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~person:"Bollerslev, Tim"
~person:"Lux, Thomas"
~source:"econis"
~subject:"Börsenkurs"
~subject:"Schätzung"
~type_genre:"Working Paper"
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Forecasting model
44
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44
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36
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36
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30
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Bollerslev, Tim
Lux, Thomas
Marcellino, Massimiliano
40
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38
McAleer, Michael
33
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21
Pierdzioch, Christian
21
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20
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18
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18
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18
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17
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17
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14
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14
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14
Ravazzolo, Francesco
14
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13
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13
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12
Jumah, Adusei
12
Kim, Hyeongwoo
12
Rossi, Barbara
12
Siliverstovs, Boriss
12
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11
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9
Cholodilin, Konstantin Arkadʹevič
9
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9
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9
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9
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9
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9
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9
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9
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8
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8
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8
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ECONIS (ZBW)
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date (oldest first)
1
Forecasting the variability of stock index returns with the multifractal random walk model for realized volatilities
Sattarhoff, Cristina
;
Lux, Thomas
-
2021
clear message: The RV-MRW is throughout the best model for all
forecast
horizons under the MAE criterium as well as for … large
forecast
horizons h=50 and 100 days under the MSE criterion. Moreover, the RV-MRW provides most accurate 20-day ahead …
Persistent link: https://www.econbiz.de/10012672178
Saved in:
2
From zero to hero: realized partial (co)variances
Bollerslev, Tim
;
Medeiros, Marcelo C.
;
Patton, Andrew J.
; …
-
2021
choose the thresholds to maximize the out-ofsample
forecast
performance of time series models based on realized partial (co …
Persistent link: https://www.econbiz.de/10012249756
Saved in:
3
Bringing an elementary agent-based model to the data : estimation via GMM and an application to forecasting of asset price volatility
Ghonghadze, Jaba
;
Lux, Thomas
-
2015
We explore the issue of estimating a simple agent-based model of price formation in an asset market using the approach of Alfarano et al. (2008) as an example. Since we are able to derive various moment conditions for this model, we can apply generalized method of moments (GMM) estimation. We...
Persistent link: https://www.econbiz.de/10010501932
Saved in:
4
Modeling and forecasting carbon dioxide emission allowance spot price volatility : multifractal vs. GARCH-type volatility models
Segnon, Mawuli
;
Lux, Thomas
;
Gupta, Rangan
-
2015
This paper applies Markov-switching multifractal (MSM) processes to model and
forecast
carbon dioxide (CO2) emission … criteria and
forecast
horizons, while MS-GARCH mostly comes out as the least successful model. Applying various VaR backtesting …
Persistent link: https://www.econbiz.de/10011296114
Saved in:
5
Tail risk premia and return predictability
Bollerslev, Tim
;
Todorov, Viktor
;
Xu, Lai
-
2014
Persistent link: https://www.econbiz.de/10010442441
Saved in:
6
Stock return and cash flow predictability : the role of volatility risk
Bollerslev, Tim
;
Xu, Lai
;
Zhou, Hao
-
2012
Persistent link: https://www.econbiz.de/10009667370
Saved in:
7
Stock return predictability and variance risk premia : statistical inference and international evidence
Bollerslev, Tim
;
Marrone, James
;
Xu, Lai
;
Zhou, Hao
-
2011
Persistent link: https://www.econbiz.de/10009406434
Saved in:
8
Risk and return : long-run relationships, fractional cointegration, and return predictability
Bollerslev, Tim
(
contributor
)
-
2011
Persistent link: https://www.econbiz.de/10009785804
Saved in:
9
Forecasting volatility and volume in the Tokyo stock market : long memory, fractality and regime switching
Lux, Thomas
(
contributor
);
Kaizoji, Taisei
(
contributor
)
-
2006
practically always improves upon the nai͏̈ve
forecast
provided by historical volatility. As a somewhat surprising result, we also …
Persistent link: https://www.econbiz.de/10003392147
Saved in:
10
The Markov-Switching Multifractal Model of asset returns : GMM estimation and linear forecasting of volatility
Lux, Thomas
(
contributor
)
-
2006
Multifractal processes have recently been proposed as a new formalism for modelling the time series of returns in finance. The major attraction of these processes is their ability to generate various degrees of long memory in different powers of returns - a feature that has been found in...
Persistent link: https://www.econbiz.de/10003392192
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