New variance ratio tests to identify random walk from the general mean reversion model

Lam, K. C.; Wong, May Chun Mei; Wong, Wing Keung

doi:10.1155/jamds/2006/12314

Cited by 15 publications

(13 citation statements)

References 61 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Promoters of behavioral biases, see, for example, Wong (2010, 2011, henceforth LLW) and the references therein developed several behavioral models to explain the overreaction and underreaction phenomena. In contrast with the efficient market theory (Lam, Wong, and Wong, 2006;Lean, McAleer, and Wong, 2010), these models suggest that sophisticated investors may earn superior returns by taking advantage of underreaction and overreaction without assuming extra risk.…”

Section: Introductionmentioning

confidence: 85%

A Pseudo-Bayesian Model for Stock Returns In Financial Crises

Fung

Lam

Siu

et al. 2011

JRFM

Self Cite

View full text Add to dashboard Cite

Recently, there has been a considerable interest in the Bayesian approach for explaining investors' behaviorial biases by incorporating conservative and representative heuristics when making financial decisions, (see, for example, Barberis, Shleifer and Vishny (1998)). To establish a quantitative link between some important market anomalies and investors' behaviorial biases, Lam, Liu, and Wong (2010) introduced a pseudo-Bayesian approach for developing properties of stock returns, where weights induced by investors' conservative and representative heuristics are assigned to observations of the earning shocks and stock prices. In response to the recent global financial crisis, we introduce a new pseudo-Bayesian model to incorporate the impact of a financial crisis. Properties of stock returns during the financial crisis and recovery from the crisis are established. The proposed model can be applied to investigate some important market anomalies including short-term underreaction, long-term overreaction, and excess volatility during financial crisis. We also explain in some detail the linkage between these market anomalies and investors' behavioral biases during financial crisis

show abstract

Section: Introductionmentioning

confidence: 85%

A Pseudo-Bayesian Model for Stock Returns In Financial Crises

Fung

Lam

Siu

et al. 2011

JRFM

Self Cite

View full text Add to dashboard Cite

show abstract

“…Penm, Terrell, Wong (2003) present simulations and an application that demonstrates the usefulness of the zero-non-zero patterned vector error-correction models (VECMs). Lam, Wong, and Wong (2006) develop some properties on the autocorrelation of the k-period returns for the general mean reversion (GMR) process in which the stationary component is not restricted to the AR(1) process but takes the form of a general ARMA process. Bai, Wong, and Zhang (2010) develop a nonlinear causality test in multivariate settings.…”

Section: Statistical and Econometric Modelsmentioning

confidence: 99%

Optimal Solution Techniques in Decision Sciences: A Review

Pho

Tran

et al. 2019

SSRN Journal

Self Cite

View full text Add to dashboard Cite

Methods to find the optimization solution are fundamental and extremely crucial for scientists to program computational software to solve optimization problems efficiently and for practitioners to use it efficiently. Thus, it is very essential to know about the idea, origin, and usage of these methods. Although the methods have been used for very long time and the theory has been developed too long, most, if not all, of the authors who develop the theory are unknown and the theory has not been stated clearly and systematically. To bridge the gap in the literature in this area and provide academics and practitioners with an overview of the methods, this paper reviews and discusses the four most commonly used methods to find the optimization solution including the bisection, gradient, Newton-Raphson, and secant methods. We first introduce the origin and idea of the methods and develop all the necessary theorems to prove the existence and convergence of the estimate for each method.We then give two examples to illustrate the approaches. Thereafter, we review the literature of the applications of getting the optimization solutions in some important issues and discuss the advantages and disadvantages of each method. We note that all the theorems developed in our paper could be well-known but, so far, we have not seen any book or paper that discusses all the theorems stated in our paper in detail. Thus, we believe the theorems developed in our paper could still have some contributions to the literature. Our review is useful for academics and practitioners in finding the optimization solutions in their studies.

show abstract

“…present simulations and an application that demonstrate the usefulness of the ZNZ patterned VECM. Lam et al (2006) develop some properties on the autocorrelation of the k-period returns for the general mean reversion (GMR) process, in which the stationary component is not restricted to the AR(1) process but takes the form of a general autoregressive-moving-average (ARMA) process. The authors derive some properties of the GMR process and three new nonparametric tests that compare the relative variability of returns over different horizons to validate the GMR process as an alternative to a random walk.…”

Section: Unit Roots Cointegration Causality Tests and Nonlinearitymentioning

confidence: 99%

Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections

Chang

McAleer

Wong

2018

JRFM

Self Cite

View full text Add to dashboard Cite

Abstract:The paper provides a review of the literature that connects Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology, and discusses research issues that are related to the various disciplines. Academics could develop theoretical models and subsequent econometric and statistical models to estimate the parameters in the associated models, as well as conduct simulation to examine whether the estimators in their theories on estimation and hypothesis testing have good size and high power. Thereafter, academics and practitioners could apply theory to analyse some interesting issues in the seven disciplines and cognate areas.

show abstract

New variance ratio tests to identify random walk from the general mean reversion model

Cited by 15 publications

References 61 publications

A Pseudo-Bayesian Model for Stock Returns In Financial Crises

A Pseudo-Bayesian Model for Stock Returns In Financial Crises

Optimal Solution Techniques in Decision Sciences: A Review

Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections

Contact Info

Product

Resources

About