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查看斯高帕斯 (Scopus) 概要
戴 天時
教授
資訊管理與財務金融學系
https://orcid.org/0000-0002-9226-3056
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(03)5712121#57054
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cameldai
mail.nctu.edu
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353
引文
10
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2002
2025
每年研究成果
概覽
指紋
網路
計畫
(31)
研究成果
(69)
獎項
(9)
活動
(1)
類似的個人檔案
(3)
指紋
查看啟用 Tian-Shyr Dai 的研究主題。這些主題標籤來自此人的作品。共同形成了獨特的指紋。
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Keyphrases
Asian Options
100%
Pairs Trading Strategy
93%
Option Pricing
81%
Barrier Options
79%
Lattice Algorithms
76%
Popular
66%
Tree Model
65%
Issuer
54%
Option Value
53%
Pricing Algorithm
53%
Jump-diffusion Process
50%
Fraud Detection
50%
Stock Prices
45%
Pairs Trading
43%
Discrete Dividends
43%
Double Barrier Option
43%
Pricing Formulae
41%
Stock Options
40%
Numerical Experiments
40%
Subexponential
39%
Corporate Bonds
37%
Deep Reinforcement Learning (deep RL)
37%
Lattice Model
35%
Dividend Payout
34%
Underlying Asset
34%
Mortality Risk
33%
Trading Performance
33%
Nonlinear Error
32%
Portfolio Values
32%
Transaction Data
31%
Price Level
29%
Financial Markets
29%
Convertible Bonds
29%
Arithmetic Average
29%
Pricing Derivatives
29%
Orientation Estimation
29%
Estimation Algorithms
29%
Machine Learning Models
29%
Fraud
28%
Numerical Methods
27%
Fingerprint Enhancement
27%
Capital Structure
27%
Analytical Formula
27%
Guaranteed Minimum Withdrawal Benefits
27%
Stop-loss
27%
Numerical Results
26%
Anisotropic Filtering
25%
Structural Breaks
25%
Asset Pricing
25%
Cloud Asset
25%
Computer Science
Option Pricing
79%
Approximation (Algorithm)
68%
Fraud Detection
62%
Continuous Time
60%
Barrier Option
50%
Diffusion Process
40%
Machine Learning
39%
Learning System
39%
Mathematical Method
37%
Monte Carlo Simulation
31%
Transaction Data
31%
Fingerprint Image
27%
Data Synthesis
25%
Binomial Lattice
25%
Experimental Result
25%
Customer Relationship
25%
Graph Neural Network
25%
Sampling Algorithm
25%
Network Option
25%
Deep Learning Method
25%
Value at Risk
25%
Neural Network
25%
Importance Sampling
25%
Deep Reinforcement Learning
25%
Underlying Asset
24%
Time Complexity
21%
Extreme Gradient Boosting
20%
Detection Performance
20%
Autoencoder
18%
Approximation Algorithms
18%
Lagrange Multiplier Method
17%
Computational Time
16%
Feature Generation
16%
Function Value
15%
Anomaly Detection
14%
Superior Performance
12%
Numerical Calculation
12%
co-integration
12%
Fast Fourier Transform
12%
Electronic Transfer
12%
Payoff Function
12%
Domain Feature
12%
Mean Algorithm
12%
Multiscale Residual Network
12%
Optimization Framework
12%
Recognition System
12%
Exact Algorithm
12%
Computational Resource
12%
Discretization Error
12%
Preprocessing Step
12%
