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Rediscovering Price Discovery

Authors: Lautier, Delphine; Ling, Julien; Villeneuve, Bertrand;

Rediscovering Price Discovery

Abstract

17th FINANCIAL RISKS INTERNATIONAL FORUM "Big Data & Algorithmic Finance"The Institut Louis Bachelier, in cooperation with the Fondation du Risque, the Europlace Institute of Finance and the Louis Bachelier "Finance and Sustainable Growth" Laboratory, is pleased to invite you to the 17th Financial Risks International Forum.This year’s forum will focus on the theme:“Big Data and Algorithmic Finance”The last 40 years have seen huge innovations in computing technology and data availability. Data derived from millions of administrative records or using new methods of data generation such as text mining are now widespread. Banks, insurance and investors are using an increasing amount of data to understand consumers’ or firms’ behavior, and design investment or trading strategies. Algorithms start to be major players in many areas, and regulations, which were mostly designed for humans, need to adapt to this new environment.This upcoming 17th Financial Risks International Forum aims to discuss the challenges posed by the use of big data and algorithmic finance. “Rediscovering Price Discovery” Julien LING, Collège de France and Renmin University of China, Delphine Lautier, and Bertrand Villeneuve, Université Paris Dauphine-PSL.

Country
France
Keywords

Event Studies, Insider Trading, C.C1.C13, 330, G.G1.G14, Dynamic Treatment Effect Models, Economie financière, 332, State Space Models, C.C3.C32, Dynamic Quantile Regressions, Diffusion Processes, Impulse Reponse Functions, C - Mathematical and Quantitative Methods::C3 - Multiple or Simultaneous Equation Models, Price discovery, C - Mathematical and Quantitative Methods::C1 - Econometric and Statistical Methods and Methodology: General::C13 - Estimation: General, VECM, G - Financial Economics::G1 - General Financial Markets::G14 - Information and Market Efficiency, SMA, Information shares, [SHS.GESTION] Humanities and Social Sciences/Business administration, Cholesky decomposition, Multiple Variables::C32 - Time-Series Models

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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