Candlestick Patterns (Every Trader Should Know)
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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. -
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. -
Spread, Volatility, and Volume Relationship in Financial Markets
Spread, volatility, and volume relationship in financial markets and market maker’s profit optimization Jack Sarkissian Managing Member, Algostox Trading LLC email: [email protected] Abstract We study the relationship between price spread, volatility and trading volume. We find that spread forms as a result of interplay between order liquidity and order impact. When trading volume is small adding more liquidity helps improve price accuracy and reduce spread, but after some point additional liquidity begins to deteriorate price. The model allows to connect the bid-ask spread and high-low bars to measurable microstructural parameters and express their dependence on trading volume, volatility and time horizon. Using the established relations, we address the operating spread optimization problem to maximize the market-maker’s profit. 1. Introduction When discussing security prices it is customary to describe them with single numbers. For example, someone might say price of Citigroup Inc. (ticker “C”) on April 18, 2016 was $45.11. While good enough for many uses, it is not entirely accurate. Single numbers can describe price only as referring to a particular transaction, in which 푁 units of security are transferred from one party to another at a price $푋 each. Price could be different a moment before or after the transaction, or if the transaction had different size, or if it were executed on a different exchange. To be entirely accurate, one should specify these numerous details when talking about security price. We will take this observation a step further. Technically speaking, other than at the time of transaction we cannot say that price exists as a single number at all. -
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. -
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. -
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. -
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. -
There's More to Volatility Than Volume
There's more to volatility than volume L¶aszl¶o Gillemot,1, 2 J. Doyne Farmer,1 and Fabrizio Lillo1, 3 1Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501 2Budapest University of Technology and Economics, H-1111 Budapest, Budafoki ut¶ 8, Hungary 3INFM-CNR Unita di Palermo and Dipartimento di Fisica e Tecnologie Relative, Universita di Palermo, Viale delle Scienze, I-90128 Palermo, Italy. It is widely believed that uctuations in transaction volume, as reected in the number of transactions and to a lesser extent their size, are the main cause of clus- tered volatility. Under this view bursts of rapid or slow price di®usion reect bursts of frequent or less frequent trading, which cause both clustered volatility and heavy tails in price returns. We investigate this hypothesis using tick by tick data from the New York and London Stock Exchanges and show that only a small fraction of volatility uctuations are explained in this manner. Clustered volatility is still very strong even if price changes are recorded on intervals in which the total transaction volume or number of transactions is held constant. In addition the distribution of price returns conditioned on volume or transaction frequency being held constant is similar to that in real time, making it clear that neither of these are the principal cause of heavy tails in price returns. We analyze recent results of Ane and Geman (2000) and Gabaix et al. (2003), and discuss the reasons why their conclusions di®er from ours. Based on a cross-sectional analysis we show that the long-memory of volatility is dominated by factors other than transaction frequency or total trading volume. -
The Best Candlestick Patterns
Candlestick Patterns to Profit in FX-Markets Seite 1 RISK DISCLAIMER This document has been prepared by Bernstein Bank GmbH, exclusively for the purposes of an informational presentation by Bernstein Bank GmbH. The presentation must not be modified or disclosed to third parties without the explicit permission of Bernstein Bank GmbH. Any persons who may come into possession of this information and these documents must inform themselves of the relevant legal provisions applicable to the receipt and disclosure of such information, and must comply with such provisions. This presentation may not be distributed in or into any jurisdiction where such distribution would be restricted by law. This presentation is provided for general information purposes only. It does not constitute an offer to enter into a contract on the provision of advisory services or an offer to buy or sell financial instruments. As far as this presentation contains information not provided by Bernstein Bank GmbH nor established on its behalf, this information has merely been compiled from reliable sources without specific verification. Therefore, Bernstein Bank GmbH does not give any warranty, and makes no representation as to the completeness or correctness of any information or opinion contained herein. Bernstein Bank GmbH accepts no responsibility or liability whatsoever for any expense, loss or damages arising out of, or in any way connected with, the use of all or any part of this presentation. This presentation may contain forward- looking statements of future expectations and other forward-looking statements or trend information that are based on current plans, views and/or assumptions and subject to known and unknown risks and uncertainties, most of them being difficult to predict and generally beyond Bernstein Bank GmbH´s control.