
his deposit contains the complete reproducible materials for Chapter 4: Methodology and Settings of the thesis: “The Unlucky Investor: How Even “Clean-Shot” Investments Are Contaminated by Upstream Pollution – A Natural-Science Approach to Financial Decision-Making in Opaque Markets” by Philipp Gandolfi (May 2026). Contents Full polished text of Chapter 4 (sections 4.1–4.7) Mixed-methods research design and operationalisation of the Biomagnification Contamination Model Detailed hardware, software, and containerised environment specifications (Docker 27.1 + Singularity 3.11) Data sources, preprocessing pipelines, and financial food-web network construction Monte-Carlo simulation design (10,000 runs per scenario), parameter calibration, random-seed strategy, and full reproducibility protocols These materials form the methodological foundation for the empirical analysis in Chapters 5 and 6. All Monte-Carlo simulations, sensitivity analyses, and figures presented in the thesis can be exactly reproduced using the accompanying codebase. Links GitHub repository: https://github.com/philippgandolfi/unlucky-investor-thesis Zenodo DOI for this record: (assigned automatically upon publication) Reproducibility declaration: All empirical results, figures, and tables in this thesis that depend on Chapter 4 can be regenerated exactly from the publicly released codebase, containerised environment, provided data, and fixed random seeds.
unlucky investor, biomagnification, supply chain risk, reaction-diffusion model, financial contamination, greenwashing, ESG risk, sustainable finance, Scope-3 emissions, Monte Carlo simulation
unlucky investor, biomagnification, supply chain risk, reaction-diffusion model, financial contamination, greenwashing, ESG risk, sustainable finance, Scope-3 emissions, Monte Carlo simulation
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