Understanding Technical Analysis and its Role in Investment Decisions
Using various market analysis tools to find out the reasons for the deviation of company fundamentals and finding ways to eradicate the deviation is the job of technical analysis. It is in nature a discipline of study, which employs the study of evaluation of investment options. It is intrinsically a trading discipline. It uses past trends of an investment to decide investment options on an investment. The nature of trends can vary from price movements to volume changes. All these past trends act as statistics for investment decisions and calculations (Parrino, Kidwell & Bates, 2012). Furthermore, in order to apply technical analysis, a past history of the trading is a must. Hence technical analysis can be applied on shares, futures, bonds, commodities, currencies, etc. to name a few. In short, all those investment options that trade, and have been trading for quite some time, technical analysis can be applied to them.
For a layman to understand the concept, it can safely be said that any market financial instrument, which is being traded on the exchange regularly or periodically, and has sufficient trading history so as to use its past trends to analyze the performance of the stock and thereby take investment decisions by predicting its future based on its past trends. So, this is what technical analysis means.
The technical analysis concept is built upon assumptions. The key assumptions are as follows:
- Artificial or non-natural price changes do not affect- dividend payouts, share repurchases and/or share splits etc. result in artificial price changes. And the form of distribution of money into the market also results in an artificial change in prices (Petty., Titman., Keown., Martin., Burrow. and Nguyen, 2012). This makes decision making using the market data difficult because of an unnatural price change, however, the basic market value remains unaffected.
- Liquidity- for accurate and efficient decision making, it is assumed that a share or security is highly liquid. Stocks with high mobility in the market are easier to trade and result in less deviation of prices because of the ready and steady demand and supply. This results in lesser fluctuations and hence, technical analysis and decision making become easier (Porter & Norton, 2014). However, for less mobile securities, prices have to be heavily negotiated upon in order to strike a buy or sell deal, and hence, there are higher fluctuations. Hence, mobility here refers to the ready market for sale and purchase, in short trading of stocks.
- External extremities- any external extremity, political turmoil, sad or happy sudden news, etc. can result in high price fluctuations.
These assumptions are fundamental in decision making. Technical analysis is an efficient tool for making a financial decision because the market patterns form the basis for decision making using technical analysis tools.
The erstwhile technique of analysis of a company’s performance was the fundamental analysis. This technique required the evaluation of a company’s performance by using its financial statements and thereby computing the intrinsic value of the company. This technique required the use of analytical tools to compute the company’s earnings, overall and per share, the company’s GDP, it’s liquidity ratios and positioning, and the list is huge (Needles & Powers, 2013). However, this system had its drawbacks. The company’s intrinsic value was determinable by the use of fundamental analysis but the real-time situation of the company and a ready comparison can be drawn by using the technique of technical analysis (Laux, 2014).
The technical analysis helps in evaluating a company’s position and status on a real-time basis since the information is readily available for a regularly trading stock or such other tradable investment instrument (Lui & Chong, 2010). In the past two decades, with dematerialization of stocks, the technique of technical analysis became very popular because of increasing competition in the market amongst the companies, and because the information so derived is comparable and there is a benefit of comparison amongst the companies belonging to the same industry (Melville, 2013).
Cryptocurrency – A Safe Form of Investment or a Scam?
Another reason for the increased use of technical analysis in the past two decades is that trends are an important tool when it comes to the principle of forecast. Financial instruments can be used to analyze the past information and performance of a company but the efficiency of the forecast of the company’s performance using the past financial data is difficult. However, using the trends of performance, the forecast is easier (Power, 2017).
Before understanding the role of cryptocurrency in investment, it is important to understand the basics of cryptocurrency because this is a newer and less known concept in the investment world. In a layman’s view, cryptocurrency is the safest form of investment. Cryptocurrency is like a digitalized form of money, which is used as a medium of exchange. It has strongly cryptographed so as to provide maximum security on its transfer. The transfer of these assets is verified and tracked and the generation of such money is regulated (Quiggin, 2013). This is therefore considered the safest form of exchange. All of it, be it generation, creation, acquisition, exchange or transfer, it is all tracked and regulated and registered by either a centralized or also decentralized banking system.
Now coming to the topic of concern here, let us understand the Ripple protocol. Ripple control is selected in this scenario. Ripple labs had come up with this unique concept of gross settlement, exchange and remittance network, as is defined in the standard Wikipedia definition of ripple. One of the modes of exchange of ripple includes cryptocurrencies along with others. Ripple employs a decentralized cryptocurrency names XRP, which is the second largest cryptocurrency in terms of market capitalization, bitcoin being the first (Quiggin, 2013).
With multiple views and perceptions regarding cryptocurrency, its usage and propaganda, it has its share of acceptances and rejections in the international financial markets. It appears that the world of cryptocurrency will see its share of bullish markets more often than the bearish market (Ross., Christensen., Drew., Bianchi., Westerfield and Jordan, 2014). The trend which looks more obvious is the bullish trend. There are multiple views against the invention of crypto. Many consider it to be a malicious invention and hold it responsible for investment market foul play and possibilities of scams are associated with crypto. However, there are many market players who are playing big bets and propagating crypto as the best possible and safest newer form of money. The big bulls are surely going to enter the market and sweep the market up to bullish trends.
The Role of CCI in Analyzing Investment Trends
Various indicators have been used in the past to identify and analyze trends in the commodity market. One such very prevalent and popular indicator is the CCI or Commodities Channel Index.
Multiple indices have been used. But none have been as versatile as this. This index helps to find new trends and also warn against unfavorable trends. CCI helps to measure a price trend and compare it with another given price trend. It can measure price trends over time, and/ or over trends, any which ways. It is a versatile index for calculation of trends. A difference between a security’s absolute and average price change is also captured by the CCI. A majority of trend movements of CCI occurs between a calculative range if -100 to +100. It favors the bears when negative and vice versa for bulls. It has been formulated and conceptualized by Donald Lambert and has been seen in Volcker (2011). It helps to analyze the trend of the investment towards being overbought or oversold and acts as an alarm for either trend. Investors can be warned earlier to the investment decisions they take. To buy, or refrain from doing so, or to sell or refrain from doing so can be determined and decided earlier and significant losses can be minimized for investors. This index works like magic for huge investors whose investment results are well capable in itself to move the market or at least create ripples in the market (Volcker, 2011). Hence it identifies the gap between the actual current price if a stock and the historical prices and forms a trend. A positive CCI indicates a higher actual current price over historical prices and a negative CCI indicates the actual current price is lower than the historic price. The magnitude of high or low is determined by the number value as computed by the CCI. The higher the magnitude, the higher is the downside, and vice versa for a low side trend. The index is unbound. The magnitude of the downside or high side is unpredictable. The index can compute any magnitude of the same.
Mathematics must also be known. Let us understand the formulas, and computations of the CCI.
Commodity Chanel Index (CCI) = (typical price- moving average)/0.015*average deviation.
Typical price = (High+Low+Close)/3 for each period under computation and trend analysis.
Moving Average = (Sum of typical prices)/ Number of periods added together.
Mean Deviation = The Typical Price minus the moving average for the period.
Understanding the Formulas and Computations of CCI
CCI models or Commodity Channel Index when compared with the traditional buy-and-hold decisions are a lot more comprehensive. CCI model or Commodity channel index is the difference between the historical prices and the current price. A positive Commodity Channel Index (CCI) represents that the current price is above the historical average price. On the other hand, a negative Commodity Channel Index (CCI) represents that the current price is below the historic average price.
There can be two ways of buy-and-sell decision making under Commodity Channel Index (CCI), +/- 100 levels and also +/-200 levels. In +/- 100 methods, readings of 100 or more indicate that the current prices will exceed the historic prices and low readings of -100 or less, indicate that the current prices are well below the historic prices. Whereas, in +/- 200 methods, readings of 200 or more indicate that the current prices will exceed the historic prices and low readings of -200 or less, indicate that the current prices are well below the historic prices.
In both approaches, a move of the trend from – 100/200 to +100/200 indicates a strong upside trend. On the other hand, a move of the trend from +100/200 to -100/200 indicates a strong downside trend.
Monthly Commodity Channel Index (CCI) model can be recommended to a long term investor. This is because for a long term investor, understanding the trends at the monthly level is more beneficial rather than comparing trends on a daily basis as the investment is going to be for a long period of time(months).
Conclusion
To end, it can be reiterated the fact that the Commodity Channel Index (CCI) model of taking investing decisions is a more comprehensive and holistic approach as compared to the traditional buy-and-sell approach. It clearly, logically and analytically shows the trends in prices of the commodity. It also makes it easier to take investing decisions. In the above research on XRP – Cryptocurrency, the monthly CCI index clearly shows that the commodity was first at an upward trend from 2014-mid 2017 and then at a downward trend till 2018. This will aid an investor in taking sound investment decisions.
The future scope for research in this area should be to make the Commodity Channel Index (CCI) even easier to understand and calculate while at the same time making it more holistic.
References
Laux, B. (2014). Discussion of The role of revenue recognition in performance reporting, 44, 349-379. Retrieved from https://doi.org/10.1080/00014788.2014.897867
Lui, K.M. and Chong, T.T.L. (2010). Do Technical Analysts Outperform Novice Traders: Experimental Evidence. Economics Bulletin, 33(4), 3080-3087. Retrieved from https://www.accessecon.com/Pubs/EB/2013/Volume33/EB-13-V33-I4-P287.pdf
Melville, A. (2013). International Financial Reporting – A Practical Guide. 4th edition. Pearson, Education Limited, UK
Needles, B.E., & Powers, M. (2013). Principles of Financial Accounting (12th Edition). Financial Accounting Series: Cengage Learning.
Parrino, R, Kidwell, D. & Bates, T. (2012). Fundamentals of corporate finance (3rd edition). Hoboken.
Petty, J. W, Titman, S., Keown, A. J., Martin, J. D., Burrow, M. and Nguyen, H. (2012) Financial Management: Principles and Applications (6th ed). Australia: Pearson Education Australia.
Porter, G. and Norton, C. (2014). Financial Accounting: The Impact on Decision Maker (10th edition). Texas: Cengage Learning
Power, T. (2017) Fund choice: Comparing super funds in 8 steps [online]. Retrieved from: https://www.superguide.com.au/boost-your-superannuation/comparing-super-funds-in-8-steps
Quiggin, J (2013). The Bitcoin Bubble and a Bad Hypothesis. Retrieved from: https://nationalinterest.org/commentary/the-bitcoin-bubble-bad-hypothesis-8353
Ross, S., Christensen, M., Drew, M., Bianchi, R., Westerfield, R. And Jordan, B.(2014). Fundamentals of Corporate Finance, 7th ed. North Ryde: McGraw-Hill Australia Pty Ltd.
Volcker, P. (2011). Financial Reform: Unfinished Business. New York Review of Books.
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