Financial Research (Hungary)

Abstract Repeat sales index methodologies are prevalent for computing indices, largely owing to their simplicity, minimal data requirements, and reliable approach to addressing real estate heterogeneity. However, this method is not without flaws, being restricted to properties sold at least twice within the sample period and demonstrating high sensitivity to the size of the dataset. In this paper, we introduce a stable and robust factorial approach that holds firm even when the data quantity is sparse due to factors such as frequent publications, thin markets, data unavailability, or a drastic drop in the number of transactions. We demonstrate that trend and volatility estimates tend to be biased with the standard repeat sales approach, but remain unbiased with our factorial method, regardless of the size of the dataset. The factorial approach exhibits greater robustness in relation to transaction numbers.

Abstract We consider a two-dimensional discontinuous piecewise linear homogeneous map in two partitions, belonging to the family of Belykh maps, whose characteristic property is that the Jacobian determinant is the same at any point of the phase plane. The fixed points of the functions defining the map have disjoint stability regions. Three kinds of discontinuity sets separating these partitions are considered. As shown in our previous works, discontinuous piecewise linear homogenous maps can have weird quasiperiodic attractors (WQAs). We prove that there are parameter regions where the existence of WQAs is generic. Owing to the complex shape of a WQA, it may appear similar to a chaotic attractor. However, a WQA does not contain any cycle or other invariant subsets, being the closure of quasiperiodic trajectories. We present examples of contact bifurcations of coexisting WQAs with their basin boundaries leading to a unique WQA, showing that these bifurcations are not associated with homoclinic/heteroclinic trajectories. We discuss also contact bifurcations leading to the divergence that may be accompanied by a long transient following the former attractor. The simplicity of the map allows us to describe the mechanism of the appearance/disappearance of WQAs, always related to the unstable eigenvector of the fixed point.

Non-canonical cGASSTING signaling emerges from alterations in classical cytosolic DNA sensing, in which cGAS-generated 23-cGAMP normally activates ER-resident STING, driving TBK1-IRF3dependent type I/III interferon and NF-B responses that eliminate pathogens and couple innate and adaptive immunity. In senescent and progeroid cells, de Faria and colleagues identified elevated DNA damage, cytoplasmic DNA accumulation, and SASP/ISG induction despite unchanged cGAMP levels and diminished classical STINGTBK1IRF3 activation, with STING instead showing nuclear envelope and chromatin localization and forming alternative complexes that reprogram inflammatory and senescence-related transcription. This non-canonical mode features sustained STAT1 and NF-B activation, robust SASP output, and organ-specific pathogenic effects on vascular smooth muscle, white adipose tissue, and connective tissues, while exerting relatively minor influence on cardiac muscle. Gulen and colleagues demonstrated that STING drives systemic low-grade inflammation in naturally aged animals, promoting inflammatory and interferon signatures in kidney, liver, and brain, microglial activation, neuronal and synaptic loss, and functional decline that can be ameliorated by pharmacological STING inhibition. Additional work links cGASSTING activation to NLRP3-dependent IL-1 maturation in Alzheimers disease models and to metabolic reprogramming, mitochondrial dysfunction, and deterioration of the NADSirtuin axis. Across these contexts, pharmacological or genetic inhibition of cGASSTING reduces SASP and ISG expression, limits inflammatory damage, and improves cellular and organismal phenotypes, highlighting non-canonical cGASSTING signaling as a central driver of inflammation-mediated senescence and metabolic decline in aging and progeroid states.

This paper describes the Extended General Intelligence (EGI) framework, a five-layer cognitive architecture that integrates semantic world modeling with persistent multi-agent reasoning. EGI organizes perception, semantic understanding, collaborative reasoning, orchestration, and meta-cognition into a unified structure, in which world-model information is represented as explicit semantic state variables shared across-agents. To illustrate how this architecture can be used in practice, we implement a multi-agent financial intelligence system and apply it to five years of central bank communications, macroeconomic indicators, risk factors, and market data (2020-2025). The system produces central bank tone indices, macro and risk-regime inferences, and market-reaction expectations. A comparative evaluation against a flat, single-prompt baseline suggests that the EGI-based design yields more stable semantic trajectories and more coherent cross-domain reasoning. The framework is intended as an architectural blueprint that may support further research on interpretable, long-horizon multi-agent intelligence.