Multi-Scale Jump and Volatility Analysis for High-Frequency Financial Data

• DOI: 10.2139/ssrn.957607
• Publication Date: 2011-12-28T12:04:55Z
• Authors: Jianqing Fan; Yazhen Wang
• Keywords: 0101 mathematics; 01 natural sciences

The wide availability of high-frequency data for many financial instruments stimulates a upsurge interest in statistical research on the estimation volatility. Jump-diffusion processes observed with market microstructure noise are frequently used to model data. Yet, existing methods developed either noisy from continuous diffusion price or jump-diffusion without noise. We propose cope both jumps and They allow us estimate integrated volatility jump variation sampled processes, contaminated Our approach is first remove then apply noise-resistent method estimated asymptotic analysis simulation study reveal that proposed wavelet can successfully be as well case no presence processes. In addition, they have outstanding efficiency. illustrated by applications two exchange rate sets.