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Erscheinungsjahr: 
1999
Schriftenreihe/Nr.: 
Research Notes No. 99-9
Verlag: 
Deutsche Bank Research, Frankfurt a. M.
Zusammenfassung: 
Many economic and econometric applications require the integration of functions lacking a closed form antiderivative, which is therefore a task that can only be solved by numerical methods. We propose a new family of probability densities that can be used as substitutes and have the property of closed form integrability. This is especially advantageous in cases where either the complexity of a problem makes numerical function evaluations very costly, or fast information extraction is required for time-varying environments. Our approach allows generally for nonparametric maximum likelihood density estimation and may thus find a variety of applications, two of which are illustrated briefly: Estimation of Value at Risk based on approximations to the density of stock returns; Recovering risk neutral densities for the valuation of options from the option price - strike price relation.
Schlagwörter: 
Option Pricing
Neural Networks
Nonparametric Density Estimation
JEL: 
C45
G13
C63
Dokumentart: 
Working Paper
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