What is he best known for?
The fields of study he is best known for:
- Statistics
- Finance
- Normal distribution
His scientific interests lie mostly in Econometrics, Valuation of options, Autoregressive conditional heteroskedasticity, Volatility and Stochastic volatility.
His studies deal with areas such as Financial economics, Asset, Likelihood function and Equity as well as Econometrics.
His work in Asset addresses issues such as Derivative, which are connected to fields such as Deposit insurance, Estimation theory and Vasicek model.
His Autoregressive conditional heteroskedasticity research includes elements of Score test, Black–Scholes model and Bivariate analysis.
His research on Black–Scholes model also deals with topics like
- Finite difference methods for option pricing and Monte Carlo methods for option pricing most often made with reference to Heteroscedasticity,
- Capital asset pricing model together with Monte Carlo method.
His work on Forward volatility as part of general Stochastic volatility study is frequently linked to Cover, bridging the gap between disciplines.
His most cited work include:
- THE GARCH OPTION PRICING MODEL (901 citations)
- MAXIMUM LIKELIHOOD ESTIMATION USING PRICE DATA OF THE DERIVATIVE CONTRACT (307 citations)
- Augmented GARCH (p,q) process and its diffusion limit (283 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Econometrics, Autoregressive conditional heteroskedasticity, Financial economics, Valuation of options and Volatility.
His research integrates issues of Statistics, Likelihood function, Interest rate and Credit risk in his study of Econometrics.
His Autoregressive conditional heteroskedasticity research includes themes of Currency, Black–Scholes model, Rational pricing, Finite difference methods for option pricing and Index.
His study on Implied volatility and Volatility risk premium is often connected to Non-qualified stock option as part of broader study in Financial economics.
His Valuation of options study combines topics from a wide range of disciplines, such as Mathematical economics and Microeconomics.
He usually deals with Volatility and limits it to topics linked to Asset and Spread option.
He most often published in these fields:
- Econometrics (48.65%)
- Autoregressive conditional heteroskedasticity (31.53%)
- Financial economics (25.23%)
What were the highlights of his more recent work (between 2013-2021)?
- Particle filter (11.71%)
- Algorithm (8.11%)
- Actuarial science (16.22%)
In recent papers he was focusing on the following fields of study:
Jin-Chuan Duan focuses on Particle filter, Algorithm, Actuarial science, Default and Latent variable.
His work in the fields of Actuarial science, such as Credit rating, Credit risk and Credit analysis, overlaps with other areas such as Decomposition.
His Default study combines topics from a wide range of disciplines, such as Financial economics and Interest rate.
His studies link Econometrics with Interest rate.
Jin-Chuan Duan frequently studies issues relating to Index and Econometrics.
His study explores the link between Parametric statistics and topics such as Autoregressive conditional heteroskedasticity that cross with problems in Metropolis–Hastings algorithm.
Between 2013 and 2021, his most popular works were:
- Density-Tempered Marginalized Sequential Monte Carlo Samplers (26 citations)
- Forward-Looking Market Risk Premium (21 citations)
- Default Correlations and Large-Portfolio Credit Analysis (9 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Finance
- Normal distribution
Actuarial science, Sample, Particle filter, Gaussian and Algorithm are his primary areas of study.
His research integrates issues of Portfolio and Default in his study of Actuarial science.
His Sample study incorporates themes from Missing data, Credit portfolio and Markov chain Monte Carlo.
Particle filter combines with fields such as Bayesian probability, Parallelizable manifold, Bayesian inference, Outlier and Metropolis–Hastings algorithm in his research.
His Metropolis–Hastings algorithm study often links to related topics such as Autoregressive conditional heteroskedasticity.
Jin-Chuan Duan integrates many fields, such as Gaussian and engineering, in his works.
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