@misc{9242540,
  abstract     = {{Hierarchical portfolio allocation methods produce diversified portfolios while avoiding the instability of mean-variance optimisation. The framework depends on two separable choices: how assets are grouped and how capital is allocated across those groups. This thesis asks which of these choices matters more for out-of-sample portfolio performance. The empirical design crosses four linkage methods with four allocation kernels, evaluated on a multi-asset ETF universe from 2008 to 2026 across 3,200 resampled walk-forward paths. The results show that allocation kernels account for most differences in risk-adjusted performance, while the linkage method mainly affects turnover. Risk-aware kernels improve risk-adjusted performance and reduce downside risk relative to 1/N. Practitioners should treat the allocation rule as the primary modelling choice in hierarchical portfolio construction, with linkage choice used mainly to manage implementation stability.}},
  author       = {{Bursic, Adam}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Decomposing Hierarchical Portfolio Performance: Tree Structure or Allocation Rule?}},
  year         = {{2026}},
}