.png){kind=icon}
返回
Pattern Matching Trading System Based on the Dynamic Time Warping Algorithm
.png){kind=icon}
OA
AI
DOI：10.3390/su10124641.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The futures market plays a significant role in hedging and speculating by investors. Although various models and instruments are developed for real-time trading, it is difficult to realize profit by processing and trading a vast amount of real-time data. This study proposes a real-time index futures trading strategy that uses the KOSPI 200 index futures time series data. We construct a pattern matching trading system (PMTS) based on a dynamic time warping algorithm that recognizes patterns of market data movement in the morning and determines the afternoon's clearing strategy. We adopt 13 and 27 representative patterns and conduct simulations with various ranges of parameters to find optimal ones. Our experimental results show that the PMTS provides stable and effective trading strategies with relatively low trading frequencies. Financial market investors are able to make more efficient investment strategies by using the PMTS. In this sense, the system developed in this paper contributes the efficiency of the financial markets and helps to achieve sustained economic growth.
Keyword:
dynamic time warping
pattern matching trading system
time series data
sliding window
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.3
论文数:
10.6W
被引数:
28.4W
机构
引用论文
Forecasting the NYSE composite index with technical analysis, pattern recognizer, neural network, and genetic algorithm:: a case study in romantic decision support使用技术分析，模式识别器，神经网络和遗传算法预测纽约证券交易所综合指数: 浪漫决策支持的案例研究
.png){kind=icon}
PREAI
分享收藏Linear triangular optimization technique and pricing scheme in residential energy management systemsOAAI
OAAI分享收藏Subsequence dynamic time warping for charting: Bullish and bearish class predictions for NYSE stocks
PREAI
分享收藏分享收藏分享收藏
查看更多内容