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Evaluating credit risk exposure in a...

Zech, Lyubov.

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Evaluating credit risk exposure in agriculture.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Evaluating credit risk exposure in agriculture./
Author:	Zech, Lyubov.
Description:	188 p.
Notes:	Source: Dissertation Abstracts International, Volume: 64-11, Section: A, page: 4143.
Contained By:	Dissertation Abstracts International64-11A.
Subject:	Economics, Agricultural. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3113222

Evaluating credit risk exposure in agriculture.
Zech, Lyubov.

Evaluating credit risk exposure in agriculture. - 188 p.

Source: Dissertation Abstracts International, Volume: 64-11, Section: A, page: 4143.

Thesis (Ph.D.)--University of Minnesota, 2003.

The thesis adapts loan portfolio management tools to agricultural lending and provides guidance on appropriate capital allocation and portfolio management using the tools.Subjects--Topical Terms:

626648
Economics, Agricultural.

Evaluating credit risk exposure in agriculture.
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035 $a (UnM)AAI3113222
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100 1 $a Zech, Lyubov. $3 1949604
245 1 0 $a Evaluating credit risk exposure in agriculture.
300 $a 188 p.
500 $a Source: Dissertation Abstracts International, Volume: 64-11, Section: A, page: 4143.
500 $a Adviser: Glenn Darwin Pederson.
502 $a Thesis (Ph.D.)--University of Minnesota, 2003.
520 $a The thesis adapts loan portfolio management tools to agricultural lending and provides guidance on appropriate capital allocation and portfolio management using the tools.
520 $a A framework is identified for modeling credit risk in agriculture. The components and methodologies of major credit risk models in commercial lending are analyzed in relationship to credit risk in agricultural lending. A CreditRisk+ type model is deemed most suitable for agricultural lending, since the data requirements of that model can be satisfied by the available data and the assumptions are appropriate for modeling credit risk in agriculture. The CreditRisk+ model is modified to overcome its drawbacks by incorporating recent research that accounts for sector correlations and uses a more stable and accurate algorithm.
520 $a The model is applied to AgStar Financial Services, ACA, a cooperative agricultural lender, in order to determine how such a lender may adapt this model for portfolio risk analysis and to make capital and portfolio management decisions. AgStar data and Farm Credit System regulatory guidelines are used to determine model parameters, such as exposures, probabilities of default and their volatilities, recovery rates in the event of default, and correlations between industry types. The model generates a loan loss distribution, which is used to derive the lender's expected and unexpected losses for the overall portfolio and individual loans.
520 $a The study shows how model results can be used for the following purposes: evaluating loan portfolio capital adequacy for both the allowance for loan loss and capital; identifying the allowance for loan loss and economic capital requirements for each portfolio segment (by industry/loan type/risk rating/etc.) to analyze loan concentration risk and set credit limits; monitoring loan concentrations and loan portfolio risk over time; studying the effect of changes in the loan portfolio composition on allowance and capital requirements; stress-testing the loan portfolio; and analyzing risk-adjusted profitability.
520 $a The model shows that AgStar is more than adequately capitalized based on the parameters estimated using 1997--2002 data. AgStar's capital position is lower than that of most other FCS associations. This raises the issue of overcapitalization within the Farm Credit System.
590 $a School code: 0130.
650 4 $a Economics, Agricultural. $3 626648
650 4 $a Economics, Finance. $3 626650
690 $a 0503
690 $a 0508
710 2 0 $a University of Minnesota. $3 676231
773 0 $t Dissertation Abstracts International $g 64-11A.
790 1 0 $a Pederson, Glenn Darwin, $e advisor
790 $a 0130
791 $a Ph.D.
792 $a 2003
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3113222