R. Hwang

发表

A semiparametric method for predicting bankruptcy

Jack C. Lee, R. Hwang, K. Cheng, 2007 .

Predicting the Loss Given Default Distribution with the Zero-Inflated Censored Beta-Mixture Regression that Allows Probability Masses and Bimodality

C. Chu, R. Hwang, Kaizhi Yu, 2020 .

On multiple-class prediction of issuer credit ratings

Cheng-Few Lee, Ruey-Ching Hwang, Cheng-Few Lee, 2009 .

A NEW VERSION OF THE LOCAL CONSTANT M-SMOOTHER

R. Hwang, 2002 .

Forecasting Forward Defaults with the Discrete‐Time Hazard Model

C. Chu, R. Hwang, 2014 .

Forecasting forward defaults: a simple hazard model with competing risks

C. Chu, R. Hwang, 2014 .

Predicting Recovery Rate at the Time of Corporate Default

J. Duan, R. Hwang, 2014 .

Predicting Loss Distributions for Small-Size Defaulted-Debt Portfolios Using a Convolution Technique that Allows Probability Masses to Occur at Boundary Points

C. Chu, R. Hwang, 2018, Journal of Financial Services Research.

Predicting credit ratings and transition probabilities: a simple cumulative link model with firm-specific frailty

C. Chu, Yi-Chi Chen, R. Hwang, 2022, Quantitative Finance.

Predicting the Loss Given Default Distribution with the Zero-Inflated Censored Beta-Mixture Regression that Allows Probability Masses and Bimodality

C. Chu, R. Hwang, Kaizhi Yu, 2020, Journal of Financial Services Research.

A Two-Stage Probit Model for Predicting Recovery Rates

R. Hwang, Huimin Chung, C. Chu, 2015, Journal of Financial Services Research.

Predicting bankruptcy using the discrete-time semiparametric hazard model

C. K. Chu, Kuang Fu Cheng, Ruey-Ching Hwang, 2010 .

Predicting recovery rates using logistic quantile regression with bounded outcomes

Ruey-Ching Hwang, Jhao-Siang Siao, C. Chu, 2016 .

DOUBLE SMOOTHING ESTIMATION OF THE MULTIVARIATE REGRESSION FUNCTION IN NONPARAMETRIC REGRESSION

R. Hwang, Mei-Lien Ken, 2002 .

Using the Box-Cox Power Transformation to Predict Temporally Correlated Longitudinal Data

Ruey-Ching Hwang, R. Hwang, 2004, Journal of Data Science.

Predicting issuer credit ratings using generalized estimating equations

R. Hwang, 2013 .

Heterogeneity in the relationship between subjective well-being and its determinants over the life cycle: A varying-coefficient ordered probit approach

R. Hwang, Yi-Chen Lin, Wen-Shuenn Deng, 2015 .

Predicting issuer credit ratings using a semiparametric method

C. K. Chu, Huimin Chung, Ruey-Ching Hwang, 2010 .

Predicting LGD distributions with mixed continuous and discrete ordinal outcomes

C. Chu, R. Hwang, Kaizhi Yu, 2020 .

Predicting Loss Distributions for Small-Size Defaulted-Debt Portfolios Using a Convolution Technique that Allows Probability Masses to Occur at Boundary Points

C. Chu, R. Hwang, 2018, Journal of Financial Services Research.

A logistic regression point of view toward loss given default distribution estimation

C. Chu, R. Hwang, 2018 .

A Two-Stage Probit Model for Predicting Recovery Rates

C. K. Chu, Huimin Chung, Ruey-Ching Hwang, 2016 .

Assessing bankruptcy prediction models via information content of technical inefficiency

C. K. Chu, Huimin Chung, Ruey-Ching Hwang, 2011 .

On estimation and prediction for temporally correlated longitudinal data

Jack C. Lee, R. Hwang, 2000 .

Local polynomial M-smoothers in nonparametric regression

Ruey-Ching Hwang, R. Hwang, 2004 .

Does the Local Rating Agency Provide ReliableCredit Ratings? An Empirical Analysis from an Emerging Market

R. Hwang, Huimin Chung, Chia-Liang Lin, 2012, The Journal of Fixed Income.

Predicting Recurrent Financial Distresses with Autocorrelation Structure: An Empirical Analysis from an Emerging Market

R. Hwang, Huimin Chung, J. Ku, 2013 .

A varying-coefficient default model

Ruey-Ching Hwang, R. Hwang, 2012 .