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Generalised autoregressive conditional heteroskedasticity model, Long memory model, Realised volatility, Stochastic volatility model, Superior predictive ability, Unobserved components

credit cycles, business cycles, defaults, credit risk, procyclicality, multivariate unobserved component models

ARFIMA, Financial market volatility, GARCH, Realised volatility, Stochastic volatility, Stock index returns, Unobserved ARMA component

Generalized Autoregressive Conditional Heteroskedasticity model, Extended Kalman filter, Time-Varying Volatility, Yield Curve

credit risk, pro-cyclicality, capital requirements, dynamic models, common factors, credit cycles, time varying parameters

financial crisis, systemic risk, credit portfolio models, frailty-correlated defaults, state space methods

financial crisis, systemic risk, credit portfolio models, frailty-correlated defaults, state space methods

Credit cycles, Business cycles, Bank lending conditions, Unobserved component models, Intensity models

Fama-Bliss data set, Kalman filter, Maximum likelihood, Yield curve

ARIMA models, Intervention, Parole abolition, Regression models, Sentence reform, Structural time series models

Common trends and cycles, Dynamic factor model, Economic convergence, Kalman filter, Multivariate unobserved components time series models

Autoregressive integrated moving average, Importance sampling, Industrial production, Inflation, Kalman filter, Monte Carlo simulation, Simulation smoothing, State space, Stochastic volatility, Unobserved components time series

Importance sampling, Maximum likelihood estimation, Micro-structure noise, Realised variance, Stochastic volatility model

Unobserved components, credit cycles, duration model, generator matrix, Monte Carlo likelihood

Autoregressive fractionally integrated moving average model, Generalised autoregressive conditional heteroskedasticity model, Long memory process, Periodic autoregressive model, Volatility

financial crisis, default risk, credit portfolio models, frailty-correlated defaults, state space methods, doubly stochastic default times

Credit risk, multivariate unobserved component models, importance sampling, non-Gaussian state space models

High-dimensional vector series, Kalman filtering and smoothing, Unbalanced panels of time series

Kalman filter, Maximum likelihood estimation, Seemingly Unrelated Regression Equations, Unobserved Components, Time varying parameters, Heating effect

dynamic models, time-varying parameters, non-linearity, exponential family, marked point processes, copulas

Kalman filter, Likelihood function, Monte Carlo integration, Newton-Raphson, Posterior mode estimation, Simulation smoothing, Stochastic volatility model

Actuarial statistics, Dynamic factor analysis

Non-Gaussian Panel Data, Common Factors, Unobserved Components, Forecasting Conditional Default Probabilities

Fama-Bliss data set, Kalman filter, Maximum likelihood, Yield curve

Non-Gaussian Panel Data, Common Factors, Unobserved Components, Forecasting

Band-pass filter, Cyclical convergence, Kalman filter, Unobserved components time series models, Phase shifts

dynamic dependence, multivariate Student's t distribution, copula

Seasonal interaction; Unobserved components; Non-linear state space models

Non-stationarity, survey forecasts, term structure of interest rates, forecasting, yield curve

Asymmetric business cycles, Unobserved Components, Nonlinear state space models, Monte Carlo likelihood, Importance sampling

Time varying parameters, Importance sampling, Monte Carlo simulation, Stochastic Volatility, Fractional Integration

Diffuse likelihood, Kalman filter, Marginal likelihood, Multivariate time series models, Profile likelihood

panel data, loss given default, default risk, dynamic beta density, dynamic ordered probit, dynamic factor model

Frequency domain estimation, frequency domain bootstrap, time-varying parameters, unobserved components models

Unobserved component models, state space methods, seasonal adjustment, time-varying parameters, forecasting

betting, importance sampling, kalman filter smoother, Non-Gaussian multivariate time series models, sport statistics

high frequency, intraday periodicity, jump testing, leverage effect, microstructure noise, pre-averaged bipower variation, spot variance

non-Gaussian state space modeling, nonlinear panel data model, binomial time series, recidivism behavior, continuous time modelling

Kalman filter, leverage, realised volatility, simulated maximum likelihood

Efficient price;, Financial markets, High-frequency data, Kalman filter, Unobserved components time series models

fractional integration, correlation, student's t copula, time-varying dependence, multivariate volatility

Kalman filter, Monte Carlo maximum likelihood, numerical integration, stochastic copula, stochastic conditional duration, stochastic volatility

Common stochastic variance, Kalman filter, State space model, unobserved components time series model

Bandpass filter, Markov chain Monte Carlo, Stochastic volatility, Trend-cycle decomposition, Unobserved components time series model

Frequency-specific model, Kalman filter, model-based seasonal adjustment, unobserved components time series model

House Prices, Business Cycles, Euro Area, Unobserved Components Model

Bivariate smoothing, Geo-statistics, Missing observations, Smoothing spline model, State space methods

fractional integration, importance sampling, kalman filter, latent factors, stochastic volatility

financial crisis, default risk, credit portfolio models, frailty-correlated defaults, state space methods

Generalised autoregressive score model, Importance sampling, Model confidence set, Nonlinear state space model, Weibull-gamma mixture

Dudley integral, Durations, Higher-order models, Nonlinear dynamics, Time-varying parameters, Volatility

panel data, non-Gaussian, importance sampling, random effects, Student's t, economic growth

Kalman filter, Monte Carlo maximum likelihood, simulation smoothing

Kalman filter, Mixed frequency, Nowcasting, Principal components, State space model, Unobserved Components Time Series Model

Kalman filter, Monte Carlo maximum likelihood, simulation smoothing

nonlinear non-Gaussian state space model, Bayesian inference, Monte Carlo estimation, Metropolis-Hastings algorithm, mixture of student's t-distributions

Autoregressive fractionally integrated moving average model, Generalised autoregressive conditional heteroskedasticity model, Long memory process, Periodic autoregressive model, Volatility

Extreme value theory, Importance sampling, Simulation, Stochastic Volatility