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Maximum likelihood estimation of stochastic volatility models
Yacine Aït-Sahalia
, Robert Kimmel
Economics
Bendheim Center for Finance
Center for Statistics & Machine Learning
Research output
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Contribution to journal
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Article
›
peer-review
277
Scopus citations
Overview
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Dive into the research topics of 'Maximum likelihood estimation of stochastic volatility models'. Together they form a unique fingerprint.
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Keyphrases
Maximum Likelihood Estimation
100%
Stochastic Volatility Model
100%
Volatility
100%
Monte Carlo Simulation
33%
Implied Volatility
33%
Option Price
33%
Approximation Results
33%
Heston Model
33%
Affine
33%
Proxy-based
33%
Small Loss
33%
Estimation Model
33%
Market Value
33%
Sampling Noise
33%
Generalized Autoregressive Conditional Heteroscedasticity (GARCH)
33%
Index Options
33%
Full Likelihood
33%
Elasticity of Variance
33%
Nested Model
33%
Approximate Likelihood
33%
CEV Model
33%
Mathematics
Maximum Likelihood Estimation
100%
Stochastic Volatility Model
100%
Variance
33%
Monte Carlo
33%
Approximates
33%
Option Price
33%
Implied Volatility
33%
Closed Form
33%
Market Price
33%
Heston Model
33%
Estimated Model
33%
GARCH Model
33%
Nested Model
33%
Economics, Econometrics and Finance
ARCH Model
14%