Embedding technical indicators into fuzzy inference system for trading stocks with high volatility

Fuzzy Inference System, which applies the concept of fuzzy logic and fuzzy set theory, has become popular in trading nowadays due to its ability to control uncertainty in financial data and simulate the decision making process of human traders. While Fuzzy Inference System is prevalent in foreign ex...

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Bibliographic Details
Main Author: Nan, Wentai
Other Authors: Quek Hiok Chai
Format: Final Year Project (FYP)
Language:English
Published: Nanyang Technological University 2024
Subjects:
Online Access:https://hdl.handle.net/10356/175158
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author Nan, Wentai
author2 Quek Hiok Chai
author_facet Quek Hiok Chai
Nan, Wentai
author_sort Nan, Wentai
collection NTU
description Fuzzy Inference System, which applies the concept of fuzzy logic and fuzzy set theory, has become popular in trading nowadays due to its ability to control uncertainty in financial data and simulate the decision making process of human traders. While Fuzzy Inference System is prevalent in foreign exchange trading, its application in stock trading remains underexplored. Fuzzy Inference Systems for stock trading proposed by existing studies fail to demonstrate their effectiveness and mainly focuses on stocks from specific sectors, which lacks generalizability. This research proposes a novel Mamdani type fuzzy inference system that integrates multiple technical indicators and risk management techniques to trade stocks with high volatility. Moreover, the system is validated on stocks from different sectors and optimized. The objective is to outperform existing Fuzzy stock trading systems and help traders generate better risk adjusted returns.
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spelling ntu-10356/1751582024-04-26T15:41:15Z Embedding technical indicators into fuzzy inference system for trading stocks with high volatility Nan, Wentai Quek Hiok Chai School of Computer Science and Engineering ASHCQUEK@ntu.edu.sg Computer and Information Science Fuzzy Inference System, which applies the concept of fuzzy logic and fuzzy set theory, has become popular in trading nowadays due to its ability to control uncertainty in financial data and simulate the decision making process of human traders. While Fuzzy Inference System is prevalent in foreign exchange trading, its application in stock trading remains underexplored. Fuzzy Inference Systems for stock trading proposed by existing studies fail to demonstrate their effectiveness and mainly focuses on stocks from specific sectors, which lacks generalizability. This research proposes a novel Mamdani type fuzzy inference system that integrates multiple technical indicators and risk management techniques to trade stocks with high volatility. Moreover, the system is validated on stocks from different sectors and optimized. The objective is to outperform existing Fuzzy stock trading systems and help traders generate better risk adjusted returns. Bachelor's degree 2024-04-22T06:55:40Z 2024-04-22T06:55:40Z 2024 Final Year Project (FYP) Nan, W. (2024). Embedding technical indicators into fuzzy inference system for trading stocks with high volatility. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175158 https://hdl.handle.net/10356/175158 en application/pdf Nanyang Technological University
spellingShingle Computer and Information Science
Nan, Wentai
Embedding technical indicators into fuzzy inference system for trading stocks with high volatility
title Embedding technical indicators into fuzzy inference system for trading stocks with high volatility
title_full Embedding technical indicators into fuzzy inference system for trading stocks with high volatility
title_fullStr Embedding technical indicators into fuzzy inference system for trading stocks with high volatility
title_full_unstemmed Embedding technical indicators into fuzzy inference system for trading stocks with high volatility
title_short Embedding technical indicators into fuzzy inference system for trading stocks with high volatility
title_sort embedding technical indicators into fuzzy inference system for trading stocks with high volatility
topic Computer and Information Science
url https://hdl.handle.net/10356/175158
work_keys_str_mv AT nanwentai embeddingtechnicalindicatorsintofuzzyinferencesystemfortradingstockswithhighvolatility