ROBINSON LOG-PERIODOGRAM REGRESSION OF TIME SERIES WITH LONG RANGE DEPENDENCE

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Firstly, we investigate the existence of long memory in volatility of the inventory returns, and examine the impact of long memory on the modeling and forecasting of multi-period volatility, the dependence structure between inventory returns and portfolio optimization. Thus, long memory is indispensable to model and measure long-term risk. Time series, auto-correlation, regression, etc. Robinson Search this author in:. Time series regression with long-range dependence. MR Digital Object Identifier: Scientific Research An Academic Publisher. Time series, auto-correlation, regression, etc.

A form of log-periodogram regression estimate of differencing and scale parameters is proposed, which can provide modest efficiency improvements over a previously proposed method for which no satisfactory theoretical justification seems previously available and further improvements in a multivariate context when differencing parameters are a priori equal. You have partial access to this content. Zentralblatt MATH identifier Tony, Eldar, Yonina C. Zentralblatt MATH identifier Time series, auto-correlation, regression, etc.

Asymptotic properties of estimators 62J Permanent link to this document https: The extensive Monte Carlo evidence reveals that both GARCH and IGARCH models without accounting for long memory will misestimate the actual long-term risk of the inventory portfolio and further bias the efficient frontier; besides, through A sensitive analysis of long memory parameter d, it is proved that the portfolio with higher long memory parameter possesses higher lohg return and lower risk level.

Firstly, we investigate the existence of long memory in volatility of the inventory returns, and examine the impact of long memory on the modeling and forecasting of multi-period volatility, the dependence structure between inventory returns and portfolio optimization. Sseries information Source Ann. Due to the illiquidity of inventories pledged, the essential of price risk management of supply chain finance is to long-term price risk measure. This paper sheds new light on the impact of serirs existence and persistence of long memory in volatility on inventory portfolio optimization.

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This paper discusses the estimation of multiple time series models which allow elements of the spectral density matrix to tend to infinity or zero at zero frequency and be unrestricted elsewhere. You do robinsob have access to this content. Download Email Please enter a valid email address. Scientific Research An Academic Publisher. Keywords Long-range dependence linear regression generalized least squares nonlinear regression.

In the generalized least squares case, we show that efficient estimation is still possible when the error autocorrelation is known only up to finitely many parameters. You do not have access to this content. Long memory in volatility, which attests a slower than exponential decay in the autocorrelation function of standard proxies of volatility, yields an additional improvement in specification of multi-period volatility models and further impact on the term structure of risk.

Log-periodogram regression of time series with long range dependence

Robinson Search this author in: On large-sample estimation of the mean of a stationary random sequence. Zentralblatt MATH identifier Secondly, we further explore the impact of the persistence of long memory in volatility on the efficient frontier of inventory portfolio via a data generation process with different long memory parameter in the FIGARCH model.

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The Annals of Statistics, 23, Hidalgo Search this author in: A form of log-periodogram regression estimate of differencing and scale parameters is proposed, which can provide modest efficiency improvements over a previously proposed method for which no satisfactory theoretical justification seems previously available and further improvements in a multivariate context when differencing parameters are a priori equal.

Robinson Search this author in:.

Robinson : Log-Periodogram Regression of Time Series with Long Range Dependence

Zentralblatt MATH identifier Thus, long memory is indispensable to model and measure long-term risk. You have partial access to this content. Abstract Article info and citation First page References Abstract A central limit theorem is established for time series regression estimates which include generalized least squares, in the presence of long-range tange in both errors and stochastic regressors.

Tony, Eldar, Yonina C.

Time series regression with long-range dependence. Permanent link to this document https: Congo from to Regressipn singularities are permitted at any frequency. A central limit theorem is established for time series regression estimates which include generalized least squares, in the presence of long-range dependence in both errors and stochastic regressors.

You have access to this content. Dates First available in Project Euclid: Robinson More by P.