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Optimal Formulations for Nonlinear Autoregressive Processes
Blasques, Francisco - 2014
theoretic optimality of the score driven nonlinear autoregressive process and the asymptotic theory for maximum likelihood …
Persistent link: https://www.econbiz.de/10013049359
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On the validity of tests for asymmetry in residual-based threshold cointegration models
Schild, Karl-Heinz; Schweikert, Karsten - In: Econometrics : open access journal 7 (2019) 1/12, pp. 1-13
This paper investigates the properties of tests for asymmetric long-run adjustment which are often applied in empirical studies on asymmetric price transmissions. We show that substantial size distortions are caused by preconditioning the test on finding sufficient evidence for cointegration in...
Persistent link: https://www.econbiz.de/10012025641
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Testing for cointegration with threshold adjustment in the presence of structural breaks
Schweikert, Karsten - 2018
In this paper, we develop new threshold cointegration tests with SETAR and MTAR adjustment allowing for the presence of structural breaks in the equilibrium equation. We propose a simple procedure to simultaneously estimate the previously unknown breakpoint and test the null hypothesis of no...
Persistent link: https://www.econbiz.de/10011842010
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Spillover dynamics for systemic risk measurement using spatial financial time series models
Blasques, Francisco; Koopman, Siem Jan; Lucas, André; … - 2014
We introduce a new model for time-varying spatial dependence. The model extends the well-known static spatial lag model. All parameters can be estimated conveniently by maximum likelihood. We establish the theoretical properties of the model and show that the maximum likelihood estimator for the...
Persistent link: https://www.econbiz.de/10010391531
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Adaptive rate-optimal detection of small autocorrelation coefficient
Guay, Alain; Guerre, Emmanuel; Lazarová, Štepána - 2009
A new test is proposed for the null of absence of serial correlation. The test uses a data-driven smoothing parameter. The resulting test statistic has a standard limit distribution under the null. The smoothing parameter is calibrated to achieve rate-optimality against several classes of...
Persistent link: https://www.econbiz.de/10003850599
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Testing for vector autoregressive dynamics under heteroskedasticity
Hafner, Christian M.; Herwartz, Helmut - 2002
In this paper we introduce a bootstrap procedure to test parameter restrictions in vector autoregressive models which is robust in cases of conditionally heteroskedastic error terms. The adopted wild bootstrap method does not require any parametric specification of the volatility process and...
Persistent link: https://www.econbiz.de/10009663846
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Predicting bid-ask spreads using long memory autoregressive conditional poisson models
Groß-Klußmann, Axel; Hautsch, Nikolaus - 2011 - This version: July 2011
that the LMACP nicely captures salient features of bid-ask spreads like the strong autocorrelation and discreteness of …
Persistent link: https://www.econbiz.de/10009229669
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Autocorrelate Your Assets or, It's Not All White Noise : A Practical Means for Generating Autocorrelated Time Series Data in Monte Carlo Simulations
Stock, Robert D. - 2020
compromises the quality of the prediction from the data. Simulations that do not take account of autocorrelation will not properly … model reality, as there is significant autocorrelation in many asset returns, for example in T-Bills and hedge fund … satisfy the statistics of any serial autocorrelation, as well as the actual (possibly non-Gaussian) joint probability …
Persistent link: https://www.econbiz.de/10012846361
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Dynamic Spatial Network Quantile Autoregression
Xu, Xiu - 2020
, and the associated asymptotic theory for estimation is also provided. Simulation results show that our model performs well …
Persistent link: https://www.econbiz.de/10012823437
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Volatility Spillovers and Heavy Tails : A Large T-Vector Autoregressive Approach
Barbaglia, Luca - 2017
Volatility is a key measure of risk in financial analysis. The high volatility of one financial asset today could affect the volatility of another asset tomorrow. These lagged effects among volatilities - which we call volatility spillovers - are studied using the Vector AutoRegressive (VAR)...
Persistent link: https://www.econbiz.de/10012943774