I Love Trading Laboratory
I Love Trading Laboratory
Lab Location:
Room 946, Hung Yu Technology Research Building
Lab Director/Supervisor:
Professor Mu-En Wu
Contact Phone:
(02) 2771-2171 #5906
E-mail:
mnwu@ntut.edu.tw
Research Areas:
Financial Data Analysis, Fund Management, Market Prediction, Information Theory, Cryptography
The I Love Trading Laboratory is dedicated to research and development in the areas of "Trading Strategy" and "Financial Management Theory and Practice."
We are a warm, united, diligent, and joyful laboratory, with members from diverse backgrounds such as information technology, finance, and mathematics. Under the guidance of Professor Wu, we work as compatible, trusting, and supportive partners.
Welcome to join us!
➝ https://ilovetradinglab.tw/For any further inquiries, please feel free to contact us.
➝ ilovetradinglab@gmail.com
The I Love Trading Lab is dedicated to two main themes:
1. Trading strategy research and development
2. Theory and practice of capital management
Themes of trading strategies include:
Day trading, Swing trading, Trend following, Contrarian trading, Pair trading, Portfolio management, Options strategies, Risk management, Momentum effects, Volatility forecasting, Trading psychology
Research instruments include:
TAIEX futures, Electronic futures, Financial futures, TAIEX options, Taiwan stocks, Stock futures, Warrants, Overseas futures
We do not engage in meaningless research. In addition to writing papers for publication, our research results are also subjected to real trades or practical exercises, undergoing market scrutiny, and some performance is publicly showcased.
Year | Student | Research |
2022 | Chen Jiazhe | Application of cost-sensitive random forest in trend-following scaling strategy |
2022 | Li Xinhong | Application of multi-objective genetic algorithm in stock price turning point research |
2022 | Chen Yanlin | Monte Carlo simulation-based estimation of stock return distribution using long short-term memory model—Applied to options spread strategy |
2022 | Li Guanrong | Analysis of quantitative trading strategy portfolio based on multi-objective genetic algorithm |
2022 | Liu Yanzhu | Designing trading strategy combination optimization technology based on mean-semi-variance using cuckoo algorithm |
2022 | Liao Chenxin | An Application of Time-Sensitive Categorical Reinforcement Learning on Options Spread Strategy - A case study of three shipping giants |
2022 | Wang Sichi | Using genetic algorithm and transfer learning for reinforcement-based stock trend prediction based on abnormal behavior |
2021 | Lin Wenyu | Research on plateau search of trading strategy parameters based on particle swarm algorithm |
2021 | Lin Yinting | Building a classifier for stock trend prediction based on transfer learning from abnormal features |
2021 | Wang Yuzhen | Research on quantitative strategy of options based on machine learning framework - A case study of TAIEX options sellers |
2021 | Lu Weiting | Exploration of warning stocks and online messages |
2020 | Ye Zhiyuan | Research on settlement day trading strategy of options based on machine learning framework |
2020 | Luo Taili | Construction of stock valuation function based on deep reinforcement learning framework |
2020 | Chen Yizhen | Study on the Kelly Criterion indicator - A case study of Taiwan stock market |
2020 | Hong Bangren | Position size management of options based on deep long short-term memory neural network architecture in transition index futures trading strategy |
2019 | Li Xinhua | Research on the relationship between stock price volatility and position size using stochastic trading mechanism |
Year | Description |
2022 | "Congratulations to student Zhao Qifang, guided by Professor Wu Mu'en, for receiving the Outstanding Domestic Graduate Research Achievement Award for the 111th academic year at our university." |
2022 | "Congratulations to student Chen Jiazhe, guided by Professor Wu Mu'en, for participating in the 15th Chongyue Thesis Award Competition in 2022 and winning an excellence award in the Management Master's Thesis category." |
2021 | "Congratulations to student Wang Yuzhen, guided by Professor Wu Mu'en, for participating in the 23rd Decision Analysis Symposium and Ministry of Science and Technology's Special Research Results Presentation, and winning the Best Paper Award." |
Master's Program in Information and Financial Management, 2nd Year
Master's Program in Information and Financial Management, 1st Year
Undergraduate Research Students
Project Year | Student | Project Title |
2022 | Lan Shi-Xiang, Hsu Hsiang-Wei, Kao Pin-Wei | NBA Game Win Rate Analysis |
2022 | Chang Chun-Lun, Hsieh Li-Chun, Liu Yu-Yen | Futures Trading Board Game Design |
2022 | Huang Yu-Wei, Lan Pei-Ju, Huang Yun-Chen | Development of Options Strategy Business Platform |
2022 | Jiang Da-Wei | Construction of Futures Trading Strategy Backtesting System |
2021 | Jian Ning-Yu, Hsu Yu-Hui, Lin Wei-Zhen | Analysis of Cyclical Stocks and Development of Investment Strategies |
2021 | Wu Hui-Zhen, Wang Zi-Wen, Chen Kuang-Tien | Using Machine Learning Models to Predict Next Day Opening and Closing Prices and Evaluate Next Day Wind Risk and Profitability Range - A Case Study of Three Shipping Giants |
2021 | Chen Min-Kuan, Cheng Yu-Li, Tu Wei-Cheng | Construction of Quantitative Trading System Based on Random Forest Framework for Options |
2021 | Chen Shin-Kuan, Yao Yu-Tse, Hsu Min-Yao | Football Sports Event Analysis |
2020 | Lin Yi-Tzu, Hsu Shu-Chih, Jing Guan | Constructing Probability Prediction Model Using Elo Prediction Method - A Sample of the English Premier League |
2020 | Chao Chi-Fang, Chen Kuan-Ting, Huang Che | Research on the Prediction of Solar Radiation Using Random Forest for Binary Option Commodities |
2020 | td>Sung Hsing-Ying, Chess Li, Yang Yin-ChangImplementation of Dynamic Pari-Mutuel Market (DPM) Mechanism in Prediction Market | |
2019 | Huang Zhi-Jia, Hsu Pei-Yu | Construction of Position Valuation Function and Stock Trading Performance Analysis Using Support Vector Machines |
2019 | Liao Chen-Hsin, Li Chia-Hui | Construction of Passive Investment Portfolio Using Machine Learning |
2019 | Hsieh Yi-An, Lu Hsuan-Ling, Huang Szu-Chi, Lin Chien-Wen | Predicting Intraday Price Changes of Index Futures through Machine Learning |
2018 | Lin Wen-Yu, Yang Yong-Ru, Wu Chia-Hsuan, Cheng Yi-Ping | Development of Quantitative Candlestick Pattern Trading Strategy |
2018 | Zeng Chun-Miao | Strategy Translation Machine |