Self-Action Effect on Price Formation in Financial Markets

2021 ◽  
Author(s):  
Jack Sarkissian ◽  
Joel Sebold ◽  
Vadim Nastasiuk
Keyword(s):  
Financial Markets ◽  
Price Formation ◽  
Action Effect

A guide on empirical tests of the EMH

2019 ◽  
Vol 18 (2) ◽  
pp. 268-295
Author(s):  
David Peón ◽  
Manel Antelo ◽  
Anxo Calvo
Keyword(s):  
Financial Markets ◽  
Design Methodology ◽  
Recent Literature ◽  
Asset Price ◽  
Efficient Market Hypothesis ◽  
Price Formation ◽  
Content Type ◽  
Economic Fundamentals ◽  
Empirical Tests ◽  
Available Information

Purpose The efficient market hypothesis (EMH) states that asset prices in financial markets always reflect all available information about economic fundamentals. The purpose of this paper is to provide a guide as to which predictions of the EMH seem to be borne out by empirical evidence. Design/methodology/approach Rather than following the classic three groups of tests for the different forms of EMH that are common in the literature, the authors consider how the two alternative definitions of the EMH and the joint hypothesis problem impact on the tests and leave the controversy unsolved. The authors briefly report the antecedents, the main theoretical and empirical contributions and recent literature on each type of tests. Findings Eventually, as a summary for each type of tests, the authors provide a critical view on the main sources of acrimony between the alternative schools of thought in understanding asset price formation. Originality/value The paper may be seen as an up-to-date introductory review for researchers on the different tests of the EMH performed, and for newcomers to understand the key sources of acrimony between rationalists and behaviorists.

scholarly journals The Effect of Ambiguity on Price Formation and Trading Behavior in Financial Markets

2021 ◽  
Author(s):  
Wenhui Li ◽  
Peter Ockenfels ◽  
Christian Wilde
Keyword(s):  
Financial Markets ◽  
Price Formation ◽  
Trading Behavior

scholarly journals Price response functions and spread impact in correlated financial markets

2021 ◽  
Vol 94 (4) ◽  
Author(s):  
Juan C. Henao-Londono ◽  
Sebastian M. Krause ◽  
Thomas Guhr
Keyword(s):  
Financial Markets ◽  
Stock Prices ◽  
Signal Strength ◽  
Price Formation ◽  
Response Functions ◽  
Trading Costs ◽  
Research Focus ◽  
Data Set ◽  
Price Response ◽  
The Impact

AbstractRecent research on the response of stock prices to trading activity revealed long-lasting effects, even across stocks of different companies. These results imply non-Markovian effects in price formation and when trading many stocks at the same time, in particular trading costs and price correlations. How the price response is measured depends on data set and research focus. However, it is important to clarify how the details of the price response definition modify the results. Here, we evaluate different price response implementations for the Trades and Quotes (TAQ) data set from the NASDAQ stock market and find that the results are qualitatively the same for two different definitions of time scale, but the response can vary by up to a factor of two. Furthermore, we show the key importance of the order between trade signs and returns, displaying the changes in the signal strength. Moreover, we confirm the dominating contribution of immediate price response directly after a trade, as we find that delayed responses are suppressed. Finally, we test the impact of the spread in the price response, detecting that large spreads have stronger impact.

Financial Markets as Interacting Individuals: Price Formation from Models of Complexity

2013 ◽  
pp. 59-76
Author(s):  
Jørgen Vitting Andersen ◽  
Andrzej Nowak
Keyword(s):  
Financial Markets ◽  
Price Formation

PRICE FORMATION BASED ON PARTICLE-CLUSTER AGGREGATION

2005 ◽  
Vol 16 (11) ◽  
pp. 1803-1810 ◽  
Author(s):  
SHIJUN WANG ◽  
CHANGSHUI ZHANG
Keyword(s):  
Financial Markets ◽  
Composite Index ◽  
Small World ◽  
Price Formation ◽  
Historical Records ◽  
Particle Cluster ◽  
Volatility Clustering ◽  
Cluster Aggregation ◽  
Tail Distribution ◽  
World Information

In the present work, we propose a microscopic model of financial markets based on particle-cluster aggregation on a two-dimensional small-world information network in order to simulate the dynamics of the stock markets. "Stylized facts" of the financial market time series, such as fat-tail distribution of returns, volatility clustering and multifractality, are observed in the model. The results of the model agree with empirical data taken from historical records of the daily closures of the NYSE composite index.

Is a Stock Exchange a Computer Solution?

2011 ◽  
Vol 3 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Fabian Muniesa
Keyword(s):  
Financial Markets ◽  
North American ◽  
Stock Exchange ◽  
Single Point ◽  
Price Formation ◽  
Computer Solution ◽  
Call Auction ◽  
Definition Of

The paper examines, through a case study on the Arizona Stock Exchange, how computerization challenged the definition of the stock exchange in the context of North-American financial markets in the 1990’s. It analyses exchange automation in terms of trials of explicitness: the computational formulation of what an exchange is calls for a detailed explication of the (variable, often conflicting and unanticipated) processes and properties of price formation. The paper focuses in particular on the argument of the concentration of liquidity in one single point, which was central to the development of the Arizona Stock Exchange (an electronic call auction). It then asks what kind of revolution is the ‘explicitness revolution’ in the design of allocation mechanisms.

scholarly journals Universal features of price formation in financial markets: perspectives from deep learning

2019 ◽  
Vol 19 (9) ◽  
pp. 1449-1459 ◽  
Author(s):  
Justin Sirignano ◽  
Rama Cont
Keyword(s):  
Deep Learning ◽  
Financial Markets ◽  
Price Formation
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