A Study on Using Both, Technical and Fundamental Analysis Together for Trading and Investing, with Reference to Day Trading Stocks & Options

Total Page:16

File Type:pdf, Size:1020Kb

A Study on Using Both, Technical and Fundamental Analysis Together for Trading and Investing, with Reference to Day Trading Stocks & Options A study on using both, technical and fundamental analysis together for trading and investing, with reference to Day Trading Stocks & Options Dissertation submitted in part fulfilment of the requirements for the degree of MSc in Management Practice at Dublin Business School A study on using both, technical and fundamental analysis together for trading and investing, with reference to Day Trading Stocks & Options Ameya Sunil Pawar (10385647) MSc in Management Practice January, 2019 DECLARATION I, AMEYA SUNIL PAWAR, declare that this research is my original work and that it has never been presented to any institution or university for the award of Degree or Diploma. In addition, I have referenced correctly all literature and sources used in this work and this this work is fully compliant with the Dublin Business School’s academic honesty policy. Signed: Ameya Pawar Date: 07 January, 2019 ABSTRACT There have always been clashes between the fundamentalists and the chartists about how the stocks and markets should be analyzed. Chartist or technical analysts are those who forecast the markets by considering the historic trends, whereas the fundamental analysts consider all the other factors that affects the stocks. Most people prefer analyzing the markets based on technical or fundamental analysis, while there are only a few who make the use of both, fundamental and technical analysis together for analyzing the stocks. Even when you search the internet for fundamental and technical analysis, the search returns with major results for the substituting nature of two, denoting the better of two. On the other side, there have been huge research done on the complementary nature of the two, proving that even if a single analysis works well in isolations, the results of complementary behavior returns with larger gains. Despite of proofs in regressions and cases and all other ways possible, investors resist to change the way of single kind of analysis based on the type of trade. This research focuses on knowing what kind of analysis is done by the traders and investors, who are members of the Facebook group “Day Trading Stocks and Options”, and the reason for that particular analysis. This is done with a view to find reason why people rarely use the complementing nature of technical and fundamental analysis, both together. Table of Contents 1. INTRODUCTION ................................................................................................................................ 9 1.1. Context ............................................................................................................................................... 9 1.2. Aims and Objectives ........................................................................................................................ 10 1.3. Research Questions .......................................................................................................................... 11 1.4. Justification for Proposed Research ................................................................................................. 12 1.5. Time, Cost and Project Management ............................................................................................... 13 1.6. Roadmap .......................................................................................................................................... 14 1.7. Scope and Limitations ...................................................................................................................... 15 1.8. Contribution ..................................................................................................................................... 17 2. LITERATURE REVIEW ................................................................................................................... 19 2.1. Introduction ...................................................................................................................................... 19 2.2. Technical Analysis ........................................................................................................................... 19 2.3. Fundamental Analysis ...................................................................................................................... 22 2.4. Substituting nature ........................................................................................................................... 25 2.5. Complementing nature ..................................................................................................................... 27 2.6. Conclusion ....................................................................................................................................... 29 3. RESEARCH METHODOLOGY ........................................................................................................ 31 3.1. Introduction and research onion ....................................................................................................... 31 3.2. Research Philosophy layer: Positivism ............................................................................................ 34 3.3 Research approach Layer: Deductive ............................................................................................... 38 3.4. Research Strategy Layer – Web-Based Survey ............................................................................... 41 3.5. Research choice layer: Mono-Method quantitative research ........................................................... 45 3.6. Time Horizon: Cross sectional ......................................................................................................... 47 3.7. Research Population ......................................................................................................................... 48 3.8. Data Collection: Google Forms ....................................................................................................... 49 3.9. Survey Design .................................................................................................................................. 50 3.10. Data analysis: Tableau ................................................................................................................... 51 3.11. Pilot test ......................................................................................................................................... 51 3.12. Ethical issues .................................................................................................................................. 52 3.13. Limitations of methodology ........................................................................................................... 54 3.14. Conclusion ..................................................................................................................................... 57 4. DATA ANALYSIS/ FINDINGS ........................................................................................................ 58 4.1. Introduction ..................................................................................................................................... 58 4.2. Survey Distribution and Response ................................................................................................... 58 4.3. Data Analysis .................................................................................................................................... 59 4.3.1. Consent form ............................................................................................................................ 59 4.3.2. General information .................................................................................................................. 60 4.3.3. Market factors influencing Investment Decisions .................................................................... 67 4.3.3.1. Technical Analysis .................................................................................................................. 71 4.3.3.2. Fundamental analysis ............................................................................................................ 78 4.3.3.3. Both ........................................................................................................................................ 85 5. DISCUSSION ..................................................................................................................................... 89 5.1. Introduction ..................................................................................................................................... 89 5.2. Sub Question 1 ................................................................................................................................. 89 5.3. Sub Question 2 ................................................................................................................................. 94 5.4. Sub Question 3 ................................................................................................................................. 98 3.5. Sub Question 4 ............................................................................................................................... 100 6. CONCLUSIONS/ RECOMMENDATIONS .................................................................................... 104 6.1. Introduction ................................................................................................................................... 104 6.2. Research Question ........................................................................................................................
Recommended publications
  • Putting Volatility to Work
    Wh o ’ s afraid of volatility? Not anyone who wants a true edge in his or her trad i n g , th a t ’ s for sure. Get a handle on the essential concepts and learn how to improve your trading with pr actical volatility analysis and trading techniques. 2 www.activetradermag.com • April 2001 • ACTIVE TRADER TRADING Strategies BY RAVI KANT JAIN olatility is both the boon and bane of all traders — The result corresponds closely to the percentage price you can’t live with it and you can’t really trade change of the stock. without it. Most of us have an idea of what volatility is. We usually 2. Calculate the average day-to-day changes over a certain thinkV of “choppy” markets and wide price swings when the period. Add together all the changes for a given period (n) and topic of volatility arises. These basic concepts are accurate, but calculate an average for them (Rm): they also lack nuance. Volatility is simply a measure of the degree of price move- Rt ment in a stock, futures contract or any other market. What’s n necessary for traders is to be able to bridge the gap between the Rm = simple concepts mentioned above and the sometimes confus- n ing mathematics often used to define and describe volatility. 3. Find out how far prices vary from the average calculated But by understanding certain volatility measures, any trad- in Step 2. The historical volatility (HV) is the “average vari- er — options or otherwise — can learn to make practical use of ance” from the mean (the “standard deviation”), and is esti- volatility analysis and volatility-based strategies.
    [Show full text]
  • Testing the Profitability of Technical Analysis in Singapore And
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by ScholarBank@NUS Testing the Profitability of Technical Analysis in Singapore and Malaysian Stock Markets Department of Electrical and Computer Engineering Zoheb Jamal HT080461R In partial fulfillment of the requirements for the Degree of Master of Engineering National University of Singapore 2010 1 Abstract Technical Analysis is a graphical method of looking at the history of price of a stock to deduce the probable future trend in its return. Being primarily visual, this technique of analysis is difficult to quantify as there are numerous definitions mentioned in the literature. Choosing one over the other might lead to data- snooping bias. This thesis attempts to create a universe of technical rules, which are then tested on historical data of Straits Times Index and Kuala Lumpur Composite Index. The technical indicators tested are Filter Rules, Moving Averages, Channel Breakouts, Support and Resistance and Momentum Strategies in Price. The technical chart patterns tested are Head and Shoulders, Inverse Head and Shoulders, Broadening Tops and Bottoms, Triangle Tops and Bottoms, Rectangle Tops and Bottoms, Double Tops and Bottoms. This thesis also outlines a pattern recognition algorithm based on local polynomial regression to identify technical chart patterns that is an improvement over the kernel regression approach developed by Lo, Mamaysky and Wang [4]. 2 Acknowledgements I would like to thank my supervisor Dr Shuzhi Sam Ge whose invaluable advice and support made this research possible. His mentoring and encouragement motivated me to attempt a project in Financial Engineering, even though I did not have a background in Finance.
    [Show full text]
  • Technical and Fundamental Analysis
    University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Supervised Undergraduate Student Research Chancellor’s Honors Program Projects and Creative Work 12-2016 Understanding the Retail Investor: Technical and Fundamental Analysis Ben Davis [email protected] Follow this and additional works at: https://trace.tennessee.edu/utk_chanhonoproj Part of the Finance and Financial Management Commons Recommended Citation Davis, Ben, "Understanding the Retail Investor: Technical and Fundamental Analysis" (2016). Chancellor’s Honors Program Projects. https://trace.tennessee.edu/utk_chanhonoproj/2024 This Dissertation/Thesis is brought to you for free and open access by the Supervised Undergraduate Student Research and Creative Work at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Chancellor’s Honors Program Projects by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. University of Tennessee Global Leadership Scholars & Chancellors Honors Program Undergraduate Thesis Understanding the Retail Investor: Technical and Fundamental Analysis Benjamin Craig Davis Advisor: Dr. Daniel Flint April 22, 2016 1 Understanding the Retail Investor: Fundamental and Technical Analysis Abstract: If there is one thing that people take more seriously than their health, it is money. Behavior and emotion influence how retail investors make decisions on the methodology of investing/trading their money. The purpose of this study is to better understand what influences retail investors to choose the method by which they invest in capital markets. By better understanding what influences retail investors to choose a certain investment methodology, eventually researchers can provide tailored and normative advice to investors as well as the financial planning industry in effectively and efficiently working with clients.
    [Show full text]
  • Investors' Awareness of Fundamental and Technical Analysis For
    International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-8 Issue-9, July 2019 Investors’ Awareness of fundamental and Technical Analysis for Investments in Securities Market Jayalakshmi. R, N. Lakshmi Abstract: The role of investors in the securities market reveals the rising prominence of financial savings and also the II. REVIEW OF LITERATURE growth of industry and the economy. The focal point is to survey the investors’ awareness of the fundamental and technical Wiwik Utami (2017) conducted a case study on investors’ analysis for investment in the securities market. The study stock investment decisions in Indonesia. The result showed identified an analysis of the economy, industries and companies that the period of investment and experience influenced the as the three fundamental components that influence and affect method of security analysis adopted before investment the investors’ investment in the securities market. decisions. Technical analysis was mostly preferred by Keywords: securities market, investors, rising prominence, regular tradinginvestors for quick decision-making. financial savings & technical analysis. Prasaanna Prakash (2016) found that the retail investors were less aware of the various investment options and the I. INTRODUCTION protective measures taken by the government. A majority of Investment in the securities market needs analysis to the retail investors chose investments for a short duration. identify and select the right instruments and right time to The researcher suggested that the retail investors be given invest to reap high returns, which in turn, can increase the proper attention. Investors’ decisions were based on investors’ wealth. Based on the analysis, the investment psychological, emotional and behavioral factors.
    [Show full text]
  • Relative Strength Index for Developing Effective Trading Strategies in Constructing Optimal Portfolio
    International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 19 (2017) pp. 8926-8936 © Research India Publications. http://www.ripublication.com Relative Strength Index for Developing Effective Trading Strategies in Constructing Optimal Portfolio Dr. Bhargavi. R Associate Professor, School of Computer Science and Software Engineering, VIT University, Chennai, Vandaloor Kelambakkam Road, Chennai, Tamilnadu, India. Orcid Id: 0000-0001-8319-6851 Dr. Srinivas Gumparthi Professor, SSN School of Management, Old Mahabalipuram Road, Kalavakkam, Chennai, Tamilnadu, India. Orcid Id: 0000-0003-0428-2765 Anith.R Student, SSN School of Management, Old Mahabalipuram Road, Kalavakkam, Chennai, Tamilnadu, India. Abstract Keywords: RSI, Trading, Strategies innovation policy, innovative capacity, innovation strategy, competitive Today’s investors’ dilemma is choosing the right stock for advantage, road transport enterprise, benchmarking. investment at right time. There are many technical analysis tools which help choose investors pick the right stock, of which RSI is one of the tools in understand whether stocks are INTRODUCTION overpriced or under priced. Despite its popularity and powerfulness, RSI has been very rarely used by Indian Relative Strength Index investors. One of the important reasons for it is lack of Investment in stock market is common scenario for making knowledge regarding how to use it. So, it is essential to show, capital gains. One of the major concerns of today’s investors how RSI can be used effectively to select shares and hence is regarding choosing the right securities for investment, construct portfolio. Also, it is essential to check the because selection of inappropriate securities may lead to effectiveness and validity of RSI in the context of Indian stock losses being suffered by the investor.
    [Show full text]
  • Fundamental Analysis to Access the Fair Value Based on Price Earning
    International Conference on Education For Economics, ISSN (Print) 2540-8372 Business, and Finance (ICEEBF) 2016 ISSN (Online) 2540-7481 Fundamental Analysis to Access the Fair Value Based on Price Earning Ratio (PER) and Dividend Discount Model (DDM) Approach as the basis for Investment Decision Making (A Study on the Insurance Sub Sector Listing in Indonesia Stock Exchange Period 2013-2015) Lisa Rahayu Ningsih Faculty of Economics, Universitas Negeri Malang, Indonesia Email: [email protected] Abstract This research aims to give explanation to assess and determine the reasonableness stock price of comparing fair value with market price. Assessing the reasonableness of stock price by Price Earning Ratio and Dividend Discount Model approaches in insurance companies listed in Indonesia Stock Exchange 2013-2015 to make investment decision. The research use descriptive research with quantitative approach. The population in this study is 12 insurance companies and the sampling technique is purposive sampling which 7 companies taken as sample with ticker stock code ABDA, AMAG, ASBI, ASDM, LPGI, MREI, ASRM. Fundamental ratio used in this research is Return On Equity (ROE), Earning Per Share (EPS), Dividend Per Share (DPS), and Dividend Payout Ratio (DPR). The result of this research showed one company that the price of its share which are undervalued and six companies that the price of overvalued condition when it measured with Price Earning Ratio method. Beside that comparing final result by using Dividend Discount Model showed that three companies is an undervalued position and four companies is an overvalued position. The decision that can be taken by investor based on undervalued condition is to buy or hold the shares whereas overvalued condition is to sell.
    [Show full text]
  • Kochmeister Awards Ceremony at the Budapest Stock Exchange
    Kochmeister awards ceremony at the Budapest Stock Exchange Budapest, 14 June 2010 Kochmeister award is handed over today for the seventh time at the Budapest Stock Exchange. The Budapest Stock Exchange founded the Kochmeister Award in 2004 to reward talented young people who submit the best paper(s) on predetermined topics related to the Stock Exchange. The award is named after Baron Frigyes Kochmeister, who played a leading role in 1864, in establishing the Budapest Commodity and Stock Exchange, and, as the first chairman of the Exchange, managed the institution for years. BSE Chief Executive Officer György Mohai handed over the prizes. Zsolt Kelemen, Deputy CEO of Finance of CIG Pannónia Life Insurance Plc. handed over the special prize offered by the company. Eighteen essays that arrived from eight national and transborder higher education institutions were in competition in the contest dedicated to the memory of Frigyes Kochmeister in 2011. The professional jury is awarded the following winners: First place: Zita-Klára Málnási - student of Babes-Bolyai University, Cluj-Napoca Title: Fundamental Analysis of the E-Star Alternative Plc. Second place: Viktor Vajda - student of Corvinus University, Budapest Title: New types of security trading platforms in the European Union Third place: Gábor Szentirmai - student of Corvinus University of Budapest Title: Fundamental Analysis of the E-Star Alternative Plc. Special prize offered by CIG Pannónia Life Insurance Plc.: Péter Szentirmai – student of Corvinus University of Budapest Title: Testing the technical trading rules of forecastability at the Budapest Stock Exchange About the Budapest Stock Exchange The CEE Stock Exchange Group (CEESEG), which comprises of the stock exchanges of Budapest, Ljubljana, Prague and Vienna, is the largest stock exchange group in the region.
    [Show full text]
  • (Form ADV, Part 2A) Cavanal Hill
    Item 1 – Cover Page Firm Brochure (Form ADV, Part 2A) Cavanal Hill Investment Management, Inc. One Williams Center 15th Floor Tulsa, Oklahoma 74172 (800) 958-2942 May 2020 This brochure (“B r o c h u r e”) provides information about the qualifications and business practices of Cavanal Hill Investment Management, Inc. If you have questions about the contents of this brochure, please contact us at (800) 955-2942 or www.cavanalhill.com. The information in this brochure has not been approved or verified by the United States Securities and Exchange Commission or by any state securities authority. Additional information about Cavanal Hill Investment Management, Inc. is available on the SEC’s website at www.adviserinfo.sec.gov. Note: While Cavanal Hill Investment Management, Inc. may refer to itself as a “registered investment adviser” or “RIA” you should be aware that registration itself does not imply any level of skill or training. 1 Item 2 – Material Changes Annual Update The Material Changes section of this brochure is updated to report any material changes to the previous version of Form ADV, Part 2A (the Firm Brochure). The section bellows provides a summary of material changes since the last update. Summary of Material Changes since the Last Update The U.S. Securities and Exchange Commission requires that each Investment Adviser provide its new clients with a copy of its Form ADV, Part 2A. The rule requires completion of specific mandatory sections and those sections are to be organized in the order specified by the rule. Investment adviser must update the information in their Form ADV, Part 2A, when a material change has occurred.
    [Show full text]
  • Download Download
    International Business & Economics Research Journal – November/December 2014 Volume 13, Number 6 The Random Walk Theory And Stock Prices: Evidence From Johannesburg Stock Exchange Tafadzwa T. Chitenderu, University of Fort Hare, South Africa Andrew Maredza, North West University, South Africa Kin Sibanda, University of Fort Hare, South Africa ABSTRACT In this paper, we test the Johannesburg Stock Exchange market for the existence of the random walk hypothesis using monthly time series of the All Share Index (ALSI) covering the period 2000 – 2011. Traditional methods, such as unit root tests and autocorrelation test, were employed first and they all confirmed that during the period under consideration, the JSE price index followed the random walk process. In addition, the ARIMA model was constructed and it was found that the ARIMA (1, 1, 1) was the model that most excellently fitted the data in question. Furthermore, residual tests were performed to determine whether the residuals of the estimated equation followed a random walk process in the series. The authors found that the ALSI resembles a series that follow random walk hypothesis with strong evidence of a wide variance between forecasted and actual values, indicating little or no forecasting strength in the series. To further validate the findings in this research, the variance ratio test was conducted under heteroscedasticity and resulted in non-rejection of the random walk hypothesis. It was concluded that since the returns follow the random walk hypothesis, it can be said that JSE, in terms of efficiency, is on the weak form level and therefore opportunities of making excess returns based on out-performing the market is ruled out and is merely a game of chance.
    [Show full text]
  • Lecture 20: Technical Analysis Steven Skiena
    Lecture 20: Technical Analysis Steven Skiena Department of Computer Science State University of New York Stony Brook, NY 11794–4400 http://www.cs.sunysb.edu/∼skiena The Efficient Market Hypothesis The Efficient Market Hypothesis states that the price of a financial asset reflects all available public information available, and responds only to unexpected news. If so, prices are optimal estimates of investment value at all times. If so, it is impossible for investors to predict whether the price will move up or down. There are a variety of slightly different formulations of the Efficient Market Hypothesis (EMH). For example, suppose that prices are predictable but the function is too hard to compute efficiently. Implications of the Efficient Market Hypothesis EMH implies it is pointless to try to identify the best stock, but instead focus our efforts in constructing the highest return portfolio for our desired level of risk. EMH implies that technical analysis is meaningless, because past price movements are all public information. EMH’s distinction between public and non-public informa- tion explains why insider trading should be both profitable and illegal. Like any simple model of a complex phenomena, the EMH does not completely explain the behavior of stock prices. However, that it remains debated (although not completely believed) means it is worth our respect. Technical Analysis The term “technical analysis” covers a class of investment strategies analyzing patterns of past behavior for future predictions. Technical analysis of stock prices is based on the following assumptions (Edwards and Magee): • Market value is determined purely by supply and demand • Stock prices tend to move in trends that persist for long periods of time.
    [Show full text]
  • Technical Analysis, Liquidity, and Price Discovery∗
    Technical Analysis, Liquidity, and Price Discovery∗ Felix Fritzy Christof Weinhardtz Karlsruhe Institute of Technology Karlsruhe Institute of Technology This version: 27.08.2016 Abstract Academic literature suggests that Technical Analysis (TA) plays a role in the decision making process of some investors. If TA traders act as uninformed noise traders and generate a relevant amount of trading volume, market quality could be affected. We analyze moving average (MA) trading signals as well as support and resistance levels with respect to market quality and price efficiency. For German large-cap stocks we find excess liquidity demand around MA signals and high limit order supply on support and resistance levels. Depending on signal type, spreads increase or remain unaffected which contra- dicts the mitigating effect of uninformed TA trading on adverse selection risks. The analysis of transitory and permanent price components demonstrates increasing pricing errors around TA signals, while for MA permanent price changes tend to increase of a larger magnitude. This suggests that liquidity demand in direction of the signal leads to persistent price deviations. JEL Classification: G12, G14 Keywords: Technical Analysis, Market Microstructure, Noise Trading, Liquidity ∗Financial support from Boerse Stuttgart is gratefully acknowledged. The Stuttgart Stock Exchange (Boerse Stuttgart) kindly provided us with databases. The views expressed here are those of the authors and do not necessarily represent the views of the Boerse Stuttgart Group. yE-mail: [email protected]; Karlsruhe Institute of Technology, Research Group Financial Market Innovation, Englerstrasse 14, 76131 Karlsruhe, Germany. zE-mail: [email protected]; Karlsruhe Institute of Technology, Institute of Information System & Marketing, Englerstrasse 14, 76131 Karlsruhe, Germany.
    [Show full text]
  • Technical-Analysis-Bloomberg.Pdf
    TECHNICAL ANALYSIS Handbook 2003 Bloomberg L.P. All rights reserved. 1 There are two principles of analysis used to forecast price movements in the financial markets -- fundamental analysis and technical analysis. Fundamental analysis, depending on the market being analyzed, can deal with economic factors that focus mainly on supply and demand (commodities) or valuing a company based upon its financial strength (equities). Fundamental analysis helps to determine what to buy or sell. Technical analysis is solely the study of market, or price action through the use of graphs and charts. Technical analysis helps to determine when to buy and sell. Technical analysis has been used for thousands of years and can be applied to any market, an advantage over fundamental analysis. Most advocates of technical analysis, also called technicians, believe it is very likely for an investor to overlook some piece of fundamental information that could substantially affect the market. This fact, the technician believes, discourages the sole use of fundamental analysis. Technicians believe that the study of market action will tell all; that each and every fundamental aspect will be revealed through market action. Market action includes three principal sources of information available to the technician -- price, volume, and open interest. Technical analysis is based upon three main premises; 1) Market action discounts everything; 2) Prices move in trends; and 3) History repeats itself. This manual was designed to help introduce the technical indicators that are available on The Bloomberg Professional Service. Each technical indicator is presented using the suggested settings developed by the creator, but can be altered to reflect the users’ preference.
    [Show full text]