scholarly journals Decision-making under Market Indeterminacy

2021 ◽  
Vol 5 (2) ◽  
pp. 22
Author(s):  
Shi Yun
Keyword(s):  
Financial Market ◽  
Stock Prices ◽  
Imperfect Information ◽  
Empirical Studies ◽  
Price Formation ◽  
Efficient Markets ◽  
Research And Practice ◽  
The Past ◽  
Efficient Markets Hypothesis ◽  
Abnormal Profits

The Efficient Markets Hypothesis (EMH) is the focusing topic in the past 50 years of financial market researches. Many empirical studies are then provided that want to test EMH but have no consensus. The perception of EMH determines the attitude and strategy of participants and regulators in financial market. One perception of EMH argues that investors’ behavior of seeking abnormal profits and arbitrage drives prices to their ‘‘correct’’ value. Investigating the “correct” value derives the concept of “market indeterminacy”. It means the inability to determine whether stock prices are efficient or inefficient. Market indeterminacy pervades stock markets because “correct” prices are unknown because of imperfect information and model sensitivity. Market indeterminacy makes arbitrage risky and makes event studies unreliable in some policy and litigation applications. The concept of market efficiency is needed to be re-recognized considering the mechanism of price formation. In order to further research and practice in law and financial market, there needs a view from the “jumping together” of disparate disciplines. Adaptive Markets Hypothesis(AMH) that using the evolutionary principles in financial market is a new viewpoint oncognitive decision and deserves to be paid more attention to.

Scoring at Halftime

2014 ◽  
Author(s):  
Ignacio Palacios-Huerta
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Efficient Markets ◽  
Efficient Markets Hypothesis ◽  
Influential Theory

This chapter is concerned with the idea of scoring at halftime but with a more scientific perspective. It suggests that what happens at halftime in some soccer games scores big in terms of allowing us to test an influential theory in economics: the efficient-markets hypothesis. The theory posits that the stock market processes information so completely and quickly that any relevant news would be incorporated fully into the stock's price before anyone had the chance to act on it. Simply put, unless one knew information that others did not know, no stock should be a better buy than any other. If the theory is correct—that is, if observed changes in stock prices are unpredictable—there is not much we can do to gain an advantage over other traders, except perhaps to try to identify the news that causes stock prices to rise and fall and to understand the size of any likely price jump.

scholarly journals Economically irrational pricing of nineteenth-century British government bonds

2016 ◽  
Vol 23 (3) ◽  
pp. 277-302 ◽  
Author(s):  
Andrew Odlyzko
Keyword(s):  
Nineteenth Century ◽  
Interest Rate ◽  
Financial Market ◽  
Anomalous Behavior ◽  
Law Of One Price ◽  
Efficient Markets ◽  
British Government ◽  
Government Bonds ◽  
Modern Economy ◽  
Efficient Markets Hypothesis

British government bonds formed the deepest, most liquid and most transparent financial market of the nineteenth century. This article shows that those bonds had long periods, extending over decades, of anomalous behavior, in which Consols, the largest and best known of these instruments, were noticeably overpriced relative to equivalent securities which offered the same interest rate and the same guarantee of payment. This finding and similar ones for other comparable pairs of British gilts appear to provide the most extreme counterexamples documented so far to the Efficient Markets Hypothesis and to the Law of One Price, and point the way to further investigations on the origins and nature of the modern economy.

A review of stock market predictions using deep learning models

2021 ◽  
Vol 23 (07) ◽  
pp. 1335-1341
Author(s):  
Amol Barwal ◽  
◽  
Nishi Gupta ◽  
Keyword(s):  
Deep Learning ◽  
Stock Market ◽  
Financial Market ◽  
Stock Prices ◽  
Learning Models ◽  
Huge Amount ◽  
Stock Trading ◽  
The Past ◽  
The World

Stock trading has always been an appealing option in the world of financial market to make significant profits. As a popular saying goes, “Trading is not gambling”. It is true for the case of stock trading also. Successful traders always do a lot of research and analysis before buying and selling their stocks. This analysis usually includes looking at past record of a stock and finding patterns for future predictions. As machines are very good at processing huge amount of data and finding patterns from the data, we can see why the use of deep learning models can be beneficial in this case. In this paper, we are going to study various deep learning models used by researchers in the past to predict stock prices.

scholarly journals Artificial Intelligence in Education (AIEd): a high-level academic and industry note 2021

AI and Ethics ◽  
2021 ◽  
Author(s):  
Muhammad Ali Chaudhry ◽  
Emre Kazim
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Tutoring Systems ◽  
Policy Makers ◽  
Tutoring Systems ◽  
Research And Practice ◽  
The Past ◽  
Artificial Intelligence In Education ◽  
Potential Impact ◽  
High Level ◽  
Contextualized Learning

AbstractIn the past few decades, technology has completely transformed the world around us. Indeed, experts believe that the next big digital transformation in how we live, communicate, work, trade and learn will be driven by Artificial Intelligence (AI) [83]. This paper presents a high-level industrial and academic overview of AI in Education (AIEd). It presents the focus of latest research in AIEd on reducing teachers’ workload, contextualized learning for students, revolutionizing assessments and developments in intelligent tutoring systems. It also discusses the ethical dimension of AIEd and the potential impact of the Covid-19 pandemic on the future of AIEd’s research and practice. The intended readership of this article is policy makers and institutional leaders who are looking for an introductory state of play in AIEd.

scholarly journals Mapping the Landscape and Structure of Research on Education for Sustainable Development: A Bibliometric Review

2020 ◽  
Vol 12 (5) ◽  
pp. 1947 ◽  
Author(s):  
Philip Hallinger ◽  
Vien-Thong Nguyen
Keyword(s):  
Sustainable Development ◽  
Knowledge Base ◽  
English Language ◽  
Current Knowledge ◽  
Empirical Studies ◽  
Education For Sustainable Development ◽  
Intellectual Structure ◽  
Geographic Diversification ◽  
The Past ◽  
K 12

This systematic review of research used science mapping as a means of analyzing the knowledge base on education for sustainable development (ESD) in K-12 schooling. The review documented the size, growth trajectory and geographic distribution of this literature, identified high impact scholars and documents, and visualized the “intellectual structure” of the field. The database examined in this review consisted of 1842 English language, Scopus-indexed documents published between 1990 and 2018. The review found that the knowledge base on ESD has grown dramatically over the past 30 years, with a rapidly accelerating rate of publication in the past decade. Although the field has been dominated by scholarship from Anglo-American_European nations, there is evidence of increasing geographic diversification of the ESD knowledge base over the past 15 years. Citation analyses identified authors who have had a significant influence on the development of this literature. Author co-citation analysis revealed three “schools of thought” that comprise the “intellectual structure” of this knowledge base: Education for Sustainable Development, Developing a Sustainability Mindset, Teaching and Learning for Sustainability. Document content analyses led to the conclusion that the current knowledge base is heavily weighted towards critical, descriptive and prescriptive papers, with an insufficient body of analytical empirical studies. Several recommendations are offered for strengthening this literature.

The Situation of Situation Research: Knowns and Unknowns

2020 ◽  
Vol 29 (5) ◽  
pp. 473-480 ◽  
Author(s):  
John F. Rauthmann ◽  
Ryne A. Sherman
Keyword(s):  
Empirical Studies ◽  
The Past ◽  
Future Situation ◽  
Person Variables

Over the past 15 years, research on the assessment of psychological situations has flourished. As a result, many basic questions about psychological situations have been answered. We discuss the theoretical and empirical studies that answered these questions, including what situations are; how they can be characterized, taxonomized, and measured; how they relate to person variables; and how persons navigate situations. We first summarize the “knowns” of psychological situation research and then proceed to chart the “unknowns” that have yet to be examined. We conclude with an agenda for future situation research.

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