Planning for the Efficient Updating of Mutual Fund Portfolios

ArXiv ID: 2311.16204 “View on arXiv”

Authors: Unknown

Abstract

Once there is a decision of rebalancing or updating a portfolio of funds, the process of changing the current portfolio to the target one, involves a set of transactions that are susceptible of being optimized. This is particularly relevant when managers have to handle the implications of different types of instruments. In this work we present linear programming and heuristic search approaches that produce plans for executing the update. The evaluation of our proposals shows cost improvements over the compared based strategy. The models can be easily extended to other realistic scenarios in which a holistic portfolio management is required

Keywords: portfolio rebalancing, linear programming, heuristic search, transaction cost optimization, portfolio management, Funds

Complexity vs Empirical Score

• Math Complexity: 6.5/10
• Empirical Rigor: 4.0/10
• Quadrant: Lab Rats
• Why: The paper uses advanced math including linear programming, combinatorial optimization, and graph search algorithms, placing it in the high complexity category. While it presents evaluation of cost improvements, it lacks detailed backtesting metrics, statistical analysis, or real-world data implementation details, keeping the empirical rigor on the lower side.

  flowchart TD
    A["Research Goal: Minimize transaction costs<br>when updating mutual fund portfolios"] --> B["Key Methodologies"]
    
    B --> B1["Linear Programming<br>Optimization"]
    B --> B2["Heuristic Search<br>Approach"]
    
    B1 --> C["Computational Process"]
    B2 --> C
    
    C["Apply models to real<br>portfolio rebalancing scenarios"] --> D["Key Findings"]
    
    D --> D1["Cost improvements over<br>standard rebalancing strategies"]
    D --> D2["Models easily extendable<br>to other portfolio management<br>scenarios"]