Refined Inference on Long Memory in Realized Volatility
There is an emerging consensus in empirical finance that realized volatility series typically display long range dependence with a memory parameter around 0.4 (Andersen et al., 2001; Martens et al., 2004). The present article provides some illustrative analysis of how long memory may arise from the...
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| Format: | text |
| Language: | English |
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Institutional Knowledge at Singapore Management University
2008
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| Online Access: | https://ink.library.smu.edu.sg/soe_research/363 https://ink.library.smu.edu.sg/context/soe_research/article/1362/viewcontent/Refined_Inference_on_Long_Memory_in_Realized_Volatility.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | There is an emerging consensus in empirical finance that realized volatility series typically display long range dependence with a memory parameter around 0.4 (Andersen et al., 2001; Martens et al., 2004). The present article provides some illustrative analysis of how long memory may arise from the accumulative process underlying realized volatility. The article also uses results in Lieberman and Phillips (2004, 2005) to refine statistical inference about by higher order theory. Standard asymptotic theory has an error rate for error rejection probabilities, and the theory used here refines the approximation to an error rate of. The new formula is independent of unknown parameters, is simple to calculate and user-friendly. The method is applied to test whether the reported long memory parameter estimates of Andersen et al. (2001) and Martens et al. (2004) differ significantly from the lower boundary of nonstationary long memory, and generally confirms earlier findings. |
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