Questioning the efficient markets hypothesis: Big data evidence of non-random stock prices

2018 ◽  
Author(s):  
Paul J. Darwen
Keyword(s):  
Big Data ◽  
Stock Prices ◽  
Efficient Markets ◽  
Efficient Markets Hypothesis

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 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.

Big data investments in knowledge and non-knowledge intensive firms: what the market tells us

2017 ◽  
Vol 21 (3) ◽  
pp. 623-639 ◽  
Author(s):  
Tingting Zhang ◽  
William Yu Chung Wang ◽  
David J. Pauleen
Keyword(s):  
Big Data ◽  
Knowledge Management ◽  
Stock Market ◽  
Value Chain ◽  
Stock Prices ◽  
Economic Value ◽  
Information Value ◽  
Publicly Traded ◽  
Content Type ◽  
Knowledge Intensive

Purpose This paper aims to investigate the value of big data investments by examining the market reaction to company announcements of big data investments and tests the effect for firms that are either knowledge intensive or not. Design/methodology/approach This study is based on an event study using data from two stock markets in China. Findings The stock market sees an overall index increase in stock prices when announcements of big data investments are revealed by grouping all the listed firms included in the sample. Increased stock prices are also the case for non-knowledge intensive firms. However, the stock market does not seem to react to big data investment announcements by testing the knowledge intensive firms along. Research limitations/implications This study contributes to the literature on assessing the economic value of big data investments from the perspective of big data information value chain by taking an unexpected change in stock price as the measure of the financial performance of the investment and by comparing market reactions between knowledge intensive firms and non-knowledge intensive firms. Findings of this study can be used to refine practitioners’ understanding of the economic value of big data investments to different firms and provide guidance to their future investments in knowledge management to maximize the benefits along the big data information value chain. However, findings of study should be interpreted carefully when applying them to companies that are not publicly traded on the stock market or listed on other financial markets. Originality/value Based on the concept of big data information value chain, this study advances research on the economic value of big data investments. Taking the perspective of stock market investors, this study investigates how the stock market reacts to big data investments by comparing the reactions to knowledge-intensive firms and non-knowledge-intensive firms. The results may be particularly interesting to those publicly traded companies that have not previously invested in knowledge management systems. The findings imply that stock investors tend to believe that big data investment could possibly increase the future returns for non-knowledge-intensive firms.

scholarly journals Methodology for Measuring the Impact of the Privacy Protection Law on the Use of Big Data

2021 ◽  
Vol 15 ◽  
pp. 62-66
Author(s):  
Oh Ky U-Cheol
Keyword(s):  
Big Data ◽  
Stock Prices ◽  
Privacy Protection ◽  
Turning Point ◽  
Personal Information ◽  
Legal Regulation ◽  
Technical Innovation ◽  
Smart Devices ◽  
Ict Revolution ◽  
The Impact

The ICT revolution triggered by the emergence of smart devices, typically represented by the iPhone and the iPad, is migrating into the new domain of ‘big data’ after passing the turning point of ‘SNS Life,’ which is represented by Twitter and FaceBook among others. These developments have brought significant changes in all areas of politics, economy and culture. The stock prices of Apple, Samsung Electronics, FaceBook and Google fluctuate depending on who takes the hegemony in the changes. Meanwhile, such a reform of the ICT sector has generated some new undesirable sideeffects, including online disclosure of personal information, malicious comments, Smishing or other forms of financial scams. As we cannot abandon either big data or privacy protection, it is critical to find a compromise. It seems both evident and selfexplanatory that the use of big data, which is attributable to technical innovation, conflicts with privacy protection based on the idea that individuals should be allowed to determine the disclosure or not of their personal information. Yet, the problem here is that the discussion of countermeasures remains at the level of catching the wind with a net. Therefore, this paper intends to present a framework that can objectively verify what impact the enhanced legal regulation concerning privacy protection has on the use of big data as the first step in exploring a compromise between the use of big data and privacy protection.

scholarly journals Sorismo en el contexto del geunismo

2012 ◽  
Author(s):  
Alejandro Sánchez-Seco López
Keyword(s):  
Great Recession ◽  
Body Politic ◽  
The Body ◽  
The Political ◽  
Efficient Markets ◽  
Efficient Markets Hypothesis ◽  
Economic Philosophy ◽  
The One ◽  
Regulatory Proposals ◽  
Economic Globalisation

En el contexto de una obra mucho más amplia y en ciernes, que propone como único sistema plenamente legítimo aquél cuyo cuerpo político viene constituido por la totalidad de habitantes del planeta, es conveniente traer a colación la filosofía política y económica de George Soros, porque aporta una visión muy diferente a la aplicada por los endiosados economistas que no supieron ver con antelación la Gran Recesión global en la que seguimos inmersos. La relación entre la realidad y el pensamiento es clave en el sorismo, como también lo es la distinción entre los diversos tipos de ciencias. La hipótesis de la eficiencia en los mercados también es cuestionada, junto con el concepto de equilibrio en economía, la incertidumbre y la falibilidad. También se acomete la crítica del fundamentalismo de mercado y a las propuestas regulatorias. Y todo en el contexto de una globalización económica poco política.Within the context of a much wider and developing piece proposing as only fully legitimate system the one the body politic of which is composed of the totality of inhabitants on the planet, it is convenient to bring to us the political and economic philosophy of George Soros for it adds a very different vision to that applied by the deified economists who could not in advance see the global Great Recession in which we keep on living. The relation between reality and thought is key within Sorism, as it is the distinction amongst the several kinds of sciences. The Efficient Markets Hypothesis is also put into question side by side with the concept of equilibrium in Economics, uncertainty, and fallibility. The critique of market fundamentalism is also implemented as well as the regulatory proposals. And all of it taking place within the context of a scarcely political but very economic globalisation.

scholarly journals FRACTAL MARKETS HYPOTHESIS AND THE GLOBAL FINANCIAL CRISIS: SCALING, INVESTMENT HORIZONS AND LIQUIDITY

2012 ◽  
Vol 15 (06) ◽  
pp. 1250065 ◽  
Author(s):  
LADISLAV KRISTOUFEK
Keyword(s):  
Financial Crisis ◽  
Complex Systems ◽  
Financial Markets ◽  
Global Financial Crisis ◽  
Efficient Markets ◽  
Investment Horizon ◽  
Heterogenous Agents ◽  
Efficient Markets Hypothesis ◽  
The Global Financial Crisis ◽  
Underlying Processes

We investigate whether the fractal markets hypothesis and its focus on liquidity and investment horizons give reasonable predictions about the dynamics of the financial markets during turbulences such as the Global Financial Crisis of late 2000s. Compared to the mainstream efficient markets hypothesis, the fractal markets hypothesis considers the financial markets as complex systems consisting of many heterogenous agents, which are distinguishable mainly with respect to their investment horizon. In the paper, several novel measures of trading activity at different investment horizons are introduced through the scaling of variance of the underlying processes. On the three most liquid US indices — DJI, NASDAQ and S&P500 — we show that the predictions of the fractal markets hypothesis actually fit the observed behavior adequately.

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