Paper Info
Title
Fuzzy Candlesticks Forecasting Using Pattern Recognition for Stock Markets.
Abstract
This paper presents a prediction system based on fuzzy modeling of Japanese candlesticks. The prediction is performed using the pattern recognition methodology and applying a lazy and nonparametric classification technique, k-Nearest Neighbours (k-NN). The Japanese candlestick chart summarizes the trading period of a commodity with only 4 parameters (open, high, low and close). The main idea of the decision system implemented in this article is to predict with accuracy, based on this vague information from previous sessions, the performance of future sessions. Therefore, investors could have valuable information about the next session and set their investment strategies.
Year
DOI
Venue
2016
10.1007/978-3-319-47364-2_31
INTERNATIONAL JOINT CONFERENCE SOCO'16- CISIS'16-ICEUTE'16
Keywords
Field
DocType
Trading,Fuzzy logic,K-NN,Forecasting,Candlesticks,Stock market
Pattern recognition,Commodity,Computer science,Investment strategy,Fuzzy logic,Decision system,Chart,Artificial intelligence,Candlestick chart,Stock market,Prediction system
Conference
Volume
ISSN
Citations 
527
2194-5357
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Rodrigo Naranjo110.70
Matilde Santos214324.39