DocumentCode :
34092
Title :
Dynamical Models of Stock Prices Based on Technical Trading Rules Part I: The Models
Author :
Li-Xin Wang
Author_Institution :
Dept. of Autom. Sci. & Technol., Xian Jiaotong Univ., Xian, China
Volume :
23
Issue :
4
fYear :
2015
fDate :
Aug. 2015
Firstpage :
787
Lastpage :
801
Abstract :
In this paper, we use fuzzy systems theory to convert the technical trading rules commonly used by stock practitioners into excess demand functions which are then used to drive the price dynamics. The technical trading rules are recorded in natural languages where fuzzy words and vague expressions abound. In Part I of this paper, we will show the details of how to transform the technical trading heuristics into nonlinear dynamic equations. First, we define fuzzy sets to represent the fuzzy terms in the technical trading rules; second, we translate each technical trading heuristic into a group of fuzzy IF-THEN rules; third, we combine the fuzzy IF-THEN rules in a group into a fuzzy system; and finally, the linear combination of these fuzzy systems is used as the excess demand function in the price dynamic equation. We transform a wide variety of technical trading rules into fuzzy systems, including moving average rules, support and resistance rules, trend line rules, big buyer, big seller, and manipulator rules, band and stop rules, and volume and relative strength rules. Simulation results show that the price dynamics driven by these technical trading rules are complex and chaotic, and some common phenomena in real stock prices such as jumps, trending, and self-fulfilling appear naturally.
Keywords :
chaos; fuzzy set theory; fuzzy systems; nonlinear equations; pricing; stock markets; fuzzy IF-THEN rules; fuzzy set theory; fuzzy system theory; fuzzy words; natural languages; nonlinear dynamic equations; price dynamic equation; stock price dynamical model; technical trading heuristics; technical trading rules; vague expression abound; Biological system modeling; Equations; Fuzzy sets; Fuzzy systems; Market research; Mathematical model; Resistance; Agent-based models; chaos; fuzzy systems; stock markets; technical analysis;
fLanguage :
English
Journal_Title :
Fuzzy Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
1063-6706
Type :
jour
DOI :
10.1109/TFUZZ.2014.2327994
Filename :
6824795
Link To Document :
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