Are institutions informed about news? T. Hendershott, D. Livdan, N. Schürhoff Discussed by: Sergey Gelman, ICEF, Higher School of Economics, Moscow The.

Slides:

Advertisements

Similar presentations

Chapter 3 Market Efficiency

Advertisements

The Efficient Market Hypothesis

Sandy Lai SMU 1 The Role of Equity Funds in the Financial Crisis Propagation Harald Hau University of Geneva and SFI

Do Individual Day Traders Make Money? Evidence from Taiwan Brad Barber Yi-Tsung Lee Yu-Jane Liu Terrance Odean

Sandy Lai SMU 1 The Role of Equity Funds in the Financial Crisis Propagation Harald Hau University of Geneva and SFI

An Analysis of Stock Returns and Aggregate Earnings Yunhao Chen Xiaoquan Jiang Bong Soo Le School of Accounting Dept of Finance Dept of Finance Florida.

Security Analysts and Conflicts of Interest Jay R. Ritter Cordell Professor of Finance University of Florida.

Konan Chan Fengfei Li National Chengchi University University of Hong Kong Tse-Chun Lin Ji-Chai Lin University of Hong Kong Louisiana State University.

Futures trading and market microstructure of the underlying security: A high frequency experiment at the single stock futures level Kate Phylaktis and.

Sentiment during recessions a discussion by Patrick J. Kelly New Economic School At the The First International Moscow Finance Conference.

1 Efficient Market Theory Dr. Rana Singh Associate Professor

Information-based Trading, Price Impact of Trades, and Trade Autocorrelation Kee H. Chung Mingsheng Li Thomas H. McInish.

FAQs re test/exam With regard to Topic 1, the following sections of Bodie et al. will not be examined: 7 th edition: Chapter 7 Appendix A and B (pp )

McGraw-Hill/Irwin Copyright © 2008 The McGraw-Hill Companies, Inc., All Rights Reserved. The Efficient Market Hypothesis CHAPTER 8.

Market Efficiency Chapter 12. Do security prices reflect information ? Why look at market efficiency - Implications for business and corporate finance.

Transaction costs, liquidity and expected returns at the Berlin Stock Exchange, Carsten Burhop, Universität zu Köln Sergey Gelman, ICEF, Higher.

Discussion of The Examination of R&D Impact on Firm Value By Chuan Yang Hwang Nanyang Technological University.

Twitter Volume Spikes: Analysis and Application in Stock Trading Yuexin Mao, Wei Wei and Bing Wang COMP4332/RMBI4310 CHAN Chun Ting ( )

Chapter 17 TECHNICAL ANALYSIS The Visual Clue.

1 Is Transparency Good For You? by Rachel Glennerster, Yongseok Shin Discussed by: Campbell R. Harvey Duke University National Bureau of Economic Research.

Academic research on ETFs Susan Christoffersen University of Toronto Panel Discussion September 22, 2014 Susan Christoffersen University of Toronto Panel.

1 Dealer Price Discrimination in New Car Purchases: Evidence from the Consumer Expenditure Survey Pinelopi Goldberg (JPE, 1996) Presented by Jake Gramlich.

CHAPTER NINE MARKET EFFICIENCY © 2001 South-Western College Publishing.

Efficient Market Hypothesis by Indrani Pramanick (44)

Efficient Capital Markets Objectives: What is meant by the concept that capital markets are efficient? Why should capital markets be efficient? What are.

Does Cross-Listing Mitigate Insider Trading? Adriana Korczak and Meziane Lasfer Cass Business School, London.

Mad Money and Smart Money: The Discrepancy of Rationality between Options and Equity Markets Presented By Carl R. Chen – University of Dayton.

Is Information Risk Priced? Evidence from the Price Discovery of Large Trades Chuan Yang Hwang Nanyang Technological University and Xiaolin Qian Nanyang.

Role of a Financial Economist in Global Enforcement Actions and Regulatory Investigations The Globalization of Enforcement Actions and Internal Investigations.

1 International Finance Chapter 15 Money, Interest Rates, and Exchange Rates.

Chinese Bond Market Challenges Sergey N. Smirnov State University Higher School of Economics Moscow.

A.G. Malliaris Loyola University Chicago Multinational Finance Society Meetings Rome, Italy, June 26-29, 2011 Contrarian and Momentum Strategies: The Impact.

©R. Schwartz Equity Markets: Trading and Structure Slide 1 Bob Schwartz Zicklin School of Business Baruch College, CUNY.

Financial Markets Investing: Chapter 11.

European bond ETFs – tracking error and the sovereign debt crisis M. Drenovak, B. Urosevic and R. Jelic Discussed by: Sergey Gelman, ICEF, Higher School.

EMH- 0 Efficient Market Hypothesis Eugene Fama, 1964 A market where there are huge number of rational, profit-maximizers actively competing, with each.

Chapter 8 The Efficient Market Hypothesis. McGraw-Hill/Irwin © 2004 The McGraw-Hill Companies, Inc., All Rights Reserved. Efficient Market Hypothesis.

McGraw-Hill/Irwin © 2007 The McGraw-Hill Companies, Inc., All Rights Reserved. Efficient Markets & The Behavioral Critique CHAPTE R 8.

The Market Hypothesis The Efficient Market Hypothesis.

McGraw-Hill/Irwin Copyright © 2005 by The McGraw-Hill Companies, Inc. All rights reserved. Chapter 12 Market Efficiency and Behavioral Finance.

Class Business Upcoming Homework Upcoming Midterm – Review Session Wed (5/18) 5 – 6 pm 270 TNRB.

CHAPTER NINE MARKET EFFICIENCY Practical Investment Management Robert A. Strong.

Fundamentals-Based versus Market-Based Cross-Sectional Models of CDS Spreads by S. Das, P. Hanouna and A. Sarin Discussed by J. Helwege FDIC September.

1 1 Ch11&12 – MBA 566 Efficient Market Hypothesis vs. Behavioral Finance Market Efficiency Random walk versus market efficiency Versions of market efficiency.

Liquidity and Market Efficiency Tarun Chordia (Emory) Richard Roll (UCLA) A. Subrahmanyam (UCLA)

1 13. Empirical market microstructure Empirical analysis of market microstructure focuses on order flows, bid/ask spread, and structure of the limit-order.

1 Transparency, Information Content and Order Placement Strategy Tai Ma, Yaling Lin, Hsiu-Kuei Cheng Department of Finance, National Sun Yat-sen University.

McGraw-Hill/Irwin © 2007 The McGraw-Hill Companies, Inc., All Rights Reserved. Efficient Markets & The Behavioral Critique CHAPTER 8.

Norges Bank Financial Stability 1 Institutional Investors, Intangible Information and the Book-to-Market Effect Discussion Sigbjørn Atle Berg Venastul,

1 Comments on “When Does Idiosyncratic Risk Really Matter” Yuanchen Chang National Chengchi University.

Profitability and Characteristics of Risk Arbitrage : Evidences from Leveraged Buyouts in the U.S. Professors: Sue-Fung Wang Keh-Luh Wan Student: Chiu-Nan.

The Effects of Experience on Investor Behavior: Evidence from India's IPO Lotteries Santosh Anagol, Vimal Balasubramaniam, Tarun Ramadorai Discussion by:

Do Demand Curves For Stocks Slope Down?: Evidence From a Regulation Induced Supply Shock Discussant: Pawan Jain.

LOGO 2010 National Taiwan University International Conference on Finance The Impact of Liquidity on Option Prices by San-Lin Chung and Yaw-Huei Wang (National.

Essentials of Investments © 2001 The McGraw-Hill Companies, Inc. All rights reserved. Fourth Edition Irwin / McGraw-Hill Bodie Kane Marcus 1 Chapter 9.

© 2013 Pearson Education, Inc., publishing as Prentice Hall. All rights reserved.2-1 The Uses of Derivatives Uses –Risk management. Derivatives are a tool.

A). Dependence between Commodities (energy or/ and non-energy) and macroeconomic variables (exchange rate, interest rate and index price) © The Author(s)

The Free Market System Financial Markets. Saving and Investment 1.investment: the purchase of an asset in hopes it appreciates or generates income ●Examples:

Discussant: Ji-Chai Lin Louisiana State University 2008 NTU Conference on Finance, Taipei.

Corporate Governance and Financial Reporting Research Discussion of “Fraud type and auditor litigation: An analysis of SEC accounting and auditing enforcement.

1 Arbitrage risk and the book- to-market anomaly Ali, Hwang and Trombley JFE (2003)

Types of financial institutions Determinants of interest rates

Does Academic Research Destroy Stock Return Predictability. R

Chapter 9 Market Efficiency.

Types of financial institutions Determinants of interest rates

Corporate Governance and Financial Reporting Research

Sven Blank (University of Tübingen)

Market Efficiency and Behavioral Finance

Cheng-Few Lee Distinguished Professor of Finance and

Presentation transcript:

Are institutions informed about news? T. Hendershott, D. Livdan, N. Schürhoff Discussed by: Sergey Gelman, ICEF, Higher School of Economics, Moscow The Second International Moscow Finance Conference 2012

Summary (I) Since Kyle (1985): the role of an informed trader is crucial – Who is informed? Mutual funds, Short sellers, Corporate insiders. – Are institutions informed? Up to now: mixed evidence, based mainly on specific news – This paper: using a very comprehensive news sample YES!

Summary (II) Excellent lit review A rich dataset: – returns and NYSE institutional trading data on 1667 stocks observed over (756 trading days) – 126,438 days with news releases from Reuters NewsScope Sentiment Engine Results: Institutional trading predicts news arrival Institutional trading predicts news sentiment Inst. trading predicts (news) returns Inst. trading predicts earnings surprise

Comments (I) Causality issue: do institutions cause news or predict (have private info)? – Institutional demand drives prices (Choi, Sias 2012 RFS; Llorente et al RFS, Baker and Warner 1993 JFE) – Institutional demand may drive news (indirect evidence: Barber et al JFE) – Only in case of earnings surprises alternative causality stories can be majorly ruled out  Possible extension: include prediction of earnings surprise date returns  Possible extension: choose certain type of news, which can not be influenced by institutionals and returns (beside EA)

Comments (II) Economic significance: 10 b.p.: – small fraction of returns s.d. ≈200 b.p.  Institutions are better informed, but not “the informed” – smaller than transaction costs (average bid-ask spreads for S&P 500 stocks were 16 b.p. in );  Do institutions trade on the information or just minimize their transaction costs? High persistence of institutional order imbalance: – link to theoretical models – Splitting order effect, literature on the size of informed trade (Llorente et al RFS): Return*volume

Comments (III): Technical Fixed effects cause problems in all panel equations, not only VAR (use Arellano-Bover (1995)) Institutional fraction (Choi and Sias 2012 RFS) – Negative sign for volume – Institutionals seem to account for 50% to over 100% of the volume (??). Who is uninformed in the latter case? Granger causality test instead of IRF Persistence in sentiment: Effect of a news published several times in different media? Surprising: simultaneous correlations in VAR low