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Az arányos csődszabály karakterizációja körbetartozások esetén
[The characterization of the proportional rule in the case of circular liabilities]

Author

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  • Csóka, Péter

Abstract

Az arányos csődszabály első használata egészen Arisztotelészig vezethető vissza. A tanulmányban olyan pénzügyi hálózatokat vizsgálunk, ahol az ágenseknek van induló pénzkészlete, és mindenki tartozhat mindenkinek. Egy adott pénzügyi hálózatban a csődszabály meghatároz egy fizetési mátrixot, amelynek elemei megmondják, hogy ki mennyit fizessen a többi szereplőnek. Egy szereplő eszközei az induló pénzkészletéből és a többiektől kapott fizetésekből állnak. A rendszerkockázati irodalomban gyakran használt arányos csődszabály azt követeli meg, hogy az ágensek a tartozásaikkal arányosan fizessenek eszközeikből, maximum a tartozások erejéig. Ha érvényes az arányos csődszabály, akkor az eszközök értéke endogén módon határozódik meg, mivel a fizetések egymástól függhetnek. Cikkünkben részletesen bemutatjuk az arányos csődszabály egyik karakterizációját, olyan tulajdonságokat, amelyek közül mindegyiket csak ez a csődszabály teljesíti: a követelések felsőkorlát-jellegét, a korlátolt felelősséget, a hitelezők elsőbbségét, a pártatlanságot, az azonos ágensek általi manipulálhatatlanságot és a folytonosságot.* Journal of Economic Literature (JEL) kód: C71, G10.

Suggested Citation

  • Csóka, Péter, 2017. "Az arányos csődszabály karakterizációja körbetartozások esetén [The characterization of the proportional rule in the case of circular liabilities]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(9), pages 930-942.
  • Handle: RePEc:ksa:szemle:1719
    DOI: 10.18414/KSZ.2017.9.930
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    References listed on IDEAS

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    JEL classification:

    • C71 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Cooperative Games
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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