Summarizing Time Series Learning Patterns in Volatile Series

Date

2004-08-27

Author

AHMAD, Saif
Taşkaya Temizel, Tuğba
AHMAD, Khurshid

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

39
views

0
downloads

Most financial time series processes are nonstationary and their frequency characteristics are time-dependant. In this paper we present a time series summarization and prediction framework to analyse nonstationary, volatile and high-frequency time series data. Multiscale wavelet analysis is used to separate out the trend, cyclical fluctuations and autocorrelational effects. The framework can generate verbal signals to describe each effect. The summary output is used to reason about the future behaviour of the time series and to give a prediction. Experiments on the intra-day European currency spot exchange rates are described. The results are compared with a neural network prediction framework.

URI

https://hdl.handle.net/11511/53967

Collections

Graduate School of Informatics, Conference / Seminar

Suggestions

OpenMETU
Core

A simplified MAP channel estimator for OFDM systems under Rayleigh fading ÇÜRÜK, SELVA; Tanık, Yalçın (2010-06-01) This paper presents a simplified Maximum A Posteriori (SMAP) channel estimator to be used in orthogonal frequency division multiplexing (OFDM) systems under the Rayleigh fading assumption for the subchannels, using a parametric correlation model and assuming that the channel is frequency selective and slowly time varying. Expressions for the mean-square error (MSE) of estimations are derived to evaluate the performance of the estimator. The relation between the correlation of subchannels taps and error vari...
Generalizing the Sampling Property of the Q-function for Error Rate Analysis of Cooperative Communication in Fading Channels- Aktas, Tugcan; Yılmaz, Ali Özgür; Aktas, Emre (2013-07-12) This paper extends some approximation methods that are used to identify closed form Bit Error Rate (BER) expressions which are frequently utilized in investigation and comparison of performance for wireless communication systems in the literature. By using this group of approximation methods, some expectation integrals, whose exact analyses are intractable and whose Monte Carlo simulation computations have high complexity, can be computed. For these integrals, by using the sampling property of the integrand...
A diversity and coding gain analysis for the cooperative wireless communication channel under fading using sampling property of the Q-function İşbi̇rli̇kli̇ kablosuz haberleşmede sönümlemeli̇ kanal i̇çi̇n Q-fonksi̇yonunun örnekleme özelli̇ǧi̇nden yararlanan bi̇r çeşi̇tleme ve kodlama kazanci anali̇zi̇ Aktaş, Tuǧcan; Yılmaz, Ali Özgür; AKTAŞ, EMRE (2012-07-09) This work presents approximation methods that are used to identify Bit Error Rate (BER) expressions which are frequently utilized in investigation and comparison of performance for wireless communication systems in the literature. In this group of approximation methods, some expectation integrals, which are complicated to analyze and time-consuming to evaluate through Monte Carlo simulations, are handled. For this group of integrals, by using the sampling property of the Q-function under mid- and high- Sign...
The effect of temporal aggregation on univariate time series analysis Sarıaslan, Nazlı; Yozgatlıgil, Ceylan; Department of Statistics (2010) Most of the time series are constructed by some kind of aggregation and temporal aggregation that can be defined as aggregation over consecutive time periods. Temporal aggregation takes an important role in time series analysis since the choice of time unit clearly influences the type of model and forecast results. A totally different time series model can be fitted on the same variable over different time periods. In this thesis, the effect of temporal aggregation on univariate time series models is studie...
Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling Gupta, Hoshin V.; Kling, Harald; Yılmaz, Koray Kamil; Martinez, Guillermo F. (2009-10-20) The mean squared error (MSE) and the related normalization, the Nash-Sutcliffe efficiency (NSE), are the two criteria most widely used for calibration and evaluation of hydrological models with observed data. Here, we present a diagnostically interesting decomposition of NSE (and hence MSE), which facilitates analysis of the relative importance of its different components in the context of hydrological modelling, and show how model calibration problems can arise due to interactions among these components. T...

Citation Formats

S. AHMAD, T. Taşkaya Temizel, and K. AHMAD, “Summarizing Time Series Learning Patterns in Volatile Series,” 2004, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53967.