bibtype V - Research Report
ARLID 0637014
utime 20251007090158.3
mtime 20250701235959.9
title (primary) (eng) Výzkumný úkol ČVUT: Tools for Adaptive Portfolio Optimization
publisher
place Praha
name ČVUT
pub_time 2025
specification
page_count 34 s.
keyword portfolio
keyword optimization
keyword structure estimation
keyword multivariate linear regression
keyword linear quadratic regulator
keyword decision making
keyword dynamic programming
author (primary)
ARLID cav_un_auth*0489870
name1 Procházka
name2 Tomáš
institution UTIA-B
full_dept (cz) Adaptivní systémy
full_dept (eng) Department of Adaptive Systems
department (cz) AS
department (eng) AS
country CZ
share 100
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url https://library.utia.cas.cz/separaty/2025/AS/prochazka-0637014.pdf
cas_special
project
project_id CA21169
agency EU-COST
country XE
ARLID cav_un_auth*0452289
abstract (eng) This research project presents a combination of techniques to develop a sound mathematical approach to the portfolio optimization problem. The problem is formulated as a Linear Quadratic Regulator and solved using Dynamic Programming. The key contributions include integrating multivariate regression modeling of returns with structure estimation for the regressor subset and employing exponential forgetting with an algorithm for varying forgetting factor. The optimal allocation is obtained by solving a constrained quadratic programming problem featuring a custom reward function. We highlight the importance of structure estimation and\nthe sequential approach, while also exploring the potential of modeling optimal allocation using the same regression framework as for returns.
RIV BB
FORD0 20000
FORD1 20200
FORD2 20205
reportyear 2026
inst_support RVO:67985556
permalink https://hdl.handle.net/11104/0370102
confidential S
arlyear 2025
mrcbU10 2025
mrcbU10 Praha ČVUT