Market inefficiencies surrounding energy announcements

2021 ◽  
Author(s):  
Sultan Alturki ◽  
Alexander Kurov
Keyword(s):  
Market Inefficiencies

scholarly journals Novel market inefficiencies from early Victorian times

2017 ◽  
Vol 24 (2) ◽  
pp. 143-165 ◽  
Author(s):  
Andrew Odlyzko
Keyword(s):  
Nineteenth Century ◽  
Economic Incentives ◽  
Bond Market ◽  
Government Bond ◽  
British Government ◽  
Victorian Culture ◽  
Market Inefficiencies ◽  
Corporate Capitalism ◽  
The Government ◽  
Pricing Anomaly

A previously unknown pricing anomaly existed for a few years in the late 1840s in the British government bond market, in which the larger and more liquid of two very large bonds was underpriced. None of the published mechanisms explains this phenomenon. It may be related to another pricing anomaly that existed for much of the nineteenth century in which terminable annuities were significantly underpriced relative to so-called ‘perpetual’ annuities that dominated the government bond market. The reasons for these mispricings seem to lie in the early Victorian culture, since the basic economic incentives as well as laws and institutions were essentially the familiar modern ones. This provides new perspectives on the origins and nature of modern corporate capitalism.

Accounting-Based Stock Price Anomalies: Separating Market Inefficiencies from Risk

1997 ◽  
Vol 14 (2) ◽  
pp. 89-136 ◽  
Author(s):  
VICTOR BERNARD ◽  
JACOB THOMAS ◽  
JAMES WAHLEN
Keyword(s):  
Stock Price ◽  
Market Inefficiencies

scholarly journals A Review of Market Segmentation and Inefficiencies of the Chinese Stock Market

2015 ◽  
Vol 4 (4) ◽  
pp. 18-28
Author(s):  
Shuang Feng ◽  
Jon Stewart
Keyword(s):  
Stock Market ◽  
Market Segmentation ◽  
Recent Literature ◽  
Emerging Market ◽  
Chinese Stock Market ◽  
Future Studies ◽  
Calendar Effects ◽  
Market Inefficiencies ◽  
The Past ◽  
Market Inefficiency

The Chinese stock market is an emerging market that has gained much importance over the past few decades. Because of this, it also serves as a great subject for studying market inefficiencies and anomalies. In this paper we provide a review of evidence regarding the development, efficiency and integration of the Chinese stock market. In particular, we review recent literature in the areas of market segmentation, cross-listings and calendar effects. This provides evidence of market inefficiency in China. We also pose questions that can be answered in future studies.

scholarly journals High-frequency data and the effectiveness of the spot exchange rate EUR/USD

2013 ◽  
Vol 61 (7) ◽  
pp. 2965-2971
Author(s):  
Petr Zeman ◽  
Martin Maršík
Keyword(s):  
Exchange Rate ◽  
Financial Markets ◽  
Statistical Tests ◽  
The Public ◽  
Market Inefficiencies ◽  
Random Walk Hypothesis ◽  
Potential Market ◽  
Spot Exchange Rate ◽  
Trading Period ◽  
Daily Changes

The boom of information technology in recent years significantly influenced the development of the financial markets. Financial markets have become accessible to the public, and increased demand for financial instruments is inevitably reflected in the advanced menu of securities dealers who currently offer a wide variety of investment in the underlying assets and through financial leverage allows investors to profit from tiny price changes of the underlying asset. Shortening of trading period and increasing the frequency of the trades clearly contributes to the growth of profits of securities dealers. The question remains whether this trading method offers the advantage to the investor himself, and whether the investor is able to take advantage of potential market inefficiencies to achieve above-average profits in the short term period. Therefore, this paper analyzes the behaviour of the spot exchange rate EUR/USD within a day, and through statistical tests examining the validity of the random walk hypothesis for the 5-minute, hourly, 4-hourly and daily changes in the spot exchange rate of the currency pair EUR/USD.

Applying Artificial Intelligence to Financial Investing

2018 ◽  
pp. 1-14
Author(s):  
Hayden Wimmer ◽  
Roy Rada
Keyword(s):  
Artificial Intelligence ◽  
Risk Management ◽  
Language Processing ◽  
Credit Scoring ◽  
Bankruptcy Prediction ◽  
Asset Valuation ◽  
Artificial Intelligence Techniques ◽  
Academic Literature ◽  
Market Inefficiencies ◽  
Knowledge Based

Artificial intelligence techniques have long been applied to financial investing scenarios to determine market inefficiencies, criteria for credit scoring, and bankruptcy prediction, to name a few. While there are many subfields to artificial intelligence this work seeks to identify the most commonly applied AI techniques to financial investing as appears in academic literature. AI techniques, such as knowledge-based, machine learning, and natural language processing, are integrated into systems that simultaneously address data identification, asset valuation, and risk management. Future trends will continue to integrate hybrid artificial intelligence techniques into financial investing, portfolio optimization, and risk management. The remainder of this article summarizes key contributions of applying AI to financial investing as appears in the academic literature.

scholarly journals The relationship between excess returns, firm size and earnings on the Johannesburg Stock Exchange

1991 ◽  
Vol 22 (3) ◽  
pp. 63-73 ◽  
Author(s):  
Michael J. Page ◽  
Francis Palmer
Keyword(s):  
Firm Size ◽  
Stock Exchange ◽  
Empirical Studies ◽  
Model Misspecification ◽  
Empirical Work ◽  
The United States ◽  
Excess Returns ◽  
Market Inefficiencies ◽  
Johannesburg Stock Exchange ◽  
The Relationship

While considerable empirical work has been conducted in the United States concerning excess returns and the relationship of these returns to firm size and E/P ratio, thus far, there have been few similar empirical studies conducted using Johannesburg Stock Exchange (JSE) data. Evidence of firm size or E/P ratio effects has been ascribed by various authors to either model misspecification or market inefficiencies. In this article the evidence is examined for the South African market using 1370 company years of data over the period 1978 to 1988, and a significant earnings effect is found, but no size effect. In the analysis the problem of data bias is considered with particular emphasis on thin trading issues, and a methodology for future empirical work is described. Finally, it is suggested that the evidence can be better explained by market inefficiencies than model misspecification.

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