Ned Davis Research Group
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INDEX Page numbers followed by n indicate note numbers. A Arnott, Robert, 391 Ascending triangle pattern, 140–141 AB model. See Abreu-Brunnermeier model Asks (offers), 8 Abreu-Brunnermeier (AB) model, 481–482 Aspray, Thomas, 223 Absolute breadth index, 327–328 ATM. See Automated teller machine Absolute difference, 327–328 ATR. See Average trading range; Average Accelerated trend lines, 65–66 true range Acceleration factor, 88, 89 At-the-money, 418 Accumulation, 213 Average range, 79–80 ACD method, 186 Average trading range (ATR), 113 Achelis, Steven B., 214n1 Average true range (ATR), 79–80 Active month, 401 Ayers-Hughes double negative divergence AD. See Chaikin Accumulation Distribution analysis, 11 Adaptive markets hypothesis, 12, 503 Ayres, Leonard P. (Colonel), 319–320 implications of, 504 ADRs. See American depository receipts ADSs. See American depository shares B 631 Advance, 316 Bachelier, Louis, 493 Advance-decline methods Bailout, 159 advance-decline line moving average, 322 Baltic Dry Index (BDI), 386 one-day change in, 322 Bands, 118–121 ratio, 328–329 trading strategies and, 120–121, 216, 559 that no longer are profitable, 322 Bandwidth indicator, 121 to its 32-week simple moving average, Bar chart patterns, 125–157. See also Patterns 322–324 behavioral finance and pattern recognition, ADX. See Directional Movement Index 129–130 Alexander, Sidney, 494 classic, 134–149, 156 Alexander’s filter technique, 494–495 computers and pattern recognition, 130–131 American Association of Individual Investors learning objective statements, 125 (AAII), 520–525 long-term, 155–156 American depository receipts (ADRs), 317 market structure and pattern American FinanceCOPYRIGHTED Association, 479, 493 MATERIALrecognition, 131 Amplitude, 348 overview, 125–126 Analysis pattern description, 126–128 description of, 300 profitability of, 133–134 fundamental, 473 Bar charts, 38–39 Andrews, Dr. -
Global Exchange Indices
Global Exchange Indices Country Exchange Index Argentina Buenos MERVAL, BURCAP Aires Stock Exchange Australia Australian S&P/ASX All Ordinaries, S&P/ASX Small Ordinaries, Stock S&P/ASX Small Resources, S&P/ASX Small Exchange Industriials, S&P/ASX 20, S&P/ASX 50, S&P/ASX MIDCAP 50, S&P/ASX MIDCAP 50 Resources, S&P/ASX MIDCAP 50 Industrials, S&P/ASX All Australian 50, S&P/ASX 100, S&P/ASX 100 Resources, S&P/ASX 100 Industrials, S&P/ASX 200, S&P/ASX All Australian 200, S&P/ASX 200 Industrials, S&P/ASX 200 Resources, S&P/ASX 300, S&P/ASX 300 Industrials, S&P/ASX 300 Resources Austria Vienna Stock ATX, ATX Five, ATX Prime, Austrian Traded Index, CECE Exchange Overall Index, CECExt Index, Chinese Traded Index, Czech Traded Index, Hungarian Traded Index, Immobilien ATX, New Europe Blue Chip Index, Polish Traded Index, Romanian Traded Index, Russian Depository Extended Index, Russian Depository Index, Russian Traded Index, SE Europe Traded Index, Serbian Traded Index, Vienna Dynamic Index, Weiner Boerse Index Belgium Euronext Belgium All Share, Belgium BEL20, Belgium Brussels Continuous, Belgium Mid Cap, Belgium Small Cap Brazil Sao Paulo IBOVESPA Stock Exchange Canada Toronto S&P/TSX Capped Equity Index, S&P/TSX Completion Stock Index, S&P/TSX Composite Index, S&P/TSX Equity 60 Exchange Index S&P/TSX 60 Index, S&P/TSX Equity Completion Index, S&P/TSX Equity SmallCap Index, S&P/TSX Global Gold Index, S&P/TSX Global Mining Index, S&P/TSX Income Trust Index, S&P/TSX Preferred Share Index, S&P/TSX SmallCap Index, S&P/TSX Composite GICS Sector Indexes -
Final Report Amending ITS on Main Indices and Recognised Exchanges
Final Report Amendment to Commission Implementing Regulation (EU) 2016/1646 11 December 2019 | ESMA70-156-1535 Table of Contents 1 Executive Summary ....................................................................................................... 4 2 Introduction .................................................................................................................... 5 3 Main indices ................................................................................................................... 6 3.1 General approach ................................................................................................... 6 3.2 Analysis ................................................................................................................... 7 3.3 Conclusions............................................................................................................. 8 4 Recognised exchanges .................................................................................................. 9 4.1 General approach ................................................................................................... 9 4.2 Conclusions............................................................................................................. 9 4.2.1 Treatment of third-country exchanges .............................................................. 9 4.2.2 Impact of Brexit ...............................................................................................10 5 Annexes ........................................................................................................................12 -
Harmonic Conditions How to Define Price and Time Cycles
Interview: Tim Hayes – A Class of its Own Your Personal Trading Coach Issue 03, April 2010 | www.traders-mag.com | www.tradersonline-mag.com Harmonic Conditions How to Define Price and Time Cycles Great Profi ts through When to Trade The Right Use of Failed Chart Patterns & When to Fade Cyclical Analysis We Show You How to Recognise Them Gaining an Edge in Forex Trading Timing Is Everything for Lasting Success TRADERS´EDITORIAL Harmonising Price with Time Harmonising price with time is one of the issues serious traders grapple with at one point in their careers. And how could this possibly be otherwise? After all, if you wish to predict the future you have to consider the past. And if you look back on the history of trading, you will automatically end up coming across some of the heroes who have written this history. Jesse Livermore is one of them, so is Ralph Nelson Elliott and, last but not least, William D. Gann. Among all the greats of the trade he certainly stands out as the enigma. Square of Nine, Gann Lines and Gann Angles, the law of vibration of the sphere of activity, i.e. the rate of internal vibration all of which you will come The harmony of price and time results in incredible forecasts across once you begin to study the trading hero. Gann’s forecasts are credited with 90% success rates and his trading results are said to have amounted to 50 million dollars. Considering that he lived from1878 to 1955, it is easy to imagine what an incredible fortune this would be today. -
The Boundaries of Technical Analysis Milton W
The Boundaries of Technical Analysis Milton W. Berg, CFA 1 Market Prognostication In his treatise on stock market patterns, the late Professor Harry V. Roberts1 observed that “of all economic time series, the history of stock prices, both individual and aggregate, has probably been most widely and intensively studied,” and “patterns of technical analysis may be little if nothing more than a statistical artifact.”2 Ibbotson and Sinquefield maintain that historical stock price data cannot be used to predict daily, weekly or monthly percent changes in the market averages. However, they do claim the ability to predict in advance the probability that the market will move between +X% and -Y% over a specific period.3 Only to this very limited extent – forecasting the probabilities of return – can historical stock price movements be considered indicative of future price movements. In Chart 1, we present a histogram of the five-day rate of change (ROC) in the S&P 500 since 1928. The five-day ROC of stock prices has ranged from -27% to + 24%. This normal distribution4 is strong evidence that five-day changes in stock prices are effectively random. Out of 21,165 observations of five-day ROCs, there have been 138 declines exceeding -8%, (0.65% of total) and 150 gains greater than +8% (0.71% of total). Accordingly, Ibbotson and Sinquefield would maintain that over any given 5-day period, the probability of the S&P 500 gaining or losing 8% or more is 1.36%. Stated differently, the probabilities of the S&P 500 returning between -7.99% and +7.99% are 98.64%. -
Execution Version
Execution Version GUARANTEED SENIOR SECURED NOTES PROGRAMME issued by GOLDMAN SACHS INTERNATIONAL in respect of which the payment and delivery obligations are guaranteed by THE GOLDMAN SACHS GROUP, INC. (the “PROGRAMME”) PRICING SUPPLEMENT DATED 23rd SEPTEMBER 2020 SERIES 2020-12 SENIOR SECURED EXTENDIBLE FIXED RATE NOTES (the “SERIES”) ISIN: XS2233188510 Common Code: 223318851 This document constitutes the Pricing Supplement of the above Series of Secured Notes (the “Secured Notes”) and must be read in conjunction with the Base Listing Particulars dated 25 September 2019, as supplemented from time to time (the “Base Prospectus”), and in particular, the Base Terms and Conditions of the Secured Notes, as set out therein. Full information on the Issuer, The Goldman Sachs Group. Inc. (the “Guarantor”), and the terms and conditions of the Secured Notes, is only available on the basis of the combination of this Pricing Supplement and the Base Listing Particulars as so supplemented. The Base Listing Particulars has been published at www.ise.ie and is available for viewing during normal business hours at the registered office of the Issuer, and copies may be obtained from the specified office of the listing agent in Ireland. The Issuer accepts responsibility for the information contained in this Pricing Supplement. To the best of the knowledge and belief of the Issuer and the Guarantor the information contained in the Base Listing Particulars, as completed by this Pricing Supplement in relation to the Series of Secured Notes referred to above, is true and accurate in all material respects and, in the context of the issue of this Series, there are no other material facts the omission of which would make any statement in such information misleading. -
Technical Analysis
ptg TECHNICAL ANALYSIS ptg Download at www.wowebook.com This page intentionally left blank ptg Download at www.wowebook.com TECHNICAL ANALYSIS THE COMPLETE RESOURCE FOR FINANCIAL MARKET TECHNICIANS SECOND EDITION ptg Charles D. Kirkpatrick II, CMT Julie Dahlquist, Ph.D., CMT Download at www.wowebook.com Vice President, Publisher: Tim Moore Associate Publisher and Director of Marketing: Amy Neidlinger Executive Editor: Jim Boyd Editorial Assistant: Pamela Boland Operations Manager: Gina Kanouse Senior Marketing Manager: Julie Phifer Publicity Manager: Laura Czaja Assistant Marketing Manager: Megan Colvin Cover Designer: Chuti Prasertsith Managing Editor: Kristy Hart Project Editor: Betsy Harris Copy Editor: Karen Annett Proofreader: Kathy Ruiz Indexer: Erika Millen Compositor: Bronkella Publishing Manufacturing Buyer: Dan Uhrig © 2011 by Pearson Education, Inc. Publishing as FT Press Upper Saddle River, New Jersey 07458 FT Press offers excellent discounts on this book when ordered in quantity for bulk purchases or special sales. For more information, please contact U.S. Corporate and Government Sales, 1-800-382-3419, [email protected]. For sales outside the U.S., please contact International Sales at [email protected]. ptg Company and product names mentioned herein are the trademarks or registered trademarks of their respective owners. All rights reserved. No part of this book may be reproduced, in any form or by any means, without permission in writing from the publisher. Printed in the United States of America First Printing November 2010 ISBN-10: 0-13-705944-2 ISBN-13: 978-0-13-705944-7 Pearson Education LTD. Pearson Education Australia PTY, Limited. Pearson Education Singapore, Pte. Ltd. Pearson Education Asia, Ltd. -
2014 2Q Manager's Letter
Value Fund Portfolio Manager’s Letter Quarter Ended June 30, 2014 July 21, 2014 Dear Aegis Investor: The Aegis Value Fund (Class I) returned 4.39 percent over the second quarter, outpacing the 2.38 percent return of its primary small-cap value benchmark, the Russell 2000 Value Index. Past performance figures for both the Aegis Value Fund and the Russell 2000 Value Index are presented in Table 1, below: Table 1: Performance of the Aegis Value Fund as of June 30, 2014 Annualized Three Year- One Three Five Ten Since I Since A Month to-Date Year Year Year Year Share Share Inception* Inception* Aegis Value Fund Cl. I 4.39% 2.87% 14.78% 16.00% 26.89% 9.26% 12.07% NA Aegis Value Fund Cl. A at NAV 4.34% NA NA NA NA NA NA 2.77% Aegis Value Fund Cl. A -With Load 0.41% NA NA NA NA NA NA -1.08% Russell 2000 Value Index 2.38% 4.20% 22.54% 14.65% 19.88% 8.24% 8.45% 4.40% * Aegis Value Fund Class I (AVALX) and A (AVFAX) Inception were 5/15/98 and 2/26/14, respectively. Performance data quoted represents past performance and does not guarantee future results. Current perfor- mance may be lower or higher than the performance data quoted. The investment return and principal value will fluctuate so that upon redemption, an investor’s shares may be worth more or less than their original cost. For performance data current to the most recent month end, please call us at 800-528-3780 or visit our website at www.aegisfunds.com. -
Cointegration of International Stock Markets: an Investigation of Diversification Opportunities
Cointegration of International Stock Markets: An Investigation of Diversification Opportunities Taimur Ali Khan February 2011 Comprehensive Exercise in Economics Carleton College Advisor: Pavel Kapinos Abstract: This paper examines the long-run convergence of the United States and 22 other developed and developing countries. I use daily data and run the Johansen (1988) and the Gregory and Hansen (1996) test to show that stock markets of most countries have become cointegrated by 2010. I also look at short- run diversification opportunities across the countries by comparing their daily returns to the daily returns of the global index (S&P 1200). China, Malaysia and Austria stand out as countries with highly favorable diversification opportunities as they are not cointegrated about with the US and are insensitive to the global index. Finally, I use the relative risk of each country (obtained from the CAPM model) to measure performance of each country over the great recession of the 2000s. I find that the relative risk of a country is a good predictor of country performance in a recession. JEL Categories: C-22, F-36, G-15 Keywords: Stock market integration, Long‐run convergence, Cointegration, Portfolio diversification, Capital Asset Pricing Model 1 1. Introduction One of the fundamental tenants of investing is holding a diversified portfolio of securities and reducing one’s exposure to risk. Consequently, fund managers are always on the look-out for securities that do not correlate together and hence provide for better opportunities to hedge risk. In recent years that has meant moving beyond the confines of one’s borders and investing in other countries as well. -
Commentary, the Market Continues to Be Characterized by · the Strategy Invests Primarily in a Divergences
Salient Tactical Growth Sub-Advised by Broadmark Asset Management LLC September 2021 Market Update In August, the rapid spread of the Delta variant of the coronavirus led to increased investor Strategy Overview concerns over the potential for global supply chain problems and a more pronounced Salient Tactical Growth is designed to slowdown in U.S. and global growth. Asian markets weakened in August as Chinese help investors sidestep market authorities targeted a wide range of firms and industries (in addition to tech companies) downturns, while participating in its with new regulations. Hong Kong’s Hang Seng Index was down more than -20% from its growth via the continuous and active 1 management of portfolio market most recent peak before rebounding at the end of the month. Also weighing on investor’s exposure. The strategy seeks to minds were the deadly attacks at the Kabul airport and the potential repercussions of a manage risk and enhance alpha with more chaotic withdrawal from Afghanistan than anyone had anticipated. the flexibility to be long, short or neutral on the market. Despite these concerns, the S&P 500 Index, Dow Jones Industrial Average and NASDAQ-100 2 · The strategy is designed as a core Index all recorded all-time highs in August, the seventh consecutive month of gains. This investment for those who worry market strength was bolstered by Federal Reserve (Fed) Chair Jerome Powell’s remarks at about losing money in equity market the Fed’s annual Jackson Hole meeting. Powell said that the Fed would likely begin to taper downturns but also want to its asset purchases in the future but is not in a hurry to do so and would give the markets participate in the market’s upside. -
AUSTRIA.EU.NFRD.2019.10.01.Pdf
Copyright © Development International e.V., 2019 ISBN: 978-3-9820398-3-1 Authors: Chris N. Bayer, PhD Juan Ignacio Ibañez, LL.M. Jiahua (Java) Xu, PhD Title: A New Responsibility for Sustainability: Corporate Non-Financial Reporting in Austria Date published: October 1, 2019 Funded by: iPoint-systems gmbh www.ipoint-systems.com Executive Summary The EU Non-Financial Reporting Directive (NFRD) is a new regulation that seeks to “increase the relevance, consistency and comparability of information disclosed by certain large undertakings and groups across the Union.”1 Large undertakings in EU member states are not only required to report on their financial basics, now they are also required by Article 1 of the Directive to disclose their non-financial performance relevant to their business impact. This would include adverse consequences they have notably on the environment, labor rights, human rights, and how they handle diversity matters and the risk of corruption, whether as a function of their own business or actors in their supply chains. “You manage what you measure.” In accordance with the Directive, the Austrian transposition stipulates that the non-financial declaration must state which reporting framework was used to create it, as well as apply non-financial key performance indicators relevant to the particular business. These requirements are the impetus behind this study and our point of departure: We systematically assess the degree of non-financial transparency and performance reporting for 2018, applying an ex-post assessment framework premised on reporting frameworks as per the Global Reporting Initiative (GRI) and the United Nations Global Compact (UNGC). By benchmarking all Austrian companies subject to the EU NFRD-transposed law on the topics required to be disclosed – environmental, human rights, employee, social (gender), and anti-corruption matters – this study reveals which companies make an effort to show their degree of responsibility, and to what degree. -
Volume 37, Issue 3
Volume 37, Issue 3 A fractal analysis of world stock markets Taro Ikeda Graduate School of Economics, Kobe University Abstract This paper provides a fractal analysis of world stock prices. We find that the majority of stock prices are fractal. Citation: Taro Ikeda, (2017) ''A fractal analysis of world stock markets'', Economics Bulletin, Volume 37, Issue 3, pages 1514-1532 Contact: Taro Ikeda - [email protected]. Submitted: December 22, 2016. Published: July 02, 2017. 1 Introduction The recent financial crisis suggests the failure of the rational expectations of economic agents. Rational expectations are a key concept for the efficient market hypothesis (i.e., the random walk model), where rational agents process all available information to form- ing stock price forecasts, and therefore prices only change in response to new shocks, and are not correlated with past shocks. This paper contributes to the macroeconomics literature using the fractal geome- try established by Benoit, B., Mandelbrot.1 The important difference between fractal geometry and the random walk is the assumption surrounding the distribution. A bell- shaped distribution for the random walk cannot account for the risk associated with very large deviations of stock prices from their mean values, and therefore the efficient mar- ket hypothesis fails to consider the big-break-down of the stock markets. However, the power-law distribution used in fractal geometry gives large deviations higher probabilities and can capture black swan events more easily than can the random walk model. This paper provides a fractal analysis of world stock markets to test the efficient market hypothesis empirically.