Quantifying Stock Return Distributions in Financial Markets

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Quantifying Stock Return Distributions in Financial Markets is …
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scholarly articleQ13442814

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P819ADS bibcode2015PLoSO..1035600B
P356DOI10.1371/JOURNAL.PONE.0135600
P932PMC publication ID4556674
P698PubMed publication ID26327593
P5875ResearchGate publication ID281519483

P50authorH. Eugene StanleyQ870027
Tobias PreisQ7811656
Helen Susannah MoatQ57414185
Federico BottaQ58584691
P2860cites workTests of nonuniversality of the stock return distributions in an emerging marketQ83183590
Quantifying the advantage of looking forwardQ24604429
Quantifying Wikipedia Usage Patterns Before Stock Market MovesQ24629584
Quantifying trading behavior in financial markets using Google TrendsQ24631411
Computational social scienceQ24653303
Quantifying the semantics of search behavior before stock market movesQ28244846
Quantifying crowd size with mobile phone and Twitter dataQ28646116
Adaptive nowcasting of influenza outbreaks using Google searchesQ28646474
Quantifying International Travel Flows Using FlickrQ28647476
Quantifying the relationship between financial news and the stock marketQ28661027
Quantifying the digital traces of Hurricane Sandy on FlickrQ28661772
Using big data to predict collective behavior in the real worldQ30765251
Cross-correlations between volume change and price changeQ33563938
Ensuring the data-rich future of the social sciencesQ33817893
Modeling the stylized facts in finance through simple nonlinear adaptive systemsQ34139363
A theory of power-law distributions in financial market fluctuationsQ34197126
Identity and privacy. Unique in the shopping mall: on the reidentifiability of credit card metadataQ34460455
The economy needs agent-based modellingQ34996108
Linking agent-based models and stochastic models of financial marketsQ36001411
Quantifying the behavior of stock correlations under market stressQ36330094
Identifying states of a financial marketQ42136283
Tests of scaling and universality of the distributions of trade size and share volume: evidence from three distinct marketsQ47262235
Power-Law Distributions in Empirical DataQ50377899
Multi-agent-based Order Book Model of financial marketsQ56032657
Scaling behaviour in the dynamics of an economic indexQ56094683
Market dynamics immediately before and after financial shocks: Quantifying the Omori, productivity, and Bath lawsQ57111634
Manifesto of computational social scienceQ57400736
Scaling and criticality in a stochastic multi-agent model of a financial marketQ59061794
Zipf distribution of U.S. firm sizesQ74485814
Scaling of the distribution of fluctuations of financial market indicesQ77994038
Econophysics: Two-phase behaviour of financial marketsQ78768871
P275copyright licenseCreative Commons Attribution 4.0 InternationalQ20007257
P6216copyright statuscopyrightedQ50423863
P433issue9
P407language of work or nameEnglishQ1860
P304page(s)e0135600
P577publication date2015-01-01
P1433published inPLOS OneQ564954
P1476titleQuantifying Stock Return Distributions in Financial Markets
P478volume10

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cites work (P2860)
Q64971409Anomaly detection in Bitcoin market via price return analysis.
Q64980337Asymmetric impact of oil prices on stock returns in Shanghai stock exchange: Evidence from asymmetric ARDL model.
Q47560804Equation-based model for the stock market
Q47147058Evolutionary dynamics of the cryptocurrency market.
Q47158815Fluctuation-driven price dynamics and investment strategies
Q28603764Quantifying the Search Behaviour of Different Demographics Using Google Correlate
Q47120714Range-based volatility, expected stock returns, and the low volatility anomaly.