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A Model for Strategic Fund Allocation and Portfolio Performance Optimization in Global Firms
Subject area: Science,Engineering and Technology · Area of research: Financial Technology
Abstract
Global firms operate within increasingly dynamic financial environments characterized by market volatility, currency fluctuations, and regulatory constraints that demand strategic fund allocation and portfolio optimization. This review proposes a comprehensive model integrating data-driven financial analytics, behavioral finance insights, and multi-objective optimization techniques to enhance fund distribution and maximize portfolio performance. The model emphasizes strategic capital budgeting, risk-adjusted return evaluation, and adaptive asset rebalancing using predictive analytics and artificial intelligence. By combining quantitative modeling with strategic management frameworks such as Modern Portfolio Theory (MPT), the Capital Asset Pricing Model (CAPM), and Mean-Variance Optimization (MVO), firms can achieve a balance between growth, liquidity, and risk tolerance. Furthermore, this review explores the integration of Environmental, Social, and Governance (ESG) metrics into fund allocation decisions to align profitability with sustainability goals. Empirical evidence and case analyses highlight how global firms can leverage technology-driven investment management platforms to achieve superior decision-making accuracy and portfolio resilience. The proposed model provides a strategic framework for executives and fund managers to optimize capital allocation, strengthen financial sustainability, and improve shareholder value amid global uncertainties.
Keywords
Strategic Fund Allocation; Portfolio Optimization; Global Firms; Predictive Analytics; Risk Management; ESG Integration
How to cite this paper
@article{1712143,
author = {Lovelyn Ekpedo, Esther Nkem Awanye, Obiajulu Obiora Morah, Omolara Adeyoyin},
title = {A Model for Strategic Fund Allocation and Portfolio Performance Optimization in Global Firms},
journal = {Iconic Research And Engineering Journals},
year = {2019},
volume = {3},
number = {6},
pages = {416-432},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1712143.pdf},
abstract = {Global firms operate within increasingly dynamic financial environments characterized by market volatility, currency fluctuations, and regulatory constraints that demand strategic fund allocation and portfolio optimization. This review proposes a comprehensive model integrating data-driven financial analytics, behavioral finance insights, and multi-objective optimization techniques to enhance fund distribution and maximize portfolio performance. The model emphasizes strategic capital budgeting, risk-adjusted return evaluation, and adaptive asset rebalancing using predictive analytics and artificial intelligence. By combining quantitative modeling with strategic management frameworks such as Modern Portfolio Theory (MPT), the Capital Asset Pricing Model (CAPM), and Mean-Variance Optimization (MVO), firms can achieve a balance between growth, liquidity, and risk tolerance. Furthermore, this review explores the integration of Environmental, Social, and Governance (ESG) metrics into fund allocation decisions to align profitability with sustainability goals. Empirical evidence and case analyses highlight how global firms can leverage technology-driven investment management platforms to achieve superior decision-making accuracy and portfolio resilience. The proposed model provides a strategic framework for executives and fund managers to optimize capital allocation, strengthen financial sustainability, and improve shareholder value amid global uncertainties.},
keywords = {Strategic Fund Allocation; Portfolio Optimization; Global Firms; Predictive Analytics; Risk Management; ESG Integration},
month = {December},
}