Finance

CHALLENGE 01

PROBLEM

Covering the full breadth of a finance course in one cohesive tool

SOLUTION

Modular calculation functions mapped to tabbed/sectioned UI panels, each with its own labelled inputs

CHALLENGE 02

PROBLEM

Distributing a Python GUI app without requiring a Python install

SOLUTION

Compiled to a standalone executable and published as a GitHub Release

CHALLENGE 01

PROBLEM

DDM produced a wildly high intrinsic value ($7.30 vs $2.33 market price) for GNE

SOLUTION

Sensitivity analysis exposed extreme fragility (k−g spread of 2.4%); qualitative risk factors and behavioural bias analysis were used to discount the DDM signal

CHALLENGE 02

PROBLEM

Small NZX universe made meaningful diversification difficult within the ethical mandate

SOLUTION

Supplemented with ASX-listed NZ companies and IFT as a listed infrastructure proxy for private real assets

CHALLENGE 03

PROBLEM

NZX50 futures hedge reduced upside disproportionately for a defensive, long-term position

SOLUTION

Concluded the hedge was unsuitable given GNE's low beta (0.23) and the 35-year horizon; Sharpe ratio logic used to justify not hedging

CHALLENGE 04

PROBLEM

AI-based FinTech tools conflict with the client's climate-conscious values

SOLUTION

Proposed a deterministic Python screener using yfinance. auditable, low-cost, and zero AI compute footprint

CHALLENGE 01

PROBLEM

Translating real cash flows into nominal prices across an inflation-adjusted timeline

SOLUTION

Applied the CPI index multiplier I(t) = (1 + inflation)^t to the real PV at each period, cleanly separating real yield arithmetic from nominal price reporting

CHALLENGE 02

PROBLEM

Demonstrating the structural difference between indexed and nominal bond behaviour

SOLUTION

Parametrised both bond types with equivalent real/nominal yield spreads (3.285% real vs 5.285% nominal) so the comparison is economically meaningful, not just cosmetic

CHALLENGE 01

PROBLEM

A 99.9% payout ratio left retention near zero, so PRAT and sustainable-growth estimates gave about 0% growth

SOLUTION

Gave both zero weight and drove interim growth from analyst EPS forecasts instead

CHALLENGE 02

PROBLEM

2024 FCFE was depressed by $4.8B of capex on new 300 mm fabs and $2.4B of net borrowing

SOLUTION

Tested a normalised base year (lower capex, no new borrowing) and found the low value came from the growth rate and required return, not the base year

CHALLENGE 03

PROBLEM

Terminal value made up 67% of both absolute valuations, making them sensitive to the terminal growth rate

SOLUTION

Weighted the absolute models alongside relative multiples and analyst consensus, and showed the Sell call holds for any consensus target below $454

CHALLENGE 01

PROBLEM

Assets trade on different days, so their return series did not line up

SOLUTION

Aligned every price history to the dates all assets traded on before computing covariance

CHALLENGE 02

PROBLEM

Random weights had to respect min/max limits and still sum to 100%

SOLUTION

Sampled long-only weights evenly from a Dirichlet(1) distribution, then clipped and redistributed the remainder until the weights fit

CHALLENGE 03

PROBLEM

Checking whether a set of limits is even achievable before optimising

SOLUTION

Feasibility test that n assets can reach 100% within the bounds, e.g. four assets capped at 20% cannot