Project description
Non-causal time series models for speculative bubble prediction
Speculative bubbles in financial markets can result in dramatic damages to portfolio performances and threaten the stability of the financial system. Autoregressive and moving average processes known as non-causal time series models have proved their capacity to reproduce standardised facts from speculative bubbles such as locally explosive trajectories. On condition that their dynamics are better understood, they will allow the formulation of predictions on future bubble trajectories. However, understanding regarding the prediction of non-causal processes remains limited. The EU-funded NONCAUSALBubble project will focus on the lack of theoretical foundations for the forecasting of strong non-causal processes. The project will be based on recent developments of extreme value and alpha-stable distribution theories. Analytical assessment of crash probabilities will lead to an intuitive prediction model of bubble identification.
Objective
Speculative bubbles on financial markets, viewed as short-term explosive deviations of prices from a typical historical level and ending in an abrupt correction, have become common events across all major asset classes. They can have a dramatic impact on portfolio performances, financial institutions solvability and can compromise the stability of the financial system. Because of their ability to reproduce stylized facts from speculative bubbles such as locally explosive trajectories, noncausal time series models -autoregressive (AR) and moving average (MA) processes with roots located inside the unit circle- have been at the center of a recent fast-emerging literature in econometrics and finance. Provided their dynamics is better understood, they will enable to formulate forecasts of future bubble trajectories. If rapid progress is being achieved on estimation and fitting problematics, prediction theory of noncausal processes remains particularly scarce and limited to special elementary cases – mostly the univariate noncausal AR(1) with independent and identically distributed Cauchy errors.
The NONCAUSALBubble project aims at specifically addressing the lack of theoretical foundations for the forecasting of heavy-tailed noncausal processes. Building on recent tools from extreme value and alpha-stable distribution theories, NONCAUSALBubble will characterise the conditional distribution of future paths given the past observed trajectory during explosive episodes for 1) higher-order and 2) multivariate noncausal ARMA models. Closed-form formulations of the predictive distribution during bubble episodes will be derived alongside analytical quantification of the crash odds, and an intuitive prediction framework in terms of bubble pattern-recognition will be developed.
The project is hosted by VU Amsterdam, one of the top research groups in time series econometrics and forecasting.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-IF-2019
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
1081 HV Amsterdam
Netherlands
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.