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Grant: Discovery Grants Program - Individual

York University

$16,000.00

Mathematical Challenges in Financial Risk Analysis

EF 2018-19

Résumé
My research project consists of the conception of various risks, the measurement, the analysis, and the management of financial risks under unexpected circumstances. Mathematical modeling, analyzing, computing (simulations) approaches are required to solve the exciting and challenging research problems proposed in the application. *In the current generation of data-rich environment, high-frequency trading algorithms and advanced learning techniques in financial markets become important issues. As a relatively new phenomenon, much of the discussion is not backed by solid academic research. They operate and improve market quality in usual times, but may stop operating and thus cause the prices to disappear (or clearly unreasonable traded prices) in extreme circumstances. Market stability also relates to the issue of liquidity risk in financial markets. At the time of stress, the high-frequency trading stops providing liquidity and becomes the demander of liquidity, the provision of liquidity seriously deteriorates, which can cause substantial volatility. This is explained by the fact that market participants react to immediate information, in other words, that noise creates noise. *Both the models and the people who use them are lacking the ability to articulate the risk of the underlying and that related to the actual market. Models become more sophisticated, but the same logic has persisted. Today, it is crucial to develop new tools (and train professionals) for risk analysis, by reworking on the determination of the exposure to risk. It is more important than ever to explore new research approaches for facing current challenges, and this proposal reflects a big part of this new trend.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
RGPIN-2018-05880
Name nom
Ku, Hyejin
Department département
Mathematics and Statistics
Organization id
38
Institution établissement
York University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2018
Competition year année de concours
2018
Award amount
16000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1508
Committee name en
Mathematics and Statistics
Committee name fr
Mathématiques et statistique
Area of application code
1205
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Mathematical sciences
Area of application fr
Sciences mathématiques
Research subject code
2960
Research subject group en
Applied mathematics
Research subject group fr
Mathématiques appliquées
Research subject en
Mathematical modelling
Research subject fr
Modélisation mathématique
Partie
1
Nb partie
5
Application title
Mathematical Challenges in Financial Risk Analysis
Keyword
NSERC
Application summary
My research project consists of the conception of various risks, the measurement, the analysis, and the management of financial risks under unexpected circumstances. Mathematical modeling, analyzing, computing (simulations) approaches are required to solve the exciting and challenging research problems proposed in the application. *In the current generation of data-rich environment, high-frequency trading algorithms and advanced learning techniques in financial markets become important issues. As a relatively new phenomenon, much of the discussion is not backed by solid academic research. They operate and improve market quality in usual times, but may stop operating and thus cause the prices to disappear (or clearly unreasonable traded prices) in extreme circumstances. Market stability also relates to the issue of liquidity risk in financial markets. At the time of stress, the high-frequency trading stops providing liquidity and becomes the demander of liquidity, the provision of liquidity seriously deteriorates, which can cause substantial volatility. This is explained by the fact that market participants react to immediate information, in other words, that noise creates noise. *Both the models and the people who use them are lacking the ability to articulate the risk of the underlying and that related to the actual market. Models become more sophisticated, but the same logic has persisted. Today, it is crucial to develop new tools (and train professionals) for risk analysis, by reworking on the determination of the exposure to risk. It is more important than ever to explore new research approaches for facing current challenges, and this proposal reflects a big part of this new trend.