統計学輪講（第１９回）

日時      2006年 9月19日(火)    15時〜16時40分
場所      経済学部新棟３階第２教室
講演者    Prof. Andrew Harvey (Cambridge University)
演題      Time-Varying Quantiles

概要
A time-varying quantile can be fitted to a sequence of observations
by formulating a time series model for the corresponding population
quantile and iteratively applying a suitably modified state space sig-
nal extraction algorithm. Quantiles estimated in this way provide
information on various aspects of a time series, including dispersion,
asymmetry and, for financial applications, value at risk. Tests for the
constancy of quantiles, and associated contrasts, are constructed using
indicator variables; these tests have a similar form to stationarity tests
and, under the null hypothesis, their asymptotic distributions belong
to the Cramer von Mises family. Estimates of the quantiles at the end
of the series provide the basis for forecasting. As such they over an
alternative to conditional quantile autoregressions and, at the same
time, give some insight into their structure and potential drawbacks.

KEYWORDS: Dispersion; quantile regression; signal extraction;
state space smoother; stationarity tests; value at risk.

統計学輪講のスケジュールに戻る．

Tokyo University