On the Expressivity and Applicability of Model Representation Formalisms

A number of first-order calculi employ an explicit model representation formalism for automated reasoning and for detecting satisfiability. Many of these formalisms can represent infinite Herbrand models. The first-order fragment of monadic, shallow, linear, Horn (MSLH) clauses, is such a formalism used in the approximation refinement calculus. Our first result is a finite model property for MSLH clause sets. Therefore, MSLH clause sets cannot represent models of clause sets with inherently infinite models. Through a translation to tree automata, we further show that this limitation also applies to the linear fragments of implicit generalizations, which is the formalism used in the model-evolution calculus, to atoms with disequality constraints, the formalisms used in the non-redundant clause learning calculus (NRCL), and to atoms with membership constraints, a formalism used for example in decision procedures for algebraic data types. Although these formalisms cannot represent models of clause sets with inherently infinite models, through an additional approximation step they can. This is our second main result. For clause sets including the definition of an equivalence relation with the help of an additional, novel approximation, called reflexive relation splitting, the approximation refinement calculus can automatically show satisfiability through the MSLH clause set formalism.Comment: 15 page

Interacting locally, acting globally: trust and proximity in social networks for the development of energy communities

In this article, we analyze the role of social capital in the formation of sustainable energy communities. Specifically, we study the impact of different dimensions of social capital (i.e., structural, relational, cognitive) in determining willingness to participate in an energy community. Our survey data suggest that social contexts contribute to the development of energy communities, via (at least) two channels: (i) a family path, with individual perspectives showing a partial correlation with those of at least one relative, and (ii) a social channel, with higher social trust and greater interaction with neighbors favoring the propensity to participate in an energy community. The social coordination required for the formation of sustainable energy communities is determined by the quality of social interactions, and the spread of virtuous behavior is determined by not only economic policies (i.e., incentives), but also forward-looking policies favoring local aggregation and the creation of high-quality social capital. Thus, local actions and interactions can contribute to solving global climate change challenges

On the Expressivity and Applicability of Model Representation Formalisms

International audienceA number of first-order calculi employ an explicit model representation formalism in support of non-redundant inferences and for detecting satisfiability. Many of these formalisms can represent infinite Herbrand models. The first-order fragment of monadic, shallow, linear, Horn (MSLH) clauses, is such a formalism used in the approximation refinement calculus (AR). Our first result is a finite model property for MSLH clause sets. Therefore, MSLH clause sets cannot represent models of clause sets with inherently infinite models. Through a translation to tree automata, we further show that this limitation also applies to the linear fragments of implicit generalizations, which is the formalism used in the model-evolution calculus (ME), to atoms with disequality constraints, the formalisms used in the non-redundant clause learning calculus (NRCL), and to atoms with membership constraints, a formalism used for example in decision procedures for algebraic data types. Although these formalisms cannot represent models of clause sets with inherently infinite models, through an additional approximation step they can. This is our second main result. For clause sets including the definition of an equivalence relation with the help of an additional, novel approximation, called reflexive relation splitting, the approximation refinement calculus can automatically show satisfiability through the MSLH clause set formalism

Good vibes only: The crypto-optimistic behavior

This paper aims at investigating the relationship between news-driven sentiments and the convergence of behavior in cryptocurrencies market, contributing to the existing literature in the field. The novelty stands in the relation set between the tone of news and returns dispersion. The average daily sentiment score deriving from a worldwide online news dataset has been exploited as a proxy of market humor, in the attempt to identify how emotions spread by the press are related to traders’ actions. By employing both Cross-sectional standard (CSSD) and absolute (CSAD) deviation, it is found that the rises and falls of optimism shape returns variability. Indeed, the paper evidences how an increase of news positivity is associated with a lower returns dispersion, evidencing the convergence of beliefs among investors

Sentiment spillover and price dynamics: Information flow in the cryptocurrency and stock market

This study examines the sentiment–returns relationship in both stock (S&P500) and cryptocurrency (Bitcoin) markets. An explorative wavelet analysis evidences period of episodic interconnectedness across different data frequencies. Therefore, Transfer Entropy (ET) measures remark the relative statistical significance, frequently outperforming traditional (VAR) estimates. In particular, ET methods successfully identify the mediating role of sentiments in connecting the two different markets. Hence, it is discussed how the potential cryptocurrencies indirect linkage with real economy moves through market sentiments

Inequalities in financial markets: Evidences from a laboratory experiment

The purpose of this paper is to examine the effects on welfare distribution of quality and quantity of information among traders in laboratory financial markets. Results lead us to conclude that signal accuracy matters in underpinning inequality distribution. Generally, there is evidence that high quality signals produce lower inequality. However, by analyzing tail behavior, there seems to be cases of overconfidence in high quality signals generating "extra" level of inequality

The Ambiguity Box: A new tool to generate ambiguity in the lab

The Ambiguity Box is a software tool that visualizes uncertainty in laboratory experiments. It is a dynamic frame composed of squares that randomly change colours, creating an uncertain and ambiguous environment. This encourages participants to infer the probabilities of each colour. The tool contributes to the economic literature by introducing a new layer of uncertainty, overcoming limitations of traditional tools like the Bingo Blower. The Ambiguity Box is more practical as it is software-based and can be used with any electronic device. It is flexible, allowing experimenters to predetermine the number of squares of each colour, making it adaptable to various experimental designs. It is easily scalable, suitable for use in different contexts, and allows for the exploration of decision-making under ambiguity in diverse settings, dealing also with extremely low probabilities

From the "age of instability" to the "age of responsibility": economic uncertainty and sustainable investments

PurposeThis paper sets out to investigate investors' sustainable preferences under different market conditions. Specifically, the authors examine the existence of a positive sustainable asset pricing gap, and whether it is influenced by the socioeconomic and financial sentiments. The increase of uncertainty rises investors' skepticism whether sustainable companies are under-performing the traditional counterparts, causing larger increasing gap. Conversely, if sustainable assets are overperforming, the increase of market uncertainty raises investors' sustainable preferences.Design/methodology/approachThe authors examine the existence of a positive sustainable asset pricing gap, and whether it is influenced by the socioeconomic and financial sentiments. Through a quantile regression, the authors remark the variability of sustainable preferences where market participants, although recognizing the present and future value added of sustainable investing, also show skepticism (i.e. asymmetric tail behavior). However, the analysis of the total change of sustainable investments returns over time demonstrates the emergence of positive viewpoints incentivized by economic and market uncertainty.FindingsThe market-driven social responsibility exalts the positive insights regarding the future of sustainable developments. As the authors discuss along the paper, investors are gaining awareness about the environmental and social goals pursued by socially responsible companies. Hence, the authors consider how economic instability might stimulate the assessment of the social and environmental impact of the unsustainable production systems, switching investments toward virtuous sustainable companies. This could generate a series of positive externalities that might improve the welfare conditions of the whole society.Originality/valueThe authors conduct an original empirical exercise, combining different techniques (i.e. quantile regressions and wavelet analysis). To the best of the authors' knowledge, this is the first paper trying to evidence a systematic connection between market uncertainty and sustainable preferences accounting for different market states (thanks to quantile regressions)