Projects per year
Personal profile
Research Interests
Financial Statistics, Statistical Computing, Bayesian Inference, Financial Eengineering
Experience
2017/2~present Associate Professor, Department of Information Management and Finance
Education/Academic qualification
PhD, Statistics, Pennsylvania State University
External positions
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Collaborations and top research areas from the last five years
Projects
- 9 Finished
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加密貨幣選擇權的定價與避險
Teng, H.-W. (PI)
1/08/22 → 31/07/23
Project: Government Ministry › Other Government Ministry Institute
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蒙地卡羅模擬方法在傳統財務問題與金融科技
Teng, H.-W. (PI)
1/08/21 → 31/10/22
Project: Government Ministry › Other Government Ministry Institute
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Machine Llearning in Financial Technology: Large Portfolio Management and Delinquency Risk Prediction
Teng, H.-W. (PI)
1/08/20 → 31/10/21
Project: Government Ministry › Other Government Ministry Institute
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Artificial Intelligence And Its Application On Derivatives Pricing
Teng, H.-W. (PI)
1/01/20 → 31/12/20
Project: Government Ministry › Other Government Ministry Institute
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Machine Llearning in Financial Technology: Large Portfolio Management and Delinquency Risk Prediction
Teng, H.-W. (PI)
1/08/19 → 31/10/20
Project: Government Ministry › Other Government Ministry Institute
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Bridging accuracy and interpretability: A rescaled cluster-then-predict approach for enhanced credit scoring
Teng, H. W., Kang, M. H., Lee, I. H. & Bai, L. C., Jan 2024, In: International Review of Financial Analysis. 91, 103005.Research output: Contribution to journal › Article › peer-review
6 Scopus citations -
Comparisons between the Markowitz model and the black-litterman model
Teng, H. W., 8 Apr 2024, Handbook Of Investment Analysis, Portfolio Management, And Financial Derivatives (In 4 Volumes). World Scientific Publishing Co., Vol. 3-4. p. 2727-2750 24 p.Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
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Machine learning methods for predicting failures of US commercial bank
Tuan, L. Q., Lin, C. Y. & Teng, H. W., 2024, In: Applied Economics Letters. 31, 15, p. 1353-1359 7 p.Research output: Contribution to journal › Article › peer-review
1 Scopus citations -
Can deep neural networks outperform Fama-MacBeth regression and other supervised learning approaches in stock returns prediction with asset-pricing factors?
Teng, H. W. & Li, Y. H., Mar 2023, In: Digital Finance. 5, 1, p. 149-182 34 p.Research output: Contribution to journal › Article › peer-review
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Importance Sampling for Calculating the Value-at-Risk and Expected Shortfall of the Quadratic Portfolio with t-Distributed Risk Factors
Teng, H. W., 2022, (Accepted/In press) In: Computational Economics.Research output: Contribution to journal › Article › peer-review
1 Scopus citations