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SEBRASouthern Extreme Bull Riding Association (Archdale, NC)
SEBRASystem for Etterbehandling av Rapporter
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In the original SEBRA model, the probability of bankruptcy is modelled mainly using key figures for an enterprise's earnings, financial strength and liquidity, see Eklund et al.
Long experience of the use of the SEBRA model has meant that we have discovered various weaknesses in it.
The original SEBRA model's accuracy rate for bankruptcy at enterprise level has generally been high and stable over time.
The original SEBRA model includes explanatory variables which are either directly or indirectly related to an enterprise's size.
Examples of variables in the SEBRA model which are directly or indirectly related to an enterprise's size include total assets, trade accounts payable, and government taxes payable relative to total assets.
The original SEBRA model largely captures the surge in banks' recorded loan losses during the banking crisis of the early 1990s.
The disadvantage of the SEBRA model is that new information comes in only once a year and that there is a time lag of nine months between the end of the financial year and the time most accounts are available in the database.
The SEBRA model predictions are compared with the predictions of the KMV Private Firm model because there are so few listed enterprises in Norway that it is not meaningful to make a comparison with the KMV Public Firm model.
We have not tested SEBRA's predictions against this model since one important purpose of the test is to compare SEBRA with a market-based credit risk model.
One important difference between SEBRA and KMV is that SEBRA predicts the probability of bankruptcy during the next three financial years (4) while KMV predicts the probability of default during the next 12 months.
With the SEBRA model, the bankruptcy probability is low for a very large portion of the enterprises.
Whereas SEBRA bases its predictions on data from the company accounts, the KMV model uses data from the consolidated accounts.