• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.157-169
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• 2016

We compare four methods to estimate a regression coefficient under linear regression models with serially correlated errors. We assume that regression errors are generated with nonlinear autoregressive models. The four methods are: ordinary least square estimator, general least square estimator, parametric regression error correction method, and nonparametric regression error correction method. We also discuss some properties of nonlinear autoregressive models by presenting numerical studies with typical examples. Our numerical study suggests that no method dominates; however, the nonparametric regression error correction method works quite well.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.3
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• pp.19-29
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• 2018

This research examined the alternatives of Jensen's alpha (α) estimation models in the Capital Asset Pricing Model, discussed by Treynor (1961), Sharpe (1964), and Lintner (1965), using the robust maximum likelihood type m-estimator (MM estimator) and Bayes estimator with conjugate prior. According to finance literature and practices, alpha has often been estimated using ordinary least square (OLS) regression method and monthly return data set. A sample of 50 securities is randomly selected from the list of the S&P 500 index. Their daily and monthly returns were collected over a period of the last five years. This research showed that the robust MM estimator performed well better than the OLS and Bayes estimators in terms of efficiency. The Bayes estimator did not perform better than the OLS estimator as expected. Interestingly, we also found that daily return data set would give more accurate alpha estimation than monthly return data set in all three MM, OLS, and Bayes estimators. We also proposed an alternative market efficiency test with the hypothesis testing Ho: α = 0 and was able to prove the S&P 500 index is efficient, but not perfect. More important, those findings above are checked with and validated by Jackknife resampling results.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.1
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• pp.74-82
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• 2011

The Bass model is a cornerstone in diffusion theory which is used for forecasting demand of durables or new services. Three well-known estimation methods for parameters of the Bass model are Ordinary Least Square (OLS), Maximum Likelihood Estimator (MLE), Nonlinear Least Square (NLS). In this paper, a hybrid method incorporating OLS and NLS is presented and it's performance is analyzed and compared with OLS and NLS by using simulation data and empirical data. The results show that NLS has the best performance in terms of accuracy and our hybrid method has the best performance in terms of stability. Specifically, hybrid method has better performance with less data. This result means much in practical aspect because the avaliable data is little when a diffusion model is used for forecasting demand of a new product.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.263-276
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• 2021

This study examines the effect of international capital flows on corporate capital structures in Vietnam by analyzing panel data from all non-financial listed firms from 2005 to 2014 using pooled ordinary least square (OLS) with a variance estimator. The analysis includes a comparison of the signs and significance of the variable coefficients from the perking order and static trade-off theories to the empirical results to determine the optimum approach to the corporate capital structure given Vietnam's high-inflation environment. The results indicate that international capital flows have a positive relation to the debt ratio in the long term, and the relationship is more robust for 2005-2009 than for 2010-2014. Corporate capital structures adjusted to changes in the business environment in different sub-periods (2005-2009 and 2010-2014). When the economic environment became more favorable, the pecking order theory's predictive power increased, and that of trade-off theory lessened. Manufacturing and non-manufacturing firms required different capital structure decisions to fuel their operations and grow under foreign competition. The analysis demonstrates that firms should intensify their use of long-term debt relative to the availability of capital, which is an implication not only for firms in particular but also for industrial innovation overall.