Portfolio management system in equity market neutral using reinforcement learning

ME Wu, JH Syu, JCW Lin, JM Ho - Applied Intelligence, 2021 - Springer
Portfolio management involves position sizing and resource allocation. Traditional and
generic portfolio strategies require forecasting of future stock prices as model inputs, which …

Kelly-based options trading strategies on settlement date via supervised learning algorithms

ME Wu, JH Syu, CM Chen - Computational Economics, 2022 - Springer
Option is a well-known financial derivative that attracts attention from investors and scholars,
due to its flexible investment strategies. In this paper, we sought to establish an option …

Effective fuzzy system for qualifying the characteristics of stocks by random trading

ME Wu, JH Syu, JCW Lin, JM Ho - IEEE transactions on fuzzy …, 2021 - ieeexplore.ieee.org
Trading strategies can be divided into two categories, ie, those with momentum
characteristic and those that appear contrarian. The characteristics of trading strategies have …

Stock selection system through suitability index and fuzzy-based quantitative characteristics

JH Syu, JCW Lin, CJ Wu, JM Ho - IEEE Transactions on Fuzzy …, 2022 - ieeexplore.ieee.org
With the rapid development of quantitative trading, stock selection is an ongoing task that
requires consideration of the characteristics of stocks and investment strategies. Fuzzy set …

Convert index trading to option strategies via LSTM architecture

JMT Wu, ME Wu, PJ Hung, MM Hassan… - Neural Computing and …, 2020 - Springer
In the past, most strategies were mainly designed to focus on stocks or futures as the trading
target. However, due to the enormous number of companies in the market, it is not easy to …

A framework of deep reinforcement learning for stock evaluation functions

TL Luo, ME Wu, CM Chen - Journal of Intelligent & Fuzzy …, 2020 - content.iospress.com
Quantitative trading is a crucial aspect of money management; however, conventional
trading strategies are based on indicators and signals, despite the fact that position sizing is …

Modified orb strategies with threshold adjusting on taiwan futures market

JH Syu, ME Wu, SH Lee, JM Ho - 2019 IEEE Conference on …, 2019 - ieeexplore.ieee.org
Opening Range Breakout (ORB) is a fairly intraday trading strategy. We set the resistance
and the support levels by the price in opening interval to follow the trend in the futures …

[HTML][HTML] Evolutionary ORB-based model with protective closing strategies

ME Wu, JH Syu, JCW Lin, JM Ho - Knowledge-Based Systems, 2021 - Elsevier
Opening range breakout (ORB) is a well-known intraday trading strategy via technical
analysis. ORB lacks robustness against market uncertainties (eg, information from …

Modifying ORB trading strategies using particle swarm optimization and multi-objective optimization

JH Syu, ME Wu - Journal of Ambient Intelligence and Humanized …, 2021 - Springer
Opening range breakout (ORB) is a well-known trading strategy in which predetermined
price thresholds are used to characterize price movements. However, some researchers …

Autoencoder based Hybrid Multi-Task Predictor Network for Daily Open-High-Low-Close Prices Prediction of Indian Stocks

D Chakraborty, S Ghosh, A Ghosh - arXiv preprint arXiv:2204.13422, 2022 - arxiv.org
Stock prices are highly volatile and sudden changes in trends are often very problematic for
traditional forecasting models to handle. The standard Long Short Term Memory (LSTM) …