Analyzing the Impact of Monetary Policy Decisions on Stock Market Volatility and Investor Behavior
Posted: Jul 28, 2023
Abstract
This research introduces a fundamentally novel computational framework that bridges quantum computing concepts with behavioral finance to address limitations in traditional analytical frameworks. Our approach represents a significant departure from existing methodologies by conceptualizing investor expectations and market states as existing in quantum superposition prior to policy announcements, with the revelation of actual policy decisions causing wave function collapse into definite market outcomes. This quantum-inspired perspective allows us to model the probabilistic nature of market expectations and the discontinuous jumps in asset prices that often accompany policy surprises in ways that classical probability theory cannot adequately capture. We draw inspiration from recent advances in quantum machine learning and quantum finance, adapting these concepts to create a hybrid quantum-classical computational architecture specifically tailored for financial market analysis.
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