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Dynamic Factor Models with Clustered Loadings: Forecasting Education Flows using Unemployment Data

Blasques, Francisco; Hoogerkamp, Meindert Heres; … - 2021

We propose a dynamic factor model which we use to analyze the relationship between education participation and national … unemployment, as well as to forecast the number of students across the many different types of education. By clustering the factor … loadings associated with the dynamic macroeconomic factor, we can measure to what extent the different types of education …

Persistent link: https://www.econbiz.de/10012427178

Forecasting the Variability of Stock Index Returns with Stochastic Volatility Models and Implied Volatility

Hol, Eugenie; Koopman, Siem Jan - 2000

In this paper we compare the predictive abilility of Stochastic Volatility (SV)models to that of volatility forecasts implied by option prices. We develop anSV model with implied volatility as an exogeneous var able in the varianceequation which facilitates the use of statistical tests for...

Persistent link: https://www.econbiz.de/10010324427

The Stochastic Volatility in Mean Model

Koopman, Siem Jan; Uspensky, Eugenie Hol - 2000

In this paper we present an exact maximum likelihood treatment forthe estimation of a Stochastic Volatility in Mean(SVM) model based on Monte Carlo simulation methods. The SVM modelincorporates the unobserved volatility as anexplanatory variable in the mean equation. The same extension...

Persistent link: https://www.econbiz.de/10010324578

Periodic Heteroskedastic RegARFIMA Models for Daily Electricity Spot Prices

Carnero, M. Angeles; Koopman, Siem Jan; Ooms, Marius - 2003

Although the main interest in the modelling of electricity prices is often on volatility aspects, we argue that stochastic heteroskedastic behaviour in prices can only be modelled correctly when the conditional mean of the time series is properly modelled. In this paper we consider different...

Persistent link: https://www.econbiz.de/10010324825

Stock Index Volatility Forecasting with High Frequency Data

Hol, Eugenie; Koopman, Siem Jan - 2002

The increasing availability of financial market data at intraday frequencies has not only led to the development of improved ex-post volatility measurements but has also inspired research into their potential value as an informa-tion source for longer horizon volatility forecasts. In this paper...

Persistent link: https://www.econbiz.de/10010324972

Time Series Models with a Common Stochastic Variance for Analysing Economic Time Series

Koopman, Siem Jan; Bos, Charles S. - 2002

The linear Gaussian state space model for which the common variance istreated as a stochastic time-varying variable is considered for themodelling of economic time series. The focus of this paper is on thesimultaneous estimation of parameters related to the stochasticprocesses of the mean part...

Persistent link: https://www.econbiz.de/10010324992

Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State Space Models

Koopman, Siem Jan; Lucas, Andre; Scharth, Marcel - 2011

We introduce a new efficient importance sampler for nonlinear non-Gaussian state space models. We propose a general and efficient likelihood evaluation method for this class of models via the combination of numerical and Monte Carlo integration methods. Our methodology explores the idea that...

Persistent link: https://www.econbiz.de/10010325813

Modeling Dynamic Volatilities and Correlations under Skewness and Fat Tails

Zhang, Xin; Creal, Drew; Koopman, Siem Jan; Lucas, Andre - 2011

We propose a new model for dynamic volatilities and correlations of skewed and heavy-tailed data. Our model endows the Generalized Hyperbolic distribution with time-varying parameters driven by the score of the observation density function. The key novelty in our approach is the fact that the...

Persistent link: https://www.econbiz.de/10010326055

Leverage and Feedback Effects on Multifactor Wishart Stochastic Volatility for Option Pricing

Asai, Manabu; McAleer, Michael - 2013

The paper proposes a general asymmetric multifactor Wishart stochastic volatility (AMWSV) diffusion process which accommodates leverage, feedback effects and multifactor for the covariance process. The paper gives the closed-form solution for the conditional and unconditional Laplace transform...

Persistent link: https://www.econbiz.de/10010326219

A Fractionally Integrated Wishart Stochastic Volatility Model

Asai, Manabu; McAleer, Michael - 2013

There has recently been growing interest in modeling and estimating alternative continuous time multivariate stochastic volatility models. We propose a continuous timefractionally integrated Wishart stochastic volatility (FIWSV) process. We derive the conditional Laplace transform of the FIWSV...

Persistent link: https://www.econbiz.de/10010326243