The log-periodic-AR(1)-GARCH(1,1) model for financial crashes

Details The log-periodic-AR(1)-GARCH(1,1) model for financial crashes The log-periodic-AR(1)-GARCH(1,1) model for financial crashes

2008-01-28

arxiv.org/abs/0801.4341v1

Economy

Quantitative Finance

Statistical Finance

17 pages, 4 figures, 12 tables, to appear in Europen Physical Journal B

Scientific paper

10.1140/epjb/e2008-00085-1

This paper intends to meet recent claims for the attainment of more rigorous statistical methodology within the econophysics literature. To this end, we consider an econometric approach to investigate the outcomes of the log-periodic model of price movements, which has been largely used to forecast financial crashes. In order to accomplish reliable statistical inference for unknown parameters, we incorporate an autoregressive dynamic and a conditional heteroskedasticity structure in the error term of the original model, yielding the log-periodic-AR(1)-GARCH(1,1) model. Both the original and the extended models are fitted to financial indices of U. S. market, namely S&P500 and NASDAQ. Our analysis reveal two main points: (i) the log-periodic-AR(1)-GARCH(1,1) model has residuals with better statistical properties and (ii) the estimation of the parameter concerning the time of the financial crash has been improved.

Affiliated with

Also associated with

No associations

Rating

The log-periodic-AR(1)-GARCH(1,1) model for financial crashes does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with The log-periodic-AR(1)-GARCH(1,1) model for financial crashes, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and The log-periodic-AR(1)-GARCH(1,1) model for financial crashes will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-157200