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~person:"Daníelsson, Jón"
~person:"Ardia, David"
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Risikomaß
44
Risk measure
43
Theorie
25
Value-at-Risk
25
Theory
23
Volatilität
16
GARCH
14
Risikomanagement
14
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Daníelsson, Jón
Ardia, David
McAleer, Michael
193
Allen, David E.
59
Härdle, Wolfgang
58
Chang, Chia-Lin
51
Wang, Ruodu
49
Stoja, Evarist
43
Hammoudeh, Shawkat
40
Jiménez-Martín, Juan-Ángel
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Vries, Casper G. de
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Fabozzi, Frank J.
37
Mittnik, Stefan
35
Dowd, Kevin
33
Polanski, Arnold
33
Pérez Amaral, Teodosio
32
Paolella, Marc S.
31
Gerlach, Richard
28
Powell, Robert
28
Embrechts, Paul
27
Lucas, André
27
Pérez-Amaral, Teodosio
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Vanduffel, Steven
27
Caporin, Massimiliano
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Rüschendorf, Ludger
25
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25
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24
Giot, Pierre
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Hoogerheide, Lennart
24
Huschens, Stefan
24
Righi, Marcelo Brutti
24
Rosazza Gianin, Emanuela
24
Schaumburg, Julia
24
Dhaene, Jan
23
Hautsch, Nikolaus
23
Brandtner, Mario
22
Kratz, Marie
22
Račev, Svetlozar T.
22
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22
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Tinbergen Instituut
5
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3
Centre Interuniversitaire sur le Risque, les Politiques Économiques et l'Emploi (CIRPÉE)
2
Volkswirtschaftliche Fakultät, Ludwig-Maximilians-Universität München
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8
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1
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1
Risk management : a modern perspective
1
Risk measures for the 21st century
1
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Tinbergen Institute Discussion Paper 2013-047/III
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ECONIS (ZBW)
43
RePEc
16
EconStor
5
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1
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1
GARCH Models for Daily Stock Returns : Impact of Estimation Frequency on
Value-at-Risk
and Expected Shortfall Forecasts
Ardia, David
-
2020
returns for constituents of the S&P 500 index. We assess the implication for one-day ahead 95% and 99%
Value-at-Risk
(VaR …
Persistent link: https://www.econbiz.de/10012857089
Saved in:
2
Downside Risk Evaluation with the R Package GAS
Ardia, David
-
2019
prediction and the evaluation of downside risk. Emphasis is given to the two key financial downside risk measures:
Value-at-Risk
…
Persistent link: https://www.econbiz.de/10012902645
Saved in:
3
Methods for Computing Numerical Standard Errors : Review and Application to
Value-at-Risk
Estimation
Ardia, David
-
2018
management where we assess the precision of the
Value–at–Risk
measure when the underlying risk model is estimated by simulation …
Persistent link: https://www.econbiz.de/10012936424
Saved in:
4
Why risk is so hard to measure
Daníelsson, Jón
;
Chen Zhou
-
2016
Persistent link: https://www.econbiz.de/10011415993
Saved in:
5
Regime changes in Bitcoin GARCH volatility dynamics
Ardia, David
;
Bluteau, Keven
;
Rüede, Maxime
- In:
Finance research letters
29
(
2019
),
pp. 266-271
Persistent link: https://www.econbiz.de/10012419095
Saved in:
6
A new bootstrap test for the validity of a set of marginal models for multiple dependent time series : an application to risk analysis
Ardia, David
;
Gatarek, Lukasz
;
Hoogerheide, Lennart F.
-
2014
for multiple time series is particularly useful if one wants to assess
Value-at-Risk
(or Expected Shortfall) predictions …
Persistent link: https://www.econbiz.de/10010250513
Saved in:
7
Methods for computing numerical standard errors : review and application to
value-at-risk
estimation
Ardia, David
;
Bluteau, Keven
;
Hoogerheide, Lennart
- In:
Journal of time series econometrics
10
(
2018
)
2
,
pp. 1-9
Persistent link: https://www.econbiz.de/10011898020
Saved in:
8
GARCH models for daily stock returns : impact of estimation frequency on
value-at-risk
and expected shortfall forecasts
Ardia, David
;
Hoogerheide, Lennart
-
2013
Persistent link: https://www.econbiz.de/10010191413
Saved in:
9
A new bootstrap test for multiple assets joint risk testing
Ardia, David
;
Gatarek, Lukasz
;
Hoogerheide, Lennart
- In:
Journal of risk
19
(
2016/2017
)
4
,
pp. 1-22
Persistent link: https://www.econbiz.de/10011710231
Saved in:
10
Forecasting risk with Markov-switching GARCH models : a large-scale performance study
Ardia, David
;
Bluteau, Keven
;
Boudt, Kris
;
Catania, Leopoldo
- In:
International journal of forecasting
34
(
2018
)
4
,
pp. 733-747
Persistent link: https://www.econbiz.de/10012031094
Saved in:
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