Initial Evidence on the Market Impact of the iXBRL Adoption

In June 2018, the SEC adopted Inline eXtensible Business Reporting Language (iXBRL), which embeds XBRL data into HTML-formatted annual reports to improve the accessibility and usefulness of the information disclosures to investors. This study assesses the effectiveness of iXBRL by examining its impact on informational efficiency and information asymmetry. Using a sample that includes iXBRL voluntary adopters before 2019, we find that iXBRL adoption lowers stock return drift and facilitates information being impounded into firm stock prices following the filing of annual reports. We also find that unlike XBRL, iXBRL reduces information asymmetry in the long run. These findings are consistent with the SEC’s intention of adopting iXBRL to combine human-readable and machine-readable information. Our study provides initial evidence on the effectiveness of iXBRL in communicating information to the external users of annual reports.

Dark Market Share around Earnings Announcements and Speed of Resolution of Investor Disagreement

This study examines how the market share of dark venues changes at earnings announcements. Our analysis shows a statistically significant increase in dark market share in the weeks prior to, during, and following the earnings announcement. We also predict and find evidence that increases in dark market share around earnings announcements are higher for firms with high quality accounting information. In addition, we find a positive relation between the change in dark market share and the speed of resolution of investor disagreement-a key dimension of informational efficiency, which suggests that dark trading is associated with an improvement in market quality. How market fragmentation changes around news events, the role accounting information plays in market fragmentation, and how changes in market fragmentation relate to market quality can help provide insights to securities regulators.

GMDH-type Neural Networks for Predicting Financial Time Series: A Study of Informational Efficiency of Stock Markets

A theory of Efficient Market Hypothesis (EMH) has been introduced by Fama to analyse financial markets. In particular the EMH theory has been proven in real cases under different conditions, including financial crises and frauds. The EMH assumes to examine the prediction accuracy of models designed on retrospective data. Such prediction models could be designed in different ways that motivated us to explore Machine Learning (ML) methods known for building models providing a high prediction performance. In this study we propose a ``deep'' learning method for building high-performance prediction models. The proposed method is based on the Group Method of Data Handling (GMDH) that is the deep learning paradigm capable of building multilayer neural-network models of a near-optimal complexity on given data. We show that the developed GMDH-type neural network has outperformed the models built by the conventional ML methods on the Warsaw Stock Exchange data. It is important that the complexity of the designed GMDH-type neural-networks is defined by the number of layers and connections between neurons. The performances of models were compared in terms of the prediction errors. We report a significantly smaller prediction error of the proposed method than that of the conventional autoregressive and "shallow’’ neural-network models. This finally allows us to conclude that traders will be advantaged by the proposed method.

Adaptive market hypothesis: An empirical analysis of the Wine Market

We test the nature of weak form informational efficiency present in the wine market using daily return of LIV-EX 50 index from 1/1/2010 to 12/6/2020. First, we employ a number of statistical tests including variance ratio tests, tests for linear and non-linear dependence and Hurst coefficient. The tests are applied on the full dataset and on four non overlapping sub-samples of equal length. The variance ratio tests provide a mixed regarding informational efficiency. Evidence of non-linear dependence in the return series was found. The Hurst coefficient values confirm the presence of long run persistence in the wine market. Based on the mixed evidence, we test the possibility of adaptive nature of the wine market. We employ the newly proposed Adaptive Index (AI) to quantify the degree of information inefficiency in the wine market at any instance. Our results confirm that wine market is adaptive and periodically shifts between states of efficiency and inefficiency. The wine market is found to be relatively free from the Covid-19 induced shock and the safe haven property of wine is thus confirmed. Finally, impact of various macroeconomic and financial events on wine market efficiency is identified by using AI.

Teaching Philosophy and Enactivism

"The paper presents a concise history of enactivism in education, especially in mathematics education. Cases described by Davis’s, Proulx and Simmt’s work showcase the idea that enactivism is a viable alternative to constructivism or to classical views both in terms of practical teaching and theoretical models related to the process of learning. The idea that the student should solve a fixed problem, discover the universally correct solution, and eventually store that correct solution to find many other universally correct solutions to other fixed problems reduces the student to a very simple mechanism aimed at informational efficiency. This problem is met by the enactivistic tradition that began with Varela and Maturana’s work, now updated to the aforementioned researchers. Contra the classical perspective, enactivism proposes the idea that the student collaboratively produces the problem, being able to see multiple solutions, and eventually becoming a performer of knowledge. The article takes these ideas developed in mathematics education and finds their use in philosophical education. The article especially focuses on the student’s problem of being unable to link a new philosophical text discussed in class with their intuition. The last part of the article offers a lesson design example. The philosophical design focuses on making the students explore their own thinking regarding the topic about to be discussed by using a philosophy text before introducing the text. Keywords: enactivism, phenomenology, philosophy of education, classroom design "

Entropy-Based Behavioural Efficiency of the Financial Market

The most known and used abstract model of the financial market is based on the concept of the informational efficiency (EMH) of that market. The paper proposes an alternative which could be named the behavioural efficiency of the financial market, which is based on the behavioural entropy instead of the informational entropy. More specifically, the paper supports the idea that, in the financial market, the only measure (if any) of the entropy is the available behaviours indicated by the implicit information. Therefore, the behavioural entropy is linked to the concept of behavioural efficiency. The paper argues that, in fact, in the financial markets, there is not a (real) informational efficiency, but there exists a behavioural efficiency instead. The proposal is based both on a new typology of information in the financial market (which provides the concept of implicit information—that is, that information ”translated” by the economic agents from observing the actual behaviours) and on a non-linear (more exactly, a logistic) curve linking the behavioural entropy to the behavioural efficiency of the financial markets. Finally, the paper proposes a synergic overcoming of both EMH and AMH based on the new concept of behavioural entropy in the financial market.

Dark Pool Trading and Information Acquisition

Theory suggests that dark pools may facilitate or discourage information acquisition. We find that more dark pool trading leads to greater information acquisition. We measure information acquisition using stock price dynamics around earnings announcements. To overcome endogeneity concerns, we exploit a large exogenous decrease to dark pool trading that results from the implementation of the Security and Exchange Commission’s (SEC’s) Tick Size Pilot Program. The results cannot be explained by lit venue liquidity, algorithmic trading, or informational efficiency. A battery of additional tests, such as documenting a shift in SEC EDGAR searches, supports the information acquisition interpretation.