Research Article
Money and the Capital Structure of a Single Owner in Incomplete Markets with Production
Issue:
Volume 14, Issue 6, December 2025
Pages:
301-308
Received:
10 September 2025
Accepted:
22 September 2025
Published:
10 November 2025
Abstract: This paper examines the influence of monetary policy on corporate economies, focusing on whether supply fluctuations affect the decisions of economic agents or whether money is neutral under specific conditions. To investigate this, we develop a two-period general equilibrium model with incomplete and production financial markets, capturing frictions and asymmetries typical of real financial systems. The model is then applied to a corporate finance context, analyzing a capital structure with a single owner. The findings show that monetary policy is generally not neutral when markets are incomplete. Neutrality of money emerges only as a special case when markets are fully complete and efficient, conditions rarely observed in practice. The equilibrium model demonstrates that monetary policy is not neutral or generally does not occur unless markets are complete. For the case of a single owner in a capital structure, Fisher’s separation theorem is valid, reinforcing the non-neutrality of money in this economy with markets and incomplete production.In other words, being in an incomplete exchange environment affects the path of consumption of economic agents, although it does not alter the firm âs operational framework. For future research, it would be relevant to extend the analysis time horizon, relax the assumption regarding currency carryover, incorporate private or public banks with fiscal policies into the model, and also consider the application of the Modigliani-Miller theorem
Abstract: This paper examines the influence of monetary policy on corporate economies, focusing on whether supply fluctuations affect the decisions of economic agents or whether money is neutral under specific conditions. To investigate this, we develop a two-period general equilibrium model with incomplete and production financial markets, capturing frictio...
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Research Article
A Multi-agent Computational Model for the Transmission of Monetary Policy to the Intrinsic Value of Stocks
Issue:
Volume 14, Issue 6, December 2025
Pages:
309-322
Received:
29 September 2025
Accepted:
18 October 2025
Published:
12 November 2025
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.
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, ...
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Research Article
An Enhanced Optimization-Based Support Vector Machine for Urolithiasis Prediction with Topological Guidance and Reflective Learning
Yuanzhe Ding
,
Ao Ma,
Zijian Chen,
Tianyue Liu,
Yun Jin,
Weiqiang Ning,
Kaijie Xu,
Junyi Lu,
Huiling Chen,
Huiliang Wang,
Wei Chen*
Issue:
Volume 14, Issue 6, December 2025
Pages:
323-348
Received:
10 September 2025
Accepted:
30 September 2025
Published:
3 December 2025
DOI:
10.11648/j.acm.20251406.13
Downloads:
Views:
Abstract: Urolithiasis, a condition characterized by the formation of stones in the urinary tract, is influenced by a confluence of factors, including genetic predispositions, dietary habits, and inadequate hydration. This condition can lead to urinary obstruction and pain, elevate the risk of infections, and, in severe cases, potentially impair kidney function. Early identification and prediction are crucial for preventing the formation of urinary stones and mitigating their consequent impacts. In this study, a machine learning model, named bTRWOA-SVM, was developed utilizing data from 1027 suspected patients at the First Affiliated Hospital of Wenzhou Medical University. This model synergizes the whale optimization algorithm (WOA) with the support vector machine (SVM) and introduces enhancements through the triangular topological search strategy and reflective learning operator to augment the search proficiency of the WOA, resulting in a variant termed TRWOA. Comparative analysis against a range of contemporaries using the CEC 2017 benchmark suite substantiated TRWOA's effective optimization capabilities and convergence precision. Furthermore, the constructed bTRWOA-SVM model, when applied to clinical data about urolithiasis, achieved a predictive accuracy of 98.830% and a specificity of 97.665%. Conclusively, the model also identified critical features influencing urolithiasis prediction, including urinary bilirubin, total protein, pH value, creatinine, and direct bilirubin, thereby providing a scientific basis for the early diagnosis and treatment of urolithiasis.
Abstract: Urolithiasis, a condition characterized by the formation of stones in the urinary tract, is influenced by a confluence of factors, including genetic predispositions, dietary habits, and inadequate hydration. This condition can lead to urinary obstruction and pain, elevate the risk of infections, and, in severe cases, potentially impair kidney funct...
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