Technical Analysis Introduction
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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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.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. -
Stock Chart Pattern Recognition with Deep Learning
Stock Chart Pattern recognition with Deep Learning Marc Velay and Fabrice Daniel Artificial Intelligence Department of Lusis, Paris, France [email protected] http://www.lusis.fr June 2018 ABSTRACT the number of patterns recognized implies having a human examining candlestick charts in order to deduce signal char- This study evaluates the performances of CNN and LSTM acteristics before implementing the detection using condi- for recognizing common charts patterns in a stock historical tions specific to that pattern. Adding different parameters data. It presents two common patterns, the method used to to modulate ratios allows us to tweak the patterns’ charac- build the training set, the neural networks architectures and teristics. This technique does not have any generalization the accuracies obtained. potential. If the pattern is slightly outside of the defined Keywords: Deep Learning, CNN, LSTM, Pattern recogni- bounds, it will not be detected, even if a human would have tion, Technical Analysis classified it otherwise. Another solution is DTW3 which consists in computing 1 INTRODUCTION the distance between two time series. DTW allows us to Patterns are recurring sequences found in OHLC1 candle- recognize a pattern that could vary in size and length. To stick charts which traders have historically used as buy and use this algorithm, we must use reference time series, which sell signals. Several studies, notably by Bulkowski2, have have to be selected by a human. The references must gener- found some correlation between patterns and future trends, alize well when compared with signals similar to the pattern although to a limited extent. The correlations were found to in order to capture the whole range. -
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. -
An Interview with John Bollinger
® AIQ Opening BellMonthly IN THIS ISSUE VOL. 6 ISSUE 2 FEBRUARY 1997 TRADING TECHNIQUES Feature John Bollinger discusses his Bollinger Bands .................. 1 AN INTERVIEW WITH JOHN BOLLINGER Se ctions account program, what percent of the By David Vomund investments are in equities and what is Price Volume Divergence your average holding period? Report .................................. 5 his month we are pleased to JB: We are primarily equity Market Review ..................... 8 present an interview with John investors. We dont buy any futures. Data Maintenance ............... 8 Bollinger, a keynote speaker at Our growth model is currently allo- Tour March seminar in Dallas. Mr. cated approximately 60% to the stock Bollinger is market, 20% to the president of bond market, and Bollinger Capital 20% to the interna- Management. He tional stock mar- provides money ket. We are management primarily interme- services and diate term traders. publishes the Our research tends Capital Growth to center on a Letter. He is best holding period of known for his three to six months Bollinger Bands, with most of the which is a feature emphasis on six in TradingExpert. months. However, For information on that doesnt Bollinger Capital preclude us from The Opening Bell Monthly Managements John Bollinger, CFA, CMT taking advantage is a publication of products and of short term AIQ Incorporated services, call 310-798-8855 or write to opportunities, for example when we see David Vomund, Chief Analyst P.O. Box 3358, Manhattan Beach, CA an attractive technical non-confirma- P.O. Box 7530 90266. Send e-mail to tion. Incline Village, Nevada 89452 [email protected]. -
Investing with Bollinger Bands
Investing with Bollinger Bands This article was written some years ago, but is very relevant to today. The charts used to illustrate the text are now somewhat dated, but still relevant for the present purpose of teaching a technique. As moving averages became more popular, some analysts noticed that when prices were moving upward, they had a tendency to rise only so far above the moving average. When prices were falling they tended to fall only so far below the moving average. How far they rose or fell seemed to vary from stock to stock and also from time to time. However, the tendency was so consistent that it could be useful to both traders and investors. These early analysts hit on the idea of drawing lines a certain percentage of the moving average above and below the moving average line. They selected the percentage stock-by-stock so that it seemed to catch most of the price action on the chart, typically 90% or more of the price action. GWT - GWA INTERNATIONAL > -2 to 291 D @ D 020103-070604 320 MOV AVS 22(0) 5 band 310 300 290 280 270 260 250 240 230 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN 03 04 Chart 1: Daily Line Chart of GWA International with a 22-day Moving Average and 5% Bands The result was something like Chart 1, where we have a daily line chart, on which is drawn a 22-day moving average, with 5% bands above and below it. -
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.