Separating Information Maximum Likelihood Method for High Frequency Financial Data is popular PDF and ePub book, written by Naoto Kunitomo in 2018-06-14, it is a fantastic choice for those who relish reading online the Mathematics genre. Let's immerse ourselves in this engaging Mathematics book by exploring the summary and details provided below. Remember, Separating Information Maximum Likelihood Method for High Frequency Financial Data can be Read Online from any device for your convenience.

Separating Information Maximum Likelihood Method for High Frequency Financial Data Book PDF Summary

This book presents a systematic explanation of the SIML (Separating Information Maximum Likelihood) method, a new approach to financial econometrics. Considerable interest has been given to the estimation problem of integrated volatility and covariance by using high-frequency financial data. Although several new statistical estimation procedures have been proposed, each method has some desirable properties along with some shortcomings that call for improvement. For estimating integrated volatility, covariance, and the related statistics by using high-frequency financial data, the SIML method has been developed by Kunitomo and Sato to deal with possible micro-market noises. The authors show that the SIML estimator has reasonable finite sample properties as well as asymptotic properties in the standard cases. It is also shown that the SIML estimator has robust properties in the sense that it is consistent and asymptotically normal in the stable convergence sense when there are micro-market noises, micro-market (non-linear) adjustments, and round-off errors with the underlying (continuous time) stochastic process. Simulation results are reported in a systematic way as are some applications of the SIML method to the Nikkei-225 index, derived from the major stock index in Japan and the Japanese financial sector.

Detail Book of Separating Information Maximum Likelihood Method for High Frequency Financial Data PDF

Separating Information Maximum Likelihood Method for High Frequency Financial Data
  • Author : Naoto Kunitomo
  • Release : 14 June 2018
  • Publisher : Springer
  • ISBN : 9784431559306
  • Genre : Mathematics
  • Total Page : 118 pages
  • Language : English
  • PDF File Size : 18,9 Mb

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