This project is aimed to develop a desktop-based application for Bursa Malaysia Stocks. The system will classify the technical analysis of all indicators as buy, sell or neutral signal. This system will allow trader to see the overall trend of technical analysis toward a particular stock. To assist Traders in decision making in stock trading. To create a system that fulfill the requirement stated by the user/trader. To help the trader to be able to see overall trend of a stock.

1. Technical Analysis Dashboard for
Bursa Malaysia Stocks
NAME: ZAIDEE YISAU
ID: 1141127819
SUPERVISOR: DR. NORAIN YUSOFF
MODERATOR: DR. KHOR KOK CHIN
Date of presentation: 26 September 2018

2. TEAM MEMBERS
MEMBER 1
Application: Technical Analysis Dashboard
Name : Zaidee Yisau
Id: 1141127819
MEMBER 2
Application : Sentiment Analysis Dashboard
Name: Muhammad Zahriel Bin Ismail
Id: 1151101702

3. Dr. Nor’ain Mohd Yusoff
Faculty of Computing and Informatics
http://mmuexpert.mmu.edu.my/norainyusoff

4. TABLE OF CONTENTS
•Introduction
•Project Overview
•Motivation and Justification
•Problem Statements and Objectives
•Project Scope
•Literature Review
•Proposed Solution
•Implementation Plan
•References
•Prototype Demonstration
•Q&A Session

5. INTRODUCTION
Technical Analysis is a method that utilize various tools to predict the price
movement based on the past price or volume data.
One of the tool that commonly used in technical analysis is indicator. Indicator is
mathematical formula that can be applied to the price or volume data to get the
value that can be used in technical analysis.
Technical analysis can be dated back to the rice trader in Japan during the 1600s.
However, modern-day version of technical analysis is based on the Dow Theory
developed by Charles Down in the 1900s according to Steven B (2000).

6. PROJECT OVERVIEW
This project is aimed to develop a desktop-based application for Bursa Malaysia
Stocks.
The system will classify the technical analysis of all indicators as buy, sell or
neutral signal. This system will allow trader to see the overall trend of technical
analysis toward a particular stock.

7. JUSTIFICATION
•According to Jean Folger (2018) , The indicator do not specifically provide a buy
or sell signal, the trader need to interpret it themselves.
• Jean Folger (2018) stated that information overload can happens when the
trader try to use too many indicators to analyze the data that it become lost

8. MOTIVATION
1. To assist Traders in decision making in stock trading.
2. To create a system that fulfill the requirement stated by the user/trader.
3. To help the trader to be able to see overall trend of a stock.

9. PROBLEM STATEMENTS
•The trader needs to analyze many indicators in order to see the trend of the
stock market toward a particular stock.
•The trader has to memorize buy and sell conditions of many indicators because
different indicator has different conditions.

10. OBJECTIVES
1. To identify the user requirement for Technical Analysis Dashboard via
interview and comparison of existing systems.
2. To formulate a system framework that can classify technical analysis as buys
signal, sell signal or neutral signal.
3. To construct and develop a prototype from system framework.
4. To evaluate the system framework from user feedbacks to further improve
the system.

11. PROJECT SCOPE
•The system will be developed as desktop application.
•The system will analyze the listed stock on the main market of Bursa Malaysia.
•The system will only use the price data for technical analysis.
•The indicator that will be used in the system are momentum indicators.

12. LITERATURE REVIEW

13. INDICATORS
Indicator is a mathematical formula that that can be applied to past market data to get the
result that can be used in technical analysis.
There are two categories of indicators, leading and lagging.
Leading Indicator: Leading indicators are used to predict the price and they will give the signal
before a new trend about to start
Lagging Indicator: . Lagging indicators will follow behind the price action and give the signal
after the trend already started.
These indicators can be further categories into sub type, such as momentum indicator.

14. TECHNICAL ANALYSIS
Momentum indicator such as Stochastic has upper limit and lower limit value, when the price
increase and cross the upper limit and decrease and cross the lower limit again, the buy signal
will be generated.
The result of each momentum indicator will be classified as signal and then summarize as one
main signal to indicate overall trend of that stock.

15. COMPARISON OF EXISTING SYSTEMS

16. PROPOSED SOLUTION

17. FUNCTIONAL AND NON-FUNCTIONAL
REQUIREMENT
Functional Non-Functional
User should be able to view summary of
technical analysis
User Friendly – Simple and easy interface
for user to operates.
User should be able to see buy, sell or
neutral signal.
Reliability – System should operates
without failure most of the time.
User should be able to view signal from
each individual indicator
Performance- System should be efficient
and respond fast to the user requests.

18. USE CASE DIAGRAM

19. CLASS DIAGRAM

20. SEQUENCE DIAGRAM
View Technical Analysis Summary

21. STATE DIAGRAM

22. ACTIVITY DIAGRAM

23. IMPLEMENTATION PLAN

24. Gantt Chart for Phase 1

25. Gantt Chart for Phase 2

26. PROPOSED TOOLS
Python (Version 3.7)
-Tkinter will be used to develop GUI
-Analyze the stock data
MySQL (Version 8.0)
-MySQL will be used as database

27. PROPOSED TOOLS
Google Finance API
-use to get stock data

28. RISK
•Hardware limitation- when analyzing the data by both technical and sentiment
analysis the performance might drops depend on the hardware.
•Availability of data- daily records of stock price data might be missing.

29. REFERENCES
Jean Folger,(2018) , Using Trading Indicators Effectively.
:https://www.investopedia.com/articles/trading/12/using-trading-indicators-effectively.asp
Steven B. Achelis , (2000), Technical Analysis from A to Z.

30. PROTOTYPE DEMONSTRATION

34. Q&A SESSION