Financial Phase Diagram Example
Description
Data, code, and summary dashboard example to support the manuscript "A Novel Analytics-Based Approach to Mining Project Valuations". ABSTRACT Mining is a capital-intensive industry where strategic decisions to buy, sell, develop, expand, or close an asset require a strong understanding of the economic value and financial risks involved. However, discounted cash flow (DCF) valuations, conventional sensitivity analyses, and probabilistic methods of quantifying uncertainty and risk either fail to consider many combinations of variables and/or are prone to inaccuracies stemming from flawed or subjective input assumptions. In contrast, this paper introduces a novel analytics-based approach to financial valuations that enables simultaneous consideration of many variables and transparently displays their individual and combined effects on the possible project outcomes, while highlighting which combinations of input variables would lead to a profitable result. This new approach explicitly defines the ‘boundary conditions’ of a successful project with respect to multiple variables, i.e. at what combination of variable values the project would meet a specified financial threshold. This approach is analogous to a geochemical phase diagram, which defines a bounded region of stability of a chemical compound with respect to different physicochemical variables. This approach is more comprehensive than DCF valuations and more transparent and objective than probabilistic-centered analysis such a Monte Carlo simulation. It also provides a useful framework to aid technical staff in project development discussions, including a dashboard tool with interactive visualizations.
Files
Steps to reproduce
1. Details in manuscript entitled "A Novel Analytics-Based Approach to Mining Project Valuations". 2. Initial DCF model is built using a synthetic example of a gold deposit as shown in BasicCF_2025.xlsx. 3. Inputs from BasicCF_2025.xlsx, including sensitivity minimums, maximums, and step sizes fed into script FinPhaseBasic7.py. 4. Script (a) recreates DCF model in BasicCF_2025.xlsx, (b) iterates sensitivity analyses flexing the initial DCF model, (c) back-calculates set(s) of inputs necessary to achieve specified NPV, and (d) outputs files to use as inputs to summary dashboard. 5. FinalResults2025.xlsx, variation_factors2025.xlsx, and Combined_results2025.xlsx are fed into summary dashboard Manuscript_dashboard.twb. This is a Tableau workbook.
Institutions
- University of Arizona