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Option pricing with model-guided nonparametric methods
Jianqing Fan
, Loriano Mancini
Operations Research & Financial Engineering
Bendheim Center for Finance
Center for Statistics & Machine Learning
Economics
Princeton Language and Intelligence (PLI)
Research output
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Contribution to journal
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Article
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peer-review
26
Scopus citations
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Dive into the research topics of 'Option pricing with model-guided nonparametric methods'. Together they form a unique fingerprint.
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Keyphrases
Option Pricing
100%
Nonparametric Methods
100%
Price Distribution
100%
Pricing Errors
100%
State Prices
100%
Model-guided
100%
Parametric Model
66%
Error Correction
66%
Automatic Correction
66%
Easy-to-implement
33%
Error Estimates
33%
Generalized Likelihood Ratio Test
33%
Systematic Bias
33%
Asset Price Dynamics
33%
Learning Approaches
33%
Predictive Ability
33%
Nonparametric Test
33%
State Price Density
33%
Nonparametric Learning
33%
Pricing Model
33%
Pricing Formulae
33%
Hedging Ability
33%
Option Pricing Model
33%
Derivative Financial Instruments
33%
Pricing Performance
33%
Parametric Option Pricing
33%
Pricing Derivatives
33%
S&P 500 Index Options
33%
Mathematics
Parametric
100%
Option Pricing
100%
Nonparametric Method
100%
Parametric Model
66%
Initial Estimate
33%
Error Estimate
33%
Generalized Likelihood Ratio
33%
Parametric Test
33%
Asset Price
33%
Method Error
33%
Economics, Econometrics and Finance
Derivative Pricing
25%