Posts from BigData

RP2: Divide and Conquer Deep Learning for Big Data in Finance (WP1)

  In the era of Finance Big Data, how can one conquer something so big and so vast? Management and learning in Finance Big Data should thus follow the holistic “Divide & Conquer” philosophy. We will develop a novel platform that supports all aspects of this philosophy, including workflow-based tools for content ingest and description, […]

03.11.2016 Read more

RP3: Deep Knowledge Extraction from Financial, Business, and Social Text (WP1)

This research project aims to transform unstructured textual content in multiple languages and formats into a structured form suitable for traditional analytic techniques in financial decision-making. The challenge is to extract semantically annotated facts in the form of relationships between concepts and entities mentioned in a stream of documents and social media. The task fits […]

03.11.2016 Read more

RP4: Complex Network Analysis in Stock Markets (WP2)

  The research project aims to study investor behaviour and the dynamics of corporate ownership, especially during financial crises via complex network analysis and big data techniques. The researcher will study in depth large financial data sets, including a unique dataset of complete trading records from all Finnish investors on publicly traded domestic stocks along […]

03.11.2016 Read more

RP5: Systemic Risk and Financial Networks (WP2)

This project seeks to analyse systemic risk from a network perspective, combining theoretical modelling, empirical  analysis, and practical (policy) applications. First, the project aims at contributing to the debate on fundamental questions such as: Is there a resilient architecture to the financial system? Should we put restrictions on institutions that are too big or too […]

03.11.2016 Read more

RP13: Machine Learning Algorithms for Risk Management in Trading Activities (WP4)

The main objective is to develop a prototype framework for pricing and risk management using machine learning  algorithms and a large variety of heterogeneous and high-volume data, including tick-by-tick quotes of bond prices, market data underlying economic indicators (such as interest rates, foreign exchange rates, inflation rates, and commodity prices) and news feeds. This predictive analytics […]

03.11.2016 Read more

Three positions available at TUT

CALL CLOSED Tampere University of Technology is the coordinator of the BigDataFinance Marie Skłodowska-Curie European Innovative Training Network. There are altogether 13 positions available for doctoral students, and currently we are seeking to fill 2 of those positions at Department of Industrial Management/Research Group on Financial Engineering and one at Department of Signal Processing. Tampere […]

23.10.2015 Read more

Project starts on the 1st of October

MSCA-ITN BigDataFinance project starts in October 2015! EU -project BigDataFinance (2015–2019) provides doctoral training and research in sophisticated data-driven risk management and research at the crossroads of Finance and Big Data for 13 researchers. The budget (EU’s contribution) is around 3,460,000 EUR. The main objectives are: i) to meet an increasing commercial demand for well-trained […]

22.10.2015 Read more