Project acronym CHANGE-POINT TESTS
Project New Results on Structural Change Tests: Theory and Applications
Researcher (PI) Elena Andreou
Host Institution (HI) UNIVERSITY OF CYPRUS
Call Details Starting Grant (StG), SH1, ERC-2007-StG
Summary The research project has two broad objectives and provides novel results in the literature of structural change or change-point tests. The first objective is to provide two new methods for restoring the non-monotone power problem of a large family of structural breaks tests that have been widely used in econometrics and statistics, as well as to show that these methods have additional contributions and can be extended to: (i) tests for a change in persistence, (ii) partial sums tests of cointegration and (iii) tests for changes in dynamic volatility models. The significance of these methods is demonstrated via the consistency of the long-run variance estimator which scales the change-point statistics, the asymptotic properties of the tests, their finite sample performance and their relevance in empirical applications and policy analysis. The second objective is threefold: First, to show that ignoring structural changes in financial time series yields biased and inconsistent risk management (Value at Risk, VaR and Excess Shortfall, ES) estimates and consequently leads to investment misallocations. Second, to propose methods for evaluating the stability of financial time series sequentially or on-line which can be used as a quality control procedure for financial risk management as well as to show that monitoring implied volatilities yields early warning indicators of a changing risk structure. Moreover we show that model averaging in the presence of structural breaks as well as other model uncertainties involved in risk management estimates, can provide robust estimates of VaR and ES. New results are derived on the optimal weights for model averaging in the context of dynamic volatility models and asymmetric loss functions. Third, we propose a novel way to construct prediction-based change-point statistics that reduce the detection delay of existing sequential tests and provide a probability about the likelihood of a structural change.
Summary
The research project has two broad objectives and provides novel results in the literature of structural change or change-point tests. The first objective is to provide two new methods for restoring the non-monotone power problem of a large family of structural breaks tests that have been widely used in econometrics and statistics, as well as to show that these methods have additional contributions and can be extended to: (i) tests for a change in persistence, (ii) partial sums tests of cointegration and (iii) tests for changes in dynamic volatility models. The significance of these methods is demonstrated via the consistency of the long-run variance estimator which scales the change-point statistics, the asymptotic properties of the tests, their finite sample performance and their relevance in empirical applications and policy analysis. The second objective is threefold: First, to show that ignoring structural changes in financial time series yields biased and inconsistent risk management (Value at Risk, VaR and Excess Shortfall, ES) estimates and consequently leads to investment misallocations. Second, to propose methods for evaluating the stability of financial time series sequentially or on-line which can be used as a quality control procedure for financial risk management as well as to show that monitoring implied volatilities yields early warning indicators of a changing risk structure. Moreover we show that model averaging in the presence of structural breaks as well as other model uncertainties involved in risk management estimates, can provide robust estimates of VaR and ES. New results are derived on the optimal weights for model averaging in the context of dynamic volatility models and asymmetric loss functions. Third, we propose a novel way to construct prediction-based change-point statistics that reduce the detection delay of existing sequential tests and provide a probability about the likelihood of a structural change.
Max ERC Funding
517 200 €
Duration
Start date: 2008-09-01, End date: 2013-08-31
Project acronym OSSMA
Project Multiple Systems of Spatial Memory: Their role in Reasoning and Action
Researcher (PI) Marios Avraamides
Host Institution (HI) UNIVERSITY OF CYPRUS
Call Details Starting Grant (StG), SH3, ERC-2007-StG
Summary The goal of the proposed project is to examine how the locations of the objects that constitute our environments are represented in memory and how such memories are used to support our actions in space. During the last three decades of research this topic has received a lot of attention by scientists from many disciplines, and over the years a number of theories have been formulated. However, our understanding of the nature and functioning of spatial memory still continues to change. More importantly, there exist empirical findings from two concentrations of research within spatial cognition that seem conflicting at first glance. On one hand, studies examining the organizational structure of spatial memory have shown that memories are encoded using allocentric reference frames; that is reference frames that encode the spatial relations among the objects of an environment. On the other hand, studies focusing on how people stay oriented towards their surroundings during locomotion suggest that egocentric representations (i.e., representations coding self-to-object relations) are involved. Recent models of spatial cognition have attempted to reconcile these findings by proposing multiple systems for spatial memory. In this project we will carry our a series of experiments in an attempt to gather empirical data to test the predictions of various theoretical models including a biologically-plausible two-system account of spatial memory that we have recently proposed (Avraamides & Kelly, in press). Drawing heavily from the literature on Stimulus-Response compatibility, this account combines the use of egocentric and allocentric representations to account for a wealth of data from all areas of spatial cognition.
Summary
The goal of the proposed project is to examine how the locations of the objects that constitute our environments are represented in memory and how such memories are used to support our actions in space. During the last three decades of research this topic has received a lot of attention by scientists from many disciplines, and over the years a number of theories have been formulated. However, our understanding of the nature and functioning of spatial memory still continues to change. More importantly, there exist empirical findings from two concentrations of research within spatial cognition that seem conflicting at first glance. On one hand, studies examining the organizational structure of spatial memory have shown that memories are encoded using allocentric reference frames; that is reference frames that encode the spatial relations among the objects of an environment. On the other hand, studies focusing on how people stay oriented towards their surroundings during locomotion suggest that egocentric representations (i.e., representations coding self-to-object relations) are involved. Recent models of spatial cognition have attempted to reconcile these findings by proposing multiple systems for spatial memory. In this project we will carry our a series of experiments in an attempt to gather empirical data to test the predictions of various theoretical models including a biologically-plausible two-system account of spatial memory that we have recently proposed (Avraamides & Kelly, in press). Drawing heavily from the literature on Stimulus-Response compatibility, this account combines the use of egocentric and allocentric representations to account for a wealth of data from all areas of spatial cognition.
Max ERC Funding
500 000 €
Duration
Start date: 2008-10-01, End date: 2013-06-30
Project acronym ReEngineeringCancer
Project Re-engineering the tumor microenvironment to alleviate mechanical stresses and improve chemotherapy
Researcher (PI) Triantafyllos Stylianopoulos
Host Institution (HI) UNIVERSITY OF CYPRUS
Call Details Starting Grant (StG), PE8, ERC-2013-StG
Summary Current chemotherapeutic agents are potent enough to kill cancer cells. Nonetheless, failure of chemotherapies for many cancers (e.g. breast and pancreatic cancers and various sarcomas) is primarily because these agents cannot reach cancer cells in amounts sufficient to cause complete cure. The abnormal microenvironment of these tumors drastically reduces perfusion and results in insufficient delivery of therapeutic agents. Tumor structural abnormalities is in large part an effect of mechanical stresses developed within the tumor due to unchecked cancer cell proliferation that strains the tumor microenvironment. Alleviation of these stresses has the potential to normalize the tumor, enhance delivery of drugs and improve treatment efficacy. Here, I propose to test the hypothesis that re-engineering the tumor microenvironment with stress-alleviating drugs has the potential to enhance chemotherapy. To explore this hypothesis, I will make use of a mixture of cutting-edge computational and experimental techniques. I will develop sophisticated models for the biomechanical response of tumors to analyze how stresses are generated and transmitted during tumor progression. Subsequently, I will perform animal studies to validate model predictions and indentify the drug that more effectively alleviates stress levels, normalizes the tumor microenvironment and improves chemotherapy. Successful completion of this research will reveal the mechanisms for stress generation and storage in tumors and will lead to new strategies for the use of chemotherapy.
Summary
Current chemotherapeutic agents are potent enough to kill cancer cells. Nonetheless, failure of chemotherapies for many cancers (e.g. breast and pancreatic cancers and various sarcomas) is primarily because these agents cannot reach cancer cells in amounts sufficient to cause complete cure. The abnormal microenvironment of these tumors drastically reduces perfusion and results in insufficient delivery of therapeutic agents. Tumor structural abnormalities is in large part an effect of mechanical stresses developed within the tumor due to unchecked cancer cell proliferation that strains the tumor microenvironment. Alleviation of these stresses has the potential to normalize the tumor, enhance delivery of drugs and improve treatment efficacy. Here, I propose to test the hypothesis that re-engineering the tumor microenvironment with stress-alleviating drugs has the potential to enhance chemotherapy. To explore this hypothesis, I will make use of a mixture of cutting-edge computational and experimental techniques. I will develop sophisticated models for the biomechanical response of tumors to analyze how stresses are generated and transmitted during tumor progression. Subsequently, I will perform animal studies to validate model predictions and indentify the drug that more effectively alleviates stress levels, normalizes the tumor microenvironment and improves chemotherapy. Successful completion of this research will reveal the mechanisms for stress generation and storage in tumors and will lead to new strategies for the use of chemotherapy.
Max ERC Funding
1 440 360 €
Duration
Start date: 2014-01-01, End date: 2018-12-31
