Date of Award
Master of Arts (AM/MA)
This thesis studies a unifying class of nonparametric spot volatility estimators proposed by Mancini et. al.(2013). This method is based on delta sequences and is conceived to include many of the existing estimators in the field as special cases. The thesis first surveys the asymptotic theory of the proposed estimators under an infill asymptotic scheme and fixed time horizon, when the state variable follows a Brownian semimartingale. Then, some extensions to include jumps and financial microstructure noise in the observed price process are also presented. The main goal of the thesis is to assess the suitability of the proposed methods with both high-frequency simulated data and real transaction data from the stock market. In conclusion, double exponential kernel shows the best properties when estimating. Besides, the theorem is robust with the presence of jumps and microstructure noise and the U-shape curves of intraday spot volatility are achieved.
Chair and Committee
Jose E. Figueroa-Lopez
Jose E. Figueroa-Lopez, Renato Feres, Todd Kuffner
Gao, Weixuan, "Spot Volatility Estimation of Ito Semimartingales Using Delta Sequences" (2016). Arts & Sciences Electronic Theses and Dissertations. 701.