Technical Stock Screener Page 1 Stock Market Winners
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Updated Index for New Trading Systems and Methods
Index A pairs trading, 530 Acceleration, 382—386 product spreads, 531—537 Accumulation—bottoms and tops, 105—110 program trading, 525—526 Accumulative average, 258 ratio chart, 529—530 Adaptive techniques, 731—751 representative subset of an index, 527 Chande’s Variable Index Dynamic Average, 736 reverse crack, 534 comparisons, 741 single stock futures and underlying stock, 527—528 correlation coefficient, r2, 739—740 soybean crush, 532—533 dynamic momentum index, 747—748 stock and futures relationships, 531 FAMA, 737—738 TED spread, 544 intraday breakout system, 748—749 ARIMA (Autoregressive Integrated Moving Average), Kaufman’s Adaptive Moving Average, 731—735 237—243 MAMA, 737—738 estimation: determining the coefficients, 240—241 Master Trading Formula, 745—746 first-order autoregression, 237 McGinley Dynamics, 742 forecast results, 241 MESA Adaptive Moving Average, 737—739 Kalman filters, 243 momentum calculations,740 second-order autoregression, 238 Parabolic Time/Price System, 742—745 trading strategies, 241—243 RSI programmed, 740—741 Arithmetic mean, 19—20, 26 process development example, 749—750 Arms’Equivolume, 490 trend-adjusted oscillator, 747 Arms Index, 504 stochastic, variable-length, 746—747 Artificial intelligence, 696—697. varying the trend period, 739—740 See also Pattern recognition, computer-based ADX (Average Directional Movement Index), 1015-1017 Aspects, planetary, 616—618 AD oscillator, 369—373 Aspray’s Demand Oscillator, 495—496 Advance-decline system, 508 Asset allocation. See Portfolio allocation Advanced techniques, 791—846 Astrology, financial, 612—625 chaotic patterns and market behavior, 826—827 Aspects, 616—618 entropy and conditional entropy, 827—829 Jupiter-Saturn cycle, 613—616 expert systems. See Expert systems lunar eclipses, 624—625 fractals. -
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. -
Elder-Disk for Tradestation CIMTR V
Elder-disk for TradeStation version 4.1 (for TradeStation v9.5 and newer) Thank you for purchasing this Elder-disk. It was originally developed in 2002 by Dr. Alexander Elder, the author of COME INTO MY TRADING ROOM, and by John Bruns, a programmer. This disk adds the indicators to TradeStation from this book, as well as the earlier book TRADING FOR A LIVING. This software is designed for use with TradeStation online. You must be a registered user of TradeStation Software to use this disk. Some of our newer studies require Radar Screen. You must have Radar Screen enabled to use them. Check with your TradeStation representative how to qualify for a complimentary Radar Screen. This Manual and software are Copyright © 2002, 2006, 2012 and 2017 by Elder.com and John Bruns. All Rights Reserved. Violators will be prosecuted. This manual is provided in PDF format, showing screen samples exactly as you will see them on your TradeStation. To view the PDF file, you need to have Acrobat Reader, a free program from Adobe. If you do not already have it installed, the viewer for PDF can be downloaded for free from www.adobe.com , look for Acrobat Reader. You can work with this manual displayed on your screen or print it out. TradeStation charts normally have a black background which looks great on a monitor but translates poorly to print. If you decide to print this manual, try a sample page with black charts first to see how they turn out. Keep in mind that this type of printing will use a lot of ink. -
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. -
Indicators Nison Power Concept EAST & WEST CONFIRMATION
Instructors: Syl Desaulniers, Nison Certified Trainer™ Tracy Knudsen, Nison Certified Trainer™ Improve Your Process… Get BIG Results KAIZEN TRADING APPRENTICESHIP Bonus Session Address student trades, concerns, follow-up questions Analysis of current market conditions Awarding of Kaizen Technician™ certification Strict Candlestick Patterns Qualifications for Strict Candle Patterns: - Shape of Candle Lines or Pattern - Trend requirement is the same for strict and non-strict patterns Important Concept with Candle Lines/Patterns: - Confirmation: Using a move after the initial candle signal to validate a move - Less important with East/West Confirmation Candlestick Lines and Patterns In Order of Candle Progression - Least to Most Bullish - Least to Most Bearish - Risk/Reward Tradeoff comes with candle progression Strict Candlestick Patterns - Bullish Strict Candlestick Patterns - Bearish Trend Progression/Multiple Time Frames Monthly, Weekly, Daily, 4 Hour, 2 Hour, 60 Minute, 30 Minute, 15 Minute… • Involves monitoring the same instrument across different frequencies (or time compressions) • No real limit as to how many frequencies can be monitored or which specific ones to choose • Trades placed in direction of longer term trend have higher probability of success • There are general guidelines that most practitioners will follow Trend Progression/Multiple Time Frames • Looking at a stock through different time frames can be confusing as a new trader. Why? • Because each time frame looks different! • A stock may look great on the daily chart, but look horrible on a 5 minute chart. • How many timeframes should a trader use? • Using three different periods gives a broad enough reading on the market • using fewer than this can result in a considerable loss of data • while using more typically provides redundant analysis. -
Identifying Chart Patterns with Technical Analysis
746652745 A Fidelity Investments Webinar Series Identifying chart patterns with technical analysis BROKERAGE: TECHNICAL ANALYSIS BROKERAGE: TECHNICAL ANALYSIS Important Information Any screenshots, charts, or company trading symbols mentioned are provided for illustrative purposes only and should not be considered an offer to sell, a solicitation of an offer to buy, or a recommendation for the security. Investing involves risk, including risk of loss. Past performance is no guarantee of future results Stop loss orders do not guarantee the execution price you will receive and have additional risks that may be compounded in pe riods of market volatility. Stop loss orders could be triggered by price swings and could result in an execution well below your trigg er price. Trailing stop orders may have increased risks due to their reliance on trigger pricing, which may be compounded in periods of market volatility, as well as market data and other internal and external system factors. Trailing stop orders are held on a separat e, internal order file, place on a "not held" basis and only monitored between 9:30 AM and 4:00 PM Eastern. Technical analysis focuses on market action – specifically, volume and price. Technical analysis is only one approach to analyzing stocks. When considering which stocks to buy or sell, you should use the approach that you're most comfortable with. As with all your investments, you must make your own determination as to whether an investment in any particular security or securities is right for you based on your investment objectives, risk tolerance, and financial situation. Past performance is no guarantee of future results. -
Technical Analysis: Technical Indicators
Chapter 2.3 Technical Analysis: Technical Indicators 0 TECHNICAL ANALYSIS: TECHNICAL INDICATORS Charts always have a story to tell. However, from time to time those charts may be speaking a language you do not understand and you may need some help from an interpreter. Technical indicators are the interpreters of the Forex market. They look at price information and translate it into simple, easy-to-read signals that can help you determine when to buy and when to sell a currency pair. Technical indicators are based on mathematical equations that produce a value that is then plotted on your chart. For example, a moving average calculates the average price of a currency pair in the past and plots a point on your chart. As your currency chart moves forward, the moving average plots new points based on the updated price information it has. Ultimately, the moving average gives you a smooth indication of which direction the currency pair is moving. 1 2 Each technical indicator provides unique information. You will find you will naturally gravitate toward specific technical indicators based on your TRENDING INDICATORS trading personality, but it is important to become familiar with all of the Trending indicators, as their name suggests, identify and follow the trend technical indicators at your disposal. of a currency pair. Forex traders make most of their money when currency pairs are trending. It is therefore crucial for you to be able to determine You should also be aware of the one weakness associated with technical when a currency pair is trending and when it is consolidating. -
Trade Clustering and Power Laws in Financial Markets
Theoretical Economics 15 (2020), 1365–1398 1555-7561/20201365 Trade clustering and power laws in financial markets Makoto Nirei Graduate School of Economics, University of Tokyo John Stachurski Research School of Economics, Australian National University Tsutomu Watanabe Graduate School of Economics, University of Tokyo This study provides an explanation for the emergence of power laws in asset trad- ing volume and returns. We consider a two-state model with binary actions, where traders infer other traders’ private signals regarding the value of an asset from their actions and adjust their own behavior accordingly. We prove that this leads to power laws for equilibrium volume and returns whenever the number of traders is large and the signals for asset value are sufficiently noisy. We also provide nu- merical results showing that the model reproduces observed distributions of daily stock volume and returns. Keywords. Herd behavior, trading volume, stock returns, fat tail, power law. JEL classification. G14. 1. Introduction Recently, the literature on empirical finance has converged on a broad consensus: Daily returns on equities, foreign exchange, and commodities obey a power law. This striking property of high-frequency returns has been found across both space and time through a variety of statistical procedures, from conditional likelihood methods and nonpara- metric tail decay estimation to straightforward log-log regression.1 A power law has also been found for trading volume by Gopikrishnan et al. (2000)andPlerou et al. (2001). Makoto Nirei: [email protected] John Stachurski: [email protected] Tsutomu Watanabe: [email protected] We have benefited from comments by the anonymous referees, Daisuke Oyama, and especially Koichiro Takaoka. -
Trading in the Australian Stockmarket Using Artificial Neural Networks
Bond University DOCTORAL THESIS Trading in the Australian Stockmarket Using Artificial Neural Networks Vanstone, Bruce J Award date: 2005 Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal. School of Information Technology Bond University Trading in the Australian Stockmarket using Artificial Neural Networks by Bruce James Vanstone Submitted to Bond University in fulfillment of the requirements for the degree Doctor of Philosophy November 2005 Abstract This thesis focuses on training and testing neural networks for use within stockmarket trading systems. It creates and follows a well defined methodology for developing and benchmarking trading systems which contain neural networks. Four neural networks and consequently four trading systems are presented within this thesis. The neural networks are trained using all fundamental or all technical variables, and are trained on different segments of the Australian stockmarket, namely all ordinary shares, and the S&P/ASX200 constituents. Three of the four trading systems containing neural networks significantly outperform the respective buy-and-hold returns for their segments of the market, demonstrating that neural networks are suitable for inclusion in stockmarket trading systems. -
Everything You Wanted to Know About Candlestick Charts Is an Unregulated Product Published by Thames Publishing Ltd
EEvveerryytthhiinngg yyoouu wwaanntteedd ttoo kknnooww aabboouutt ccaannddlleessttiicckk cchhaarrttss by Mark Rose • Read candlestick charts accurately • Spot patterns quickly and easily • Use that information to make profitable trading decisions Contents Chapter 1. What is a candlestick chart? 3 Chapter 2. Candlestick shapes: 6 Anatomy of a candle 6 Doji 7 Marubozo 8 Chapter 3. Candlestick Patterns 9 Harami (bullish / bearish) 9 Hammer / Hanging Man 11 Inverted Hammer / Shooting Star 13 Engulfing (bullish/ bearish) 14 Morning Star / Evening Star 15 Three White Soldiers / Three Black Crows 16 Piercing Line / Dark Cloud Cover 17 Chapter 4. The history of candlestick charts 18 Conclusion 20 Candlestick Cheat Sheet 22 2 Chapter 1. What is a candlestick chart? Before I start to talk about candlestick patterns, I’d like to get right back to basics on candles: what they are, what they look like, and why we use them … Drawing lines When you look at a chart of market prices, you can usually choose from line charts or candlestick charts. A line chart will take its price levels from the opening or closing prices according to the timeframe you have selected. So, if you’re looking at a one-minute line chart of closing prices, it will plot the closing price for each one-minute period – something like this … Line charts can be useful for looking at the “bigger picture” and finding long-term trends, but they simply cannot offer up the kind of information contained in a candlestick chart. Here is a one-minute candlestick chart for the same period … 3 At first glance, it might look a little confusing, but I can assure you that once you’re used to candlestick charts – you won’t look back. -
Relative Strength Index (RSI)
Understanding Technical Analysis : Relative Strength Index (RSI) Understanding Relative Strength Index Hi 74.57 Relative Strength Index (RSI) is a technical indicator that is categorised under Potential supply momentum indicator. Basically, all momentum indicators measures thedisruption rate dueof riseto and fall of the financial instrument's price. Usually, momentum attacksindicators on two oilare dependent indicators as they are best used with other indicators sincetankers they near do Iran not tell the traders or analysts the potential direction of the financial instrument. Among Brent the popular type of momentum indicators are Stochastic Indicator, Commodity Channel Index and Relative Strength Index. In this factsheet, we will explore the Relative Strength Index or better known as RSI. What is RSI? WTI Developed by J. Welles Wilder Jr. in his seminal 1978 book, "New Concepts in Technical Trading WTI Systems." Measures the speed and change of price movement of the financial instruments. As RSI is a type of oscillator, thisLo 2,237.40indicator is represented as a set of line that has(24 values Mar 2020) from 0 to 100. Generally, a reading below 30 indicatesLo 18,591.93 an oversold condition, while a value above (2470 Mar signals 2020) an overbought condition. Leading vs Lagging Indicator RSI is a leading type of indicator. A leading type of indicator is an indicator that can provide the traders or analyst with future price movement. Another example of leading indicator is Stochastic Indicator. In contrast, a lagging indicator is an indicator that follows the price movement of the financial instruments. Despite their lagging nature in providing trading signals, traders or analysts prefer to use lagging indicators as they are more reliable.