@article{10.11648/j.acm.20251406.12,
  author = {Marcelo de Oliveira Passos and Mathias Schneid Tessmann and Jean Rodrigues Venecian and Alex Cerqueira Pinto},
  title = {A Multi-agent Computational Model for the Transmission of Monetary Policy to the Intrinsic Value of Stocks
},
  journal = {Applied and Computational Mathematics},
  volume = {14},
  number = {6},
  pages = {309-322},
  doi = {10.11648/j.acm.20251406.12},
  url = {https://doi.org/10.11648/j.acm.20251406.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.acm.20251406.12},
  abstract = {This paper presents a multi agent computational framework that deploys heterogeneous agents to investigate how shifts in short term interest rates and in the expected path of rates shape the intrinsic value of a broad stock market index. The model elucidates the transmission channels through which monetary policy propagates to market fundamentals, operationalized via the index’s theoretical replicating portfolio. By distinguishing valuation changes rooted in fundamentals from those driven by sentiment or feedback dynamics, the framework enables the systematic identification and quantification of speculative expansions (bull markets) and contractions (bear markets), thereby advancing a more disciplined understanding of market cycles. A central innovation is an investment oriented metric that produces a weekly time series of the Value Gap (VG), defined as the deviation between the model implied intrinsic value and the observed index level. This measure supports continuous monitoring of mispricing, facilitates comparative analysis across monetary policy regimes, and offers practical signals for risk management and asset allocation. Empirical evaluation yields two principal findings. First, the adverse effect of tighter monetary policy on VG materializes only when the index constituents exhibit a negative aggregate net cash flow, indicating that balance sheet conditions condition the pass through from policy rates to valuation gaps. Second, symmetric adjustments in the policy rate—upward or downward—tend to induce correspondingly directional movements in the index’s fundamental value (VB), highlighting a robust mapping from policy stance to market-implied fundamentals. Overall, the study contributes to the literature on monetary transmission and asset pricing by clarifying the interaction between policy rates, corporate cash flow profiles, and valuation dispersion. It also delivers a transparent and implementable analytical tool for detecting market imbalances, guiding tactical positioning, and informing strategic investment decisions under evolving policy environments.
},
 year = {2025}
}

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TY  - JOUR
T1  - A Multi-agent Computational Model for the Transmission of Monetary Policy to the Intrinsic Value of Stocks

AU  - Marcelo de Oliveira Passos
AU  - Mathias Schneid Tessmann
AU  - Jean Rodrigues Venecian
AU  - Alex Cerqueira Pinto
Y1  - 2025/11/12
PY  - 2025
N1  - https://doi.org/10.11648/j.acm.20251406.12
DO  - 10.11648/j.acm.20251406.12
T2  - Applied and Computational Mathematics
JF  - Applied and Computational Mathematics
JO  - Applied and Computational Mathematics
SP  - 309
EP  - 322
PB  - Science Publishing Group
SN  - 2328-5613
UR  - https://doi.org/10.11648/j.acm.20251406.12
AB  - This paper presents a multi agent computational framework that deploys heterogeneous agents to investigate how shifts in short term interest rates and in the expected path of rates shape the intrinsic value of a broad stock market index. The model elucidates the transmission channels through which monetary policy propagates to market fundamentals, operationalized via the index’s theoretical replicating portfolio. By distinguishing valuation changes rooted in fundamentals from those driven by sentiment or feedback dynamics, the framework enables the systematic identification and quantification of speculative expansions (bull markets) and contractions (bear markets), thereby advancing a more disciplined understanding of market cycles. A central innovation is an investment oriented metric that produces a weekly time series of the Value Gap (VG), defined as the deviation between the model implied intrinsic value and the observed index level. This measure supports continuous monitoring of mispricing, facilitates comparative analysis across monetary policy regimes, and offers practical signals for risk management and asset allocation. Empirical evaluation yields two principal findings. First, the adverse effect of tighter monetary policy on VG materializes only when the index constituents exhibit a negative aggregate net cash flow, indicating that balance sheet conditions condition the pass through from policy rates to valuation gaps. Second, symmetric adjustments in the policy rate—upward or downward—tend to induce correspondingly directional movements in the index’s fundamental value (VB), highlighting a robust mapping from policy stance to market-implied fundamentals. Overall, the study contributes to the literature on monetary transmission and asset pricing by clarifying the interaction between policy rates, corporate cash flow profiles, and valuation dispersion. It also delivers a transparent and implementable analytical tool for detecting market imbalances, guiding tactical positioning, and informing strategic investment decisions under evolving policy environments.

VL  - 14
IS  - 6
ER  - 

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