Breach of continuous disclosure in Australia

Given that disclosure is important for the efficient functioning of capital markets, this paper explores the impact of infringement of continuous disclosure by Australian listed firms. We observe a significantly negative market reaction for our sample firms around the day an infringement is announced. Our findings also provide partial evidence of an increase in spreads and a decrease in price informativeness following the announcement of a breach. Overall, our results indicate that the market considers the breach of continuous disclosure to be a relatively important incident

Do criminal sanctions deter insider trading?

Many developed markets have taken what appears to be a tough stance on illegal insider trading through the use of criminal sanctions. Although criminal sanctions represent a much greater penalty than civil sanctions, the higher burden of proof required makes their enforceability weaker. This trade-off between severity and enforceability makes the impact of criminal sanctions ambiguous. In this paper, we empirically examine this issue by studying the deterrence of insider trading following the introduction of criminal sanctions in a developed market. Significant changes in sanction regimes are rare, especially when criminal sanctions are introduced without other changes. In February 2008, New Zealand introduced criminal sanctions for insider trading. This change of law offers a unique setting in which to examine the deterrence effect of criminalization. Using measures for the cost of trading, degree of information asymmetry, and probability of informed trading, we find that the enactment of this law led to a worsening in these measures. These findings suggest that the weaker enforceability of criminalization outweighs the associated increased severity of the penalties

Why do financial literacy programmes fail?

Numerous studies have found a positive relationship between financial literacy and financial experience. Typically, this relationship is interpreted as being a causal relationship, i.e. an increase in financial literacy leads to better financial decision making. However, a simple relationship cannot be interpreted in a causal way. In this paper, we show evidence for a causal relationship running the opposite way, i.e. people with more financial experience seem to acquire more financial knowledge and become more financially literate. This finding has important implications as it suggests that programmes targeted at improving financial literacy could be more effective if they incorporate experiential components

Price discovery in US-Canadian cross-listed shares

Given the increasing integration of markets around the world, concerns have been expressed about the survival of smaller national exchanges in competition with larger, more liquid exchanges. Several theories have been put forward regarding the likely long-term survival of smaller exchanges, but little actual empirical evidence has been presented to suggest which of the theories, if any, are correct. We explore this issue within the setting of Canadian and US firms cross-listing onto each other’s exchanges using the component share measure of each exchanges contribution to price discovery. We look at Gonzalo and Granger (1995) component shares over a 14 year period from 1996-2009 and find that each market is on average informationally dominant for its own companies, with the exception of Canadian firms listing on the NASDAQ. We also find that there is considerable time variation in the component shares, but little evidence that the Canadian market is systematically losing competitiveness to the US exchanges as has been feared. We also find that known determinants of the level of price discovery appear unrelated to the changes in price discovery

Macroeconomic news announcements and price discovery: evidence from Canadian-U.S. cross-listed firms

This study employs macroeconomic news announcements as a proxy for new information arrivals and examines their impact on price discovery. We compare the price discovery of 38 Canadian companies listed on the Toronto Stock Exchange (TSX) and the New York Stock Exchange (NYSE) for the period 2004–2011. First, we observe that price discovery shifts significantly during macroeconomic news announcement days. Second, the NYSE becomes more important in terms of price discovery, regardless of the origin of the news. Third, we examine the relation between price discovery and market microstructure variables. After controlling for liquidity shocks, we find that the impact of news announcements persists. Intraday analyses of price discovery on periods surrounding news releases further support these findings. Overall, our findings suggest that there is a difference in information-processing capability of the two markets, with the U.S. market being better at processing information than the Canadian market during macroeconomic news announcements

Do insiders crowd out analysts?

Both insiders and analysts are involved in the collection and dissemination of information to the market, roles which impact heavily on price efficiency and resource allocation. The differences between the two groups, however, result in a competitive relationship with analysts at a disadvantage as they face greater costs associated with information gathering. As a result they may choose not to participate in a onesided competition. We employ transaction data to examine the impact of firm-year aggregate insider trading intensity on the level of analyst following. We find a negative relationship between insider trading intensity and analyst coverage. This result was driven by large blockholders suggesting that analysts are attracted to higher levels of information asymmetry from which they profit

Cross border mergers and acquisitions and default risk

Using a cross-country sample of mergers and acquisitions, we examine the role of cultural, institutional, geographic and managerial factors on post-merger default risk. We find that cultural factors, especially the relative difference in uncertainty avoidance between the acquiring and target country, play a significant role in affecting post-merger default risk. Furthermore, we find that institutional quality affects the post-merger default risk of acquiring firms. In contrast to the prior research we do not find any evidence indicating that managerial incentives drive post-merger default risk changes. Also, we do not find any evidence indicating the relevance of geographic distance on default risk

A Generative Framework for Low-Cost Result Validation of Outsourced Machine Learning Tasks

The growing popularity of Machine Learning (ML) has led to its deployment in various sensitive domains, which has resulted in significant research focused on ML security and privacy. However, in some applications, such as autonomous driving, integrity verification of the outsourced ML workload is more critical--a facet that has not received much attention. Existing solutions, such as multi-party computation and proof-based systems, impose significant computation overhead, which makes them unfit for real-time applications. We propose Fides, a novel framework for real-time validation of outsourced ML workloads. Fides features a novel and efficient distillation technique--Greedy Distillation Transfer Learning--that dynamically distills and fine-tunes a space and compute-efficient verification model for verifying the corresponding service model while running inside a trusted execution environment. Fides features a client-side attack detection model that uses statistical analysis and divergence measurements to identify, with a high likelihood, if the service model is under attack. Fides also offers a re-classification functionality that predicts the original class whenever an attack is identified. We devised a generative adversarial network framework for training the attack detection and re-classification models. The evaluation shows that Fides achieves an accuracy of up to 98% for attack detection and 94% for re-classification.Comment: 16 pages, 11 figure

The emotional side of software developers in JIRA

Issue tracking systems store valuable data for testing hypotheses concerning maintenance, building statistical prediction models and (recently) investigating developer affectiveness. For the latter, issue tracking systems can be mined to explore developers emotions, sentiments and politeness |affects for short. However, research on affect detection in software artefacts is still in its early stage due to the lack of manually validated data and tools. In this paper, we contribute to the research of affects on software artefacts by providing a labeling of emotions present on issue comments. We manually labeled 2,000 issue comments and 4,000 sentences written by developers with emotions such as love, joy, surprise, anger, sadness and fear. Labeled comments and sentences are linked to software artefacts reported in our previously published dataset (containing more than 1K projects, more than 700K issue reports and more than 2 million issue comments). The enriched dataset presented in this paper allows the investigation of the role of affects in software development

Limited evidence on the effectiveness of interventions to reduce livestock predation by large carnivores

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