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  • Article
  • Article
    Citation - WoS: 16
    Citation - Scopus: 16
    The Timing Database: an Open-Access, Live Repository for Interval Timing Studies
    (Springer, 2023-01-03) Brochard, Renaud; Karşılar, Hakan; Akdoğan, Başak; De Corte, Benjamin; Aydoğan, Turaç; Baccarani, Alessia; Duyan, Yalçın Akın; Balci, Fuat
    Interval timing refers to the ability to perceive and remember intervals in the seconds to minutes range. Our contemporary understanding of interval timing is derived from relatively small-scale, isolated studies that investigate a limited range of intervals with a small sample size, usually based on a single task. Consequently, the conclusions drawn from individual studies are not readily generalizable to other tasks, conditions, and task parameters. The current paper presents a live database that presents raw data from interval timing studies (currently composed of 68 datasets from eight different tasks incorporating various interval and temporal order judgments) with an online graphical user interface to easily select, compile, and download the data organized in a standard format. The Timing Database aims to promote and cultivate key and novel analyses of our timing ability by making published and future datasets accessible as open-source resources for the entire research community. In the current paper, we showcase the use of the database by testing various core ideas based on data compiled across studies (i.e., temporal accuracy, scalar property, location of the point of subjective equality, malleability of timing precision). The Timing Database will serve as the repository for interval timing studies through the submission of new datasets.
  • Article
    Citation - WoS: 9
    Citation - Scopus: 9
    Numerical Averaging in Mice
    (Springer, 2020-11-04) Balcı, Fuat; Duyan, Yalcın Akın; Gür, Ezgi
    Rodents can be trained to associate different durations with different stimuli (e.g., light/sound). When the associated stimuli are presented together, maximal responding is observed around the average of individual durations (akin to averaging). The current study investigated whether mice can also average independently trained numerosities. Mice were initially trained to make 10 or 20 lever presses on a single (run) lever to obtain a reward and each fixed-ratio schedule was signaled either with an auditory or visual stimulus. Then, mice were trained to press another lever to obtain the reward after they responded on the run lever for the minimum number of presses [Fixed Consecutive Number (FCN)-10 or -20 trials] signaled by the corresponding discriminative stimulus. Following this training, FCN trials with the compound stimulus were introduced to test the counting behavior of mice when they encountered conflicting information regarding the number of responses required to obtain the reward. Our results showed that the numbers of responses on these compound test trials were around the average of the number of responses in FCN-10 and FCN-20 trials particularly when the auditory stimulus was associated with a fewer number of required responses. The counting strategy explained the behavior of the majority of the mice in the FCN-Compound test trials (as opposed to the timing strategy). The number of responses in FCN-Compound trials was accounted for equally well by the arithmetic, geometric, and Bayesian averages of the number of responses observed in FCN-10 and FCN-20 trials.
  • Article
    Citation - WoS: 21
    Citation - Scopus: 21
    Testing for Systemic Risk Using Stock Returns
    (Springer, 2016-05-26) Kupiec, Paul; Güntay, Levent
    The literature proposes several stock return-based measures of systemic risk but does not include a classical hypothesis tests for detecting systemic risk. Using a joint null hypothesis of Gaussian returns and the absence of systemic risk, we develop a hypothesis test statistic to detect systemic risk in stock returns data. We apply our tests on conditional value-at-risk (CoVaR) and marginal expected shortfall (MES) estimates of the 50 largest US financial institutions using daily stock return data between 2006 and 2007. The CoVaR test identifies only one institution as systemically important while the MES test identifies 27 firms including some of the financial institutions that experienced distress in the past financial crisis. We perform a simulation analysis to assess the reliability of our proposed test statistics and find that our hypothesis tests have weak power, especially tests using CoVaR. We trace the power issue to the inherent variability of the nonparametric CoVaR and MES estimators that have been proposed in the literature. These estimators have large standard errors that increase as the tail dependence in stock returns strengthens.
  • Book Part
    Citation - WoS: 2
    Citation - Scopus: 2
    Compliance and Reporting Trends: Essential Strategies
    (Springer, 2016-12-20) Son-Turan, Semen
    The digital age, with decreasing barriers to entry, paving the way for low-cost competition, saw an influx of new financial products and services globally. Soon the increasingly technology-driven financial landscape transformed itself with the democratization of finance diffusing to all levels of society. The standing rules and regulations of financial markets were confronted with an epitome of complexities marked by higher transparency, increased efficiencies, a wide range of substitutes, abundant information, a huge number of stakeholders and a bulk of aspiring entrepreneurs. However, a new game necessitates new rules, and a considerable disruption in old ways of doing is sure to witness unorthodox problems that need to be dealt with, and preferably foreseen, through a different lens. Sooner or later, these new digitally enhanced financial markets are destined to break down, dragging down everyone who once had faith in them, if not supported by proper compliance and corporate social performance and reporting standards. This chapter explores newly emerging trends in compliance and reporting standards for financial institutions.