Chi Tim Ng
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View article: Modile as a conservative tail risk measurer: the solution of an optimisation problem with 0-1 loss function
Modile as a conservative tail risk measurer: the solution of an optimisation problem with 0-1 loss function Open
Quantiles and expectiles, which are two important concepts and tools in tail risk measurements, can be regarded as an extension of median and mean, respectively. Both of these tail risk measurers can actually be embedded in a common framew…
View article: Mathematical Integration of Remotely-Sensed Information into a Crop Modelling Process for Mapping Crop Productivity
Mathematical Integration of Remotely-Sensed Information into a Crop Modelling Process for Mapping Crop Productivity Open
Remote sensing is a useful technique to determine spatial variations in crop growth while crop modelling can reproduce temporal changes in crop growth. In this study, we formulated a hybrid system of remote sensing and crop modelling based…
View article: Variable selection under multicollinearity using modified log penalty
Variable selection under multicollinearity using modified log penalty Open
To handle the multicollinearity issues in the regression analysis, a class of 'strictly concave penalty function' is described in this paper. As an example, a new penalty function called 'modified log penalty' is introduced. The penalized …
View article: Impacts of regional climate change on barley yield and its geographical variationin South Korea
Impacts of regional climate change on barley yield and its geographical variationin South Korea Open
1. Ahn J., Hur J., and Shim K., 2010. A simulation of the agro-climate index over the Korean Peninsula using dynamical downscaling with a numerical weather prediction model. Kor. J. Agric. Forest Meteorol., 12, 1-10. Google Scholar
View article: A descent algorithm for constrained LAD-Lasso estimation with applications in portfolio selection
A descent algorithm for constrained LAD-Lasso estimation with applications in portfolio selection Open
To improve the out-of-sample performance of the portfolio, Lasso regularization is incorporated to the Mean Absolute Deviance (MAD)-based portfolio selection method. It is shown that such a portfolio selection problem can be reformulated a…
View article: Computational explosion in the frequency estimation of sinusoidal data
Computational explosion in the frequency estimation of sinusoidal data Open
This paper highlights the computational explosion issues in the autoregressive moving average approach of frequency estimation of sinusoidal data with a large sample size. A new algorithm is proposed to circumvent the computational explosi…
View article: Portfolio selection based on asymmetric Laplace distribution, coherent risk measure, and expectation-maximization estimation
Portfolio selection based on asymmetric Laplace distribution, coherent risk measure, and expectation-maximization estimation Open
In this paper, portfolio selection problem is studied under Asymmetric Laplace Distribution(ALD) framework. Asymmetric Laplace distribution is able to capture tail-heaviness, skewness, andleptokurtosis observed in empirical financial data …
View article: Change-point estimators with true identification property
Change-point estimators with true identification property Open
The change-point problem is reformulated as a penalized likelihood estimation problem. A new non-convex penalty function is introduced to allow consistent estimation of the number of change points, and their locations and sizes. Penalized …
View article: A New Integral Representation of the Coverage Probability of a Random Convex Hull
A New Integral Representation of the Coverage Probability of a Random Convex Hull Open
In this paper, the probability that a given point is covered by a random convex hull generated by independent and identically-distributed random points in a plane is studied. It is shown that such probability can be expressed in terms of a…
View article: Likelihood inferences for high dimensional factor analysis of time series with applications in finance
Likelihood inferences for high dimensional factor analysis of time series with applications in finance Open
This paper investigates likelihood inferences for high-dimensional factor analysis of time series data. A matrix decomposition technique is developed to obtain expressions of the likelihood functions and its derivatives. With such expressi…
View article: Stochastic integral convergence: A white noise calculus approach
Stochastic integral convergence: A white noise calculus approach Open
By virtue of long-memory time series, it is illustrated in this paper that white noise calculus can be used to handle subtle issues of stochastic integral convergence that often arise in the asymptotic theory of time series. A main difficu…