Stochastic dynamic models for foreclosed housing acquisition and redevelopment

Armagan Bayram; Senay Solak; Michael Johnson; David Turcotte

Stochastic dynamic models for foreclosed housing acquisition and redevelopment

Armagan Bayram
, Senay Solak
, Michael Johnson
, David Turcotte

Public Policy & Public Affairs

University of Massachusetts
University of Massachusetts Boston

Research output: Contribution to conference › Paper › peer-review

Abstract

Over the past three years, increased rates of mortgage foreclosures in the U.S. have had devastating impacts on individuals, communities, organizations and government. In the nonprofit sector, community development corporations (CDCs) are key actors in foreclosure prevention. This paper develops dynamic and stochastic programming models to assist community-based organizations in choosing foreclosed properties for acquisition and redevelopment, taking into account uncertain market conditions that change over time. We analytically study a dynamic programming model under certain dominance relationships and characterize the optimal property acquisition policy. We then seek insights for the general stochastic model through a multistage stochastic programming formulation and its numerical analysis.

Original language	English
State	Published - 2011
Event	61st Annual Conference and Expo of the Institute of Industrial Engineers - Reno, NV, United States Duration: May 21 2011 → May 25 2011

Conference

Conference	61st Annual Conference and Expo of the Institute of Industrial Engineers
Country/Territory	United States
City	Reno, NV
Period	5/21/11 → 5/25/11

ASJC Scopus Subject Areas

Industrial and Manufacturing Engineering

Keywords

Dynamic programming
Foreclosure
Portfolio management
Resource allocation
Stochastic programming

Cite this

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title = "Stochastic dynamic models for foreclosed housing acquisition and redevelopment",

abstract = "Over the past three years, increased rates of mortgage foreclosures in the U.S. have had devastating impacts on individuals, communities, organizations and government. In the nonprofit sector, community development corporations (CDCs) are key actors in foreclosure prevention. This paper develops dynamic and stochastic programming models to assist community-based organizations in choosing foreclosed properties for acquisition and redevelopment, taking into account uncertain market conditions that change over time. We analytically study a dynamic programming model under certain dominance relationships and characterize the optimal property acquisition policy. We then seek insights for the general stochastic model through a multistage stochastic programming formulation and its numerical analysis.",

keywords = "Dynamic programming, Foreclosure, Portfolio management, Resource allocation, Stochastic programming",

author = "Armagan Bayram and Senay Solak and Michael Johnson and David Turcotte",

year = "2011",

language = "English",

note = "61st Annual Conference and Expo of the Institute of Industrial Engineers ; Conference date: 21-05-2011 Through 25-05-2011",

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TY - CONF

T1 - Stochastic dynamic models for foreclosed housing acquisition and redevelopment

AU - Bayram, Armagan

AU - Solak, Senay

AU - Johnson, Michael

AU - Turcotte, David

PY - 2011

Y1 - 2011

N2 - Over the past three years, increased rates of mortgage foreclosures in the U.S. have had devastating impacts on individuals, communities, organizations and government. In the nonprofit sector, community development corporations (CDCs) are key actors in foreclosure prevention. This paper develops dynamic and stochastic programming models to assist community-based organizations in choosing foreclosed properties for acquisition and redevelopment, taking into account uncertain market conditions that change over time. We analytically study a dynamic programming model under certain dominance relationships and characterize the optimal property acquisition policy. We then seek insights for the general stochastic model through a multistage stochastic programming formulation and its numerical analysis.

AB - Over the past three years, increased rates of mortgage foreclosures in the U.S. have had devastating impacts on individuals, communities, organizations and government. In the nonprofit sector, community development corporations (CDCs) are key actors in foreclosure prevention. This paper develops dynamic and stochastic programming models to assist community-based organizations in choosing foreclosed properties for acquisition and redevelopment, taking into account uncertain market conditions that change over time. We analytically study a dynamic programming model under certain dominance relationships and characterize the optimal property acquisition policy. We then seek insights for the general stochastic model through a multistage stochastic programming formulation and its numerical analysis.

KW - Dynamic programming

KW - Foreclosure

KW - Portfolio management

KW - Resource allocation

KW - Stochastic programming

UR - https://www.scopus.com/pages/publications/84900304892

UR - https://www.scopus.com/pages/publications/84900304892#tab=citedBy

M3 - Paper

AN - SCOPUS:84900304892

T2 - 61st Annual Conference and Expo of the Institute of Industrial Engineers

Y2 - 21 May 2011 through 25 May 2011

ER -

Stochastic dynamic models for foreclosed housing acquisition and redevelopment

Abstract

Conference

ASJC Scopus Subject Areas

Keywords

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Cite this