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A Quantitative Analysis of Bank Fail...
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Mgboji, Emmanuel U.
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A Quantitative Analysis of Bank Failures in the United States: Predicting the Duration and Culmination of Financial Crisis.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
A Quantitative Analysis of Bank Failures in the United States: Predicting the Duration and Culmination of Financial Crisis./
作者:
Mgboji, Emmanuel U.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:
221 p.
附註:
Source: Dissertation Abstracts International, Volume: 80-08(E), Section: A.
Contained By:
Dissertation Abstracts International80-08A(E).
標題:
Finance. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13806888
ISBN:
9781392007952
A Quantitative Analysis of Bank Failures in the United States: Predicting the Duration and Culmination of Financial Crisis.
Mgboji, Emmanuel U.
A Quantitative Analysis of Bank Failures in the United States: Predicting the Duration and Culmination of Financial Crisis.
- Ann Arbor : ProQuest Dissertations & Theses, 2019 - 221 p.
Source: Dissertation Abstracts International, Volume: 80-08(E), Section: A.
Thesis (Ph.D.)--Northcentral University, 2019.
Federal and State legislators formulate laws to promote the safety and soundness of financial institutions and to maintain public confidence in the banking system. Predicting tools that could determine ways to minimize financial crises such as the 2007--2009 crisis could be beneficial to the national economy. Whereas financial experts and bank executives attribute the incidence of bank failures to inappropriate banking regulation and erratic interest rate movements, it is not proven whether regulatory reforms, frequency of bank examinations, or the direction of interest rates could actually predict bank failure rates. The purpose of this study was to determine the degree to which two economic variables, bank examinations (measured by bank liquidity position) and interest rate movements (measured by term spread of interest rates), could be used to predict bank distress, which could then be used to predict the eventual bank failures (measured by GDP growth) and how long and systemic they can last. Data for the study was collected from the FFIEC and the U.S. Bureau of Economic Analysis (BEA) for the period of 1984 to 2017. The dataset for the whole period and for each of the three financial crisis periods was evaluated using the autoregression distributive lag (ARDL) and vector autoregression (VAR) models. The study indicated a statistically significant relationship between two components of the banking industry, bank liquidity position and term spread of interest rates, that could be used to predict when a financial crisis might begin and end. This study determined that before the three financial crises, bank liquidity position increased significantly, peaked, and then decreased throughout the crisis periods. For the periods evaluated, bank liquidity position reached an average maximum of 17.3 months before the end of each crisis. The term spread of interest rates quickly turned negative but began to rise during the crises on the average of 1.21% and about 11.3 months before to the end of the crisis.
ISBN: 9781392007952Subjects--Topical Terms:
542899
Finance.
A Quantitative Analysis of Bank Failures in the United States: Predicting the Duration and Culmination of Financial Crisis.
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Federal and State legislators formulate laws to promote the safety and soundness of financial institutions and to maintain public confidence in the banking system. Predicting tools that could determine ways to minimize financial crises such as the 2007--2009 crisis could be beneficial to the national economy. Whereas financial experts and bank executives attribute the incidence of bank failures to inappropriate banking regulation and erratic interest rate movements, it is not proven whether regulatory reforms, frequency of bank examinations, or the direction of interest rates could actually predict bank failure rates. The purpose of this study was to determine the degree to which two economic variables, bank examinations (measured by bank liquidity position) and interest rate movements (measured by term spread of interest rates), could be used to predict bank distress, which could then be used to predict the eventual bank failures (measured by GDP growth) and how long and systemic they can last. Data for the study was collected from the FFIEC and the U.S. Bureau of Economic Analysis (BEA) for the period of 1984 to 2017. The dataset for the whole period and for each of the three financial crisis periods was evaluated using the autoregression distributive lag (ARDL) and vector autoregression (VAR) models. The study indicated a statistically significant relationship between two components of the banking industry, bank liquidity position and term spread of interest rates, that could be used to predict when a financial crisis might begin and end. This study determined that before the three financial crises, bank liquidity position increased significantly, peaked, and then decreased throughout the crisis periods. For the periods evaluated, bank liquidity position reached an average maximum of 17.3 months before the end of each crisis. The term spread of interest rates quickly turned negative but began to rise during the crises on the average of 1.21% and about 11.3 months before to the end of the crisis.
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