Pattern matching trading system based on the dynamic time warping algorithm

Sang Hyuk Kim, Hee Soo Lee, Han Jun Ko, Seung Hwan Jeong, Hyun Woo Byun, Kyong Joo Oh

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number4641
JournalSustainability (Switzerland)
Volume10
Issue number12
DOIs
Publication statusPublished - 2018 Dec 6

Fingerprint

Pattern matching
financial market
investor
market
futures market
economic growth
Time series
Profitability
time series
Economics
profit
Processing
efficiency
simulation
time
Financial markets
index

All Science Journal Classification (ASJC) codes

  • Geography, Planning and Development
  • Renewable Energy, Sustainability and the Environment
  • Management, Monitoring, Policy and Law

Cite this

Kim, Sang Hyuk ; Lee, Hee Soo ; Ko, Han Jun ; Jeong, Seung Hwan ; Byun, Hyun Woo ; Oh, Kyong Joo. / Pattern matching trading system based on the dynamic time warping algorithm. In: Sustainability (Switzerland). 2018 ; Vol. 10, No. 12.
@article{cf1afb32b08d4e19b5b649079a8f5385,
title = "Pattern matching trading system based on the dynamic time warping algorithm",
abstract = "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.",
author = "Kim, {Sang Hyuk} and Lee, {Hee Soo} and Ko, {Han Jun} and Jeong, {Seung Hwan} and Byun, {Hyun Woo} and Oh, {Kyong Joo}",
year = "2018",
month = "12",
day = "6",
doi = "10.3390/su10124641",
language = "English",
volume = "10",
journal = "Sustainability",
issn = "2071-1050",
publisher = "MDPI AG",
number = "12",

}

Pattern matching trading system based on the dynamic time warping algorithm. / Kim, Sang Hyuk; Lee, Hee Soo; Ko, Han Jun; Jeong, Seung Hwan; Byun, Hyun Woo; Oh, Kyong Joo.

In: Sustainability (Switzerland), Vol. 10, No. 12, 4641, 06.12.2018.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Pattern matching trading system based on the dynamic time warping algorithm

AU - Kim, Sang Hyuk

AU - Lee, Hee Soo

AU - Ko, Han Jun

AU - Jeong, Seung Hwan

AU - Byun, Hyun Woo

AU - Oh, Kyong Joo

PY - 2018/12/6

Y1 - 2018/12/6

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85058041114&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85058041114&partnerID=8YFLogxK

U2 - 10.3390/su10124641

DO - 10.3390/su10124641

M3 - Article

VL - 10

JO - Sustainability

JF - Sustainability

SN - 2071-1050

IS - 12

M1 - 4641

ER -