Nine papers across five fields. What unites them is a method, not a subject: take something a discipline treats as random, and show the order underneath.
How population ageing reshapes contemporary economies — and its role in pinning interest rates at the zero lower bound.
A simulation framework for strategic allocation that revisits and extends the Black–Litterman model.
A risk-based allocation strategy that balances each asset's contribution to the portfolio's drawdown, not just its variance.
Balanced sampling meets wave mechanics: inclusion probabilities as complex amplitudes on a sphere, resolved by pivotal martingale transfers.
Proves that no reordering of the cube method's landing can change the sampling design — only dependent rounding can, cutting median imbalance by 29–45%.
A structural approach to Semitic root morphology, mapping Arabic etymology onto a geometric cube.
A wave-mechanics approach to financial derivatives — the seed of the Quantum finance framework.
A quantum-mechanical macroeconomy, derived rather than postulated: an overlapping-generations mean-field game mapped exactly into a Schrödinger system.
A quantitative assessment of trans-continental dust transport and its effect on forests in Amazonia and Europe.
The PhD gathers these threads into one programme: quantitative methods for finance, developed with the rigour of the physical sciences and the openness of a beginner.
Doctoral research at the University of Évry-Paris-Saclay, at the intersection of asset allocation, macro-finance and mathematical modelling.
Presented at the American Finance Association (AFA), the European Finance Association (EFA) and the Financial Management Association (FMA) annual meetings.