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A Statistical Analysis of the Predictive Power of Japanese Candlesticks Mohamed Jamaloodeen Georgia Gwinnett College, [email protected]
Journal of International & Interdisciplinary Business Research Volume 5 Article 5 June 2018 A Statistical Analysis of the Predictive Power of Japanese Candlesticks Mohamed Jamaloodeen Georgia Gwinnett College, [email protected] Adrian Heinz Georgia Gwinnett College, [email protected] Lissa Pollacia Georgia Gwinnett College, [email protected] Follow this and additional works at: https://scholars.fhsu.edu/jiibr Part of the Finance and Financial Management Commons Recommended Citation Jamaloodeen, Mohamed; Heinz, Adrian; and Pollacia, Lissa (2018) "A Statistical Analysis of the Predictive Power of Japanese Candlesticks," Journal of International & Interdisciplinary Business Research: Vol. 5 , Article 5. Available at: https://scholars.fhsu.edu/jiibr/vol5/iss1/5 This Article is brought to you for free and open access by FHSU Scholars Repository. It has been accepted for inclusion in Journal of International & Interdisciplinary Business Research by an authorized editor of FHSU Scholars Repository. Jamaloodeen et al.: Analysis of Predictive Power of Japanese Candlesticks A STATISTICAL ANALYSIS OF THE PREDICTIVE POWER OF JAPANESE CANDLESTICKS Mohamed Jamaloodeen, Georgia Gwinnett College Adrian Heinz, Georgia Gwinnett College Lissa Pollacia, Georgia Gwinnett College Japanese Candlesticks is a technique for plotting past price action of a specific underlying such as a stock, index or commodity using open, high, low and close prices. These candlesticks create patterns believed to forecast future price movement. Although the candles’ popularity has increased rapidly over the last decade, there is still little statistical evidence about their effectiveness over a large number of occurrences. In this work, we analyze the predictive power of the Shooting Star and Hammer patterns using over six decades of historical data of the S&P 500 index. -
Copyrighted Material
Index 12b-1 fee, 68–69 combining with Western analysis, 3M, 157 122–123 continuation day, 116 ABC of Stock Speculation, 157 doji, 115 accrual accounting, 18 dragonfl y doji, 116–117 accumulated depreciation, 46–47 engulfi ng pattern, 120, 121 accumulation phase, 158 gravestone doji, 116, 117, 118 accumulation/distribution line, hammer, 119 146–147 hanging man, 119 Adaptive Market Hypothesis, 155 harami, 119, 120 Altria, 29, 127, 185–186 indicators 120 Amazon.com, 151 long, 116, 117, 118 amortization, 47, 49 long-legged doji, 118 annual report, 44–46 lower shadow, 115 ascending triangle, 137–138, 140 marubozu, 116 at the money, 192 real body, 114–115 AT&T, 185–186 segments illustrated, 114 shadows, 114 back-end sales load, 67–68 short,116, 117 balance sheet, 46–50 spinning top, 118–119 balanced mutual funds, 70–71 squeeze alert, 121, 122, 123 basket of stocks, 63 tails, 114 blue chip companies, 34 three black crows, 122, 123 Boeing, 134–135 three white soldiers, 122, 123 book value, 169 trend-based, 117–118 breadth, 82–83, 97 upper shadow, 115 breakaway gap, 144 wicks, 114 break-even rate, 16–17 capital assets, 48, 49 breakout, 83–84, 105–106 capitalization-based funds, 71 Buffett, Warren, 152 capitalization-weighted average, 157 bull and bear markets,COPYRIGHTED 81, 174–175 Caterpillar, MATERIAL 52–54, 55, 57, 58, 59, 131 Bureau of Labor Statistics (BLS), 15 CBOE Volatility Index (VIX), 170, 171 Buy-and-hold strategy, 32, 204–205 Chaikin Money Flow (CMF), 146 buy to open/sell to open, 96 channel, 131–132 charting calendar spreads, 200–201 -
Stock Market Prediction Using Candlestick Chart
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 07 Issue: 01 | Jan 2020 www.irjet.net p-ISSN: 2395-0072 Stock Market Prediction using Candlestick Chart Razik Batliwala1, Muddassir Khan2, Durvesh Bhushan3 1,2Information Technology, PadmabhushanVasantdada Patil Pratishthan’s College of Engineering, Sion Mumbai 3Vaity Information Technology PadmabhushanVasantdada Patil Pratishthan’s College of Engineering, Sion Mumbai ------------------------------------------------------------------------***------------------------------------------------------------------------- Abstract—The stock market is a place where shares of publicly listed companies are traded. There shares based on brought and sold on this basis of there stock. The price of stocks and assets are an important part of the economy. There are many factors that affect share prices. However there is no specific cause for the prices to rise or fall. This makes investment subject to various risks. We proposed a novel method for prediction of stocks price on the basis of statistical data and making of candlestick chart for up to 3-4 days to find if investment are beneficial or loss of money, It is also beneficial to analyzing in future stock. In this paper we developing (LCS) Longest Common Subsequence Algorithm to retrieve numerical sequences that partially match. It also use for real time service provider to provide stock market sentiments. Keywords—Stock price prediction; Technical analysis; Candlestick charts; Longest common subsequence algorithm for numbers; Multi numerical attributes; Nse,Bse stock average. 1. INTRODUCTION Stock market prediction techniques play a crucial role to bring more people into market and encourage markets as a whole. Fundamental analysis and technical analysis are two popular approaches to successful stock trading. -
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. -
Calibration of Bollinger Bands Parameters for Trading Strategy Development in the Baltic Stock Market
ISSN 1392 – 2785 Inzinerine Ekonomika-Engineering Economics, 2010, 21(3), 244-254 Calibration of Bollinger Bands Parameters for Trading Strategy Development in the Baltic Stock Market Audrius Kabasinskas, Ugnius Macys Kaunas University of Technology K. Donelaicio st. 73, LT-44029, Kaunas, Lithuania e-mail: [email protected], [email protected] In recent decades there was a robust boom in "Bollinger plotter" was developed using the most investment sector in Lithuania, as more people chose to popular mathematical toolbox MatLab in order to solve invest money in investment funds rather than keep money in stated problems. Application is capable of charting the closet. The Baltic States Market turnover has increased Bollinger Bands and 6 other technical indicators with from 721 MEUR in 2000 to 978 MEUR in 2008 (with peak desired period of time. This software is not a fully 2603 MEUR in 2005). When difficult period appeared in automated decision making system, as decisions are global markets, a lot of attention was dedicated towards the usually made based on value judgment. managing of investments. Investment management firms in Since the stock returns usually have distributions with Lithuania gain significance in personal as well as in fat tails, then less than 95% of data fit in the Bollinger business section increasingly; even though these firms are trading channels. However the Bollinger bands trading considerably young (the first one in Lithuania was signals were supported by additional indicators (e.g. %b), established in year 2000). so the loss of data is not significant. Successful investment begins with the financial Our calibration results show that short term investor analysis of stock, asset or index, which you are going to should apply 10 days moving average and use a trading invest. -
FOREX WAVE THEORY.Pdf
FOREX WAVE THEORY This page intentionally left blank FOREX WAVE THEORY A Technical Analysis for Spot and Futures Currency Traders JAMES L. BICKFORD McGraw-Hill New York Chicago San Francisco Lisbon London Madrid Mexico City Milan New Delhi San Juan Seoul Singapore Sydney Toronto Copyright © 2007 by The McGraw-Hill Companies. All rights reserved. Manufactured in the United States of America. Except as permitted under the United States Copyright Act of 1976, no part of this publication may be reproduced or distributed in any form or by any means, or stored in a database or retrieval system, without the prior written permission of the publisher. 0-07-151046-X The material in this eBook also appears in the print version of this title: 0-07-149302-6. All trademarks are trademarks of their respective owners. Rather than put a trademark symbol after every occurrence of a trademarked name, we use names in an editorial fashion only, and to the benefit of the trademark owner, with no intention of infringement of the trademark. Where such designations appear in this book, they have been printed with initial caps. McGraw-Hill eBooks are available at special quantity discounts to use as premiums and sales pro- motions, or for use in corporate training programs. For more information, please contact George Hoare, Special Sales, at [email protected] or (212) 904-4069. TERMS OF USE This is a copyrighted work and The McGraw-Hill Companies, Inc. (“McGraw-Hill”) and its licen- sors reserve all rights in and to the work. Use of this work is subject to these terms. -
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. -
Stock Market Explained
Stock Market Explained A Beginner's Guide to Investing and Trading in the Modern Stock Market © Ardi Aaziznia www.PeakCapitalTrading.com Copyrighted Material © Peak Capital Trading CHAPTER 1 Copyrighted Material © Peak Capital Trading Figure 1.1: “covid-19” and “stock market” keyword Google search trends between April 2019 and April 2020. As you can see, there is a clear correlation. As the stock market drop hit the news cycles, people started searching more and more about the stock market in Google! Copyrighted Material © Peak Capital Trading COVID-19 Bear Market 2019 Bull Market 2020 recession due to pandemic v Figure 1.2: Comparison between the bull market of 2019 and the bear market of 2020, as shown by the change in share value of 500 of the largest American companies. These companies are tracked by the S&P 500 and are traded in an exchange-traded fund known as the SPDR S&P 500 ETF Trust (ticker: SPY). For your information, S&P refers to Standard & Poor’s, one of the indices which used to track this information. Copyrighted Material © Peak Capital Trading Figure 1.3: How this book is organized. Chapters 1-4 and 7-11 are written by me. Chapters 5 and 6 on day trading are written by Andrew Aziz. Copyrighted Material © Peak Capital Trading CHAPTER 2 Copyrighted Material © Peak Capital Trading Figure 2.1: The return on investing $100 in an exchange-traded fund known as the SPDR S&P 500 ETF Trust (ticker: SPY) (which tracks the share value of 500 of the largest American companies (as rated by the S&P 500)) vs. -
Candlestick—The Main Mistake of Economy Research in High Frequency Markets
International Journal of Financial Studies Article Candlestick—The Main Mistake of Economy Research in High Frequency Markets Michał Dominik Stasiak Department of Investment and Real Estate, Poznan University of Economics and Business, al. Niepodleglosci 10, 61-875 Poznan, Poland; [email protected] Received: 4 August 2020; Accepted: 1 October 2020; Published: 10 October 2020 Abstract: One of the key problems of researching the high-frequency financial markets is the proper data format. Application of the candlestick representation (or its derivatives such as daily prices, etc.), which is vastly used in economic research, can lead to faulty research results. Yet, this fact is consistently ignored in most economic studies. The following article gives examples of possible consequences of using candlestick representation in modelling and statistical analysis of the financial markets. Emphasis should be placed on the problem of research results being detached from the investing practice, which makes most of the results inapplicable from the investor’s point of view. The article also presents the concept of a binary-temporal representation, which is an alternative to the candlestick representation. Using binary-temporal representation allows for more precise and credible research and for the results to be applied in investment practice. Keywords: high frequency econometric; technical analysis; investment decision support; candlestick representation; binary-temporal representation JEL Classification: C01; C53; C90 1. Introduction While researching any subject literature, often one can notice that some popular methods in scientific research are copied and used without second thought by further researchers. Nowadays, the vast majority of papers pertaining to the analysis of course trajectory on financial markets and connected prediction possibilities use historical data in the form of a candlestick representation (or its derivatives such as daily opening prices, usually called daily prices, etc.) (Burgess 2010; Kirkpatrick and Dahlquist 2010; Schlossberg 2012). -
Modeling and Analyzing Stock Trends
Modeling and Analyzing Stock Trends A Major Qualifying Project Submitted to the Faculty of Worcester Polytechnic Institute in partial fulllment of the requirements for the Degree in Bachelor of Science Mathematical Sciences By Laura Cintron Garcia Date: 5/6/2021 Advisor: Dr. Mayer Humi This report represents work of WPI undergraduate students submitted to the faculty as evidence of a degree requirement. WPI routinely publishes these reports on its web site without editorial or peer review. For more information about the projects program at WPI, see http://www.wpi.edu/Academics/Projects 1 Abstract Abstract The goal of this project is to create and compare several dierent stock prediction models and nd a correlation between the predic- tions and volatility for each stock. The models were created using the historical data, DJI index, and moving averages. The most accurate prediction model had an average of 5.3 days spent within a predic- tion band. A correlation of -0.0438 was found between that model an a measure of volatility, indicating that more prediction days means lower volatility. 2 2 Acknowledgments Without the help of some people, it would have been signicantly more di- cult to complete this project without a group. I want to extend my gratitude to Worcester Polytechnic Institute and the WPI Math Department for their great eorts and success this year regarding school and projects during the pandemic. They did everything they could to ensure these projects was still a rich experience for the students despite everything. I would also like to thank my MQP advisor, Professor Mayer Humi for his assistance and guidance on this project, for allowing me to work indepen- dently while always being willing to meet with me or answer any questions, and for continuously encouraging me to do what I thought was best for the project. -
Japanese Candlestick Patterns
Presents Japanese Candlestick Patterns www.ForexMasterMethod.com www.ForexMasterMethod.com RISK DISCLOSURE STATEMENT / DISCLAIMER AGREEMENT Trading any financial market involves risk. This course and all and any of its contents are neither a solicitation nor an offer to Buy/Sell any financial market. The contents of this course are for general information and educational purposes only (contents shall also mean the website http://www.forexmastermethod.com or any website the content is hosted on, and any email correspondence or newsletters or postings related to such website). Every effort has been made to accurately represent this product and its potential. There is no guarantee that you will earn any money using the techniques, ideas and software in these materials. Examples in these materials are not to be interpreted as a promise or guarantee of earnings. Earning potential is entirely dependent on the person using our product, ideas and techniques. We do not purport this to be a “get rich scheme.” Although every attempt has been made to assure accuracy, we do not give any express or implied warranty as to its accuracy. We do not accept any liability for error or omission. Examples are provided for illustrative purposes only and should not be construed as investment advice or strategy. No representation is being made that any account or trader will or is likely to achieve profits or losses similar to those discussed in this report. Past performance is not indicative of future results. By purchasing the content, subscribing to our mailing list or using the website or contents of the website or materials provided herewith, you will be deemed to have accepted these terms and conditions in full as appear also on our site, as do our full earnings disclaimer and privacy policy and CFTC disclaimer and rule 4.41 to be read herewith.