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71
Estimating and Forecasting Volatility Using Leverage Effect
Wang, Christina Dan
-
2017
This research provides a theoretical foundation for our previous empirical finding that leverage effect has a role in estimating and forecasting volatility. This empirics is also related to earlier econometric studies of news impact curves (Engle and Ng, Chen and Ghysels). Our new theoretical...
Persistent link: https://www.econbiz.de/10012941856
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72
Ultra High Frequency Volatility Estimation with Dependent Microstructure Noise
Ait-Sahalia, Yacine
-
2010
We analyze the impact of time series dependence in market microstructure noise on the properties of estimators of the integrated volatility of an asset price based on data sampled at frequencies high enough for that noise to be a dominant consideration. We show that combining two time scales for...
Persistent link: https://www.econbiz.de/10012762451
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73
A Tale of Two Time Scales : Determining Integrated Volatility with Noisy High Frequency Data
Zhang, Lan
-
2010
It is a common practice in finance to estimate volatility from the sum of frequently-sampled squared returns. However market microstructure poses challenges to this estimation approach, as evidenced by recent empirical studies in finance. This work attempts to lay out theoretical grounds that...
Persistent link: https://www.econbiz.de/10012762713
Saved in:
74
Assessment of Uncertainty in High Frequency Data : The Observed Asymptotic Variance
Mykland, Per A.
-
2016
The availability of high frequency financial data has generated a series of estimators based on intra-day data, improving the quality of large areas of financial econometrics. However, estimating the standard error of these estimators is often challenging. The root of the problem is that...
Persistent link: https://www.econbiz.de/10013006101
Saved in:
75
Ultra High Frequency Volatility Estimation with Dependent Microstructure Noise
Ait-Sahalia, Yacine
-
2016
Persistent link: https://www.econbiz.de/10012991211
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76
The Five Trolls Under the Bridge : Principal Component Analysis with Asynchronous and Noisy High Frequency Data
Chen, Dachuan
-
2018
We develop a principal component analysis (PCA) for high frequency data. As in Northern fairly tales, there are trolls waiting for the explorer. The first three trolls are market microstructure noise, asynchronous sampling times, and edge effects in estimators. To get around these, a robust...
Persistent link: https://www.econbiz.de/10012928323
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77
Edgeworth Expansions for Realized Volatility and Related Estimators
Zhang, Lan
-
2005
This paper shows that the asymptotic normal approximation is often insufficiently accurate for volatility estimators based on high frequency data. To remedy this, we compute Edgeworth expansions for such estimators. Unlike the usual expansions, we have found that in order to obtain meaningful...
Persistent link: https://www.econbiz.de/10012466953
Saved in:
78
Ultra High Frequency Volatility Estimation with Dependent Microstructure Noise
Ait-Sahalia, Yacine
-
2005
We analyze the impact of time series dependence in market microstructure noise on the properties of estimators of the integrated volatility of an asset price based on data sampled at frequencies high enough for that noise to be a dominant consideration. We show that combining two time scales for...
Persistent link: https://www.econbiz.de/10012467303
Saved in:
79
A Tale of Two Time Scales : Determining Integrated Volatility with Noisy High Frequency Data
Zhang, Lan
-
2003
It is a common practice in finance to estimate volatility from the sum of frequently-sampled squared returns. However market microstructure poses challenges to this estimation approach, as evidenced by recent empirical studies in finance. This work attempts to lay out theoretical grounds that...
Persistent link: https://www.econbiz.de/10012468583
Saved in:
80
Comment
Ait-Sahalia, Yacine
;
Mykland, Per A.
;
Zhang, Lan
- In:
Journal of Business & Economic Statistics
24
(
2006
)
April
,
pp. 162-167
Persistent link: https://www.econbiz.de/10005238320
Saved in:
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