The Natural Pattern-based Fuzzy Investment System

Research background: The underlying research problem concerns simplifying nature’s infinite sustainability pattern into a usable system to prove self-care in the financial field. Many disciplines have discovered self-sustaining systems, implying one should also exist in the portfolio- or asset management field. Purpose of the article: This paper models and applies a self-sustaining investment system based on nature’s sustainability pattern to present a usable and easily adaptable financial self-care model that can contribute to societal and individual well-being. Methods: This interdisciplinary research incorporates fractal patterns from nature and integrates these into an innovative investment decision system via a working and utilizable model. The article approaches the problem in three ways. First, it applies an unprecedented, proprietary fuzzy heuristic approach to parse the Mandelbrot set hiding nature’s growth code. Second, it subjects the resulting model system to static, dynamic, and iterative methods. Finally, it tests the above in practice in a focus group research project based on individual decisions in a portfolio collision. Findings & value added: The paper brings manageable order to investment decision processes using a specific econophysics approach to provide a complex whole of frames, alternatives, and dynamic wealth management functions. The paper attempts to demonstrate the self-sustaining power of the natural order in investment portfolio returns, behavioral finance, and wealth management decisions. The theory of an efficient, well-functioning, self-sustaining investment decision system based on heuristic criteria is developable and has been proven. The study made the organizational dominance measurable and – through fuzzy logic – simplified the complexity of the Mandelbrot set. The research also shows the scalability of the fuzzy symmetry framework, implying that it is transferable to other disciplines.