Time-series average ∆CoVaR and VaR estimates
Quantile Sieve Estimates For Time Series
... 5. Simulations and applications In this section, we first apply nonparametric quantile sieve estimates to some arti- ficially generated data. As approximating function classes, we use feedforward neural networks as ...
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CoVaR
... against VaR for 240 portfolios, grouped by 60 portfolios for each of the four financial ...and VaR have only a weak relationship in the cross ...the time series. This can be seen in Figure ...
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Time Series Estimates of the Italian Consumer Confidence Indicator
... At most 3 0.01 Notes: *** Significance at 10%; **Significance at 5%. EG = Engle-Granger t-test for cointegration. SL = Saikkonen and Lutkepohl (2000a, b, c) test for the cointegrating rank of a VAR process. FMOLS ...
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Time Series Estimates of the Italian Consumer Confidence Indicator
... At most 3 0.01 Notes: *** Significance at 10%; **Significance at 5%. EG = Engle-Granger t-test for cointegration. SL = Saikkonen and Lutkepohl (2000a, b, c) test for the cointegrating rank of a VAR process. FMOLS ...
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Nonparametric Estimate for Conditional Quantiles of Time Series: An application for VaR
... CaViaR estimates have the highest maximum value, while the parametric quantile regression have the lowest minimum value, as compared to the other two implemented ...
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Censored time series analysis with autoregressive moving average models
... Time series measurements are often observed with data irregularities, ...biased estimates when we implement classical analysis tools that ignore ...
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Estimates of Average Inelastic Deformation Demands for Regular Steel Frames by the Endurance Time Method
... Endurance Time (ET) method is a new dynamic pushover procedure in which structures are subjected to gradually intensifying acceleration functions and their performance is assessed based on the length of the ...
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On Multivariate Time Series Model Selection Involving Many Candidate VAR Models
... We can certainly apply these two ways to perform the model selection, however, in this paper we will propose another more efficient method. Now consider the marginal distribution of an individual component of V which ...
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Time Series Analysis of Wind Speed Using VAR and the Generalized Impulse Response Technique
... the VAR may be estimated using ordinary least squares regression which produces unbiased and asymptotically efficient estimates since all the regressors are predetermined and provided that the error term is ...
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Regional Output Spillovers in China: Estimates from a VAR Model
... countries converge to the same level of income per capita. Convergence is achieved by poor countries growing more rapidly so that eventually they catch up with their richer rivals. The initial tests of convergence were ...
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Student Enrolment and Output Effects in Poland: 2SLS and VAR Estimates
... and VAR/VEC estimates are in firm support of the stock version (the Nelson-Phelps approach) of the higher education effects on output, while the evidence of the investment version (neoclassical model) are ...
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Short Term Forecasting Performances of Classical VAR and Sims Zha Bayesian VAR Models for Time Series with Collinear Variables and Correlated Error Terms
... classical VAR and Bayesian VAR for time series with collinear variables and correlated error terms in the short ...corresponding estimates of the regression coefficient ...
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Trend Analysis with Effective Covariates Based On Auto Regressive- Moving Average Time Series Residuals
... parametric estimates, which are simple to ...selected time varying regression model follows a pattern that suggest ARMA ...a time series which is the series of changes from one period ...
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Order identification and estimation of moving average and auto-regressive dynamic models for count time series
... Time series analysis of count data is a dynamic research area which has attracted the attention of researchers over the last few ...of time series analysis such as, identifying the nature of ...
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VAR Estimates of the Housing and Stock Wealth Effects: Cross-country Evidence
... structural VAR model to analyze the relationship between consumption, income, and stock and housing ...to time series data of eight developed ...our estimates imply an immediate MPC of 8 ∼ 9 ...
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Forecasting Performances of the Reduced Form VAR and Sims-Zha Bayesian VAR Models when the Multiple Time Series are Jointly Influenced by Collinearity and Autocorrelated Error
... 11 different from the posterior mean. They also proposed an algorithm that uses generated data as latent variables in numerical simulation of Bayesian estimates under loss entropy loss. However, in recent times, ...
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Long Memory Analysis of Daily Average Temperature Time Series
... a series as long memory based on a slowly declining autocorrelation structure, “Such autocorrelation structure suggests that the process must depend strongly upon values of time series far away from ...
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Estimates by bootstrap interval for time series forecasts obtained by theta model
... for time series forecasting called Theta, and implementation of resampling technique known as computer intensive "bootstrap" to estimate the prediction for the point forecast obtained by this method ...
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The Asymptotic Distribution of Nonparametric Estimates of the Lyapunov Exponent for Stochastic Time Series
... References in publications to Discussion Papers (other than mere acknowledgment by a writer that he has access to such unpublished material) should be cleared with the author to prot[r] ...
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Omitted Variable Bias in Time Series Estimates of Capital Gains Realizations
... realizations by implementing a simple model to allow for the effects of potentially omitted variables in time series equations. I jointly estimate contemporaneous capital gains realizations of individuals ...
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