The Future of Computer Trading in Financial Markets an International Perspective
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Trading Frictions and Market Structure: an Empirical Analysis
Trading Frictions and Market Structure: An Empirical Analysis Charlie X. Cai, David Hillier, Robert Hudson, and Kevin Keasey1 February 3, 2005 JEL Classi…cation: G12; G14; D23; L22. Keywords: SETS; SEAQ; Trading Friction; Market Structure. 1 The Authors are from the University of Leeds. Address for correspondence: Charlie X. Cai, Leeds University Business School, Maurice Keyworth Building, The University of Leeds, Leeds LS2 9JT, UK., e-mail: [email protected]. All errors are our own. Trading Frictions and Market Structure: An Empirical Analysis Abstract Market structure a¤ects the informational and real frictions faced by traders in equity markets. We present evidence which suggests that while real fric- tions associated with the costs of supplying immediacy are less in order driven systems, informational frictions resulting from increased adverse selection risk are considerably higher in these markets. Firm value, transaction size and order location are all major determinants of the trading costs faced by investors. Consistent with the stealth trading hypothesis of Barclay and Warner (1993), we report that informational frictions are at their highest for small trades which go through the order book. Finally, while there is no doubt that the total costs of trading on order-driven systems are lower for very liquid securities, the inherent informational ine¢ ciencies of the format should be not be ignored. This is particularly true for the vast majority of small to mid-size stocks that experience infrequent trading and low transac- tion volume. JEL Classi…cation: G12; G14; D23; L22. Keywords: SETS; SEAQ; Trading Friction; Market Structure. 1 Introduction Trading frictions in …nancial markets are an important determinant of the liquidity of securities and the intertemporal e¢ ciency of prices. -
Reverse Stock Split Faq
REVERSE STOCK SPLIT FAQ 1 What is a reverse stock split? A reverse stock split involves replacing, by exchange, a certain number of old shares (in the present case, 20) for one new share, without altering the amount of the company's capital. In practice such an operation creates the following mechanical effects: - the number of new shares in circulation on the market is reduced proportionally to the exchange ratio (several old shares are transformed into one new share); - the par value, and as a consequence, the market price, of each new share are raised proportionally to the exchange ratio. What is the goal of this reverse stock split? The reverse stock split forms part of Soitec’s desire to support its renewed profitable growth momentum, having refocused on its core electronics business. Moreover, the reverse stock split may reduce the volatility of the price of Soitec share caused by its current low price level. What is the proposed exchange ratio for this reverse stock split? The exchange ratio is 1 for 20. In other words, one new share with par value of €2.00 will be exchanged for 20 old shares with par value of €0.10. Why was this 1:20 ratio chosen? This exchange ratio has been chosen for the purpose of positioning the new shares in the average of the values of the shares listed on Euronext. When will the reverse stock split be effective? In accordance with the notice published in the Bulletin des Annonces Légales Obligatoires on 23 December 2016, the reverse stock split will take effect on 8 February 2017, i.e. -
Did Spillovers from Europe Indeed Contribute to the 2010 U.S. Flash Crash?
No. 622 / January 2019 Did Spillovers From Europe Indeed Contribute to the 2010 U.S. Flash Crash? David-Jan Jansen Did Spillovers From Europe Indeed Contribute to the 2010 U.S. Flash Crash? David-Jan Jansen * * Views expressed are those of the authors and do not necessarily reflect official positions of De Nederlandsche Bank. De Nederlandsche Bank NV Working Paper No. 622 P.O. Box 98 1000 AB AMSTERDAM January 2019 The Netherlands Did Spillovers From Europe Indeed Contribute to the 2010 U.S. Flash Crash?* David-Jan Jansen a a De Nederlandsche Bank, Amsterdam, The Netherlands This version: January 2019 Abstract Using intraday data, we study spillovers from European stock markets to the U.S. in the hours before the flash crash on 6 May 2010. Many commentators have pointed to negative market sentiment and high volatility during the European trading session before the Flash Crash. However, based on a range of vector autoregressive models, we find no robust evidence that spillovers increased at that time. On the contrary, spillovers on 6 May were mostly smaller than in the preceding days, during which there was great uncertainty surrounding the Greek sovereign debt crisis. The absence of evidence for spillovers underscores the difficulties in understanding the nature of flash events in financial markets. Keywords: flash crash, spillovers, financial stability, connectedness. JEL classifications: G15, N22, N24. * This paper benefitted from discussions with Sweder van Wijnbergen as well as from research assistance by Jack Bekooij. Any errors and omissions remain my responsibility. Views expressed in the paper do not necessarily coincide with those of de Nederlandsche Bank or the Eurosystem. -
Cracks in the Pipeline 2
MEDIA CONTACT: Lauren Strayer | [email protected] 212-389-1413 FINANCIAL PIPELINE .o rg Series CRACKS IN THE PIPELINE 2 HIGH FREQUENCY TRADING by: Wallace C. Turbeville his is the second of a series of articles, that increase the inefficiency of Capital Intermediation and entitled “The Financial Pipeline Series”, its cost. The increased volumes in the traded markets are examining the underlying validity of the largely a result of high-speed, computer driven trading assertion that regulation of the financial by large banks and smaller specialized firms. This article markets reduces their efficiency. These illustrates how this type of trading (along with other activ- articles assert that the value of the finan- ities discussed in subsequent articles) extracts value from cial markets is often mis-measured. The the Capital Intermediation process rendering it less efficient. efficiency of the market in intermediat- It also describes how the value extracted is a driver of even ing flows between capital investors and more increased volume creating a dangerous and powerful capital users (like manufacturing and service businesses, feedback loop. individuals and governments) is the proper measure. Unreg- Tying increased trading volume to inefficiencies runs ulated markets are found to be chronically inefficient using counter to a fundamental tenet of industry opponents to Tthis standard. This costs the economy enormous amounts financial reform. They assert that burdens on trading will each year. In addition, the inefficiencies create stresses to the reduce volumes and thereby impair the efficient functioning system that make systemic crises inevitable. Only prudent of the markets. regulation that moderates trading behavior can reduce these The industry’s position that increased volume reduces inefficiencies. -
Ai: Understanding and Harnessing the Potential Wireless & Digital Services Ai: Understanding and Harnessing the Potential White Paper
AI: UNDERSTANDING AND HARNESSING THE POTENTIAL WIRELESS & DIGITAL SERVICES AI: UNDERSTANDING AND HARNESSING THE POTENTIAL WHITE PAPER CONTENTS INTRODUCTION ..............................................................................................................................................................................02 1. THE PRODUCTIVITY CONUNDRUM: WILL AI HELP US BREAK INTO A NEW CYCLE? ...........................................................05 1.1 Global productivity growth is faltering ...................................................................................................... 05 1.2 AI has the potential to drive productivity improvements and hence economic growth .................................... 06 2. AI FUTURES ........................................................................................................................................................................11 2.1 Replacing the smartphone with a ubiquitous voice assistant ....................................................................... 11 2.2 Your AI powered personal digital assistant ............................................................................................... 12 2.3 Is AI the missing piece for a truly smart city? ........................................................................................... 14 2.4 City of the future ................................................................................................................................... 16 2.5 Giving medics more time to care ............................................................................................................ -
Evidence from the Toronto Stock Exchange
The impact of trading floor closure on market efficiency: Evidence from the Toronto Stock Exchange Dennis Y. CHUNG Simon Fraser University and Karel HRAZDIL* Simon Fraser University This draft: July 1, 2013 For the 2013 Auckland Finance Meeting Abstract: We are the first to evaluate the impact of the trading floor closure on the corresponding efficiency of the stock price formation process on the Toronto Stock Exchange (TSX). Utilizing short-horizon return predictability as an inverse indicator of market efficiency, we demonstrate that while the switch to all electronic trading resulted in higher volume and lower trading costs, the information asymmetry among investors increased as more informed and uninformed traders entered the market. The TSX trading floor closure resulted in a significant decrease in informational efficiency, and it took about six years for efficiency to return to its pre-all-electronic-trading level. In multivariate setting, we provide evidence that changes in information asymmetry and increased losses to liquidity demanders due to adverse selection account for the largest variations in the deterioration of the aggregate level of informational efficiency. Our results suggest that electronic trading should complement, rather than replace, the exchange trading floor. JEL Codes: G10; G14 Keywords: Electronic trading; Trading floor; Market efficiency; Toronto Stock Exchange. * Corresponding author. Address of correspondence: Beedie School of Business, 8888 University Drive, Simon Fraser University, Burnaby, B.C., V5A 1S6, Canada; Phone: +1 778 782 6790; Fax: +1 778 782 4920; E-mail addresses: [email protected] (D.Y. Chung), [email protected] (K. Hrazdil). We acknowledge financial support from the CA Education Foundation of the Institute of Chartered Accountants of British Columbia and the Social Sciences and Humanities Research Council of Canada. -
Pre-Arranged Trading in the Securities Market 17 3.3
Page 1 of 1 23 May 2018 Circular No. DC/AM - 29 of 2018 SGX LAUNCHES SERIES 2 OF TRADE SURVEILLANCE HANDBOOK The inaugural Trade Surveillance Handbook was published in September 2016 as part of SGX’s collaborative efforts with Members to combat potential irregular trading activities, and enhance surveillance tools of Members. To build on these efforts, SGX has developed a second series of the Trade Surveillance Handbook (“Handbook 2”) with the aim to promulgate fair trading practices and uphold market integrity in our marketplace. Trade Surveillance Handbook – Series Two Handbook 2, featuring Wash trades, Order Management during Opening Routine and Momentum Ignition, seeks to provide Members with a better understanding of SGX’s expectations in relation to these trading practices in our derivatives markets. The Handbook also includes a set of surveillance guidelines and markers which Members may incorporate in detecting and examining these trading malpractices. This Handbook further provides as illustration, two cases heard before the independent Disciplinary Committee so that Members can appreciate the assessments and considerations of SGX and the Disciplinary Committee. The third case study sets out guidelines for Members and Trading Representative to consider in accepting and executing customers’ orders in the securities market. The Trade Surveillance Handbook 2 is attached in the Appendix. SGX to Continue Collaboration with Members and Stakeholders SGX will continue to work closely with Members and stakeholders to uphold robust compliance and surveillance standards, and encourage early disruption of potential irregular trading activities. All these are crucial to promoting greater investor confidence in our marketplace. Your feedback and questions on the Handbook are most welcome. -
Algorithmic Approach to Options Trading
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 08 Issue: 05 | May 2021 www.irjet.net p-ISSN: 2395-0072 Algorithmic Approach to Options Trading Shubham Horambe1, Ketan Khanolkar1, Dhairya Dixit1, Huzaifa Shaikh1, Prof. Manasi U. Kulkarni2 1B. Tech Student, Dept of Computer Engineering and IT, VJTI College, Mumbai, Maharashtra, India 2 Assistant Professor, Dept of Computer Engineering and IT, VJTI College, Mumbai, Maharashtra, India ----------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - Majority of the traders lose money whilst trading sitting in front of the screen for hours. Due to this continuous in options owing to market speculation, emotional trading and monitoring requirement, the performance of Manual Trading lack of risk management. The purpose of this research paper is is limited to the amount of time of the day the trader can to introduce an automated way of trading in options in order dedicate to trading. Other than this, Manual Trading also to tackle these problems. To achieve this, we have adopted suffers from time delays, which is the ability to execute some basic option strategies namely Covered Call, Protective trades in a small-time window. Also, for predicting Put and Covered Strangle. These strategies have been tested unprecedented non-random changes that take place in trade over a period of 5 years (2015-2019) for a set of stocks in the prices, a trader must delve into and analyze more and more U.S options market. information which is more powerful than information available on open-sources like news platforms. This is very Key Words: Options, Algorithmic Trading, Call Option, Put difficult to do for humans, as unlike computers, we can Option. -
Appendix F. List of Questionnaires and Record Books, with Selected Facsimiles
Appendix F. List of Questionnaires and Record Books, With Selected Facsimiles Page Page General Forms Census of Construction Industries NC-9901 Report of Organization ---------------------- 2 CC-1509 Building Construction—General NC-9926 Classification Report ------------------------ 5 Contractors and Operative Builders ----------------102 NC-9923 General Schedule --------------------------- 6 CC-1609 Heavy Construction Other Than Building Census of Retail Trade Construction—Contractors --------------------------106 CB-5202 Paint, Glass, Wallpaper --------------------- 8 CC-1729 Painting and Paper Hanging Special Trade Contractors ----------------------------------- 110 CB-5302 General Merchandise------------------------ 11 Census of Manufactures CB-5400 Food ------------------------------------------ 15 MA-1000(L) 1992 Annual Survey of Manufactures--- 114 CB-5504 Gasoline Service Stations------------------- 19 MC-2002 Meat Processing Plants--------------------- 118 Census of Wholesale Trade MC-2004 Dairy Products-------------------------------127 CB-5001 Short Form ----------------------------------- 23 Census of Mineral Industries CB-5012 Motor Vehicles ------------------------------- 25 MC-1001 Iron, Ferroalloy, Uranium, and CB-5013 Motor Vehicles Parts and Supplies --------- 29 Miscellaneous Metal Ores --------------------------138 CB-5099 Miscellaneous Durable Goods -------------- 33 MC-1301 Oil and Gas Field Operations --------------146 Census of Service Industries MC-1401 Stone, Sand, and Gravel -------------------153 CB-7001 Hotels -
Theoretical and Practical Aspects of Algorithmic Trading Dissertation Dipl
Theoretical and Practical Aspects of Algorithmic Trading Zur Erlangung des akademischen Grades eines Doktors der Wirtschaftswissenschaften (Dr. rer. pol.) von der Fakult¨at fuer Wirtschaftwissenschaften des Karlsruher Instituts fuer Technologie genehmigte Dissertation von Dipl.-Phys. Jan Frankle¨ Tag der m¨undlichen Pr¨ufung: ..........................07.12.2010 Referent: .......................................Prof. Dr. S.T. Rachev Korreferent: ......................................Prof. Dr. M. Feindt Erkl¨arung Ich versichere wahrheitsgem¨aß, die Dissertation bis auf die in der Abhandlung angegebene Hilfe selbst¨andig angefertigt, alle benutzten Hilfsmittel vollst¨andig und genau angegeben und genau kenntlich gemacht zu haben, was aus Arbeiten anderer und aus eigenen Ver¨offentlichungen unver¨andert oder mit Ab¨anderungen entnommen wurde. 2 Contents 1 Introduction 7 1.1 Objective ................................. 7 1.2 Approach ................................. 8 1.3 Outline................................... 9 I Theoretical Background 11 2 Mathematical Methods 12 2.1 MaximumLikelihood ........................... 12 2.1.1 PrincipleoftheMLMethod . 12 2.1.2 ErrorEstimation ......................... 13 2.2 Singular-ValueDecomposition . 14 2.2.1 Theorem.............................. 14 2.2.2 Low-rankApproximation. 15 II Algorthmic Trading 17 3 Algorithmic Trading 18 3 3.1 ChancesandChallenges . 18 3.2 ComponentsofanAutomatedTradingSystem . 19 4 Market Microstructure 22 4.1 NatureoftheMarket........................... 23 4.2 Continuous Trading -
Perspectives on the Equity Risk Premium – Siegel
CFA Institute Perspectives on the Equity Risk Premium Author(s): Jeremy J. Siegel Source: Financial Analysts Journal, Vol. 61, No. 6 (Nov. - Dec., 2005), pp. 61-73 Published by: CFA Institute Stable URL: http://www.jstor.org/stable/4480715 Accessed: 04/03/2010 18:01 Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/page/info/about/policies/terms.jsp. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use. Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained at http://www.jstor.org/action/showPublisher?publisherCode=cfa. Each copy of any part of a JSTOR transmission must contain the same copyright notice that appears on the screen or printed page of such transmission. JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected]. CFA Institute is collaborating with JSTOR to digitize, preserve and extend access to Financial Analysts Journal. http://www.jstor.org FINANCIAL ANALYSTS JOURNAL v R ge Perspectives on the Equity Risk Premium JeremyJ. -
Tony Ramirez, Et Al. V. Marathon Patent Group Inc, Et Al. 18-CV
Case 2:18-cv-06309-FMO-PLA Document 1 Filed 07/20/18 Page 1 of 11 Page ID #:1 Adam C. McCall (SBN 302130) 1 [email protected] 2 LEVI & KORSINSKY, LLP 445 South Figueroa Street, 31st Floor 3 Los Angeles, California 90025 4 Telephone: (213) 985-7290 5 Facsimile: (202) 333-2121 6 Attorneys for Plaintiff 7 [Additional counsel on signature page] 8 9 UNITED STATES DISTRICT COURT 10 11 CENTRAL DISTRICT OF CALIFORNIA 12 TONY RAMIREZ, ) Case No. 18-cv-06309 13 ) Plaintiff, ) CLASS ACTION COMPLAINT FOR 14 vs. ) VIOLATIONS OF FEDERAL 15 ) SECURITIES LAWS MARATHON PATENT GROUP INC., ) 16 DOUG CROXALL, EDWARD KOVALIK, ) JURY TRIAL DEMANDED 17 CHRISTOPHER ROBICHAUD, ) RICHARD TYLER, AND RICHARD ) 18 CHERNICOFF, ) 19 ) Defendants. ) 20 ) 21 22 23 24 25 26 27 28 30 31 32 Case 2:18-cv-06309-FMO-PLA Document 1 Filed 07/20/18 Page 2 of 11 Page ID #:2 1 Plaintiff Tony Ramirez (“Plaintiff”), by his undersigned attorneys, alleges the following 2 on information and belief, except as to those allegations pertaining to its own knowledge and 3 conduct, which is made on personal knowledge: 4 INTRODUCTION 5 1. Plaintiff asserts this action for violating federal securities laws to remedy false 6 and misleading disclosures made by Marathon Patent Group Inc. (“Marathon” or the 7 “Company”) and its Board of Directors (the “Board) in a proxy statement issued in connection 8 with the Company’s 2017 annual meeting of stockholders (the “Annual Meeting”). 9 2. On June 8, 2017, the Company filed a Schedule 14A Proxy Statement (the 10 “Proxy”) with the Securities and Exchange Commission (the “SEC”) for the Annual Meeting.