An Investment Monitoring Model for Tracking Cash Position and Forecasting Portfolio Resilience under Volatile Conditions - Ebehiremen Faith Iziduh; Olawale Olasoji; Oluwatobi Opeyemi Adeyelu (International Journal of Scientific Research in Civil Engineering, 2022)
In an increasingly volatile and interconnected financial environment, effective investment monitoring and resilience forecasting have become essential components of sound portfolio management. This paper introduces a structured, integrative model designed to track cash positions and forecast portfolio resilience under dynamic market conditions. Anchored in core financial principles such as liquidity management, drawdown risk, and market signal interpretation, the model functions as a real-time decision support system. It is composed of three interrelated modules: a cash tracker, a risk forecaster, and a signal analyzer, each designed to translate complex financial and market data into intuitive, actionable insights. The model operates across daily, weekly, and event-driven contexts, enhancing both situational awareness and forward-looking risk governance. Key resilience metrics—such as liquidity buffers, scenario thresholds, and early warning indicators—allow asset managers to assess vulnerability and take preemptive action. Importantly, the model remains adaptable across market regimes, maintaining relevance in bull, bear, and sideways markets alike. The framework contributes meaningfully to both theoretical discourse and practical application in investment management by transforming monitoring from a reactive exercise into a proactive, structured discipline.