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Grant: Discovery Grants Program - Individual

HEC Montréal

$26,000.00

Stochastic dynamic programming for modelling and solving extended multivariate structural models

FY 2020-21

Summary
The aim of this research program is threefold. First, we propose to design a set of stochastic dynamic programs for modelling structural settings with multiple public companies. Each firm assumes an extended balance-sheet structure with 1- an arbitrary corporate-debt portfolio, 2- multiple seniority classes, 3- options embedded in corporate bonds, 4- tax benefits, 5- bankruptcy costs, and 6- a reorganization process. Next, we propose to solve and implement our stochastic dynamic programs in the most efficient way. This step results in the valuation of the above-mentioned corporate securities. The model-estimation step, based on approximate- and pseudo-maximum likelihood, is subject to the success of an IVADO grant application (University of Montreal). The funding decision is in November 2017. The modelling, valuation, and estimation steps result in operational and realistic structural models. The last part of this research program consists of a numerical and empirical investigation of North American public companies. Given the finding of Leboeuf and Pinnington (2017) (Bank of Canada) that Canadian firms are becoming riskier, a comparative credit-risk study of Canadian firms and their associated American firms is planned in the presence of contagion effects. A corporate default results in a loss of value for the firm's claimholders and a loss of positions for the firm's workers. Corporate credit-risk models are thus useful for market participants in that they help preclude financial distress and its adverse events. This research program is innovative for it considers 1- an extended balance-sheet structure with multiple tangible/intangible corporate securities and a reorganisation process, 2- efficient stochastic dynamic programs under various multivariate Markov-Lévy processes, and 3- an empirical and numerical credit-risk investigation on Canadian public companies. Designing, solving, and implementing our efficient stochastic dynamic programs is discussed depending on the number of public companies underlying the structural framework with a special focus on intermediate-dimensional state spaces. Approximate- and neuro-dynamic programming are used. The expected benefits consist essentially of a set of publications in solid academic journals of the JCR database. The credit-risk investigation of Canadian public companies will be the subject of a scientific meeting that will bring together scholars, academics, and professionals to discuss this issue.
Program
Discovery Grants Program - Individual
Recipient
Location
Quebec, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
RGPIN-2018-04432
Name nom
Ben-Ameur, Hatem
Department département
Sciences de décision
Organization id
65
Institution établissement
HEC Montréal
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2020
Competition year année de concours
2018
Award amount
26000
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
1509
Committee name en
Civil, Industrial and Systems Engineering
Committee name fr
Génie civil, industriel et des systèmes
Area of application code
1206
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Engineering
Area of application fr
Génie
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
Installment
inst:3-5
Partie
3
Nb partie
5
Application title
Stochastic dynamic programming for modelling and solving extended multivariate structural models
Keyword
NSERC
Application summary
The aim of this research program is threefold. First, we propose to design a set of stochastic dynamic programs for modelling structural settings with multiple public companies. Each firm assumes an extended balance-sheet structure with 1- an arbitrary corporate-debt portfolio, 2- multiple seniority classes, 3- options embedded in corporate bonds, 4- tax benefits, 5- bankruptcy costs, and 6- a reorganization process. Next, we propose to solve and implement our stochastic dynamic programs in the most efficient way. This step results in the valuation of the above-mentioned corporate securities. The model-estimation step, based on approximate- and pseudo-maximum likelihood, is subject to the success of an IVADO grant application (University of Montreal). The funding decision is in November 2017. The modelling, valuation, and estimation steps result in operational and realistic structural models. The last part of this research program consists of a numerical and empirical investigation of North American public companies. Given the finding of Leboeuf and Pinnington (2017) (Bank of Canada) that Canadian firms are becoming riskier, a comparative credit-risk study of Canadian firms and their associated American firms is planned in the presence of contagion effects. A corporate default results in a loss of value for the firm's claimholders and a loss of positions for the firm's workers. Corporate credit-risk models are thus useful for market participants in that they help preclude financial distress and its adverse events. This research program is innovative for it considers 1- an extended balance-sheet structure with multiple tangible/intangible corporate securities and a reorganisation process, 2- efficient stochastic dynamic programs under various multivariate Markov-Lévy processes, and 3- an empirical and numerical credit-risk investigation on Canadian public companies. Designing, solving, and implementing our efficient stochastic dynamic programs is discussed depending on the number of public companies underlying the structural framework with a special focus on intermediate-dimensional state spaces. Approximate- and neuro-dynamic programming are used. The expected benefits consist essentially of a set of publications in solid academic journals of the JCR database. The credit-risk investigation of Canadian public companies will be the subject of a scientific meeting that will bring together scholars, academics, and professionals to discuss this issue.