Viewing Relative Strength with Point and Figure Charting
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Point and Figure Charts
Point and Figure Charts Point-and-figure (P&F) chart is a special type of graphical analysis, which lays stress to prediction of medium-term and long-term trends. Conclusion Let’s single out advantages and disadvantages of Point and Figure charts. Point and Figure Advantages 1. P&F charts send only clear buy or sell signals without any dual nature. 2. P&F charts take into account only “important” price changes and filter out market noise. This being said, the “importance” of changes is set by a trader. 3. P&F charts are not affected by time effect, which sometimes introduces additional element of uncertainty on general charts. 4. P&F charts allow to identify support and resistance levels, and also trend lines. 5. P&F charts are very intelligible. Point and Figure Disadvantages 1. P&F charts send clear signals only for medium-term and long-term periods and are almost not intended for short-term trade. Building Point and Figure Charts The majority of the most popular charts, used for technical analysis, are built in accordance with opening price, closing price, maximum or minimum for a definite period. Only closing price for a period is used for building Point and Figure charts. Point and Figure charts consist of X and O columns, which reflect the filtered price changes. Increase in prices is shown by “X” boxes, and drop in prices is shown by “O” boxes. New boxes are created only in case of price change by the size of a box or more in one of directions. -
Predicting SARS-Cov-2 Infection Trend Using Technical Analysis Indicators
medRxiv preprint doi: https://doi.org/10.1101/2020.05.13.20100784; this version posted May 20, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Predicting SARS-CoV-2 infection trend using technical analysis indicators Marino Paroli and Maria Isabella Sirinian Department of Clinical, Anesthesiologic and Cardiovascular Sciences, Sapienza University of Rome, Italy ABSTRACT COVID-19 pandemic is a global emergency caused by SARS-CoV-2 infection. Without efficacious drugs or vaccines, mass quarantine has been the main strategy adopted by governments to contain the virus spread. This has led to a significant reduction in the number of infected people and deaths and to a diminished pressure over the health care system. However, an economic depression is following due to the forced absence of worker from their job and to the closure of many productive activities. For these reasons, governments are lessening progressively the mass quarantine measures to avoid an economic catastrophe. Nevertheless, the reopening of firms and commercial activities might lead to a resurgence of infection. In the worst-case scenario, this might impose the return to strict lockdown measures. Epidemiological models are therefore necessary to forecast possible new infection outbreaks and to inform government to promptly adopt new containment measures. In this context, we tested here if technical analysis methods commonly used in the financial market might provide early signal of change in the direction of SARS-Cov-2 infection trend in Italy, a country which has been strongly hit by the pandemic. -
A Test of Macd Trading Strategy
A TEST OF MACD TRADING STRATEGY Bill Huang Master of Business Administration, University of Leicester, 2005 Yong Soo Kim Bachelor of Business Administration, Yonsei University, 200 1 PROJECT SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF BUSINESS ADMINISTRATION In the Faculty of Business Administration Global Asset and Wealth Management MBA O Bill HuangIYong Soo Kim 2006 SIMON FRASER UNIVERSITY Fall 2006 All rights reserved. This work may not be reproduced in whole or in part, by photocopy or other means, without permission of the author. APPROVAL Name: Bill Huang 1 Yong Soo Kim Degree: Master of Business Administration Title of Project: A Test of MACD Trading Strategy Supervisory Committee: Dr. Peter Klein Senior Supervisor Professor, Faculty of Business Administration Dr. Daniel Smith Second Reader Assistant Professor, Faculty of Business Administration Date Approved: SIMON FRASER . UNI~ER~IW~Ibra ry DECLARATION OF PARTIAL COPYRIGHT LICENCE The author, whose copyright is declared on the title page of this work, has granted to Simon Fraser University the right to lend this thesis, project or extended essay to users of the Simon Fraser University Library, and to make partial or single copies only for such users or in response to a request from the library of any other university, or other educational institution, on its own behalf or for one of its users. The author has further granted permission to Simon Fraser University to keep or make a digital copy for use in its circulating collection (currently available to the public at the "lnstitutional Repository" link of the SFU Library website <www.lib.sfu.ca> at: ~http:llir.lib.sfu.calhandlell8921112~)and, without changing the content, to translate the thesislproject or extended essays, if .technically possible, to any medium or format for the purpose of preservation of the digital work. -
2021 Mid-Year Outlook July 2021 Economic Recovery, Updated Vaccine, and Portfolio Considerations
2021 Mid-Year Outlook July 2021 Economic recovery, updated vaccine, and portfolio considerations. Key Observations • Financial market returns year-to-date coincide closely with the premise of an expanding global economic recovery. Economic momentum and a robust earnings backdrop have fostered uniformly positive global equity returns while this same strength has been the impetus for elevated interest rates, hampering fixed income returns. • Our baseline expectation anticipates that the continuation of the economic revival is well underway but its relative strength may be shifting overseas, particularly to the Eurozone, where amplifying vaccination efforts and the prospects for additional stimulus reign. • Our case for thoughtful risk-taking remains intact. While the historically sharp and compressed pace of the recovery has spawned exceptionally strong returns across many segments of the capital markets and elevated valuations, the economic expansion should continue apace, fueled by still highly accommodative stimulus, reopening impetus and broader vaccination. Financial Market Conditions Economic Growth Forecasts for global economic growth in 2021 and 2022 remain robust with the World Bank projecting a 5.6 percent growth rate for 2021 and a 4.3 percent rate in 2022. If achieved, this recovery pace would be the most rapid recovery from crisis in some 80 years and provides a full reckoning of the extraordinary levels of stimulus applied to the recovery and of the herculean efforts to develop and distribute vaccines. GDP Growth Rates Source: FactSet Advisory services offered through Veracity Capital, LLC, a registered investment advisor. 1 While the case for further global economic growth remains compelling, we are mindful that near-term base effect comparisons and a bifurcated pattern of growth may be masking some complexities of the recovery. -
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. -
Proquest Dissertations
INFORMATION TO USERS This manuscript has been reproduced from the microfilm master. UMI films the text directly from the original or copy sutxnitted. Thus, some thesis and dissertation copies are in typewriter face, while others may be from any type of computer printer. The quality of this reproduction is dependent upon the quality of the copy submitted. Broken or indisünct print, colored or poor quality illustrations and photographs, print bleedthrough, substandard margins, and improper alignment can adversely affect reproduction. In the unlikely event that the author did not send UMI a complete manuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note will indicate the deletion. Oversize materials (e.g., maps, drawings, charts) are reproduced by sectioning the original, beginning at the upper left-hand comer and continuing from left to right in equal sections with small overlaps. Photographs included in the original manuscript have been reproduced xerographically in this copy. Higher quality 6” x 9” black and white photographic prints are available for any photographs or illustrations appearing in this copy for an additional charge. Contact UMI directly to order. Bell & Howell Information and Leaming 300 North Zeeb Road. Ann Arbor, Ml 48106-1346 USA 800-521-0600 UMÏ METAPHORS OF EXCHANGE AND THE SHANGHAI STOCK MARKET DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in the Graduate School o f The Ohio State University By Susan Diane Menke, M A ***** The Ohio State University 2000 Dissertation committee: Approved by: Dr. -
Forecasting Direction of Exchange Rate Fluctuations with Two Dimensional Patterns and Currency Strength
FORECASTING DIRECTION OF EXCHANGE RATE FLUCTUATIONS WITH TWO DIMENSIONAL PATTERNS AND CURRENCY STRENGTH A THESIS SUBMITTED TO THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES OF MIDDLE EAST TECHNICAL UNIVERSITY BY MUSTAFA ONUR ÖZORHAN IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PILOSOPHY IN COMPUTER ENGINEERING MAY 2017 Approval of the thesis: FORECASTING DIRECTION OF EXCHANGE RATE FLUCTUATIONS WITH TWO DIMENSIONAL PATTERNS AND CURRENCY STRENGTH submitted by MUSTAFA ONUR ÖZORHAN in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Engineering Department, Middle East Technical University by, Prof. Dr. Gülbin Dural Ünver _______________ Dean, Graduate School of Natural and Applied Sciences Prof. Dr. Adnan Yazıcı _______________ Head of Department, Computer Engineering Prof. Dr. İsmail Hakkı Toroslu _______________ Supervisor, Computer Engineering Department, METU Examining Committee Members: Prof. Dr. Tolga Can _______________ Computer Engineering Department, METU Prof. Dr. İsmail Hakkı Toroslu _______________ Computer Engineering Department, METU Assoc. Prof. Dr. Cem İyigün _______________ Industrial Engineering Department, METU Assoc. Prof. Dr. Tansel Özyer _______________ Computer Engineering Department, TOBB University of Economics and Technology Assist. Prof. Dr. Murat Özbayoğlu _______________ Computer Engineering Department, TOBB University of Economics and Technology Date: ___24.05.2017___ I hereby declare that all information in this document has been obtained and presented in accordance with academic rules and ethical conduct. I also declare that, as required by these rules and conduct, I have fully cited and referenced all material and results that are not original to this work. Name, Last name: MUSTAFA ONUR ÖZORHAN Signature: iv ABSTRACT FORECASTING DIRECTION OF EXCHANGE RATE FLUCTUATIONS WITH TWO DIMENSIONAL PATTERNS AND CURRENCY STRENGTH Özorhan, Mustafa Onur Ph.D., Department of Computer Engineering Supervisor: Prof. -
Charles Dow Desarrolla Lo Que Hoy Se Conoce Como El Dow Jones Industrial Average®
Hitos 1896 • Charles Dow desarrolla lo que hoy se conoce como el Dow Jones Industrial Average®. 1923 • Standard Statistics Company, antecesora de Standard & Poor’s, desarrolla su primer indicador del mercado accionario con cobertura a 233 empresas. 1926 • Standard Statistics Company lanza al mercado un índice compuesto de precios que incluía 90 acciones. 1941 • Standard Statistics se fusiona con Poor’s Publishing para formar Standard & Poor's. • El indicador del mercado accionario creado en 1923 aumenta su número de compañías de 233 a 416. 1946 • El Dow Jones Industrial Average cumple 50 años. 1957 • Standard & Poor’s publica por primera vez el S&P 500® como un índice de 500 acciones. 1972 • El S&P 500 se convierte en el primer índice bursátil con publicación diaria. 1975 • ExxonMobil se convierte en el primer fondo de pensiones vinculado al S&P 500 y la industria comienza a expandirse. • La calidad institucional llega al mercado general. Vanguard lanza el primer fondo mutuo de índices de consumo, el Vanguard 500, y utiliza el S&P 500 como benchmark. 1982 • CME Group comienza a operar los primeros índices de futuros ―S&P 500 index futures― en la Bolsa de Valores de Chicago (Chicago Mercantile Exchange). 1983 • El Mercado de Opciones de la Bolsa de Chicago (CBOE®) comienza a operar el primer índice de opciones. Estas opciones se basaban en el S&P 500 y el S&P 100. S&P Dow Jones Indices – Hitos 2016 1991 • Standard & Poor’s lanza al mercado el S&P MidCap 400®, el primer índice destacado de títulos de capitalización media en Estados Unidos. -
Results of the S&P Paris-Aligned & Climate Transition (PACT) Indices
INDEX ANNOUNCEMENT Results of the S&P Paris-Aligned & Climate Transition (PACT) Indices Consultation on Eligibility Requirements and Constraints AMSTERDAM, MAY 18, 2021: S&P Dow Jones Indices (“S&P DJI”) has conducted a consultation with market participants on potential changes to the S&P Paris-Aligned & Climate Transition (PACTTM) Indices. S&P DJI will make changes to the eligibility requirements and optimization constraints used in these indices. The changes are designed to ensure the indices continue to meet their objective, reflect evolving expectations for environmental, social and governance (ESG) business exclusions, while including additional stability to the turnover and stock counts following fluctuations caused by the existing rules. The table below summarizes the changes, and which indices they will impact. Index Family1 Methodology Change CT PA Current Updated Environmental X X CT: Weighted-average S&P DJI CT: Weighted-average S&P DJI ESG Score Score Environmental Score (waE) of the CT Index (waESG) of the CT Index should be ≥ the Constraint to should be ≥ the waE of the eligible universe. eligible waESG of the eligible universe. ESG Score Constraint PA: Weighted-average S&P DJI PA: Weighted-average S&P DJI ESG Score Environmental Score (waE) of the PA Index (waESG) of the PA Index should be ≥ the should be ≥ the waE of the eligible universe waESG of the universe after 20% of the + (20% × (max E score in eligible universe – worst ESG score performing companies by eligible universe’s waE)). count are removed and weight redistributed. Introduce X X No buffer, minimum stock weight lower Minimum stock weight threshold ≥1 buffer rule and threshold of 0.01%, maximum weight of 5%. -
Stock Market Efficiency Withstands Another Challenge: Solving the “Sell in May/Buy After Halloween” Puzzle
Econ Journal Watch, Volume 1, Number 1, April 2004, pp 29-46. Stock Market Efficiency Withstands another Challenge: Solving the “Sell in May/Buy after Halloween” Puzzle EDWIN D. MABERLY* AND RAYLENE M. PIERCE** A COMMENT ON: BOUMAN, SVEN AND BEN JACOBSEN. 2002. THE HALLOWEEN INDICATOR, ‘SELL IN MAY AND GO AWAY’: ANOTHER PUZZLE. AMERICAN ECONOMIC REVIEW 92(5): 1618-1635. ABSTRACT, KEYWORDS, JEL CODES OVER THE PAST TWENTY YEARS FINANCIAL ECONOMISTS HAVE documented numerous stock return patterns related to calendar time. The list includes patterns related to the month-of-the-year (January effect), day- of-the-week (Monday effect), day-of-the-month (turn-of-the-month effect), and market closures due to exchange holidays (the holiday effect) to name just a few.1 This research is cited as evidence of market inefficiencies (see, * University of Canterbury. Chiristchurch, New Zealand. ** Lincoln University. Canterbury, New Zealand. This paper benefited from editorial comments by Professor Tom Saving of Texas A&M University and encouraging comments by Professor Burton Malkiel of Princeton University. Additionally, constructive comments were provided by an anonymous referee. 1 The January effect is frequently misinterpreted as implying that stock returns, irrespective of market size, are unusually large in January. From Fama (1991, 1586-1587), the January effect refers to the phenomenon that “stock returns, especially returns on small stocks, are on average higher in January than in other months. Moreover, much of the higher January return on small stocks comes on the last trading day in December and the first 5 trading days in January.” 29 EDWIN D. -
Trend-Wave Trading Harnessing the Power of the Elliott Wave Principle with the Discipline of Trend Following
Technical Analysis Trend-Wave Trading Harnessing the Power of the Elliott Wave Principle with the Discipline of Trend Following June 2011 Murray Gunn CFTe Head of Technical Analysis HSBC Bank plc +44 20 7991 6797 [email protected] View HSBC Global Research at: http://www.research.hsbc.com Issuer of report: HSBC Bank plc Disclosures and Disclaimer This report must be read with the disclosures and the analyst ABC certifications in the Disclosure appendix, and with the Disclaimer, which forms part of it Global Research1 The Elliott Wave Principle – A Basic Guide 1 Elliott Wave Principle A Fractal Design (5) Ralph Nelson Elliott (3) (B) Price action occurs in regular patterns Long 5 moves (or waves) in the direction of the primary Term 2 (4) 5 (A) trend 2 (1) 3 C 4 2 (C) 3 moves (or waves) when the price action is 1 A 4 correcting against the primary trend 5 1 3 B 1 4 (2) B 5 Repeat at every time frame or fractal Medium 3 Term 3 A 2 1 5 Mass human psychology is patterned C 1 4 5 B (5) Ratio analysis/natural mathematics (Phi, the golden 3 5 (B) 2 2 C ratio, 1.618, Leonardo Fibonacci) 1 4 A C 3 4 2 (3) 1 A 2 5 1 4 4 Elliott heavily influenced by Charles Dow Short B 3 B 1 Term 5 Wave Principle is the purest form of TA 3 A 2 (A) 3 (1) 5 The 1 C 5 4 (C) Full 3 B (4) Putting it all Cycle 1 A 2 together 2 4 C 2 (2) 2 Waves Are Self Similar in FORM… …but they do NOT have to be self similar in TIME or depth (AMPLITUDE) (5) Much more like REALITY 5 (3) 3 1 5 3 B 4 D 4 2 1 E (4) (1) 5 C 3 4 B 2 A 1 A 2 C 3 (2) Elliott’s Wave Principle is technical analysis Elliott heavily influenced by Charles Dow Empirical observations confirmed Dow’s Theory Refined Dow’s work into more detail Price and volume = pure technical analysis Edwards & Magee pattern recognition a derivative of Dow and Elliott 4 Dow Theory • Charles Dow’s editorials in his Wall Street Journal around 1900 • Analysis of price action of the market averages (Dow Industrials, Transports, Utilities) Distribution • Markets have 3 “movements” (value, primary and phase secondary movement). -
Relative Strength Index (RSI) Application in Identifying Trading Movements of Selected IT Sector Companies in India 1P
IJMBS VOL . 7, Iss UE 1, JAN - MARCH 2017 ISSN : 2230-9519 (Online) | ISSN : 2231-2463 (Print) Relative Strength Index (RSI) Application in Identifying Trading Movements of Selected IT Sector Companies in India 1P. Selvam, 2L. Rakesh 1Business Studies, Sree Sastha Institute of Engineering & Technology, Chennai, India 2Senior Business Analyst, The Royal Bank of Scotland, Chennai, India Abstract The other variation of computing RSI: The stock market has been an integral part of the economy of any RSI = 100 X (1/(D/D+U) RSI – 100 ((100/U) /( 1+U/D)) country. The stock market plays a pivotal role in the growth of the Where, industry and commerce of the country that would subsequently D = an average of downward price change affect the economy of the country to a great extent. In the recent U = an average of upward price change past, share market investment has become one of the predominant As mentioned early, RSI usually makes fluctuation between 0 investment avenues for investors. Hence, investors wishing to make to 100. RSI peaks are an indication of overbought levels and an investment in share market are required to be conversant with suggest price tops, while RSI troughs are an indication of oversold share market trading practices, price fluctuations and appropriate levels and share price bottoms. Two horizontal lines are normally time for buying and selling securities. This article is proposed to drawn at 30 (indicating an oversold area) and 70 (indicating an apply the momentum oscillator by the name “Relative Strength overbought area). These two RSI lines can be adjusted depending Index – (RSI)” for figuring out an overbought and oversold on the market environment.