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Book part
Publication date: 21 November 2014

Bruce E. Hansen

These moments of the asymptotic distribution of the least-squares estimator of the local-to-unity autoregressive model are computed using computationally simple…

Abstract

These moments of the asymptotic distribution of the least-squares estimator of the local-to-unity autoregressive model are computed using computationally simple integration. These calculations show that conventional simulation estimation of moments can be substantially inaccurate unless the simulation sample size is very large. We also explore the minimax efficiency of autoregressive coefficient estimation, and numerically show that a simple Stein shrinkage estimator has minimax risk which is uniformly better than least squares, even though the estimation dimension is just one.

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Essays in Honor of Peter C. B. Phillips
Type: Book
ISBN: 978-1-78441-183-1

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Book part
Publication date: 21 November 2014

Alex Maynard and Dongmeng Ren

We compare the finite sample power of short- and long-horizon tests in nonlinear predictive regression models of regime switching between bull and bear markets, allowing…

Abstract

We compare the finite sample power of short- and long-horizon tests in nonlinear predictive regression models of regime switching between bull and bear markets, allowing for time varying transition probabilities. As a point of reference, we also provide a similar comparison in a linear predictive regression model without regime switching. Overall, our results do not support the contention of higher power in longer horizon tests in either the linear or nonlinear regime switching models. Nonetheless, it is possible that other plausible nonlinear models provide stronger justification for long-horizon tests.

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Essays in Honor of Peter C. B. Phillips
Type: Book
ISBN: 978-1-78441-183-1

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Book part
Publication date: 21 November 2014

Yixiao Sun

New asymptotic approximations are established for the Wald and t statistics in the presence of unknown but strong autocorrelation. The asymptotic theory extends the usual…

Abstract

New asymptotic approximations are established for the Wald and t statistics in the presence of unknown but strong autocorrelation. The asymptotic theory extends the usual fixed-smoothing asymptotics under weak dependence to allow for near-unit-root and weak-unit-root processes. As the locality parameter that characterizes the neighborhood of the autoregressive root increases from zero to infinity, the new fixed-smoothing asymptotic distribution changes smoothly from the unit-root fixed-smoothing asymptotics to the usual fixed-smoothing asymptotics under weak dependence. Simulations show that the new approximation is more accurate than the usual fixed-smoothing approximation.

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Book part
Publication date: 13 December 2013

Nikolay Gospodinov, Ana María Herrera and Elena Pesavento

This article investigates the robustness of impulse response estimators to near unit roots and near cointegration in vector autoregressive (VAR) models. We compare…

Abstract

This article investigates the robustness of impulse response estimators to near unit roots and near cointegration in vector autoregressive (VAR) models. We compare estimators based on VAR specifications determined by pretests for unit roots and cointegration as well as unrestricted VAR specifications in levels. Our main finding is that the impulse response estimators obtained from the levels specification tend to be most robust when the magnitude of the roots is not known. The pretest specification works well only when the restrictions imposed by the model are satisfied. Its performance deteriorates even for small deviations from the exact unit root for one or more model variables. We illustrate the practical relevance of our results through simulation examples and an empirical application.

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VAR Models in Macroeconomics – New Developments and Applications: Essays in Honor of Christopher A. Sims
Type: Book
ISBN: 978-1-78190-752-8

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Book part
Publication date: 21 November 2014

Kyungchul Song

When a parameter of interest is nondifferentiable in the probability, the existing theory of semiparametric efficient estimation is not applicable, as it does not have an…

Abstract

When a parameter of interest is nondifferentiable in the probability, the existing theory of semiparametric efficient estimation is not applicable, as it does not have an influence function. Song (2014) recently developed a local asymptotic minimax estimation theory for a parameter that is a nondifferentiable transform of a regular parameter, where the transform is a composite map of a continuous piecewise linear map with a single kink point and a translation-scale equivariant map. The contribution of this paper is twofold. First, this paper extends the local asymptotic minimax theory to nondifferentiable transforms that are a composite map of a Lipschitz continuous map having a finite set of nondifferentiability points and a translation-scale equivariant map. Second, this paper investigates the discontinuity of the local asymptotic minimax risk in the true probability and shows that the proposed estimator remains to be optimal even when the risk is locally robustified not only over the scores at the true probability, but also over the true probability itself. However, the local robustification does not resolve the issue of discontinuity in the local asymptotic minimax risk.

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Book part
Publication date: 19 December 2012

Badi H. Baltagi, Chihwa Kao and Long Liu

This chapter studies the asymptotic properties of within-groups k-class estimators in a panel data model with weak instruments. Weak instruments are characterized by the…

Abstract

This chapter studies the asymptotic properties of within-groups k-class estimators in a panel data model with weak instruments. Weak instruments are characterized by the coefficients of the instruments in the reduced form equation shrinking to zero at a rate proportional to nTδ, where n is the dimension of the cross-section and T is the dimension of the time series. Joint limits as (n,T)→∞ show that this within-group k-class estimator is consistent if 0≤δ<12 and inconsistent if 12≤δ<∞.

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30th Anniversary Edition
Type: Book
ISBN: 978-1-78190-309-4

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Book part
Publication date: 15 April 2020

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Essays in Honor of Cheng Hsiao
Type: Book
ISBN: 978-1-78973-958-9

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Book part
Publication date: 21 November 2014

Abstract

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Essays in Honor of Peter C. B. Phillips
Type: Book
ISBN: 978-1-78441-183-1

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Book part
Publication date: 16 December 2009

Zongwu Cai and Yongmiao Hong

This paper gives a selective review on some recent developments of nonparametric methods in both continuous and discrete time finance, particularly in the areas of…

Abstract

This paper gives a selective review on some recent developments of nonparametric methods in both continuous and discrete time finance, particularly in the areas of nonparametric estimation and testing of diffusion processes, nonparametric testing of parametric diffusion models, nonparametric pricing of derivatives, nonparametric estimation and hypothesis testing for nonlinear pricing kernel, and nonparametric predictability of asset returns. For each financial context, the paper discusses the suitable statistical concepts, models, and modeling procedures, as well as some of their applications to financial data. Their relative strengths and weaknesses are discussed. Much theoretical and empirical research is needed in this area, and more importantly, the paper points to several aspects that deserve further investigation.

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Nonparametric Econometric Methods
Type: Book
ISBN: 978-1-84950-624-3

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Article
Publication date: 17 March 2021

Rattaphon Wuthisatian

The study examines the existence of calendar anomalies, including the day-of-the-week (DOW) effect and the January effect, in the Stock Exchange of Thailand.

Abstract

Purpose

The study examines the existence of calendar anomalies, including the day-of-the-week (DOW) effect and the January effect, in the Stock Exchange of Thailand.

Design/methodology/approach

Using daily stock returns from March 2014 to March 2019, the study performs regression analysis to examine predictable patterns in stock returns, the DOW effect and the January effect, respectively.

Findings

There is strong evidence of a persistent monthly pattern and weekday seasonality in the Thai stock market. Specifically, Monday returns are negative and significantly lower than the returns on other trading days of the week, and January returns are positive and significantly higher than the returns on other months of the year.

Practical implications

The findings offer managerial implications for investors seeking trading strategies to maximize the possibility of reaching investment goals and inform policymakers regarding the current state of the Thai stock market.

Originality/value

First, the study investigates calendar anomalies in the Thai stock market, specifically the DOW effect and the January effect, which have received relatively little attention in the literature. Second, this is the first study to examine calendar anomalies in the Thai stock market across different groups of companies and stock trading characteristics using a range of composite indexes. Furthermore, the study uses data during the period 2014–2019, which should provide up-to-date information on the patterns of stock returns in Thailand.

Details

Journal of Economic Studies, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0144-3585

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