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Return-volatility relationship : insights from linear and non-linear quantile regression
Allen, David E.
;
Singh, Abhay Kumar
;
Powell, Robert
; …
-
2013
Persistent link: https://www.econbiz.de/10009724826
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2
Using exponentially weighted quantile regression to estimate value at risk and expected shortfall
Taylor, James W.
- In:
Journal of financial econometrics : official journal of …
6
(
2008
)
3
,
pp. 382-406
Persistent link: https://www.econbiz.de/10003748064
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3
A quantile regression neural network approach to estimating the conditional density of multiperiod returns
Taylor, James W.
- In:
Journal of forecasting
19
(
2000
)
4
,
pp. 299-311
Persistent link: https://www.econbiz.de/10001504631
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A quantile regression approach to estimating the distribution of multiperiod returns
Taylor, James W.
- In:
The journal of derivatives : the official publication …
7
(
1999
)
1
,
pp. 64-78
Persistent link: https://www.econbiz.de/10001432473
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5
An approximate long-memory range-based approach for value at risk estimation
Meng, Xiaochun
;
Taylor, James W.
- In:
International journal of forecasting
34
(
2018
)
3
,
pp. 377-388
Persistent link: https://www.econbiz.de/10012030985
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6
Forecasting value at risk and expected shortfall using a semiparametric approach based on the asymmetric laplace distribution
Taylor, James W.
- In:
Journal of business & economic statistics : JBES ; a …
37
(
2019
)
1
,
pp. 121-133
Persistent link: https://www.econbiz.de/10012176554
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