Technical Analysis Of Predicting Stock Market.
The stock market is a collection of markets comprising of buyers and sellers where the issuing and exchange of bonds and equities, mostly in the form of stocks or shares, takes place (Times, 2017). Also referred to as the share market, the stock market is a vital component of the market as it enables companies and businesses source for capital, as well as dealing with inflation in exchange for giving the investors (those who buy the shares) a piece of the company’s ownership (Teweles & Bradley, 1998).
For companies to attract investors, they place their shares on the stock market where they are listed. Stocks can be categorized in various ways one of them being based on the Country where the company is located. For example, if a company is located in the United States of America, it is listed on the US stock exchange. This, however, does not confine the company from trading with other countries beyond its country’s borders.
Despite its importance in the sustainability of a company, stocks are quite often very unpredictable (David Fabian, 2014). They can change in value any time depending on the market forces, and this discourages investors. Technical analysts of stock markets, therefore, play the role of trying to predict the future value of the stock of a particular company based on past data on the company.
Analyzing the value of stock majorly depends on statistics; analysts go through financial audit reports, profit and loss statements, balance sheets, any other financial records of the company, as well as the policies of the company (Edwards et al., 2013). With this information they can draw patterns, charts, and graphs which they use to predict the future of the company worth in the stock markets. Besides this, the technical analysts also analyze sales data, competition, managerial capacities, the capacity of the company, treasury reports, production indexes, price statistics among other data. It starts with observing the trend and a rising trend is a good sign.
Technical analysts are vital in deciding if it is the right time to sell, buy or hold (Michael Kahn, 2010). However, nothing is always certain, as dictating if and when stocks will go up and down is very difficult and all that analysts can do is predict a probability. In addition to knowing the risks that surround stock exchange, technical analysts help put more confidence in investors to buy shares.
In technical analysis, there are three assumptions that are made; first, the market discounts everything this is because technical analysts consider only the price movement citing that the stock price is a direct reflection of all the factors that affect a company. Secondly, technical analysts believe that price moves in trends thus after establishing a particular trend the likelihood of future price movement will be the same. Thirdly, in most cases, history tends to repeat itself in regards to price movement. This is attributed to market psychology where participants tend to have the same consistent response to different market changes (Group, 2014).
Unlike technical analysts, fundamental analysts study everything that affects the company from the overall economy of the country as well as the industry conditions surrounding the company (Jack D. Schwager, 1995).
Muscat Securities Market (MSM) is a stock exchange located and operating in Oman. It was started in 1988 and later restructured in 1998, the securities exchange, which is owned by the government of Oman, has a listing of over 116 companies. MSM established its index in 1990 and currently has 30 companies listed which are the most stable and therefore are used to establish the price movement as well as provide a benchmark for other individual investors (MSM, 2017).
This research will, therefore, study the 30 companies listed on the MSM index and analyze their profitability and security investment-wise with the help of technical analysis.
Objectives of the Research
- To determine better ways that will give investors more confidence in investing
- To analyze securities of companies listed on the MSM security index
- To implement the knowledge of technical analysis in knowing when to buy, sell or hold stock
- Why is technical analysis important in the stock market?
- How can technical analysis be used to measure the security of a company an investor is interested in?
- How can technical analysis be used in future in helping investors in making the right decisions when they want to invest in stocks?
Rationale of the Study
The objective of this study is to analyze the various types of technical analysis tools and understand the role that it plays in stock exchange. The study will analyze technical analysis as a tool that can be used by companies and investors in predicting the future of a company in relation to its shares and the value it holds. The Stock exchange is a platform where all parties can have a win-win. Using technical analysis will help investors know which companies are good to invest which will ultimately create money for them as well through profits as provide capital to companies being invested on.
Technical analysis is just not observations and drawing of conclusions.
The use of technical analysis in predicting stock markets has received its share of criticism over the years with authors like Lo and Hasanhodzic citing that the process is based on intuition and deserves more academic study (Lo & Hasanhodzic, 2011). In their book, they further continue to state that qualitative analysis is a much stronger method as it is based on statistics as opposed to technical analysis which is to a great extent a probability. Technical analysis focuses on occurrences that have taken place before and have tended to repeat over the years. This then creates a trend that analysts use to predict future stock prices.
Analysts and experts consider ‘analysis’ is a scientific process and thus it should follow scientific procedures of collecting data, doing calculations to produce undoubted and proven results. However, technical analysis is not known for using scientific procedure. A technical analyst will observe a graph and decide there if the stock is rising or falling and if it is the best time to sell or buy. It has zero scientific value (Comeau, 2015) hence the source of its criticism.
Despite that, its importance still cannot be ignored. Technical analysis can still and has in the past given useful predictions on the stock market. Besides carrying out scientific research and calculations, observing the market trends and behavior can give a hint on where the market is headed. In cases of depression, there is no need for scientific research the graph can tell it all. Technical analysis helps investors be aware of the market forces and the factors that affect the stock markets such as politics, imports, and exports among others.
Charles Kirkpatrick and Julie Dahlquist in their book categorize technical analysis as more of a short-term plan used by traders rather than long-term suitable for investors (Kirkpatrick & Dahlquist, 2010). For short-term traders changes or announcements by the company doesn’t affect them much since these changes do not take place minute by minute or day by day but rather takes a process for these changes to be felt on the ground. However, for long-term investors, technical analysis is not quite suitable.
A short-term trader, therefore, relies more on a technical analyst since they need to be aware of market price behavior and its interpretation which is either should I buy, should I sell or should I hold?
However, for technical analysis to work almost precisely, various tools must be used on the same test subject to validate the observations. For example, in analyzing a company if it is secured for investment in the stock market, technical analysts may use Relative Strength Index as well as Moving Average Convergence Divergence together to validate the findings (Nupur Joshi, 2017).
Even with the use of multiple tools, some experts believe that technical analysis throws people off and often give the wrong information to investors (Jonas Elmerraji, 2015). Both technical analysis and fundamental analysis can be used to complement each other. A technical analyst can highlight a certain market price change, establish a trend and this trend is then picked up by a fundamental analyst who then does a scientific research to attain a long-term investment solution.
Another criticism comes to play when all players in the market practice and follow technical analysis meaning that to avoid a fail in the stock market previous mistakes should be avoided thus the role of technical analysis becomes futile.
In a report done by Cheol-Ho Park and Scott Irwin in 2003 revealed that 30-40 per cent of those who use technical analysis regarded it as a significant tool in determining and highlighting price movement for up to six months (Park & Irwin, 2004). However, there is need to explore the deficiencies that technical analysis has and find solutions to them to make the tool more profitable to investors.
With new emerging technologies such as computers, the verification of data and conclusions drawn by technical analysis has improved. Now computers are being used to key in data, monitor trends, and automate the entire process giving more authenticity to the results concluded (Scott et al., 2016).
Technical analysis is deeply rooted in human behavior; it observes how investors react the same way to the same events over and over (Kahn, 2009). For example, during political elections especially in regions where there is conflict or tensions in a country, the stock markets do not perform as well as they should. Most market prices drop significantly or remain stagnant. This is a behavior that has been observed over the years and therefore, will most likely take place in future elections.
The stock market is dependent on human will to invest and to sell, and this is often accompanied by ‘moods’ and swings of ideas and decisions. Thus, the role of technical analysts who can read and interpret these swings should not be ignored just because scientific research has not been done to prove the changes in the market.
However, despite the criticisms, technical analysis is still being used because unlike fundamental analysis, technical analysis is much more efficient in highlighting and predicting turning points in the stock market. This is most likely because technical analysis is concerned with shorter periods of time such as day to day changes (Moosa, 2007).
Data collection refers to the process of collecting primary or secondary data from the field. This can be done through asking questions, observation or by analyzing data that already exists. While collecting data for research, the researcher needs to know where to find the sources of their information as well the kind of information they are looking for (Kumar, 2008).
This research will use secondary data. This type of data is collected or gathered from sources different from the primary data (Burt et al., 2009). To know the difference, it is Fhimportant to understand what primary data is. Primary data is collected directly and first-hand from the field by the researcher. The data that was used for this research was obtained from financial statements and statistical charts of companies listed on the Muscat Securities Market (MSM) index.
The study period was of five years. The researcher collected data of the sampled firms between the years of 2011 and 2015.
Sampling Design, Sample Size, and Population
Sampling design refers to the process or the strategy that the researcher will use while collecting data for their research. Selecting a strategy for data collection is very important because the techniques used directly affects the quality of the results of research (De Vaus, 2001). This process is done very consciously by the researcher with the aim of answering the research objective(s) and question(s) that guide the actual research (Shuib et al., 2013).
The researcher studied nine firms to be part of the research. These companies were selected from the 30 companies listed on the MSM index. These firms provided the basis of the entire research. They are as follows:
- Financial Sector: Ahli Bank, Bank Dhofar, and Bank Muscat.
- Industrial Sector: Al Anwar Ceramic Titles, Al Hassan Engineering, and Dhofar Cattle Feed.
- Service Sector: ACWA Power Barka, Al Jazeera Service, and Oman Investment and Finance.
Tools Used in the Research
Data collection tool refers to and instrument that the researcher will use to collect their data. While selecting a proper research tool, the researcher needs to keep in mind they type of research they are conducting; a qualitative or quantitative research. It also needs to be relevant to the theoretical framework of the research as well as the objectives of the research.
Quantitative research emphasizes on collecting statistical data or analyzing numerical data to explain a certain phenomenon or trend. For this research, the researcher used various quantitative research tools in collecting the data. These tools included:
- Bollinger bands
- Relative Strength Index
- Moving Average Convergence Divergence
Bollinger band is a tool that was invented in the 1980s by John Bollinger. It is used to measure how high or how long the price share is in relation to previous trades. Due to the rapidly changing trends, a tool that could adapt to these changes was greatly needed. Bollinger bands helps an investor establish how high or how low the prices in the market are. On the upper band of the chart, the prices are usually high. Alternatively, when the prices are low, they are usually in the lower band. Due to its flexibility, Bollinger bands can be used in all financial markets such as forex and equities and also for very short periods of time (BANDS, 2017).
Bollinger Bands are straight forward in how it is presented. It consists of three bands; that is: a middle band and two outer bands- an upper and lower bands. The upper band indicates an overbought territory while the lower band indicates that a security has been oversold. However, most experts will use Bollinger bands together with other technical analysis tools to get a better perspective and interpretation of the current state of the stock market (John Devcic, 2007).
The points where the lines intersect are the indicators of when it is the right time to buy or sell.
Studies show that Bollinger bands are effective in comparing price action and indicator action and this helps in arriving at decisions of whether to buy or sell. Due to its nature, Bollinger bands also help in recognizing patterns, defining in a clearer perspective the highs and lows as well as momentum shifts.
However, it should be noted that Bollinger bands are not for the long-term, they do not give continuous advice of when to invest, but rather they help an investor identify where the odds might favor them (Bands, 2017). For example, when the lower band and the closing price intersect, then it is a good time to buy. Similarly, when the upper band and the closing price intersect then, it is a good time to sell.
Ahli Bank on 15th December 2011 gave an indicator to sell as closing price 0.268 indicated that there will be a drop in price. On 11th July 2012, the company then gives a buy signal to its investors as the lower band intersects the closing band at 0.14 which rise to 0.18 the following day.
According to the chart above, Bank Dhofar gave a signal to its investors to sell on 7th May 2012 as the closing price of 0.45 intersects the middle band and this shows that there will be a fall in price the next day. A buy signal was also made in April 2011 when the closing price intersected with the lower band indicating there would be a rise in price the following day.
Bank Muscat gave indicated that it was time to sell on 15th March 2012. The bank then indicated that it was time to buy signal on 10th September 2013 when the lower band and the closing price intersect at 0.49.
The chart above shows that Al Anwar Ceramic Titles hinted to investors to sell on 23rd March 2011 when the intersection was at 0.32. The company also gave a hint to investors to buy in March 2013 when closing price and the lower band intersected at 0.43. Prices then fell to 0.42 the next day.
Al Hassan Engineering gave a buy signal on 4th April 2011 when the closing price and the lower band intersect at 0.45. The price then rises to 0.49 the following day. In the following year, on 15th April 2011, the company indicated that it was time to sell after the intersection at 0.27. Prices then fell to 0.23 the following day.
The chart above shows that Dhofar Cattle Feed indicated to investors that it was the best time to sell on 13th April 2011 after the closing price and the upper band intersected at 0.14 pointing to a fall in price. On 15th November 2012, the company gave a buy signal after the closing price intersected with the lower band at 0.16. Prices then rose to 0.17 the following day.
ACWA Power Barka indicated that it was time to sell on 20th March 2012 after the closing price intersected with the upper band at 1.67 indicating that the price will fall. On 4th April of the same year, the company indicated a buy signal after the closing price and the lower band intersected at 0.29.
According to the chart above, Al Jazeera Service gave a sell signal on 3rd April 2012 after the closing price intersected with the upper band at 0.27 indicating that prices would fall.
According to the chart, the company indicated it was best to sell in August 2013 after the closing price intersected with the upper band which would indicate that prices would fall. Prices fell the following day.
Relative Strength Index (RSI)
The Relative Strength Index (RSI) brought in by economist J. Welles Wilder, and it is described as ‘an oscillator that is used to quantify the rapidity and change of price movements’ (Fedility, 2016).
The RSI swings back and forth between zero and 100 and is observed over a period of 14 days. When there is significant trading on the stock market RSI is above 70, and when there is less trading, the RSI is below 30. Not only can you use RSI to be able to know when to buy or sell by checking signals that are generated by looking for divergences, but one can also observe the general trend of the stock market.
However, while using RSI, it is important to note that considerable price movements often mislead investors since it creates a false buy or sell signals.
Wilder highlighted the potential that RSI (through divergence of elements on the chart) has in being able to indicate market turns. When price goes up on the chart and the RSI goes slightly up, it creates a bearish divergence. However, when the price goes low and the RSI in turn goes even lower, a bullish divergence takes place (Wilder, 1978).
On 20th January 2011, the RSI is more than 70 indicating a sell signal because shares are overbought. On 12th May of the same year, the RSI is below 30 and this implies that it is a good time to buy.
According to this chart, Bank Dhofar gave a sell signal of 14th July 2014 when the RSI was more than 70. Similarly, the bank gave a buy signal in August 2015 when the RSI was less than 30.
On 5th April 2012, Bank Muscat gave a buy signal when the RSI was less than 30.
Al Anwar Ceramic Titles gave a sell signal on 1st November 2012 when the RSI was more than 70. On 10th June 2014, the company gave a buy signal when the RSI was below 30.
Al Hassan Engineering gave a sell signal on 29th October 2013 when the RSI was more than 70. On 7th August 2014, the company gave a buy signal when the RSI wend below 30.
On 16th August, Dhofar cattle Feed gave a sell signal when its RSI was above 70. However, on 9th December the company gave a buy signal after the RSI wend below 30.
The above company indicated to its investors that it is time to buy on 25th April 2011. The company then gave a sell signal on 17th September 2012 when the RSI was above 70.
According to the chart, Al Jazeera Service hinted that it was time to buy on 18th July 2011 and gave a sell signal on 17th February 2013 when the RSI was above 70.
Oman investment and Finance indicated that it was time to sell on 29th March 2011 when the RSI was above 70. On 9th February, the company gave a buy signal when the RSI was below 30 with a closing price of 0.23 which then increases to 0.26 the following day.
Moving Average Convergence Divergence (MACD)
This is type of financial tool introduced by Gerald Appel and is used in predicting stock prices (Appel, 2005). MACD focuses on observing trends on the momentum and the duration of a stock price.
While interpreting a MACD, experts focus on the convergence and the divergence. When averages in the chart come closer together other, a convergence takes place. When averages draw apart, then a divergence takes place. The shorter moving average (normally 12 days) is much faster as compared to the longer moving average which lasts for 26 days. Thus, the short moving average is responsible for most MACD movements (Charts, 2016).
A positive MACD indicates that the Exponential Moving Average (EMA) of 12 days is above the EMA of 26 days. This means a positive value increases as the shorter EMA diverges further from the longer EMA resulting to increase in the upside momentum.
A negative MACD on the other hand, indicate that the EMA of 12 days is below the EMA of 26 days. With that in mind, negative values increases as the shorter EMA diverges further below, the longer EMA resulting to an increase in the downside momentum.
According to the above Ahli Bank’s graph, the bank indicated it was time to sell on 14th March 2012. On 25th March 2015, the bank gives a buy signal when the short moving average intersected the long moving average from below.
According to the above graph, on 9th April 2012 Bank Dhofar gives a sell signal. On August 2014, the short moving average intersects the long moving average from below hence indicating it is time to buy.
Bank Muscat on the 8th of April 2012 indicated it was time to sale On 7th February 2013, the company gave a buy signal after the short moving average intersected with the long moving average from below.
The company hinted on an avenue to buy on 24th October 2011. Also, there was a sell signal after the short moving average intersected with the long moving average from above.
On 4th March 2013, Al Hassan Engineering gave a buy signal when short moving average intersected with the long moving average from below indicating an increase in the closing price. However, on 27th February 2014, a sell signal was given when the short moving average intersected with the long moving average from above indicating a fall in price.
A buy signal was given on5th February 2014 when the short moving average intersected with the long moving average from below. On the September of the same year, a sell signal was given after the short moving average intersected with the long moving average from above indicating a fall in price.
On 3rd April 2012, ACWB gave a sell signal after the short moving average intersected with the long moving average from above. This then saw a rapid decline in price over the next months. On 25th April, the company then gave a buy signal after the short moving average intersected with the long moving average from below.
On December 2011, Al Jazeera Service gave a buy signal after the short moving average intersected with the long moving average from below. This indicated a rise in the price. On August 2014, the company then gave a sell signal when the sort moving average intersected with the long moving average from above indicating a fall in the market price.
On 6th December 2012, Oman Investing and Finance gave a buy indication after the short moving average intersected with the long moving average from below indicating a rise in the market price. However, on 26th August 2014, the company gave a sell signal after the short moving average intersected with the long moving average from above indicating a fall in price.
Other technical analysis tools
Apart from the three tools discussed above, there are other tools which are also used in the technical analysis of predicting stock markets. They briefly include:
In Dow Theory, analysts focus on the trend to distinguish the overall direction of the market. This tool, introduced by Charles Dow, identifies three trends within the market: the primary trend (which lasts for almost a year), the secondary trend (three weeks to three months), and the minor trend (three weeks).
However, most analysist don’t focus too much on the minor trends as it can lead to irrational trading due to its constant movements.
A candlestick is a technical analysis tool that reflects the high points, low points, opening, and closing prices of stock for a specified period. On the chart, the wide part of the candlestick is called the ‘real body’ and is particularly useful to investors as it tells whether the closing price was higher or lower than the opening price. Each day shows its specific candlestick therefore if in a month there were 25 trading days there will be 25 candlesticks for that month (Charts, 2016).
Specific colors are used to indicate this. Black or red indicates that the stock closed lower while white or green indicates that the stock closed higher.
Limitation of the research
This research based its findings on secondary data from financial statements of 9 companies listed on the Muscat Securities Markets (MSM) index. This data is prone to manipulation, the data may be of a lower quality, the data may not be useful in relation to the theoretical framework of the research, and the data may be outdated.
From discussions above, it is now clear the importance of technical analysis in predicting changes in the stock market. Different technical analysis tools have their ways of predicting the future of stocks when to buy, when to sell, or when to hold. These tools follow market patterns and analyze them to be able to assist investors in making the right decisions. However, as highlighted in the literature review, technical analysis tools are best for short-term investments as opposed to long-term investments of over a year. Technical analysis works best in a time frame of 6 months thus is best for traders.
Bollinger Bands defines stock trends with highs and lows. Intersecting points on the chart indicate to the investor if it is the right time to sell or buy. When the upper band intersects with the closing price, then it is time to sell because that indicates that the prices will fall. Alternatively, when the lower band intersects with the closing price, it is time to buy since the prices will rise. These patterns have been studied, and the results are factual, at least for the short-term.
Relative Strength Index (RSI) uses divergence between the RSI and the price action to give signals on whether it is the right time to sell or buy. If the RSI is above 70, it is time to sell. If it below 30, it is time to buy.
Moving Average Convergence Divergence (MACD) uses convergence and divergence to interpret the stock market trends. Like Bollinger Bands, intersecting points dictate if it is time to sell or buy. If the short moving average intersects the long moving average from below then, it is time to buy. This is because there will be an increase in price. However, if the short moving average intersects with the long moving average from above, then it is time to sell since prices will drop.
Despite the effectiveness of these tools, it is not wise for an investor to use one tool in making their investment decisions. Using these tools together and cross-checking data from one technical analysis tool to another will increase the odds to an investor’s favor. Technical analysis tools help experts and investors know the turning point of a market. For long-term investments, tools like fundamental analysis are the better choice.
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