I hereby declare that this project report is based on my original work with the exception of quotations and citations which have been duly acknowledged. I certify that this project report entitled "A SURVEY OF VARIOUS STATISTICAL ANALYSIS METHODS FOR MONITORING STOCK PRICES". The copyright of this report belongs to the author under the terms of the Copyright Act 1987 as qualified by the Intellectual Property Policy of Universiti Tunku Abdul Rahman.
Appropriate acknowledgment should always be given for the use of any material contained in or derived from this report. I would like to thank everyone who contributed to the successful completion of this project. Wong for his invaluable advice, guidance and great patience during the development of the research.
The main concern of this study is to determine which statistical methods are useful for stock monitoring. All seven stocks are alerted to the R Chart and the Candlestick Chart is used to study the behavior of the stocks based on the collected data.
General Introduction
Importance of the Study
Most stock traders used statistical analysis methods and tools to set their trading strategy. There are 'big seven' techniques used to improve statistical process control, which are the control sheet, control chart, defect concentration diagram, pareto chart, histogram, cause-effect diagram and scatter diagram. The control chart is used to measure the performance and variability of the sequential or time-related process.
Robert (1959) pioneered the use of a control chart in studying marker levels and changes. Dumiĉić and Žmuk (2015) applied the CUSUM and EWMA control chart to study the performance of short-term stock trading. However, the presence of non-normality and autocorrelation affects the performance of the statistical control chart.
Control chart can be used in stock trading and monitoring as it can measure a process period. Apart from that, the stock traders used statistical analysis methods like box plot, histogram, candlestick, relative strength index, moving average convergence divergence etc. to determine their trading strategy.
Problem Statement
Aims and Objectives
Introduction
Literature Review
They concluded that the buy-and-hold strategy produces less profit than the moving average. Frankel and Froot (1990) found that market professionals tend to incorporate technical analysis into market forecasting. Dumiĉić and Žmuk (2015) claimed that the control charts are not widely used in stock trading and portfolio analysis.
Overcoming the autocorrelation problem, Žmuk (2016) shows that the control chart approach resulted in higher portfolio returns in equity trading compared to the pick-and-hold strategy. He concluded that the higher portfolio profit was obtained when residual-based CUSUM control chart was used in the short run and EWMA control chart was used in the long run when average prices were taken into account. However, Gandy (2012) stated that the statistical control charts are rarely applied in portfolio analysis and stock trading.
Kovarik and Sarga (2014) concluded that the control charts can be applied not only in production processes in the financial management of companies. They found that the new approach is useful for studying the statistical properties of a stock market.
Introduction
Models
Xbar (𝑿 ̅ ) Chart
Candlestick Chart
The white candlestick indicates that the closing price is higher than the opening price, which means that the bulls are in control. The candlestick chart is a bar chart used to describe the price movements of a security or currency over time. The thick part of the candlestick is called the real body and it shows the range between the opening and closing prices.
It is represented as an empty or full form, which means that the closing price is lower than the opening price, while the empty form is the opposite.
Introduction
In a nutshell, the observed process is not response to the 𝑋̅ Control Chart for Public bank stock. Overall, all the points for the Tenaga National Share fall within the statistical control limit. This simply means that the 𝑋̅ Control Chart is not sensitive to detect buy or sell signals for the investors who would like to invest in Tenaga National Stock.
Since no points fall outside the control limit, the 𝑋̅ Control Chart fails to provide a buy or sell signal for Petronas Gas Stock. In general, all Hap Seng Stock points fall within the statistical control limit indicating that the 𝑋̅ control chart is not alert to the price change for Stock Seng. It shows that the R Control Chart is more sensitive than the 𝑋̅ control chart in Public Bank stock and capable of giving buy and sell signals to investors who wish to invest in Public Bank stock.
It is said to be more sensitive in detecting the buy and sell signal than the 𝑋̅ Control Chart on Nestle Stock. Therefore, the R Control Chart is more sensitive in detecting buy or sell signals compared to the 𝑋̅ Control Chart on Hap Seng Stock.
Candlestick Chart
A linear trendline is used instead of a polynomial or other model as it shows the rise and fall of price from a constant level and is commonly used when trading stocks on candlesticks. Therefore, the months of June, July and August are enlarged for further investigation in Figure 4.18. This means that the buying pressure is higher and buyers have dominated this session, but sellers will eventually force the price lower.
There is a black candlestick on July 6th which is a Marubozu means that the sellers are in control of the price action on Tenaga National Stock on this day from the first trade to the last trade on this day. The dark cloud cover pattern involves a large black candlestick and forms a "dark cloud" over the preceding bullish trend which can be seen in Figure 4.22. In this case, a bearish engulfing pattern is shown as the bulls push the price higher on the open.
From Figure 4.24, the candlestick chart trendline on Petronas Dagangan Stock for the month of April, May and June shows a downward trend. However, most of the candlesticks fall above the trendline, which means that the price is expected to rise even though it is on a downward trend during these three months. Since the closing price and the opening price are close to each other, the buyers can absorb the selling pressure and push the price back up.
The candlesticks for the month of January are even indicating that there is not much fluctuation in the price. A long black candle on February 6 is a reversal pattern that indicates the price decline. The range of the price decreased on the following day and the lowest price was found on February 9.
The price falls sharply on 6 July and wide range and can be seen in figure 4.27. These patterns indicate that the closing price on June 11th is the opening price of the following day, June 12th. On the second day, the price opens lower than the previous low, and yet the buying pressure manages to push the price up to an even higher level.
Conclusions
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