28 Sayı: 8
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1142/s0218348x20400137
  • Dergi Adı: FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Compendex, INSPEC, zbMATH, DIALNET, Civil Engineering Abstracts
  • Anahtar Kelimeler: Supply Chain Finance, Fractal Theory, Risk Measurement, Volatility Model, PERFORMANCE
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

Supply chain finance is a new financing model tailored for small and medium-sized enterprises, which integrates capital flow into supply chain management, providing commercial trade capital services for enterprises in all aspects of the supply chain and providing new loan financing services for vulnerable enterprises in the supply chain. Fractal originally is a general term for a graph, structure or phenomenon that does not have a feature length but has a statistically significant self-similarity; fractal theory is an emerging edge science that describes the complex system with a random structure and has been widely used in physics, chemistry, geography, economics and many other fields. On the basis of summarizing and analyzing previous published literature works, this paper expounded the research situation and significance of risk measurement in supply chain finance, elaborated the development background, current status and future challenges of fractal theory, proposed the improved fractal volatility model and financial evaluation model, performed risk analysis of supply chain finance through evaluation modeling and elastic fractal dimension, constructed a financial risk measurement model based on fractal theory, and discussed the importance of model parameter estimation, residual test and accuracy examination in risk measurement of supply chain finance. The final empirical analysis shows that the improved fractal volatility model and the proposed financial risk measurement model has better risk measurement ability under different out-of-sample prediction periods, and obtain more accurate conclusion of asymmetry determination of financial assets gains under the common inspection level. The study results of this paper provide a reference for the further researches on risk measurement of supply chain finance based on fractal theory.