Quality Indexes of Predictive Models in Risk and Portfolio Management
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F10%3A00043193" target="_blank" >RIV/00216224:14310/10:00043193 - isvavai.cz</a>
Výsledek na webu
—
DOI - Digital Object Identifier
—
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Quality Indexes of Predictive Models in Risk and Portfolio Management
Popis výsledku v původním jazyce
For a measurement of partial processes of a financial institution, especially their components like scoring models or other predictive models, it is possible to use quantitative indexes such as Gini index, K-S statistics, Lift and Information statistics.They can be used for comparison of several developed models at the moment of development. It is possible to use them for monitoring of quality of models after the deployment into real business as well. The outcome is then an effective tool to attract new creditworthy customers, and at the same time, control losses. This paper deals with definition of good/bad client, which is crucial for further computations. The main part is devoted to quality indexes based on distribution functions and on density functions. It brings some interesting results connected to Lift in general and for normally distributed data. An application on real data is included too.
Název v anglickém jazyce
Quality Indexes of Predictive Models in Risk and Portfolio Management
Popis výsledku anglicky
For a measurement of partial processes of a financial institution, especially their components like scoring models or other predictive models, it is possible to use quantitative indexes such as Gini index, K-S statistics, Lift and Information statistics.They can be used for comparison of several developed models at the moment of development. It is possible to use them for monitoring of quality of models after the deployment into real business as well. The outcome is then an effective tool to attract new creditworthy customers, and at the same time, control losses. This paper deals with definition of good/bad client, which is crucial for further computations. The main part is devoted to quality indexes based on distribution functions and on density functions. It brings some interesting results connected to Lift in general and for normally distributed data. An application on real data is included too.
Klasifikace
Druh
J<sub>x</sub> - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)
CEP obor
BB - Aplikovaná statistika, operační výzkum
OECD FORD obor
—
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2010
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
The Journal of Financial Decision Making
ISSN
1790-4870
e-ISSN
—
Svazek periodika
6
Číslo periodika v rámci svazku
1
Stát vydavatele periodika
GR - Řecká republika
Počet stran výsledku
11
Strana od-do
—
Kód UT WoS článku
—
EID výsledku v databázi Scopus
—