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Scharth, Marcel; Kohn, Robert - In: Journal of econometrics 190 (2016) 1, pp. 133-147

Persistent link: https://www.econbiz.de/10011591626

Modeling high-frequency financial data using R and Stan : a bayesian autoregressive conditional duration approach

Tabash, Mosab I.; Navas, T. Muhammed; Thayyib, P. V.; … - In: Journal of open innovation : technology, market, and … 10 (2024) 2, pp. 1-16

In econometrics, Autoregressive Conditional Duration (ACD) models use high-frequency economic or financial duration data, which mostly exhibit irregular time intervals. The ACD model is widely used to examine the duration of transaction volume and duration of price variations in stock markets....

Persistent link: https://www.econbiz.de/10014581582

Volatility and GMM : Monte Carlo studies and empirical estimations

Nagel, Hartmut; Schöbel, Rainer - In: Statistical papers 40 (1999) 3, pp. 297-321

Persistent link: https://www.econbiz.de/10001401125

Particle Gibbs with ancestor sampling for stochastic volatility models with: heavy tails, in mean effects, leverage, serial dependence and structural breaks

Nonejad, Nima - In: Studies in nonlinear dynamics and econometrics : SNDE ; … 19 (2015) 5, pp. 561-584

Persistent link: https://www.econbiz.de/10011431022

Long memory modelling of inflation with stochastic variance and structural breaks

Bos, Charles S.; Koopman, Siem Jan; Ooms, Marius - 2007

We investigate changes in the time series characteristics of postwar U.S. inflation. In a model-based analysis the conditional mean of inflation is specified by a long memory autoregressive fractionally integrated moving average process and the conditional variance is modelled by a stochastic...

Persistent link: https://www.econbiz.de/10011373822