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EnglishWe consider a stochastic process driven by diffusions and jumps. Given a discreterecord of observations, we devise a technique for identifying the times when jumps larger than asuitably defined threshold occurred. This allows us to determine a consistent non-parametricestimator of the integrated volatility when the infinite activity jump component is Lévy. Jump sizeestimation and central limit results are proved in the case of finite activity jumps. Some simulationsillustrate the applicability of the methodology in finite samples and its superiority on the multipowervariations especially when it is not possible to use high frequency data.
| Titolo: | Non-parametric Threshold Estimation for Models with Stochastic Diffusion Coefficient and Jumps |
| Autori: | |
| Data di pubblicazione: | 2018 |
| Abstract: | We consider a stochastic process driven by diffusions and jumps. Given a discreterecord of observations, we devise a technique for identifying the times when jumps larger than asuitably defined threshold occurred. This allows us to determine a consistent non-parametricestimator of the integrated volatility when the infinite activity jump component is Lévy. Jump sizeestimation and central limit results are proved in the case of finite activity jumps. Some simulationsillustrate the applicability of the methodology in finite samples and its superiority on the multipowervariations especially when it is not possible to use high frequency data. |
| Handle: | http://hdl.handle.net/11562/1001156 |
| ISBN: | 978 1 78811 061 7 |
| Appare nelle tipologie: | 02.01 Contributo in volume (Capitolo o Saggio) |
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