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subject:"Volatility"
type_genre:"Article in journal"
~isPartOf:"Applied financial economics"
~isPartOf:"Asia-Pacific financial markets"
~isPartOf:"Empirical economics : a journal of the Institute for Advanced Studies, Vienna, Austria"
~isPartOf:"Journal of forecasting"
~subject:"Stochastic process"
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Search: subject_exact:"Estimation theory"
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Volatility
Stochastic process
Estimation theory
354
Schätztheorie
354
Theorie
120
Theory
120
Time series analysis
94
Zeitreihenanalyse
94
Forecasting model
88
Prognoseverfahren
88
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Article in journal
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33
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Taylor, James W.
2
Abraham, Bovas
1
Abramov, Vyacheslav M.
1
An, Yang
1
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1
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1
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1
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1
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1
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1
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1
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1
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1
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1
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1
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1
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1
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1
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Applied financial economics
Asia-Pacific financial markets
Empirical economics : a journal of the Institute for Advanced Studies, Vienna, Austria
Journal of forecasting
Journal of econometrics
139
Journal of business & economic statistics : JBES ; a publication of the American Statistical Association
48
Economics letters
35
Econometric reviews
31
Economic modelling
27
Econometric theory
24
Journal of empirical finance
22
Studies in nonlinear dynamics and econometrics : SNDE ; quarterly publ. electronically on the internet
20
Journal of financial econometrics : official journal of the Society for Financial Econometrics
19
International journal of forecasting
17
Quantitative finance
17
Finance research letters
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International journal of theoretical and applied finance
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The North American journal of economics and finance : a journal of financial economics studies
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11
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Finance and stochastics
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Operations research
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International journal of economics and financial issues : IJEFI
8
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7
Applied economics letters
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Decisions in economics and finance : DEF ; a journal of applied mathematics
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International journal of financial engineering
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Journal of applied econometrics
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ECONIS (ZBW)
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1
Mixed-frequency predictive regressions with parameter learning
Leippold, Markus
;
Yang, Hanlin
- In:
Journal of forecasting
42
(
2023
)
8
,
pp. 1955-1972
Persistent link: https://www.econbiz.de/10014432824
Saved in:
2
Dynamic forecasting for nonstationary high-frequency financial data with jumps based on series decomposition and reconstruction
Song, Yuping
;
Li, Zhenwei
;
Ma, Zhiren
;
Sun, Xiaoyu
- In:
Journal of forecasting
42
(
2023
)
5
,
pp. 1055-1068
Persistent link: https://www.econbiz.de/10014338810
Saved in:
3
Forecasting stock return volatility : realized volatility-type or duration-based estimators
Fei, Tianlun
;
Liu, Xiaoquan
;
Wen, Conghua
- In:
Journal of forecasting
42
(
2023
)
7
,
pp. 1594-1621
Persistent link: https://www.econbiz.de/10014432725
Saved in:
4
Forecasting Bitcoin volatility : a new insight from the threshold regression model
Zhang, Yaojie
;
He, Mengxi
;
Wen, Danyan
;
Wang, Yudong
- In:
Journal of forecasting
41
(
2022
)
3
,
pp. 633-652
Persistent link: https://www.econbiz.de/10013166172
Saved in:
5
Demand systems with heteroscedastic disturbances
Serletis, Apostolos
;
Xu, Libo
- In:
Empirical economics : a journal of the Institute for …
58
(
2020
)
4
,
pp. 1913-1921
Persistent link: https://www.econbiz.de/10012219723
Saved in:
6
Effects of jumps and small noise in high-frequency financial econometrics
Kunitomo, Naoto
;
Kurisu, Daisuke
- In:
Asia-Pacific financial markets
24
(
2017
)
1
,
pp. 39-73
Persistent link: https://www.econbiz.de/10011742284
Saved in:
7
Short‐term stock price prediction based on limit order book dynamics
An, Yang
;
Chan, Ngai Hang
- In:
Journal of forecasting
36
(
2017
)
5
,
pp. 541-556
Persistent link: https://www.econbiz.de/10011860685
Saved in:
8
Long memory of financial time series and hidden Markov models with time‐varying parameters
Nystrup, Peter
;
Madsen, Henrik
;
Lindström, Erik
- In:
Journal of forecasting
36
(
2017
)
8
,
pp. 989-1002
Persistent link: https://www.econbiz.de/10011860941
Saved in:
9
Modeling and forecasting aggregate stock market volatility in unstable environments using mixture innovation regressions
Nonejad, Nima
- In:
Journal of forecasting
36
(
2017
)
6
,
pp. 718-740
Persistent link: https://www.econbiz.de/10011861413
Saved in:
10
Predicting stock return volatility : can we benefit from regression models for return intervals?
Fischer, Henning
;
Blanco-Fernández, Ángela
;
Winker, Peter
- In:
Journal of forecasting
35
(
2016
)
2
,
pp. 113-146
Persistent link: https://www.econbiz.de/10011580244
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