Abstract: The increasingly complex and interconnected nature of the global economy have greatly increased the level of volatility and uncertainty faced by investment portfolios in the U.S. This study thus considers several risk management approaches in mitigating losses on portfolios during times of economic turbulence. The key models considered are Value at Risk (VaR), Conditional VaR, GARCH-type volatility models, Multi-asset risk modeling, and Scenario-based stress testing. Emphasis is placed on the need for integration of a set of both quantitative and qualitative models that account for market, credit, liquidity, and currency risks. The results of the study have revealed that portfolios that use diversified models actually hold up better when faced with global shocks as compared to conventional strategies that may mindlessly stick to one model. The study also highlighted the fact that adaptive decision-making, together with continuous monitoring, should be considered in the face of ever-evolving markets. This paper attempts to bring forth some answers to the question of which risk management framework might best stabilize portfolios and foster subsequent decision-making in the face of perpetual global volatility.
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DOI:
10.17148/IJIREEICE.2024.12814
[1] Joel Adetokunbo, "Risk Management Models for U.S. Investment Portfolios in a Volatile Global Economy," International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering (IJIREEICE), DOI 10.17148/IJIREEICE.2024.12814