DOCSLIB.ORG

An Empirical Analysis of the Adaptive Market Hypothesis and Investor Sentiment in Extreme Circumstances

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
An Empirical Analysis of the Adaptive Market Hypothesis and Investor Sentiment in Extreme Circumstances An Empirical Analysis of the Adaptive Market Hypothesis and Investor Sentiment in Extreme Circumstances Andrew Urquhart Submitted in fulfilment of the requirements for the degree of Doctor of Philosophy Department of Economics Newcastle University Business School Newcastle University June 2013 Abstract The Efficient Market Hypothesis (EMH) has been widely studied in the literature, however there remains no consensus among academics whether markets are efficient or not. Although it was initially thought to hold, the recent explosion of studies that find that markets are not efficient has cast serious doubt on the validity of the EMH. Furthermore, the vast majority of the literature examines the EMH over some predetermined sample period, disregarding the fact that the level of efficiency may change over time and a large sample period may not be efficient or not for the whole period. A new theory that tries to accommodate both these facets is the Adaptive Market Hypothesis (AMH), proposed by Andrew Lo (2004). This theory enables market efficiency and market inefficiencies to co-exist together and market efficiency to evolve over time. The main objective of this thesis is to examine the AMH and stock return behaviour in major stock markets using very long data and determine whether it is a more appropriate model for describing stock market behaviour than the EMH. A five-type classification is proposed to distinguish the differing behaviour of stock returns over time. Daily data is spilt into five- yearly subsamples and investigated in respect of linear and nonlinear time-series tests, three calendar anomalies and the moving average technical rule. The results suggest that the AMH provides a better description of the behaviour of stock returns than the classic EMH. Linked to the AMH is the fact that investors are not rational and investor psychology plays a real role in investor’s decision making. With that in mind, this thesis also examines the level of investor sentiment in stock returns during World War Two in Britain. This is a time period that has not been studied in great detail and provides an opportunity to examine investor sentiment in extreme circumstances. The empirical results show that there was strong negative investor sentiment from major negative events and a strong level of local bias during the period known as the Blitz. ii Acknowledgements I would like to thank my supervisors Professor Robert Hudson and Dr Fabrizio Casalin for their support through my research. Their advice on the direction of the work and helpful comments, together with encouragement, has proved invaluable. A special thanks to Robert for his countless hours of reflecting, reading and most of all patience throughout the entire process. I am also indebted to Peter Lomas for the scholarship that enabled this research to be conducted and also to members of Newcastle University Business School Economics department for their informal and extremely helpful comments and support. My parents deserve sincere thanks for their encouragement and support throughout my studies and also to Lizzi for her support and patience throughout. iii Table of Contents Chapter 1: Introduction .......................................................................................................... 1 1.1. Motivation for Study ................................................................................................... 1 1.2. Objective of Study ....................................................................................................... 3 1.3. Contributions of Study ................................................................................................ 4 1.4. Chapter Outline ........................................................................................................... 4 Chapter 2: Literature Review ................................................................................................. 7 2.1. Introduction ..................................................................................................................... 7 2.2. The Efficient Market Hypothesis .................................................................................... 8 2.2.1. Assumptions of Market Efficiency ......................................................................... 10 2.2.2. Forms of Market Efficiency ................................................................................... 11 2.3. Development of the Martingale and Random Walk...................................................... 12 2.3.1. Martingales ............................................................................................................. 12 2.3.2. Random Walk ......................................................................................................... 13 2.4. Tests for Market Efficiency........................................................................................... 15 2.4.1. Linear Tests ............................................................................................................ 16 2.4.2. Non-Linear.............................................................................................................. 16 2.5. Anomalies...................................................................................................................... 17 2.6. Technical Analysis ........................................................................................................ 19 2.7. Problems with Conventional Tests ................................................................................ 20 2.8. The Adaptive Markets Hypothesis ................................................................................ 23 2.9. Classification of the Behaviour of Stock Returns ......................................................... 26 2.10. Markets Examined in this Study ................................................................................. 28 2.10.1. Dow Jones Industrial Average .............................................................................. 29 2.10.2. Financial Times 30 ............................................................................................... 29 2.10.3. Tokyo Stock Price Index ...................................................................................... 30 2.11. Summary ..................................................................................................................... 31 Chapter 3: An Examination of the Independent Behaviour of Stock Returns ................ 33 3.1. Introduction ................................................................................................................... 33 3.2. Literature Review .......................................................................................................... 34 3.3. Data ............................................................................................................................... 40 3.4. Linear Methodology ...................................................................................................... 44 3.4.1. Autocorrelation ....................................................................................................... 44 3.3.2. Runs Test ................................................................................................................ 45 3.4.2. Variance-Ratio Test ................................................................................................ 46 3.4.4. Unit Roots ............................................................................................................... 49 3.5. Nonlinear Methodology ................................................................................................ 55 3.5.1. McLeod Li Test ...................................................................................................... 56 3.5.2. Engle LM Test ........................................................................................................ 57 3.5.3. BDS Test................................................................................................................. 57 3.6. Empirical Results .......................................................................................................... 61 3.6.1. Linear Empirical Results ........................................................................................ 61 3.6.2. Nonlinear Empirical Results ................................................................................... 74 3.7. Conclusion ..................................................................................................................... 80 Chapter 4 – The Behaviour of Calendar Anomalies .......................................................... 83 4.1. Introduction ................................................................................................................... 83 4.2. Literature Review .......................................................................................................... 84 4.2.1. Monday effect ......................................................................................................... 84 4.2.2. January Effect ......................................................................................................... 86 iv 4.2.3. Turn-of-the-month Effect ....................................................................................... 88 4.3. Methodology ................................................................................................................. 90 4.4. Data ..............................................................................................................................
Load more

Recommended publications
  • A Sentiment Analysis Approach to the Prediction of Market Volatility
    A Sentiment Analysis Approach to the Prediction of Market Volatility JUSTINA DEVEIKYTE, Dept. of Computer Science & Information Systems Birkbeck, University of London HELYETTE GEMAN, Dept. of Economics, Mathematics & Statistics Birkbeck, University of London CARLO PICCARI, Dept. of Economics, Mathematics & Statistics Birkbeck, University of London ALESSANDRO PROVETTI, Dept. of Computer Science & Information Systems Birkbeck, University of London Prediction and quantification of future volatility and returns play an important role in financial modelling, both in portfolio optimization and risk management. Natural language processing today allows to process news and social media comments to detect signals of investors’ confidence. We have explored the relationship between sentiment extracted from financial news and tweets and FTSE100 movements. We investigated the strength of the correlation between sentiment measures on a given day and market volatility and returns observed the next day. The findings suggest that there is evidence of correlation between sentiment and stock market movements: the sentiment captured from news headlines could be used as a signal to predict market returns; the same does not apply for volatility. Also, in a surprising finding, for the sentiment found in Twitter comments we obtained a correlation coefficient of -0.7, and p-value below 0.05, which indicates a strong negative correlation between positive sentiment captured from the tweets on a given day and the volatility observed the next day. We developed an accurate classifier for the prediction of market volatility in response to the arrival of new information by deploying topic modelling, based on Latent Dirichlet Allocation, to extract feature vectors from a collection of tweets and financial news.
    [Show full text]
  • Whole Day Download the Hansard
    Thursday Volume 655 28 February 2019 No. 261 HOUSE OF COMMONS OFFICIAL REPORT PARLIAMENTARY DEBATES (HANSARD) Thursday 28 February 2019 © Parliamentary Copyright House of Commons 2019 This publication may be reproduced under the terms of the Open Parliament licence, which is published at www.parliament.uk/site-information/copyright/. 497 28 FEBRUARY 2019 498 Stephen Barclay: As the shadow spokesman, the right House of Commons hon. and learned Member for Holborn and St Pancras (Keir Starmer), said yesterday,there have been discussions between the respective Front Benches. I agree with him Thursday 28 February 2019 that it is right that we do not go into the details of those discussions on the Floor of the House, but there have The House met at half-past Nine o’clock been discussions and I think that that is welcome. Both the Chair of the Select Committee, the right hon. Member for Leeds Central (Hilary Benn) and other distinguished PRAYERS Members, such as the right hon. Member for Birkenhead (Frank Field), noted in the debate yesterday that there had been progress. It is important that we continue to [MR SPEAKER in the Chair] have those discussions, but that those of us on the Government Benches stand by our manifesto commitments in respect of not being part of a EU customs union. BUSINESS BEFORE QUESTIONS 21. [909508] Luke Pollard (Plymouth, Sutton and NEW WRIT Devonport) (Lab/Co-op): I have heard from people Ordered, from Plymouth living in the rest of the EU who are sick I beg to move that Mr Speaker do issue his Warrant to the to the stomach with worry about what will happen to Clerk of the Crown to make out a New Writ for the electing of a them in the event of a no deal.
    [Show full text]
  • 1 Investor Sentiment and the Market Reaction to Dividend News
    Investor sentiment and the market reaction to dividend news: European evidence Abstract Purpose: This paper examines the effect of investor sentiment on the market reaction to dividend change announcements. Design/methodology/approach: We use the European Economic Sentiment Indicator data, from Directorate General for Economic and Financial Affairs (DG ECFIN), as a proxy for investor sentiment and focus on the market reaction to dividend change announcements, using panel data methodology. Findings: Using data from three European markets, our results indicate that the investor sentiment has some influence on the market reaction to dividend change announcements, for two of the three analysed markets. Globally, we find no evidence of investor sentiment influencing the market reaction to dividend change announcements for the Portuguese market. However, we find evidence that the positive share price reaction to dividend increases enlarges with sentiment, in the case of the UK markets, whereas the negative share price reaction to dividend decreases reduces with sentiment, in the French market. Research limitations/implications: We have no access to dividend forecasts, so, our findings are based on naïve dividend changes and not unexpected change dividends. Originality/value: This paper offers some insights on the effect of investor sentiment on the market reaction to firms’ news, a strand of finance that is scarcely developed and contributes to the analysis of European markets that are in need of research. As the best of our knowledge, this is the first study to analyse the effect of investor sentiment on the market reaction to dividend news, in the context of European markets. Key Words: Investor Sentiment, Dividend News, Market Reaction, Behavioural Finance Classification: Research Paper 1 1.
    [Show full text]
  • Do Sentiment Indicators Improve Dynamic Asset Allocation?
    EDHEC RISK AND ASSET MANAGEMENT RESEARCH CENTRE 393-400 promenade des Anglais 06202 Nice Cedex 3 Tel.: +33 (0)4 93 18 32 53 E-mail: [email protected] Web: www.edhec-risk.com When to Pick the Losers: Do Sentiment Indicators Improve Dynamic Asset Allocation? October 2006 Devraj Basu EDHEC Business School Chi-Hsiou Hun Durham Business School, University of Durham Roel Oomen Warwick Business School, University of Warwick Alexander Stremme Warwick Business School, University of Warwick Abstract Recent finance research that draws on behavioral psychology suggests that investors systematically make errors in forming expectations about asset returns. These errors are likely to cause significant mis-pricing in the short run, and the subsequent reversion of prices to their fundamental level implies that measures of investor sentiment are likely to be correlated with stock returns. A number of empirical studies using both market and survey data as proxies for investor sentiment have found support for this hypothesis. In this paper we investigate whether investor sentiment (as measured by certain components of the University of Michigan survey) can help improve dynamic asset allocation over and above the improvement achieved based on commonly used business cycle indicators. We find that the addition of sentiment variables to business cycle indicators considerably improves the performance of dynamically managed portfolio strategies, both for a standard market-timer as well as for a momentum investor. For example, sentiment-based dynamic trading strategies, even out-of-sample, would not have incurred any significant losses during the October 1987 crash or the collapse of the dot.com bubble in late 2000.
    [Show full text]
  • Sentiment and Speculation in a Market with Heterogeneous Beliefs
    Online seminar via Zoom Thursday, September 17, 2020 11:00 am Sentiment and speculation in a market with heterogeneous beliefs Ian Martin Dimitris Papadimitriou∗ April, 2020 Abstract We present a model featuring risk-averse investors with heterogeneous beliefs. Individuals who are correct in hindsight, whether through luck or judgment, be- come relatively wealthy. As a result, market sentiment is bullish following good news and bearish following bad news. Sentiment drives up volatility, and hence also risk premia. In a continuous-time Brownian limit, moderate investors trade against market sentiment in the hope of capturing a variance risk premium created by the presence of extremists. In a Poisson limit that features sudden arrivals of information, CDS rates spike following bad news and decline during quiet times. ∗Martin: London School of Economics, http://personal.lse.ac.uk/martiniw/. Papadimitriou: University of Bristol, https://sites.google.com/site/papadimitrioudea/. We thank Brandon Han, Nobu Kiyotaki, John Moore, Jeremy Stein, Andrei Shleifer, John Campbell, Eben Lazarus, Pe- ter DeMarzo and seminar participants at LSE, Arizona State University, Harvard University, HKUST, Shanghai Jiao Tong University (SAIF) and the NBER Summer Institute for comments. Ian Martin is grateful for support from the Paul Woolley Centre and from the ERC under Starting Grant 639744. 1 In the short run, the market is a voting machine, but in the long run it is a weighing machine. |Benjamin Graham. In this paper, we study the effect of heterogeneity in beliefs on asset prices. We work with a frictionless dynamically complete market populated by a continuum of risk-averse agents who differ in their beliefs about the probability of good news.
    [Show full text]
  • Does Sentiment Matter for Stock Market Returns? Evidence from a Small European Market
    Does sentiment matter for stock market returns? Evidence from a small European market Carla Fernandes †1 University of Aveiro Paulo Gama ‡ University of Coimbra/ISR-Coimbra * Elisabete Vieira University of Aveiro/GOVCOPP March, 2010 † Address: ISCA-UA, R. Associação Humanitária dos Bombeiros de Aveiro, Apartado 58, 3811-902 Aveiro, Portugal. Phone: +351 234 380 110 . Fax: +351 234 380 111 . E-mail: [email protected] . ‡ Address: Faculdade de Economia, Av. Dias da Silva, 165, 3004-512 Coimbra, Portugal. Phone: +351 239 790 523. Fax: +351 239 403 511. E-mail: [email protected] . * Address: ISCA-UA, R. Associação Humanitária dos Bombeiros de Aveiro, Apartado 58, 3811-902 Aveiro, Portugal. Phone: +351 234 380 110 . Fax: +351 234 380 111 . E-mail: [email protected] . Does sentiment matter for stock market returns? Evidence from a small European market Abstract An important issue in finance is whether noise traders, those who act on information that has no value, influence prices. Recent research indicates that investor sentiment affects the return distribution of a few categories of assets in some stock markets. Other studies also document that US investor sentiment is contagious. This paper investigates whether Consumer Confidence (CC) and the Economic Sentiment Indicator (ESI) – as proxies for investor sentiment – affects Portuguese stock market returns, at aggregate and industry levels, for the period between 1997 to 2009. Moreover the impact of US investor sentiment on Portuguese stock market returns is also addressed. We find several interesting results. First, our results provide evidence that consumer confidence index and ESI are driven by both, rational and irrational factors.
    [Show full text]
  • Filming the End of the Holocaust War, Culture and Society
    Filming the End of the Holocaust War, Culture and Society Series Editor: Stephen McVeigh, Associate Professor, Swansea University, UK Editorial Board: Paul Preston LSE, UK Joanna Bourke Birkbeck, University of London, UK Debra Kelly University of Westminster, UK Patricia Rae Queen’s University, Ontario, Canada James J. Weingartner Southern Illimois University, USA (Emeritus) Kurt Piehler Florida State University, USA Ian Scott University of Manchester, UK War, Culture and Society is a multi- and interdisciplinary series which encourages the parallel and complementary military, historical and sociocultural investigation of 20th- and 21st-century war and conflict. Published: The British Imperial Army in the Middle East, James Kitchen (2014) The Testimonies of Indian Soldiers and the Two World Wars, Gajendra Singh (2014) South Africa’s “Border War,” Gary Baines (2014) Forthcoming: Cultural Responses to Occupation in Japan, Adam Broinowski (2015) 9/11 and the American Western, Stephen McVeigh (2015) Jewish Volunteers, the International Brigades and the Spanish Civil War, Gerben Zaagsma (2015) Military Law, the State, and Citizenship in the Modern Age, Gerard Oram (2015) The Japanese Comfort Women and Sexual Slavery During the China and Pacific Wars, Caroline Norma (2015) The Lost Cause of the Confederacy and American Civil War Memory, David J. Anderson (2015) Filming the End of the Holocaust Allied Documentaries, Nuremberg and the Liberation of the Concentration Camps John J. Michalczyk Bloomsbury Academic An Imprint of Bloomsbury Publishing Plc LONDON • OXFORD • NEW YORK • NEW DELHI • SYDNEY Bloomsbury Academic An imprint of Bloomsbury Publishing Plc 50 Bedford Square 1385 Broadway London New York WC1B 3DP NY 10018 UK USA www.bloomsbury.com BLOOMSBURY and the Diana logo are trademarks of Bloomsbury Publishing Plc First published 2014 Paperback edition fi rst published 2016 © John J.
    [Show full text]
  • Bombed, 128, 142, 160; Surrenders, 153 Aarhus: and an Air Attack, 209
    Index compiled by the author Aachen: bombed, 128, 142, 160; surrenders, 153 Armed Forces of the Committee for the Liberation of the Aarhus: and an air attack, 209 Peoples of Russia (VS-KONR): 176 Abbeville: 160 Armenians: 230 Abdul Kalam, A P.J.: quoted, 226 Arnhem: 163, 207, 210, 214 Abyssinia (Ethiopia): 16, 116, 206, 213, 222; war dead, Arromanches: 150, 151, 222 257 Ascension Island: 121 Acasta (destroyer): 131 Aschaffenburg: bombed, 167 ‘Ace of the Deep’: 91 ‘Asia Women’s Fund’: to make reparations, 200 Adam, Ken: 210 Assam: 192, 218, 244 Adenauer, Konrad: 240 Athens: 33, 34, 98, 107, 109; Churchill in, 220; liberated, Admiral Graf Spee: 5 162 Admiral Hipper: 83 Atlantic Charter: 220, 221 Admiral Scheer: 28, 83 Atlantic Ferry Organisation (ATFERO): 29 Adriatica (Displaced Persons’ (DP) camp): 238 Atlantic Ocean: 51, 52, 70, 74, 119, 120 Afric Star (merchant ship): sunk, 30 atom bomb: 134, 198, 222; dropped, 201, 202 African-American soldiers: in action, 168, 211 atrocities against civilians: 35, 40, 57, 59, 61, 79, 98, 100, Agent Zigzag: 117 101, 102, 103, 105, 106, 112, 156, 173, 192, 229, Akashi: bombed, 193 233 Alamein: 80, 109, 213, 226 Attlee, Clement: and Dresden, 175 Alaska-Canada (Alcan) Highway: 82 Attu Island: 82 Albania: 16, 33, 162, 209, 229, 230; war dead, 256 Aung San, General: leads resistance, 192 Albanian volunteers with the SS: 73 Auschwitz: 88, 90, 91, 101, 103, 109; deportations to, Alderney Island: 224 107, 158; revolt in, 108, 218; escapees from, and a Aleutian Islands: 56, 63, 82 bombing request, 158; evacuated,
    [Show full text]
  • Volunteer Translator Pack
    TRANSLATION EDITORIAL PRINCIPLES 1. Principles for text, images and audio (a) General principles • Retain the intention, style and distinctive features of the source. • Retain source language names of people, places and organisations; add translations of the latter. • Maintain the characteristics of the source even if these seem difficult or unusual. • Where in doubt make footnotes indicating changes, decisions and queries. • Avoid modern or slang phrases that might be seem anachronistic, with preference for less time-bound figures of speech. • Try to identify and inform The Wiener Library about anything contentious that might be libellous or defamatory. • The Wiener Library is the final arbiter in any disputes of style, translation, usage or presentation. • If the item is a handwritten document, please provide a transcription of the source language as well as a translation into the target language. (a) Text • Use English according to the agreed house style: which is appropriate to its subject matter and as free as possible of redundant or superfluous words, misleading analogies or metaphor and repetitious vocabulary. • Wherever possible use preferred terminology from the Library’s Keyword thesaurus. The Subject and Geographical Keyword thesaurus can be found in this pack. The Institutional thesaurus and Personal Name thesaurus can be provided on request. • Restrict small changes or substitutions to those that help to render the source faithfully in the target language. • Attempt to translate idiomatic expressions so as to retain the colour and intention of the source culture. If this is impossible retain the expression and add translations in a footnote. • Wherever possible do not alter the text structure or sequence.
    [Show full text]
  • Gifts for Book Lovers HAPPY NEW YEAR to ALL OUR LOVELY
    By Appointment To H.R.H. The Duke Of Edinburgh Booksellers Est. 1978 www.bibliophilebooks.com ISSN 1478-064X CATALOGUE NO. 338 JAN 2016 78920 ART GLASS OF LOUIS COMFORT TIFFANY Inside this issue... ○○○○○○○○○○ by Paul Doros ○○○○○○○○○○ WAR AND MILITARIA The Favrile ‘Aquamarine’ vase of • Cosy & Warm Knits page 10 1914 and the ‘Dragonfly’ table lamp are some of the tallest and most War is not an adventure. It is a disease. It is astonishingly beautiful examples of • Pet Owner’s Manuals page 15 like typhus. ‘Aquamarine’ glass ever produced. - Antoine de Saint-Exupery The sinuous seaweed, the • numerous trapped air bubbles, the Fascinating Lives page 16 varying depths and poses of the fish heighten the underwater effect. See pages 154 to 55 of this • Science & Invention page 13 78981 AIR ARSENAL NORTH glamorous heavyweight tome, which makes full use of AMERICA: Aircraft for the black backgrounds to highlight the luminescent effects of 79025 THE HOLY BIBLE WITH Allies 1938-1945 this exceptional glassware. It is a definitive account of ILLUSTRATIONS FROM THE VATICAN Gifts For Book by Phil Butler with Dan Louis Comfort Tiffany’s highly collectable art glass, Hagedorn which he considered his signature artistic achievement, LIBRARY $599.99 NOW £150 Lovers Britain ran short of munitions in produced between the 1890s and 1920s. Called Favrile See more spectacular images on back page World War II and lacked the dollar glass, every piece was blown and decorated by hand. see page 11 funds to buy American and The book presents the full range of styles and shapes Canadian aircraft outright, so from the exquisite delicacy of the Flowerforms to the President Roosevelt came up with dramatically dripping golden flow of the Lava vases, the idea of Lend-Lease to assist the from the dazzling iridescence of the Cypriote vases to JANUARY CLEARANCE SALE - First Come, First Served Pg 18 Allies.
    [Show full text]
  • BIOLOGY 639 SCIENCE ONLINE the Unexpected Brains Behind Blood Vessel Growth 641 THIS WEEK in SCIENCE 668 U.K
    4 February 2005 Vol. 307 No. 5710 Pages 629–796 $10 07%.'+%#%+& 2416'+0(70%6+10 37#06+6#6+8' 51(69#4' #/2.+(+%#6+10 %'..$+1.1); %.10+0) /+%41#44#;5 #0#.;5+5 #0#.;5+5 2%4 51.76+105 Finish first with a superior species. 50% faster real-time results with FullVelocity™ QPCR Kits! Our FullVelocity™ master mixes use a novel enzyme species to deliver Superior Performance vs. Taq -Based Reagents FullVelocity™ Taq -Based real-time results faster than conventional reagents. With a simple change Reagent Kits Reagent Kits Enzyme species High-speed Thermus to the thermal profile on your existing real-time PCR system, the archaeal Fast time to results FullVelocity technology provides you high-speed amplification without Enzyme thermostability dUTP incorporation requiring any special equipment or re-optimization. SYBR® Green tolerance Price per reaction $$$ • Fast, economical • Efficient, specific and • Probe and SYBR® results sensitive Green chemistries Need More Information? Give Us A Call: Ask Us About These Great Products: Stratagene USA and Canada Stratagene Europe FullVelocity™ QPCR Master Mix* 600561 Order: (800) 424-5444 x3 Order: 00800-7000-7000 FullVelocity™ QRT-PCR Master Mix* 600562 Technical Services: (800) 894-1304 Technical Services: 00800-7400-7400 FullVelocity™ SYBR® Green QPCR Master Mix 600581 FullVelocity™ SYBR® Green QRT-PCR Master Mix 600582 Stratagene Japan K.K. *U.S. Patent Nos. 6,528,254, 6,548,250, and patents pending. Order: 03-5159-2060 Purchase of these products is accompanied by a license to use them in the Polymerase Chain Reaction (PCR) Technical Services: 03-5159-2070 process in conjunction with a thermal cycler whose use in the automated performance of the PCR process is YYYUVTCVCIGPGEQO covered by the up-front license fee, either by payment to Applied Biosystems or as purchased, i.e., an authorized thermal cycler.
    [Show full text]
  • SB-4309-March-NA.Pdf
    Scottishthethethethe www.scottishbanner.com Banner 37 Years StrongScottishScottishScottish - 1976-2013 Banner A’BannerBanner Bhratach Albannach 44 Volume 36 Number 11 The world’s largest international Scottish newspaper May 2013 Years Strong - 1976-2020 www.scottishbanner.com A’ Bhratach Albannach Volume 36 Number 11 The world’s largest international Scottish newspaper May 2013 VolumeVolumeVolume 43 36 36 NumberNumber Number 911 11The The The world’s world’s world’s largest largest largest international international international Scottish Scottish newspaper newspaper newspaper May MarchMay 2013 2013 2020 The Broar Brothers The Rowing Scotsmen » Pg 16 Celebrating USMontrose Barcodes Scotland’s first railway through The 1722 Waggonway 7 25286 844598 0 1 » Pg 8 the ages » Pg 14 Highland, 7 25286 844598 0 9 Scotland’s Bard through Lowlands, the ages .................................................. » Pg 3 Final stitches sewn into Arbroath Tapestry ............................ » Pg 9 Our Lands A Heritage of Army Pipers .......... » Pg 32 7 25286 844598 0 3 » Pg 27 7 25286 844598 1 1 7 25286 844598 1 2 THE SCOTTISH BANNER Volume 43 - Number 9 Scottishthe Banner The Banner Says… Volume 36 Number 11 The world’s largest international Scottish newspaper May 2013 Publisher Offices of publication Valerie Cairney Australasian Office: PO Box 6202 Editor Bagpipes-the world’s instrument Marrickville South, Sean Cairney NSW, 2204 pipes attached where the legs and In this issue Tel:(02) 9559-6348 EDITORIAL STAFF neck would be. Today you will find The sound of Scotland made its way Jim Stoddart [email protected] both synthetic and leather varieties recently across the Atlantic Ocean The National Piping Centre available, with fans of each.
    [Show full text]