Investing With Purpose: A Danish Case Study on Goals-Based Investing

Abstract

This thesis investigates the practical implementation of Goals-Based Investing within a Danish context. Goals-Based Investing offers an alternative to traditional portfolio optimisation by aligning wealth allocation to distinct personal financial goals rather than optimising for overall risk-adjusted returns. The primary research question is: Can GBI be operationalised as a practical investment framework under the Danish regulatory and taxation system? The literature review explores normative and behavioural finance theories, contrasting Modern Portfolio Theory with the goal-centric approach of Goals-Based Investing. The methodology chapter details the development of a simulation-based model that integrates Danish taxation, pension rules, and account structures. The model applies dynamic optimisation to allocate investor contributions and wealth across multiple sub-portfolios, each targeting a specific financial goal. Two hypothetical investor profiles were used as a case study: a young investor with no initial wealth and a mid-career investor with DKK 200,000 of investable assets. Each profile was simulated across 1,000 Monte Carlo paths over a 50-year horizon. The analysis finds that the model reliably structures wealth across sub-portfolios and provides consistent guidance under varying market conditions. For the young investor, essential retirement goals were met in nearly all scenarios, though shorter-term ambitions such as housing deposits had very low success probabilities due to limited capital. The mid-career investor achieved a more balanced distribution of goal attainment across retirement, family, and lifestyle objectives. The thesis concludes that the Goals-Based model is feasible to implement in a Danish context, although with certain limitations. It further concludes that while the GBI model is not yet suitable as a stand-alone product for retail investors, it holds clear potential as a structured decision-support tool for financial advisers. It can translate client objectives into tailored, quantitatively grounded investment strategies that complement existing advisory models.