Generating Schemes for Long Memory Processes: Regimes, Aggregation and Linearity (2004)
James Davidson, Philipp Sibbertsen
This paper analyses a class of nonlinear time series models exhibiting long memory. These processes exhibit short memory fluctuations around a local mean (regime) which switches randomly such that...
On Robust Local Polynomial Estimation With Long-Memory Errors (2001)
Jan Beran, Yuanhua Feng, Sucharita Ghosh, Philipp Sibbertsen
Prediction in time series models with a trend requires reliable estimation of the trend function at the right end of the observed series. Local polynomial smoothing is a suitable tool because...
Nonparametric M-Estimation with long-memory errors (2000)
Ghosh, Sucharita, Sibbertsen, Philipp, Beran, Jan
We investigate the behavior of nonparametric kernel M-estimator in the presence of long-memoryerrors. The optimal bandwidth and central limit theorem are obtained. It turns out that in the...
On robust local polynomial estimation with long-memory errors (2000)
Beran, Jan, Feng, Yuanhua, Ghosh, Sucharita, Sibbertsen, Philipp
Prediction in time series models with a trend requires reliable estima-tion of the trend function at the right end of the observed series. Localpolynomial smoothing is a suitable tool because...
Nonparametric M-Estimation with long-memory errors (2000)
Beran, Jan, Ghosh, Sucharita, Sibbertsen, Philipp
We investigate the behavior of nonparametric kernel M-estimator in the presence of long-memory errors. The optimal bandwidth and central limit theorem are obtained. It turns out that in the Gaussian...
On robust local polynomial estimation with long-memory errors (2000)
Beran, Jan, Feng, Yuanhua, Ghosh, Sucharita, Sibbertsen, Philipp
Prediction in time series models with a trend requires reliable estima- tion of the trend function at the right end of the observed series. Local polynomial smoothing is a suitable tool because...
Robust CUSUM-M test in the presence of long-memory disturbances (2000)
We derive the limiting null distribution of the robust CUSUM-M test and the recursive CUSUM-M test for structural change of the coefficients of a linear regression model with long-memory...
Nonparametric M-estimation with long-memory errors (2000)
Jan Beran, Sucharita Ghosh, Philipp Sibbertsen
We investigate the behavior of nonparametric kernel M-estimators in the presence of long-memory errors. The optimal bandwidth and a central limit theorem are obtained. It turns out that in the...
Robust CUSUM-M test in the presence of long-memory disturbances (2000)
We derive the limiting null distribution of the robust CUSUM-M test and the recursive CUSUM-M test for structural change of the coefficients of a linear regression model with long-memory...
Testing for structural change in the presence of long memory (2000)
Krämer, Walter, Sibbertsen, Philipp
We derive the limiting null distributions of the standard and OLS-based CUSUM-tests for structural change of the coefficients of a linear regression model in the context of long memory disturbances....
On robust local polynomial estimation with long-memory errors (2000)
Beran, Jan, Feng, Yuanhua, Ghosh, Sucharita, Sibbertsen, Philipp
Prediction in time series models with a trend requires reliable estimation of the trend function at the right end of the observed series. Local polynomial smoothing is a suitable tool because...
Nonparametric M-estimation with long-memory errors (2000)
Ghosh, Sucharita, Sibbertsen, Philipp
We investigate the behavior of nonparametric kernel M-estimators in the presence of long-memory errors. The optimal bandwidth and a central limit theorem are obtained. It turns out that in the...
Zugl.: Dortmund, Universiẗat, Diss., 1998.
S-estimation in the nonlinear regression model with long-memory error terms (1999)
In this paper we consider the asymptotic distribution of S-estimators in the nonlinear regression model with long-memory error terms. S-estimators are robust estimates with a high breakdown point and...
S - estimators in the linear regression model with long - memory error terms (1998)
We investigate the behaviour of S - estimators in the linear regression model, when the error terms are long - memory Gaussian processes. It turns out that under mild regularity conditions S -...
Phillips-Perron-type unit root tests in the nonlinear ESTAR framework
Rothe, Christoph, Sibbertsen, Philipp
In this paper, we propose Phillips-Perron type, semiparametric testing procedures to distinguish a unit root process from a mean-reverting exponential smooth transition autoregressive one. The...
On robust local polynomial estimation with long-memory errors
Jan Beran, Yuanhua Feng, Sucharita Gosh, Philipp Sibbertsen
Prediction in time series models with a trend requires reliable estima- tion of the trend function at the right end of the observed series. Local polynomial smoothing is a suitable tool because...
Nonparametric M-Estimation with Long-Memory Errors
Jan Beran, Sucharita Gosh, Philipp Sibbertsen
We investigate the behavior of nonparametric kernel M-estimators in the presence of long-memory errors. The optimal bandwidth and a central limit theorem are obtained. It turns out that in the...
Tests of Bias in Log-Periodogram Regression
Davidson, James, Sibbertsen, Philipp
This paper proposes simple Hausman-type tests to check for bias in the log-periodogram regression of a time series believed to be long memory. The statistics are asymptotically standard normal on the...
Divergence of credit valuation in Germany - Continuous theory and discrete practice -
Weibach, Rafael, Sibbertsen, Philipp
Lending is associated with credit risk. Modelling the loss stochastically, the cost of credit risk is the expected loss. In credit business the probability that the debtor will default in payments...
Empirical likelihood confidence intervals for the mean of a long-range dependent process
Nordman, Dan Nordman, Sibbertsen, Philipp, Lahiri, Soumendra N.
This paper considers blockwise empirical likelihood for real-valued linear time processes which may exhibit either short- or long-range dependence. Empirical likelihood approaches intended for weakly...
Phillips-Perron-type unit root tests in the nonlinear ESTAR framework
Christoph Rothe, Philipp Sibbertsen
Exponential smooth transition autoregressive model, unit roots, Monte Carlo simulations, purchasing power parity, C12, C32,
Empirical likelihood confidence intervals for the mean of a long-range dependent process
Daniel J. Nordman, Philipp Sibbertsen, Soumendra N. Lahiri
This paper considers blockwise empirical likelihood for real-valued linear time processes which may exhibit either short- or long-range dependence. Empirical likelihood approaches intended for weakly...
Testing for a break in persistence under long-range dependencies
Sibbertsen, Philipp, Kruse, Robinson
We show that tests for a break in the persistence of a time series in the classical I(0) - I(1) framework have serious size distortions when the actual data generating process exhibits long-range...
S-Estimation in the Linear Regression Model with Long-Memory Error Terms
The phenomenon of long-memory plays an important role in economics. This paper considers the asymptotic properties of S -estimators -- a class of robust estimates with a high breakdown-point and good...
On robust local polynomial estimation with long-memory errors
Beran, Jan, Feng, Yuanhua, Ghosh, Sucharita, Sibbertsen, Philipp
Can we distinguish between common nonlinear time series models and long memory?
Kuswanto, Heri, Sibbertsen, Philipp
We show that specific nonlinear time series models such as SETAR, LSTAR, ESTAR and Markov switching which are common in econometric practice can hardly be distinguished from long memory by standard...
The Power of the KPSS-Test for Cointegration when Residuals are Fractionally Integrated
Sibbertsen, Philipp, Krämer, Walter
We show that the power of the KPSS-test against integration, as measured by divergence rates of the test statistic under the alternative, remains the same when residuals from an OLS-regression rather...
Long memory in volatilities of German stock returns
We show that there is strong evidence of long-range dependence in the volatilities of several German stock returns. This will be done by applying a method using the difference of the classical...
Sibbertsen, Philipp, Stahl, Gerhard, Luedtke, Corinna
Model risk as part of the operational risk is a serious problem for financial institutions. As the pricing of derivatives as well as the computation of the market or credit risk of an institution...
A Study on "Spurious Long Memory in Nonlinear Time Series Models"
Kuswanto, Heri, Sibbertsen, Philipp
This paper discusses the existence of spurious long memory in common nonlinear time series models, namely Markov switching and threshold models. We describe the asymptotic behavior of the process in...
Log-periodogram estimation of the memory parameter of a long-memory process under trend
We show that log-periodogram-based estimators for the memory parameter in a stationary invertible long-memory process do not confuse small trends with long-range dependence. In the case of slowly...
Tests of bias in log-periodogram regression
Davidson, James, Sibbertsen, Philipp
This paper proposes simple Hausman-type tests to check for bias in the log-periodogram regression of a time series believed to be long memory. The statistics are asymptotically standard normal on the...
S-Estimators in the Linear Regression Model With Long-Memory Error Terms
We investigate the behaviour of S - estimators in the linear regression model, when the error terms are long - memory Gaussian processes. It turns out that under mild regularity conditions S -...
Testing for a break in persistence under long-range dependencies
Philipp Sibbertsen, Robinson Kruse
We show that tests for a break in the persistence of a time series in the classical I(0)/I(1) framework have serious size distortions when the actual data-generating process (DGP) exhibits long-range...
Testing for a break in persistence under long-range dependencies and mean shifts
Sibbertsen, Philipp, Willert, Juliane
We show that the CUSUM-squared based test for a change in persistence by Leybourne et al. (2007) is not robust against shifts in the mean. A mean shift leads to serious size distortions. Therefore,...
Testing for Long Memory Against ESTAR Nonlinearities
Kuswanto, Heri, Sibbertsen, Philipp
We develop a Wald type test to distinguish between long memory and ESTAR nonlinearity by using a directed-Wald statistic to overcome the problem of restricted parameters under the alternative. The...
What do we know about real exchange rate non-linearities?
Robinson Kruse, Michael Frömmel, Lukas Menkhoff, Philipp Sibbertsen
This research points to the serious problem of potentially misspecified alternative hypotheses when testing for unit roots in real exchange rates. We apply a popular unit root test against nonlinear...