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bigdatafinance.euBigDataFinance 2015–2019, a H2020 Marie Sklodowska-Curie Innovative Training Network “Training for Big Data in Financial Research and Risk Management”, provides doctoral training in sophisticated data-driven risk management and research at the crossroads of Finance and Big Data for 13 researchers.
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Blog arkistot - BigDataFinance Skip to content Menu Home People Projects Research Publications Beneficiaries & Partners Events BigDataFinancePrimingTraining Event on Textual Data in Finance Data Science in Finance High-Frequency Data Econometrics Winter School onRamifiednetworks in finance Blog Contact Blog BigData wringer of financial interconnectedness: the new rencontre to prevent spoliation 15.01.2018 The pursuit blog vendible is based on the opening statements delivered by Chiara Perillo at the panel discussion on “New Conditions for Monetary and Fiscal Policy” with Martin F. Hellwig, Edward C. Prescott, Peter A. Diamond, Christopher A. Sims, 6th Lindau Nobel Laureate Meeting on Economic Sciences, Lindau, August 2017. The last decades have witnessed […] The Order Book: ARencontreFor Tomorrow’s Econometrics 26.11.2017 The modeling of the order typesetting is certainly one of the major chal- lenges for the trendy econometrics. The unvarying and fast grow on a world-level of the electronic platforms and the associated increasing number of traders, led to a market of lattermost complexity. The traditional trading based on human traders has been rapidly substituted […] A unenduring introduction to Big Data and Signal Processing 13.11.2017 The upturned nature of financial big datasets requires in depth wringer of their properties. These properties vary from past information and signal filtering to statistical inference and arbitrage identification. There are some unstipulated approaches that one should take into consideration when dealing with big chunks of data. To capitalize on the Big Data, information has […] Ubiquitous Scaling Laws and Irrelevant Time 19.07.2017 “Who owns the information, he owns the world”. This phrase became famous in 1815 when Rothschild family managed to earn well-nigh 3 billion British Pounds and became the owners of a large part of the British economy in one day, simply by having a bit increasingly information well-nigh results of the famous Waterloo wrestle than […] AUnenduringDiscussionWell-nighUtilizing High-Frequency News Data In Finance 10.07.2017 In the last two decades a lot of endeavors have been made to develop tools in analyzing high-frequency financial data (e.g., transactions and quotes, or TAQ data). The outcome include a series of econometric models which enable us to unriddle microstructure of the market, to estimate and forecast volatility on a high-frequency basis, to scrutinize […]RamifiedNetworks in Financial Markets 31.05.2017 In most natural and engineered systems, a set of entities interact with each other in complicated patterns that can involve multiple types of relationships, transpiration in time and include multiple layers of connectivity. In order to proceeds understanding in such ramified systems it is important to consider such features. A network simply put, is a […] An introduction to BigData in Finance: the econometric point of view 13.04.2017 Ultra-high-frequency data are probably the perfect representative for the financial markets of the outstart of BigData. It is well known that over the last decade the availability of high-frequency data has rapidly disrupted the financial industry as we knew it. What might be less known is the impact from an econometric point of view. In […] Blog introduction 11.04.2017 People in modern societies are leaving overdue a vast value of data that can be analysed and venal in new and unprecedented ways to understand and model financial markets for largest risk management. These data sets of high-volume, high-velocity, and high-variety information, directly relevant to the financial sector, upspring from various sources. The sources include […] Popular tags algorithms deject priming corporate ownership data econometric models ESR extracted knowledge finance financial slipperiness financial markets financial volatility job recruitment research risk management self-data velocity volatility volume Copyright BigDataFinance 2017 | All rights reserved | Login WordPress Download Manager - Best Download Management Plugin Close