Dataset for stock price prediction with LSTM and technical indicators: Evidence from Taiwan-listed firms

This dataset provides daily stock price and trading volume information for three Taiwan-listed firms, covering the period from January 2010 to January 2024. The raw data include open, high, low, and close (OHLC) prices as well as trading volumes, retrieved from the Taiwan Stock Exchange through the Yahoo Finance API. To facilitate financial forecasting research, the dataset also includes derived technical indicators such as moving averages (5-day, 10-day, 20-day), Relative Strength Index (RSI), and Moving Average Convergence Divergence (MACD). In addition, the data are structured into training-ready input–output matrices for Long Short-Term Memory (LSTM) neural networks using a sliding window approach. This dataset is intended for use in stock price prediction, technical trading strategy evaluation, and machine learning research in finance. It can also be applied for replication studies, cross-industry comparisons, and educational purposes.本数据集提供三家台湾上市企业的每日股价与交易量数据，覆盖2010年1月至2024年1月的时间区间。原始数据包含开盘价、最高价、最低价与收盘价（OHLC）及交易量，通过雅虎财经（Yahoo Finance）API从台湾证券交易所获取。为助力金融预测研究，本数据集还包含衍生技术指标，如5日、10日、20日移动平均线（moving averages）、相对强弱指数（Relative Strength Index, RSI）以及指数平滑异同移动平均线（Moving Average Convergence Divergence, MACD）。此外，该数据集采用滑动窗口方法，构建了适用于长短期记忆（Long Short-Term Memory, LSTM）神经网络的可直接用于训练的输入-输出矩阵。本数据集可应用于股价预测、技术交易策略评估及金融领域机器学习研究，同时也可用于复现研究、跨行业对比及教学用途。