Search results for "causality"
showing 10 items of 258 documents
A dynamic analysis of SP 500, FTSE 100 and EURO STOXX 50 indices under different exchange rates.
2018
In this study, we assess the dynamic evolution of short-term correlation, long-term cointe-gration and Error Correction Model (hereafter referred to as ECM)-based long-term Granger causality between each pair of US, UK, and Eurozone stock markets from 1980 to 2015 using the rolling-window technique. A comparative analysis of pairwise dynamic integration and causality of stock markets, measured in common and domestic currency terms, is conducted to evaluate comprehensively how exchange rate fluctuations affect the time-varying integration among the S&P 500, FTSE 100 and EURO STOXX 50 indices. The results obtained show that the dynamic correlation, cointegration and ECM-based long-run Gra…
Corruption-Related Disclosure in the Banking Industry: Evidence From GIPSI Countries
2022
This paper empirically investigates corruption-related disclosure in the banking industry, aiming to identify the most relevant theories which explain why financial institutions disclose corruption-related information to the public in their annual financial reports.Using a total sample of 88 banks from the GIPSI countries during the period 2011-2019, our results reveal that, on average, banks involved in corruption issues disclose less on corruption-related information than banks not involved in any corruption scandal. Moreover, banks not involved in corruption cases disclose even more information after other banks’ corruption events become public. These basic relationships, however, are sh…
Newton's Law of Universal Gravitation and Hume's Conception of Causality
2013
This article investigates the relationship between Hume’s causal philosophy and Newton’s philosophy of nature. I claim that Newton’s experimentalist methodology in gravity research is an important background for understanding Hume’s conception of causality: Hume sees the relation of cause and effect as not being founded on a priori reasoning, similar to the way that Newton criticized non-empirical hypotheses about the properties of gravity. However, according to Hume’s criteria of causal inference, the law of universal gravitation is not a complete causal law, since it does not include a reference either to contiguity or to temporal priority. It is still argued that because of the empirical…
Explicit Granger causality in kernel Hilbert spaces
2020
Granger causality (GC) is undoubtedly the most widely used method to infer cause-effect relations from observational time series. Several nonlinear alternatives to GC have been proposed based on kernel methods. We generalize kernel Granger causality by considering the variables cross-relations explicitly in Hilbert spaces. The framework is shown to generalize the linear and kernel GC methods, and comes with tighter bounds of performance based on Rademacher complexity. We successfully evaluate its performance in standard dynamical systems, as well as to identify the arrow of time in coupled R\"ossler systems, and is exploited to disclose the El Ni\~no-Southern Oscillation (ENSO) phenomenon f…
Quantifying High-Order Interactions in Cardiovascular and Cerebrovascular Networks
2022
We present a method to analyze the dynamics of physiological networks beyond the framework of pairwise interactions. Our method defines the so-called O-information rate (OIR) as a measure of the higher-order interaction among several physiological variables. The OIR measure is computed from the vector autoregressive representation of multiple time series, and is applied to the network formed by heart period, systolic and diastolic arterial pressure, respiration and cerebral blood flow variability series measured in healthy subjects at rest and after head-up tilt. Our results document that cardiovascular, cerebrovascular and respiratory interactions are highly redundant, and that redundancy …
Caso fortuito e culpa levissima: premesse ad uno studio sul nesso di causalità nel pensiero giuridico tardo medievale
2022
Lo studio esamina lo sviluppo del nesso causale nel diritto comune tardo medievale
Online Topology Identification from Vector Autoregressive Time Series
2019
Causality graphs are routinely estimated in social sciences, natural sciences, and engineering due to their capacity to efficiently represent the spatiotemporal structure of multivariate data sets in a format amenable for human interpretation, forecasting, and anomaly detection. A popular approach to mathematically formalize causality is based on vector autoregressive (VAR) models and constitutes an alternative to the well-known, yet usually intractable, Granger causality. Relying on such a VAR causality notion, this paper develops two algorithms with complementary benefits to track time-varying causality graphs in an online fashion. Their constant complexity per update also renders these a…
Coming up Roses
2022
Discussing two short stories by contemporary Scottish author Ali Smith, my article recommends a close reading of short prose narratives as potential examples of ungendered character-narration. I combine queer and unnatural narrative theory to consider how forms of telling contribute to gender ambiguity. Further, I advocate interpretative strategies that resist naturalization and causal explanations. Instead, a queer reading of Smith’s “erosive” (2003) and “The beholder” (2015) delights in their ambiguity, waywardness, and narrative inventiveness. The texts can be approached as exercises in unknowing.
 Keywords: queer narratology, unnatural narratology, ungendering, narrative voice, cau…
Searching for the truth about schizophrenia requires the application of similarly high standards of proof to biological and social risk factors
2013
In their provocative paper, Bentall and Varese (2012) criticize our review on child abuse and schizophrenia (Sideli, Mule, La Barbera, & Murray, 2012) and suggest that we have a biological bias whi...
Estimating the decomposition of predictive information in multivariate systems
2015
In the study of complex systems from observed multivariate time series, insight into the evolution of one system may be under investigation, which can be explained by the information storage of the system and the information transfer from other interacting systems. We present a framework for the model-free estimation of information storage and information transfer computed as the terms composing the predictive information about the target of a multivariate dynamical process. The approach tackles the curse of dimensionality employing a nonuniform embedding scheme that selects progressively, among the past components of the multivariate process, only those that contribute most, in terms of co…