Jakarta Stock exchange forecasting using ...

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data from time i to i+1. Percentage change of the data as U. Devide U into ... 280 GB hard disk space ... 50 JKSE composite index data taken weekly from 13.

SENG HANSUN

JAKARTA STOCK EXCHANGE (JKSE) FORECASTING USING FUZZY TIME SERIES 2013 INTERNATIONAL CONFERENCE ON ROBOTICS, BIOMIMETICS, INTELLIGENT COMPUTATIONAL SYSTEMS YOGYAKARTA - INDONESIA

INTRODUCTION

A time series is a set of regular time-ordered observations of a quantitative characteristic of an individual or collective phenomenon taken at successive periods.

GOAL Time series characteristics

JKSE composite index data

Time series analysis

forecasting

Soft Computing

Fuzzy Time Series

FUZZY TIME SERIES start

New interval

Decide the fuzzy sets with triangular membership function

end

Compare the data from time i to i+1

Percentage change of the data as U

Decide the density based distribution of each interval Defuzzify the fuzzy data based on the formula given

Forecasted data

Devide U into several intervals Percentage change of forecasted data

Calculate the forecasted data

SYSTEM SPECIFICATION WEB BASED SYSTEM • Windows 7 Professional 64-bit • Processor Intel ® Core ™ i5 • Installed Memory 2.048 MB • 280 GB hard disk space • 12.1” monitor, keyboard, optical mouse • PHP Excel Reader library • JPGraph 3.5.0 library • PHP version 5.3.1

EXPERIMENTAL 50 JKSE composite index data taken weekly from 13 August 2012 to 29 July 2013.

Initial interval value used: 17

EXPERIMENTAL RESULT

EXPERIMENTAL RESULT

EXPERIMENTAL RESULT

EXPERIMENTAL RESULT

CONCLUSIONS • Fuzzy time series method using percentage change as the universe of discourse can be used to forecast the JKSE composite index data. • Market traders can use the proposed method to take the best decision on buying or selling their shares based on the condition of the previous stock market data.

FUTURE WORK

• Building a new approach or algorithm to choose initial interval number, so we can get a better forecasting result.

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