Hierarchical Portfolio Allocation in an Active Management Framework
Typ
Examensarbete för masterexamen
Program
Engineering mathematics and computational science (MPENM), MSc
Publicerad
2022
Författare
Deumic, Adnan
Meijer, James
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
This master’s thesis focuses on developing and evaluating a hierarchical portfolio
allocation algorithm that combines hierarchical clustering and Markowitz Modern
Portfolio Theory while being adapted to an active management framework. Sixteen
different constellations were constructed and evaluated on equities return data from
01/03/1990 to 10/01/2022, using three different sets of observations as input and
five different performance measures.
The results demonstrate that the combination of Equal Risk Contribution and Single
Linkage generates the best outcomes. In general, the results also show that
Tracking Error is significantly smaller when Equal Risk Contribution is used as a
between-cluster allocation method. Moreover, the choice of linkage criteria is crucial
for cluster size and the numerical stability of the associated sample covariance matrices.
For instance, Single Linkage produces the smallest set of clusters, followed by
Group-Average Linkage, Complete Linkage, and Ward’s method. In addition, the
ordering of the leaves in the hierarchical structure did not have a significant effect
on the results. The suggested hierarchical portfolio allocation algorithm performs
consistently and is able to capture the hierarchical structure between assets during
different market conditions.
Beskrivning
Ämne/nyckelord
hierarchical clustering, portfolio allocation, active management, minimum variance, modern portfolio theory, graph theory, covariance matrix, correlation, clustering