| 000 | 01948nam a22003975i 4500 | ||
|---|---|---|---|
| 001 | 978-3-8349-6666-7 | ||
| 003 | DE-He213 | ||
| 005 | 20140220083820.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 110517s2011 gw | s |||| 0|eng d | ||
| 020 |
_a9783834966667 _9978-3-8349-6666-7 |
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| 024 | 7 |
_a10.1007/978-3-8349-6666-7 _2doi |
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| 050 | 4 | _aHD30.23 | |
| 072 | 7 |
_aKJT _2bicssc |
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| 072 | 7 |
_aKJMD _2bicssc |
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| 072 | 7 |
_aBUS049000 _2bisacsh |
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| 082 | 0 | 4 |
_a658.40301 _223 |
| 100 | 1 |
_aSchläfer, Timo. _eauthor. |
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| 245 | 1 | 0 |
_aRecovery Risk in Credit Default Swap Premia _h[electronic resource] / _cby Timo Schläfer. |
| 264 | 1 |
_aWiesbaden : _bGabler, _c2011. |
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| 300 |
_aXIX, 112p. 21 illus. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 520 | _aThe finance literature looks at a number of factors to explain risk premia in corporate debt, such as liquidity effects, jump-to-default risk, and contagion risk. Stochastic recovery rates as a source of systematic risk have not received much attention so far, most likely due to the difficulties around decomposing the expected loss. Timo Schläfer exploits the fact that differently-ranking debt instruments of the same issuer face identical default risk but different default-conditional recovery rates. He shows that this allows isolating recovery risk without any of the rigid assumptions employed by priors and implements his approach using credit default swap data. | ||
| 650 | 0 | _aEconomics. | |
| 650 | 1 | 4 | _aEconomics/Management Science. |
| 650 | 2 | 4 | _aOperations Research/Decision Theory. |
| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer eBooks | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783834928443 |
| 856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-8349-6666-7 |
| 912 | _aZDB-2-SBE | ||
| 999 |
_c108774 _d108774 |
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