國立虎尾科技大學 |

Inference for functional time series with applications to yield curves and intraday cumulative returns.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Inference for functional time series with applications to yield curves and intraday cumulative returns./
作者:	Young, Gabriel J.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2016,
面頁冊數:	176 p.
附註:	Source: Dissertation Abstracts International, Volume: 77-11(E), Section: B.
Contained By:	Dissertation Abstracts International77-11B(E).
標題:	Statistics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10138072
ISBN:	9781339936833

Inference for functional time series with applications to yield curves and intraday cumulative returns.
Young, Gabriel J.

Inference for functional time series with applications to yield curves and intraday cumulative returns. - Ann Arbor : ProQuest Dissertations & Theses, 2016 - 176 p.

Source: Dissertation Abstracts International, Volume: 77-11(E), Section: B.

Thesis (Ph.D.)--Colorado State University, 2016.

Econometric and financial data often take the form of a functional time series. Examples include yield curves, intraday price curves and term structure curves. Before an attempt is made to statistically model or predict such series, we must address whether or not such a series can be assumed stationary or trend stationary. We develop extensions of the KPSS stationarity test to functional time series. Motivated by the problem of a change in the mean structure of yield curves, we also introduce several change point methods applied to dynamic factor models. For all testing procedures, we include a complete asymptotic theory, a simulation study, illustrative data examples, as well as details of the numerical implementation of the testing procedures. The impact of scheduled macroeconomic announcements has been shown to account for sizable fractions of total annual realized stock returns. To assess this impact, we develop methods of derivative estimation which utilize a functional analogue of local-polynomial smoothing. The confidence bands are then used to find time intervals of statistically increasing cumulative returns.

ISBN: 9781339936833Subjects--Topical Terms:

556824
Statistics.

Inference for functional time series with applications to yield curves and intraday cumulative returns.
LDR:02138nam a2200313 4500 001 890637
005 20180727091501.5
008 180907s2016 ||||||||||||||||| ||eng d
020 $a 9781339936833
035 $a (MiAaPQ)AAI10138072
035 $a (MiAaPQ)colostate:13597
035 $a AAI10138072
040 $a MiAaPQ $c MiAaPQ
100 1 $a Young, Gabriel J. $3 1148436
245 1 0 $a Inference for functional time series with applications to yield curves and intraday cumulative returns.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2016
300 $a 176 p.
500 $a Source: Dissertation Abstracts International, Volume: 77-11(E), Section: B.
500 $a Adviser: Piotr S. Kokoszka.
502 $a Thesis (Ph.D.)--Colorado State University, 2016.
520 $a Econometric and financial data often take the form of a functional time series. Examples include yield curves, intraday price curves and term structure curves. Before an attempt is made to statistically model or predict such series, we must address whether or not such a series can be assumed stationary or trend stationary. We develop extensions of the KPSS stationarity test to functional time series. Motivated by the problem of a change in the mean structure of yield curves, we also introduce several change point methods applied to dynamic factor models. For all testing procedures, we include a complete asymptotic theory, a simulation study, illustrative data examples, as well as details of the numerical implementation of the testing procedures. The impact of scheduled macroeconomic announcements has been shown to account for sizable fractions of total annual realized stock returns. To assess this impact, we develop methods of derivative estimation which utilize a functional analogue of local-polynomial smoothing. The confidence bands are then used to find time intervals of statistically increasing cumulative returns.
590 $a School code: 0053.
650 4 $a Statistics. $3 556824
650 4 $a Finance. $3 559073
650 4 $a Economics. $3 555568
690 $a 0463
690 $a 0508
690 $a 0501
710 2 $a Colorado State University. $b Statistics. $3 1148437
773 0 $t Dissertation Abstracts International $g 77-11B(E).
790 $a 0053
791 $a Ph.D.
792 $a 2016
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10138072