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Exogeneity Tests, Incomplete Models, Weak Identification and Non-Gaussian Distributions : Invariance and Finite-Sample Distributional Theory
Doko Tchatoka, Firmin - 2017
We study the distribution of Durbin-Wu-Hausman (DWH) and Revankar-Hartley (RH) tests for exogeneity from a finite-sample viewpoint, under the null and alternative hypotheses. We consider linear structural models with possibly non-Gaussian errors, where structural parameters may not be identified...
Persistent link: https://www.econbiz.de/10012966708
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Consistent pretesting for jumps
Corradi, Valentina; Silvapulle, Mervyn J.; Swanson, … - 2014
If the intensity parameter in a jump diffusion model is identically zero, then parameters characterizing the jump size density cannot be identified. In general, this lack of identification precludes consistent estimation of identified parameters. Hence, it should be standard practice to...
Persistent link: https://www.econbiz.de/10010361470
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A smooth permanent surge process
González, Andrés - 2004
In this paper we introduce the Smooth Permanent Surge [SPS] model. The model is an integrated non lineal moving average process with possibly unit roots in the moving average coefficients. The process nests the Stochastic Permanent Break [STOPBREAK] process by Engle and Smith (1999) and in a...
Persistent link: https://www.econbiz.de/10010281224
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A smooth permanent surge process
González, Andrés (contributor) - 2004 - [Elektronische Ressource]
In this paper we introduce the Smooth Permanent Surge [SPS] model. The model is an integrated non lineal moving average process with possibly unit roots in the moving average coefficients. The process nests the Stochastic Permanent Break [STOPBREAK] process by Engle and Smith (1999) and in a...
Persistent link: https://www.econbiz.de/10002465176
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Bootstrapping laplace transforms of volatility
Hounyo, Ulrich; Liu, Zhi; Varneskov, Rasmus Tangsgaard - In: Quantitative economics : QE ; journal of the … 14 (2023) 3, pp. 1059-1103
bootstrap methods. Specifically, since standard wild bootstrap procedures deliver inconsistent inference, we propose a local … Gaussian (LG) bootstrap, establish its first‐order asymptotic validity, and use Edgeworth expansions to show that the LG … bootstrap inference achieves second‐order asymptotic refinements. Moreover, we provide new Laplace transform‐based estimators of …
Persistent link: https://www.econbiz.de/10014362565
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Presentation - Stock Market Layering Fraud as a Stochastic Optimal Stopping Problem
Qureshi, Faisal - 2019
The proliferation of algorithmic high-frequency trading in financial markets has also led to an increase in new types of fraudulent activity. Since the flash-crash of 2010 first brought it to popular prominence, layering or spoofing fraud has become a major concern for financial regulators...
Persistent link: https://www.econbiz.de/10012891797
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Stationarity Testing Under Endogenous Smooth Deterministic Components : Some Asymptotic Results
Landajo, Manuel - 2008
distribution depends on the unknown parameters of the model. Bootstrap techniques permit this problem to be circumvented, and the …
Persistent link: https://www.econbiz.de/10012725818
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Testing for restricted stochastic dominance
Davidson, Russell (contributor);  … - 2006
Asymptotic and bootstrap tests are studied for testing whether there is a relation of stochastic dominance between two … be used to perform bootstrap tests that can turn out to provide much improved reliability of inference compared with the … asymptotic tests so far proposed in the literature. -- stochastic dominance ; empirical likelihood ; bootstrap test …
Persistent link: https://www.econbiz.de/10003301664
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Non-parametric stochastic simulations to investigate uncertainty around the OECD indicator model forecasts
Rusticelli, Elena - 2012
The forecasting uncertainty around point macroeconomic forecasts is usually measured by the historical performance of the forecasting model, using measures such as root mean squared forecasting errors (RMSE). This measure, however, has the major drawback that it is constant over time and hence...
Persistent link: https://www.econbiz.de/10009690936
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Nonparametric inference for second order stochastic dominance
Schmid, Friedrich; Trede, Mark - 1996
This paper deals with nonparametric inference for second order stochastic dominance of two random variables. If their distribution functions are unknown they have to be inferred from observed realizations. Thus, any results on stochastic dominance are influenced by sampling errors. We establish...
Persistent link: https://www.econbiz.de/10008992397