Monte Carlo-based tail exponent estimator

Economy – Quantitative Finance – Computational Finance

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

10.1016/j.physa.2010.06.054

In this paper we propose a new approach to estimation of the tail exponent in financial stock markets. We begin the study with the finite sample behavior of the Hill estimator under {\alpha}-stable distributions. Using large Monte Carlo simulations, we show that the Hill estimator overestimates the true tail exponent and can hardly be used on samples with small length. Utilizing our results, we introduce a Monte Carlo-based method of estimation for the tail exponent. Our proposed method is not sensitive to the choice of tail size and works well also on small data samples. The new estimator also gives unbiased results with symmetrical confidence intervals. Finally, we demonstrate the power of our estimator on the international world stock market indices. On the two separate periods of 2002-2005 and 2006-2009, we estimate the tail exponent.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Monte Carlo-based tail exponent estimator 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 Monte Carlo-based tail exponent estimator, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Monte Carlo-based tail exponent estimator will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-498197

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.