Academic Journal

Adaptive data-driven portfolio optimization in the non-stationary financial market under constraints

Bibliographic Details
Title: Adaptive data-driven portfolio optimization in the non-stationary financial market under constraints
Authors: Dombrovskii, Vladimir V.
Contributors: Томский государственный университет Экономический факультет Кафедра математических методов и информационных технологий в экономике
Source: Вестник Томского государственного университета. Управление, вычислительная техника и информатика. 2013. № 3. С. 5-13
Publisher Information: Федеральное государственное бюджетное образовательное учреждение высшего профессионального образования «Национальный исследовательский Томский государственный университет», 2013.
Publication Year: 2013
Subject Terms: финансовые рынки, адаптивная оптимизация, Инвестиционный портфель, управление инвестиционным портфелем, ИНВЕСТИЦИОННЫЙ ПОРТФЕЛЬ, НЕСТАЦИОНАРНЫЙ ФИНАНСОВЫЙ РЫНОК, АДАПТИВНАЯ ОПТИМИЗАЦИЯ, УПРАВЛЕНИЕ С ПРОГНОЗИРУЮЩЕЙ МОДЕЛЬЮ
Description: In this work we propose a novel methodology for optimal dynamic allocation of a portfolio of risky financial assets under hard constraints on trading volume amounts. Our approach is direct in that it uses directly the observed historical data to construct an adaptive algorithm for online portfolio selection. The problem of portfolio optimization is stated as a dynamic problem of tracking a financial benchmark. We use the model predictive control (MPC) methodology in order to solve the problem. The main features of our approach are (a) the ability to adapt to non-stationary market environments by dynamically incorporating new information into the decision process; (b) no stochastic assumptions are needed about the stock prices, and (c) the flexibility of dealing with portfolio constraints. We also present the numerical modeling results, based on futures traded on the Russian Stock Exchange FORTS that give evidence of capacity and effectiveness of proposed approach.
Document Type: Article
File Description: text/html; application/pdf
Language: Russian
ISSN: 2311-2085
1998-8605
Access URL: http://cyberleninka.ru/article/n/adaptive-data-driven-portfolio-optimization-in-the-non-stationary-financial-market-under-constraints
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Accession Number: edsair.dedup.wf.002..0495d6f4052aa744a5787ef417bb7d6d
Database: OpenAIRE
Description
ISSN:23112085
19988605