Supplementary Results For Greenwood and Hanson 2009, Catering to Characteristics Last revision: June 2009
|
|
|
- Dylan Daniels
- 5 years ago
- Views:
Transcription
1 Supplementary Results For Greenwood and Hanson 2009, Catering to Characteristics Last revision: June 2009
2 Appendix Table I Robustness to Forecasting Regressions Robustness of regressions of monthly long-short characteristic portfolio returns on lagged values of the corresponding characteristic issuer-repurchaser spread: Rt a b ISSREPt 1 ut The sample period includes monthly returns from July 1963 to June The long-short portfolios are formed based on firm characteristics: the book-to-market (B/M) ratio, sales growth (ΔS/S), accruals (Acc/A), Size (ME), nominal share price (P), Age, CAPM beta (β), residual volatility (σ), the Shumway bankruptcy hazard rate (SHUM), dividend policy (Div), and profitability (E/B). All characteristics except for dividend policy are measures as their NYSE decile rank; dividend policy is measured by a dummy variable that takes a value of one if the firm paid a dividend in year t-1. Monthly returns between July of year t and June of year t+1 are matched to the issuer-repurchaser spread in year t-1. Standard errors are clustered by 12-month blocks running from July t to June t+1. The corresponding t-statistics are shown in brackets. Panel A. Issuer-repurchaser spreads are based on raw characteristics (rather than characteristic deciles) B/M [-2.72] [-2.41] [-2.72] [-2.33] ΔS/S t [-1.19] [-0.89] [-0.26] [-0.12] Acc/A [-0.22] [-0.48] [0.38] [0.11] ME [-2.17] [-3.91] [-2.17] [-3.90] P [-3.55] [-3.88] [-2.98] [-3.36] Age [-0.97] [-0.84] [-0.21] [-0.04] [-1.29] [-1.57] [-1.12] [-1.40] [-0.89] [-1.39] [-0.46] [-0.88] SHUM [-1.03] [-1.35] [-1.08] [-1.27] Div [-0.98] [-1.85] [-0.30] [-1.14] E/B [-1.85] [-2.08] [-0.10] [-0.78] Panel B. Issuer-repurchaser spreads are based on cross-sectional regression of NS decile on characteristic decile B/M [-2.68] [-2.41] [-2.32] [-2.10] ΔS/S t [-0.95] [-0.58] [-0.07] [0.22] Acc/A [-0.51] [-0.45] [-0.26] [0.00] ME [-1.64] [-2.95] [-1.71] [-3.09] P [-3.05] [-3.42] [-2.45] [-2.95] Age [-0.71] [-0.57] [-0.07] [0.16] [-0.88] [-1.21] [-0.65] [-0.99] [-0.22] [-0.34] [0.22] [0.17] SHUM [-2.08] [-2.96] [-1.93] [-2.69] Div [-1.18] [-1.44] [-0.79] [-0.87] E/B [-1.42] [-1.59] [0.36] [-0.19]
3 Appendix Table I Continued Panel C. Net Issuance Spread = difference in average NS between firms with high and low values of characteristic (i.e., highlow NS spreads) Panel B: 1-year ahead issuance purged R B/M [-1.78] [-1.76] [-1.60] [-1.60] ΔS/S t [-1.00] [-0.67] [-0.19] [0.19] Acc/A [-1.42] [-1.59] [-0.83] [-1.31] ME [-2.05] [-3.07] [-1.97] [-3.04] P [-3.14] [-3.33] [-2.27] [-2.59] Age [-1.01] [-0.95] [-0.47] [-0.27] [-1.40] [-1.20] [-1.08] [-0.91] [-1.17] [-1.11] [-0.60] [-0.50] SHUM [-1.86] [-1.77] [-1.35] [-1.41] Div [-1.38] [-1.73] [-0.86] [-1.11] E/B [-3.02] [-3.51] [0.31] [-0.06] Panel D. Net Issuance Spread = difference in average NS decile between firms with high and low values of characteristic (i.e., high-low NS spreads) B/M [-2.57] [-2.64] [-2.28] [-2.33] ΔS/S t [-0.68] [-0.49] [0.22] [0.38] Acc/A [-0.41] [-0.49] [0.58] [0.28] ME [-1.61] [-2.95] [-1.68] [-3.11] P [-3.39] [-3.88] [-2.62] [-3.01] Age [-1.26] [-1.18] [-0.87] [-0.64] [-0.96] [-1.04] [-0.63] [-0.77] [-0.44] [-0.50] [0.06] [0.02] SHUM [-1.43] [-2.18] [-1.15] [-1.80] Div [-1.40] [-1.94] [-0.89] [-1.29] E/B [-1.44] [-1.88] [0.36] [-0.38]
4 Appendix Table I--Continued Panel E. Decile 10 minus decile 1 characteristic portfolio returns (i.e., not size balanced 30/70 portfolios) b [t] b [t] B [t] B [t] B/M [1.96] [-2.24] [-1.03] [-1.33] ΔS/S t [0.27] [-0.52] [0.66] [-0.16] Acc/A [0.66] [-0.62] [0.07] [-0.14] ME [-2.30] [-4.05] [-2.33] [-4.28] P [-3.18] [-5.74] [-3.06] [-5.15] Age [-2.16] [-2.32] [-2.03] [-1.79] [-0.89] [-1.15] [-0.74] [-1.22] [-0.93] [-1.79] [-0.44] [-1.18] SHUM [-1.60] [-5.31] [-1.71] [-4.43] Div ----Not valid for this construction Not valid for this construction--- E/B [-1.98] [-2.50] [-1.27] [-1.45] Panel F. Control for lagged characteristic returns (cumulative return over previous 12 months) B/M [-2.30] [-1.87] [-2.08] [-1.69] ΔS/S t [0.42] [-0.87] [1.05] [0.03] Acc/A [0.36] [-0.29] [1.28] [0.64] ME [-1.08] [-4.08] [-1.06] [-4.11] P [-2.74] [-3.16] [-2.29] [-2.88] Age [-0.85] [-0.73] [-0.09] [0.08] [-0.74] [-1.06] [-0.50] [-0.87] [-0.39] [-0.88] [0.12] [-0.33] SHUM [-1.46] [-2.68] [-1.28] [-2.39] Div [-0.89] [-1.93] [-0.39] [-1.26] E/B [-1.25] [-1.36] [0.63] [0.01]
5 Appendix Table I--Continued Panel G. Include a time trend B/M [-2.45] [-2.07] [-2.11] [-1.74] ΔS/S t [0.01] [-0.73] [0.95] [0.11] Acc/A [-0.03] [-0.51] [0.49] [0.21] ME [-1.44] [-4.47] [-1.50] [-4.63] P [-2.20] [-3.35] [-2.04] [-2.76] Age [-0.99] [-1.17] [-0.49] [-0.95] [-1.03] [-1.66] [-0.76] [-1.60] [-0.80] [-2.73] [-0.38] [-2.57] SHUM [-1.52] [-2.70] [-1.39] [-2.35] Div [-1.07] [-2.31] [-0.46] [-1.86] E/B [-2.19] [-1.45] [-1.80] [-0.92] Panel H. Include a recession Control B [t] b [t] b [t] b [t] B/M [-2.49] [-1.61] [-2.24] [-1.38] ΔS/S t [0.65] [-0.67] [1.37] [0.17] Acc/A [-0.19] [-0.43] [0.49] [0.39] ME [-1.29] [-3.54] [-1.29] [-3.57] P [-2.92] [-2.85] [-2.34] [-2.28] Age [-1.02] [-1.07] [-0.41] [-0.40] [-0.97] [-1.36] [-0.72] [-1.16] [-0.50] [-1.26] [-0.05] [-0.73] SHUM [-1.66] [-2.27] [-1.51] [-2.03] Div [-1.08] [-2.60] [-0.54] [-1.78] E/B [-1.58] [-1.24] [0.05] [-0.16]
6 Appendix Table I--Continued Panel I. Small firms only B [t] b [t] b [t] b [t] B/M [-3.01] [-2.61] [2.92] [-2.42] ΔS/S t [-1.64] [-2.77] [0.78] [-1.61] Acc/A [-1.64] [-1.26] [0.84] [-0.35] ME ----Not valid for this construction Not valid for this construction--- P [-3.97] [-3.84] [2.87] [-2.85] Age [-1.31] [-1.09] [0.38] [0.15] [-1.13] [-1.52] [0.79] [-1.22] [-0.81] [-1.27] [0.43] [-0.87] SHUM [-1.86] [-2.78] [1.83] [-2.53] Div ----Not valid for this construction Not valid for this construction--- E/B [-2.31] [-1.33] [0.96] [-0.29] Panel J. Large firms only B [t] b [t] b [t] b [t] B/M [-2.06] [-1.82] [-1.68] [-1.52] ΔS/S t [2.67] [0.46] [2.73] [0.70] Acc/A [0.61] [0.15] [0.99] [0.45] ME ----Not valid for this construction Not valid for this construction--- P [-2.04] [-3.35] [-1.98] [-3.37] Age [-0.57] [-0.48] [-0.14] [-0.19] [-0.76] [-0.96] [-0.60] [-0.87] [-0.18] [-0.58] [-0.34] [0.03] SHUM [-1.41] [-2.76] [-1.21] [-2.52] Div ----Not valid for this construction Not valid for this construction--- E/B [-0.51] [-2.21] [1.12] [-0.91]
7 Appendix Table II Stambaugh Bias Adjustment: Annual Forecasting Regressions Regressions of annual long-short portfolio returns on lagged values of the issuer-repurchaser spread for the corresponding characteristic: Rt a b ISSREPt 1 ut We use annual forecasting regressions here to facilitate the comparison between OLS and Stambaugh bias-adjusted coefficients. The left- column in each panel show OLS estimates; the right-column show the Stambaugh (1999) bias- adjusted coefficients, with standard errors computed following Amihud and Hurvich (2004). The sample period includes annual (July though June) returns from July 1963 to June The long-short portfolios are formed based on firm characteristics: the book-to-market (B/M) ratio, sales growth (ΔS/S), accruals (Acc/A), Size (ME), nominal share price (P), Age, CAPM beta (β), residual volatility (σ), the Shumway bankruptcy hazard rate (SHUM), dividend policy (Div), and profitability (E/B). All characteristics except for dividend policy are measures as their NYSE decile rank; dividend policy is measured by a dummy variable that takes a value of one if the firm paid a dividend in year t OLS Annual Bias-adjusted Annual OLS Annual Bias-adjusted Annual B/M [-2.37] [-2.28] [-2.20] [-2.11] ΔS/S t [0.48] [0.72] [-0.63] [-0.38] Acc/A [-0.38] [-0.37] [-1.45] [-1.37] ME [-1.89] [-2.12] [-1.80] [-1.99] P [-2.39] [-2.46] [-2.56] [-2.55] Age [-0.69] [-0.68] [-0.39] [-0.32] [-1.18] [-1.27] [-1.08] [-1.19] [-0.66] [-0.78] [-0.45] [-0.56] SHUM [-1.78] [-1.77] [-2.29] [-2.07] Div [-0.78] [-1.01] [-0.74] [-0.87] E/B [-1.52] [-1.32] [-1.84] [-1.80]
A Corporate Arbitrage Approach to the Cross-section of Stock Returns
A Corporate Arbitrage Approach to the Cross-section of Stock Returns Robin Greenwood Harvard University rgreenwood@hbs.edu Samuel Hanson Harvard University shanson@hbs.edu Revised: December 2008 (First
Characteristic Timing
Characteristic Timing Robin Greenwood Samuel Hanson Working Paper 09-099 Copyright 2009, 2010 by Robin Greenwood and Samuel Hanson Working papers are in draft form. This working paper is distributed for
Share Issuance and Factor Timing
Share Issuance and Factor Timing Robin Greenwood Harvard Business School and NBER rgreenwood@hbs.edu Samuel Hanson Harvard University shanson@hbs.edu Revised: December 2010 (First draft: November 2008)
Supplementary Material and Data for Catering Through Nominal Share Prices. Malcolm Baker, Robin Greenwood, and Jeffrey Wurgler October 1, 2008
Supplementary Material and Data for Catering Through Nominal Share Prices Malcolm Baker, Robin Greenwood, and Jeffrey Wurgler October, 2008 Table A. Data table: Raw Market-to-Book Data. The market-to-book
Stock Liquidity and Default Risk *
Stock Liquidity and Default Risk * Jonathan Brogaard Dan Li Ying Xia Internet Appendix A1. Cox Proportional Hazard Model As a robustness test, we examine actual bankruptcies instead of the risk of default.
Management Science Online Appendix Tables: Hiring Cheerleaders: Board Appointments of "Independent" Directors
Management Science Online Appendix Tables: Hiring Cheerleaders: Board Appointments of "Independent" Directors Table A1: Summary Statistics This table shows summary statistics for the sample of sell side
Internet Appendix for: Cyclical Dispersion in Expected Defaults
Internet Appendix for: Cyclical Dispersion in Expected Defaults João F. Gomes Marco Grotteria Jessica Wachter August, 2017 Contents 1 Robustness Tests 2 1.1 Multivariable Forecasting of Macroeconomic Quantities............
Internet Appendix to The Booms and Busts of Beta Arbitrage
Internet Appendix to The Booms and Busts of Beta Arbitrage Table A1: Event Time CoBAR This table reports some basic statistics of CoBAR, the excess comovement among low beta stocks over the period 1970
Internet Appendix for: Cyclical Dispersion in Expected Defaults
Internet Appendix for: Cyclical Dispersion in Expected Defaults March, 2018 Contents 1 1 Robustness Tests The results presented in the main text are robust to the definition of debt repayments, and the
Internet Appendix to Is Information Risk Priced? Evidence from Abnormal Idiosyncratic Volatility
Internet Appendix to Is Information Risk Priced? Evidence from Abnormal Idiosyncratic Volatility Table IA.1 Further Summary Statistics This table presents the summary statistics of further variables used
Internet Appendix to Leverage Constraints and Asset Prices: Insights from Mutual Fund Risk Taking
Internet Appendix to Leverage Constraints and Asset Prices: Insights from Mutual Fund Risk Taking In this Internet Appendix, we provide further discussion and additional empirical results to evaluate robustness
Volatility Appendix. B.1 Firm-Specific Uncertainty and Aggregate Volatility
B Volatility Appendix The aggregate volatility risk explanation of the turnover effect relies on three empirical facts. First, the explanation assumes that firm-specific uncertainty comoves with aggregate
Daily Data is Bad for Beta: Opacity and Frequency-Dependent Betas Online Appendix
Daily Data is Bad for Beta: Opacity and Frequency-Dependent Betas Online Appendix Thomas Gilbert Christopher Hrdlicka Jonathan Kalodimos Stephan Siegel December 17, 2013 Abstract In this Online Appendix,
Online Appendix to. The Value of Crowdsourced Earnings Forecasts
Online Appendix to The Value of Crowdsourced Earnings Forecasts This online appendix tabulates and discusses the results of robustness checks and supplementary analyses mentioned in the paper. A1. Estimating
A Lottery Demand-Based Explanation of the Beta Anomaly. Online Appendix
A Lottery Demand-Based Explanation of the Beta Anomaly Online Appendix Section I provides details of the calculation of the variables used in the paper. Section II examines the robustness of the beta anomaly.
The New Issues Puzzle
The New Issues Puzzle Professor B. Espen Eckbo Advanced Corporate Finance, 2009 Contents 1 IPO Sample and Issuer Characteristics 1 1.1 Annual Sample Distribution................... 1 1.2 IPO Firms are
Lecture 5. Predictability. Traditional Views of Market Efficiency ( )
Lecture 5 Predictability Traditional Views of Market Efficiency (1960-1970) CAPM is a good measure of risk Returns are close to unpredictable (a) Stock, bond and foreign exchange changes are not predictable
Internet Appendix. Table A1: Determinants of VOIB
Internet Appendix Table A1: Determinants of VOIB Each month, we regress VOIB on firm size and proxies for N, v δ, and v z. OIB_SHR is the monthly order imbalance defined as (B S)/(B+S), where B (S) is
Appendix A. Mathematical Appendix
Appendix A. Mathematical Appendix Denote by Λ t the Lagrange multiplier attached to the capital accumulation equation. The optimal policy is characterized by the first order conditions: (1 α)a t K t α
Appendix. In this Appendix, we present the construction of variables, data source, and some empirical procedures.
Appendix In this Appendix, we present the construction of variables, data source, and some empirical procedures. A.1. Variable Definition and Data Source Variable B/M CAPX/A Cash/A Cash flow volatility
September 12, 2006, version 1. 1 Data
September 12, 2006, version 1 1 Data The dependent variable is always the equity premium, i.e., the total rate of return on the stock market minus the prevailing short-term interest rate. Stock Prices:
Appendix Tables for: A Flow-Based Explanation for Return Predictability. Dong Lou London School of Economics
Appendix Tables for: A Flow-Based Explanation for Return Predictability Dong Lou London School of Economics Table A1: A Horse Race between Two Definitions of This table reports Fama-MacBeth stocks regressions.
Internet Appendix for Corporate Cash Shortfalls and Financing Decisions. Rongbing Huang and Jay R. Ritter. August 31, 2017
Internet Appendix for Corporate Cash Shortfalls and Financing Decisions Rongbing Huang and Jay R. Ritter August 31, 2017 Our Figure 1 finds that firms that have a larger are more likely to run out of cash
Time-variation of CAPM betas across market volatility regimes for Book-to-market and Momentum portfolios
Time-variation of CAPM betas across market volatility regimes for Book-to-market and Momentum portfolios Azamat Abdymomunov James Morley Department of Economics Washington University in St. Louis October
Internet Appendix. Fundamental Trading under the Microscope: Evidence from Detailed Hedge Fund Transaction Data. Sandro Lunghi Inalytics
Internet Appendix Fundamental Trading under the Microscope: Evidence from Detailed Hedge Fund Transaction Data Bastian von Beschwitz Federal Reserve Board Sandro Lunghi Inalytics Daniel Schmidt HEC Paris
Internet Appendix for Buyout Activity: The Impact of Aggregate Discount Rates
Internet Appendix for Buyout Activity: The Impact of Aggregate Discount Rates Valentin Haddad, Erik Loualiche, and Matthew Plosser * In this Internet Appendix we present several robustness tables. IAI
Fama-French in China: Size and Value Factors in Chinese Stock Returns
Fama-French in China: Size and Value Factors in Chinese Stock Returns November 26, 2016 Abstract We investigate the size and value factors in the cross-section of returns for the Chinese stock market.
Aggregate Volatility Risk: Explaining the Small Growth Anomaly and the New Issues Puzzle
Aggregate Volatility Risk: Explaining the Small Growth Anomaly and the New Issues Puzzle Alexander Barinov Terry College of Business University of Georgia E-mail: abarinov@terry.uga.edu http://abarinov.myweb.uga.edu/
Decimalization and Illiquidity Premiums: An Extended Analysis
Utah State University DigitalCommons@USU All Graduate Plan B and other Reports Graduate Studies 5-2015 Decimalization and Illiquidity Premiums: An Extended Analysis Seth E. Williams Utah State University
High Idiosyncratic Volatility and Low Returns. Andrew Ang Columbia University and NBER. Q Group October 2007, Scottsdale AZ
High Idiosyncratic Volatility and Low Returns Andrew Ang Columbia University and NBER Q Group October 2007, Scottsdale AZ Monday October 15, 2007 References The Cross-Section of Volatility and Expected
Market Frictions, Price Delay, and the Cross-Section of Expected Returns
Market Frictions, Price Delay, and the Cross-Section of Expected Returns forthcoming The Review of Financial Studies Kewei Hou Fisher College of Business Ohio State University and Tobias J. Moskowitz Graduate
Web Appendix: Do Arbitrageurs Amplify Economic Shocks?
Web Appendix: Do Arbitrageurs Amplify Economic Shocks? Harrison Hong Princeton University Jeffrey D. Kubik Syracuse University Tal Fishman Parkcentral Capital Management We have carried out a number of
Asubstantial portion of the academic
The Decline of Informed Trading in the Equity and Options Markets Charles Cao, David Gempesaw, and Timothy Simin Charles Cao is the Smeal Chair Professor of Finance in the Smeal College of Business at
Momentum, Business Cycle, and Time-varying Expected Returns
THE JOURNAL OF FINANCE VOL. LVII, NO. 2 APRIL 2002 Momentum, Business Cycle, and Time-varying Expected Returns TARUN CHORDIA and LAKSHMANAN SHIVAKUMAR* ABSTRACT A growing number of researchers argue that
Internet Appendix for The Joint Cross Section of Stocks and Options *
Internet Appendix for The Joint Cross Section of Stocks and Options * To save space in the paper, additional results are reported and discussed in this Internet Appendix. Section I investigates whether
Are Firms in Boring Industries Worth Less?
Are Firms in Boring Industries Worth Less? Jia Chen, Kewei Hou, and René M. Stulz* January 2015 Abstract Using theories from the behavioral finance literature to predict that investors are attracted to
Online Appendix. Do Funds Make More When They Trade More?
Online Appendix to accompany Do Funds Make More When They Trade More? Ľuboš Pástor Robert F. Stambaugh Lucian A. Taylor April 4, 2016 This Online Appendix presents additional empirical results, mostly
University of California Berkeley
University of California Berkeley A Comment on The Cross-Section of Volatility and Expected Returns : The Statistical Significance of FVIX is Driven by a Single Outlier Robert M. Anderson Stephen W. Bianchi
Risk Neutral Skewness Anomaly and Momentum Crashes
Risk Neutral Skewness Anomaly and Momentum Crashes Paul Borochin School of Business University of Connecticut Yanhui Zhao School of Business University of Connecticut This version: January, 2018 Abstract
Common Risk Factors in the Cross-Section of Corporate Bond Returns
Common Risk Factors in the Cross-Section of Corporate Bond Returns Online Appendix Section A.1 discusses the results from orthogonalized risk characteristics. Section A.2 reports the results for the downside
Assessing Model Stability Using Recursive Estimation and Recursive Residuals
Assessing Model Stability Using Recursive Estimation and Recursive Residuals Our forecasting procedure cannot be expected to produce good forecasts if the forecasting model that we constructed was stable
Does Transparency Increase Takeover Vulnerability?
Does Transparency Increase Takeover Vulnerability? Finance Working Paper N 570/2018 July 2018 Lifeng Gu University of Hong Kong Dirk Hackbarth Boston University, CEPR and ECGI Lifeng Gu and Dirk Hackbarth
Robustness Checks for Idiosyncratic Volatility, Growth Options, and the Cross-Section of Returns
Robustness Checks for Idiosyncratic Volatility, Growth Options, and the Cross-Section of Returns Alexander Barinov Terry College of Business University of Georgia This version: July 2011 Abstract This
BAM Intelligence. 1 of 7 11/6/2017, 12:02 PM
1 of 7 11/6/2017, 12:02 PM BAM Intelligence Larry Swedroe, Director of Research, 6/22/2016 For about ree decades, e working asset pricing model was e capital asset pricing model (CAPM), wi beta specifically
Value at Risk and Expected Stock Returns
Value at isk and Expected Stock eturns August 2003 Turan G. Bali Associate Professor of Finance Department of Economics & Finance Baruch College, Zicklin School of Business City University of New York
AN ALTERNATIVE THREE-FACTOR MODEL FOR INTERNATIONAL MARKETS: EVIDENCE FROM THE EUROPEAN MONETARY UNION
AN ALTERNATIVE THREE-FACTOR MODEL FOR INTERNATIONAL MARKETS: EVIDENCE FROM THE EUROPEAN MONETARY UNION MANUEL AMMANN SANDRO ODONI DAVID OESCH WORKING PAPERS ON FINANCE NO. 2012/2 SWISS INSTITUTE OF BANKING
Economic Valuation of Liquidity Timing
Economic Valuation of Liquidity Timing Dennis Karstanje 1,2 Elvira Sojli 1,3 Wing Wah Tham 1 Michel van der Wel 1,2,4 1 Erasmus University Rotterdam 2 Tinbergen Institute 3 Duisenberg School of Finance
Table IA.1 CEO Pay-Size Elasticity and Increased Labor Demand Panel A: IPOs Scaled by Full Sample Industry Average
Table IA.1 CEO Pay-Size Elasticity and Increased Labor Demand Panel A: IPOs Scaled by Industry Average (1) (2) (3) (4) (5) Ln(Market Value) 0.423 0.419 0.423 0.423 0.255 (33.29) (30.84) (33.29) (33.29)
Regression Discontinuity and. the Price Effects of Stock Market Indexing
Regression Discontinuity and the Price Effects of Stock Market Indexing Internet Appendix Yen-Cheng Chang Harrison Hong Inessa Liskovich In this Appendix we show results which were left out of the paper
SFSU FIN822 Project 1
SFSU FIN822 Project 1 This project can be done in a team of up to 3 people. Your project report must be accompanied by printouts of programming outputs. You could use any software to solve the problems.
Currency Risk and Information Diffusion
Department of Finance Bowling Green State University srrush@bgsu.edu Contributions What Will We Learn? Information moves from currency markets to equity markets at different speeds Adverse selection in
Supplementary Appendix for Outsourcing Mutual Fund Management: Firm Boundaries, Incentives and Performance
Supplementary Appendix for Outsourcing Mutual Fund Management: Firm Boundaries, Incentives and Performance JOSEPH CHEN, HARRISON HONG, WENXI JIANG, and JEFFREY D. KUBIK * This appendix provides details
Supplemental Appendix for Cost Pass-Through to Higher Ethanol Blends at the Pump: Evidence from Minnesota Gas Station Data.
November 18, 2018 Supplemental Appendix for Cost Pass-Through to Higher Ethanol Blends at the Pump: Evidence from Minnesota Gas Station Data Jing Li, MIT James H. Stock, Harvard University and NBER This
Long Run Stock Returns after Corporate Events Revisited. Hendrik Bessembinder. W.P. Carey School of Business. Arizona State University.
Long Run Stock Returns after Corporate Events Revisited Hendrik Bessembinder W.P. Carey School of Business Arizona State University Feng Zhang David Eccles School of Business University of Utah May 2017
Economics of Behavioral Finance. Lecture 3
Economics of Behavioral Finance Lecture 3 Security Market Line CAPM predicts a linear relationship between a stock s Beta and its excess return. E[r i ] r f = β i E r m r f Practically, testing CAPM empirically
A Note on Predicting Returns with Financial Ratios
A Note on Predicting Returns with Financial Ratios Amit Goyal Goizueta Business School Emory University Ivo Welch Yale School of Management Yale Economics Department NBER December 16, 2003 Abstract This
Caught on Tape: Institutional Trading, Stock Returns, and Earnings Announcements
Caught on Tape: Institutional Trading, Stock Returns, and Earnings Announcements The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters.
MANAGEMENT SCIENCE doi /mnsc ec
MANAGEMENT SCIENCE doi 10.1287/mnsc.1100.1159ec e-companion ONLY AVAILABLE IN ELECTRONIC FORM informs 2010 INFORMS Electronic Companion Quality Management and Job Quality: How the ISO 9001 Standard for
Internet Appendix for: Does Going Public Affect Innovation?
Internet Appendix for: Does Going Public Affect Innovation? July 3, 2014 I Variable Definitions Innovation Measures 1. Citations - Number of citations a patent receives in its grant year and the following
Pricing and Mispricing in the Cross Section
Pricing and Mispricing in the Cross Section D. Craig Nichols Whitman School of Management Syracuse University James M. Wahlen Kelley School of Business Indiana University Matthew M. Wieland J.M. Tull School
Style-Driven Earnings Momentum
Style-Driven Earnings Momentum Sebastian Mueller This Version: March 2013 First Version: November 2011 Appendix attached Abstract This paper shows that earnings announcements contain information about
What Drives Anomaly Returns?
What Drives Anomaly Returns? Lars A. Lochstoer and Paul C. Tetlock UCLA and Columbia Q Group, April 2017 New factors contradict classic asset pricing theories E.g.: value, size, pro tability, issuance,
Asset Pricing and Excess Returns over the Market Return
Supplemental material for Asset Pricing and Excess Returns over the Market Return Seung C. Ahn Arizona State University Alex R. Horenstein University of Miami This documents contains an additional figure
Online Appendix Table 1. Robustness Checks: Impact of Meeting Frequency on Additional Outcomes. Control Mean. Controls Included
Online Appendix Table 1. Robustness Checks: Impact of Meeting Frequency on Additional Outcomes Control Mean No Controls Controls Included (Monthly- Monthly) N Specification Data Source Dependent Variable
Revisiting Idiosyncratic Volatility and Stock Returns. Fatma Sonmez 1
Revisiting Idiosyncratic Volatility and Stock Returns Fatma Sonmez 1 Abstract This paper s aim is to revisit the relation between idiosyncratic volatility and future stock returns. There are three key
Liquidity and IPO performance in the last decade
Liquidity and IPO performance in the last decade Saurav Roychoudhury Associate Professor School of Management and Leadership Capital University Abstract It is well documented by that if long run IPO underperformance
Earnings Dispersion and Aggregate Stock Returns
Tepper School of Business Carnegie Mellon University Year 2009 Earnings Dispersion and Aggregate Stock Returns Bjorn N. Jorgensen Jing Li Gil Sadka University of Colorado at Boulder Carnegie Mellon University,
Credit Expansion and Neglected Crash Risk. Online Appendix
Credit Expansion and Neglected Crash Risk Online Appendix Matthew Baron and Wei Xiong A. Additional details on data construction Here we present additional information related to data sources and variable
Idiosyncratic Volatility, Growth Options, and the Cross-Section of Returns
Idiosyncratic Volatility, Growth Options, and the Cross-Section of Returns This version: September 2013 Abstract The paper shows that the value effect and the idiosyncratic volatility discount (Ang et
Post-Earnings-Announcement Drift (PEAD): The Role of Revenue Surprises
Post-Earnings-Announcement Drift (PEAD): The Role of Revenue Surprises Joshua Livnat Department of Accounting Stern School of Business Administration New York University 311 Tisch Hall 40 W. 4th St. New
Managerial Insider Trading and Opportunism
Managerial Insider Trading and Opportunism Mehmet E. Akbulut 1 Department of Finance College of Business and Economics California State University Fullerton Abstract This paper examines whether managers
Unpublished Appendices to Market Reactions to Tangible and Intangible Information. Market Reactions to Different Types of Information
Unpublished Appendices to Market Reactions to Tangible and Intangible Information. This document contains the unpublished appendices for Daniel and Titman (006), Market Reactions to Tangible and Intangible
Alternative factor specifications, security characteristics, and the cross-section of expected stock returns
Journal of Financial Economics 49 (1998) 345 373 Alternative factor specifications, security characteristics, and the cross-section of expected stock returns Michael J. Brennan, Tarun Chordia, Avanidhar
Online Appendix for. Short-Run and Long-Run Consumption Risks, Dividend Processes, and Asset Returns
Online Appendix for Short-Run and Long-Run Consumption Risks, Dividend Processes, and Asset Returns 1 More on Fama-MacBeth regressions This section compares the performance of Fama-MacBeth regressions
Assessing the probability of financial distress of UK firms
Assessing the probability of financial distress of UK firms Evangelos C. Charalambakis Susanne K. Espenlaub Ian Garrett First version: June 12 2008 This version: January 15 2009 Manchester Business School,
Retail Investors Biased Beliefs about Stocks that They Hold: Evidence from. China s Split Share Structure Reform. Yan Luo.
Retail Investors Biased Beliefs about Stocks that They Hold: Evidence from China s Split Share Structure Reform Yan Luo luoyan@fudan.edu.cn School of Management, Fudan University, No. 670 Guoshun Road,
Cost of Capital and Liquidity of Foreign Private Issuers Exempted From Filing with the SEC: Information Risk Effect or Earnings Quality Effect?
Cost of Capital and Liquidity of Foreign Private Issuers Exempted From Filing with the SEC: Information Risk Effect or Earnings Quality Effect? Giorgio Gotti University of Texas at El Paso ggotti@utep.edu
The Impact of Shareholder Taxation on Merger and Acquisition Behavior
The Impact of Shareholder Taxation on Merger and Acquisition Behavior Eric Ohrn, Grinnell College Nathan Seegert, University of Utah Grinnell College Department of Economics Seminar November 8, 2016 Introduction
Alpha or Beta in the Eye of the Beholder: What Drives Hedge Fund Flows? Internet Appendix
Alpha or Beta in the Eye of the Beholder: What Drives Hedge Fund Flows? Internet Appendix This appendix consists of four parts. Section IA.1 analyzes whether hedge fund fees influence investor preferences
Table I Descriptive Statistics This table shows the breakdown of the eligible funds as at May 2011. AUM refers to assets under management. Panel A: Fund Breakdown Fund Count Vintage count Avg AUM US$ MM
Pricing and Mispricing in the Cross-Section
Pricing and Mispricing in the Cross-Section D. Craig Nichols Whitman School of Management Syracuse University James M. Wahlen Kelley School of Business Indiana University Matthew M. Wieland Kelley School
Liquidity skewness premium
Liquidity skewness premium Giho Jeong, Jangkoo Kang, and Kyung Yoon Kwon * Abstract Risk-averse investors may dislike decrease of liquidity rather than increase of liquidity, and thus there can be asymmetric
Time-Varying Liquidity and Momentum Profits*
Time-Varying Liquidity and Momentum Profits* Doron Avramov Si Cheng Allaudeen Hameed Abstract A basic intuition is that arbitrage is easier when markets are most liquid. Surprisingly, we find that momentum
Internet Appendix for Collateral Shocks and Corporate Employment
Internet Appendix for Collateral Shocks and Corporate Employment Nuri Ersahin Rustom M. Irani University of Illinois at Urbana-Champaign March 1, 2018 Appendix IA.I: First-stage for IV estimation This
Momentum, Business Cycle and Time-Varying Expected Returns. Tarun Chordia and Lakshmanan Shivakumar * FORTHCOMING, JOURNAL OF FINANCE
Momentum, Business Cycle and Time-Varying Expected Returns By Tarun Chordia and Lakshmanan Shivakumar * FORTHCOMING, JOURNAL OF FINANCE Tarun Chordia is from the Goizueta Business School, Emory University
ANALYSIS ON RISK RETURN TRADE OFF OF EQUITY BASED MUTUAL FUNDS
ANALYSIS ON RISK RETURN TRADE OFF OF EQUITY BASED MUTUAL FUNDS GULLAMPUDI LAXMI PRAVALLIKA, MBA Student SURABHI LAKSHMI, Assistant Profesor Dr. T. SRINIVASA RAO, Professor & HOD DEPARTMENT OF MBA INSTITUTE
Growth Opportunities, Investment-Specific Technology Shocks and the Cross-Section of Stock Returns
Growth Opportunities, Investment-Specific Technology Shocks and the Cross-Section of Stock Returns Leonid Kogan 1 Dimitris Papanikolaou 2 1 MIT and NBER 2 Northwestern University Boston, June 5, 2009 Kogan,
Risk-Adjusted Futures and Intermeeting Moves
issn 1936-5330 Risk-Adjusted Futures and Intermeeting Moves Brent Bundick Federal Reserve Bank of Kansas City First Version: October 2007 This Version: June 2008 RWP 07-08 Abstract Piazzesi and Swanson
Internet Appendix: High Frequency Trading and Extreme Price Movements
Internet Appendix: High Frequency Trading and Extreme Price Movements This appendix includes two parts. First, it reports the results from the sample of EPMs defined as the 99.9 th percentile of raw returns.
Trading Costs of Asset Pricing Anomalies Appendix: Additional Empirical Results
Trading Costs of Asset Pricing Anomalies Appendix: Additional Empirical Results ANDREA FRAZZINI, RONEN ISRAEL, AND TOBIAS J. MOSKOWITZ This Appendix contains additional analysis and results. Table A1 reports
Testing the Robustness of. Long-Term Under-Performance of. UK Initial Public Offerings
Testing the Robustness of Long-Term Under-Performance of UK Initial Public Offerings by Susanne Espenlaub* Alan Gregory** and Ian Tonks*** 22 July, 1998 * Manchester School of Accounting and Finance, University
Online Appendix. Arbitrage Asymmetry and the Idiosyncratic Volatility Puzzle
Online Appendix to accompany Arbitrage Asymmetry and the Idiosyncratic Volatility Puzzle by Robert F. Stambaugh, Jianfeng Yu, and Yu Yuan November 4, 2014 Contents Table AI: Idiosyncratic Volatility Effects
Two Essays on Asset Pricing
Two Essays on Asset Pricing Jungshik Hur Dissertation submitted to the Faculty of the Virginia Polytechnic Institute and State University in partial fulfillment of the requirements for the degree of Doctor
Stock price synchronicity and the role of analyst: Do analysts generate firm-specific vs. market-wide information?
Stock price synchronicity and the role of analyst: Do analysts generate firm-specific vs. market-wide information? Yongsik Kim * Abstract This paper provides empirical evidence that analysts generate firm-specific
University of Texas at Dallas School of Management. Investment Management Spring Estimation of Systematic and Factor Risks (Due April 1)
University of Texas at Dallas School of Management Finance 6310 Professor Day Investment Management Spring 2008 Estimation of Systematic and Factor Risks (Due April 1) This assignment requires you to perform
TABLE I SUMMARY STATISTICS Panel A: Loan-level Variables (22,176 loans) Variable Mean S.D. Pre-nuclear Test Total Lending (000) 16,479 60,768 Change in Log Lending -0.0028 1.23 Post-nuclear Test Default
Hedge Funds as International Liquidity Providers: Evidence from Convertible Bond Arbitrage in Canada
Hedge Funds as International Liquidity Providers: Evidence from Convertible Bond Arbitrage in Canada Evan Gatev Simon Fraser University Mingxin Li Simon Fraser University AUGUST 2012 Abstract We examine
Disagreement in Economic Forecasts and Expected Stock Returns
Disagreement in Economic Forecasts and Expected Stock Returns Turan G. Bali Georgetown University Stephen J. Brown Monash University Yi Tang Fordham University Abstract We estimate individual stock exposure
Purging Investor Sentiment Index from Too Much Fundamental Information
Purging Investor Sentiment Index from Too Much Fundamental Information Liya Chu Qianqian Du Jun Tu Singapore Management University (Chu, Tu) Southwestern University of Finance and Economics (Du) Lingnan
Dispersion in Analysts Earnings Forecasts and Credit Rating
Dispersion in Analysts Earnings Forecasts and Credit Rating Doron Avramov Department of Finance Robert H. Smith School of Business University of Maryland Tarun Chordia Department of Finance Goizueta Business