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Asset Prices and the Trading Process

Paper Session

Sunday, Jan. 5, 2020 8:00 AM - 10:00 AM (PDT)

Manchester Grand Hyatt, Seaport A
Hosted By: American Finance Association
  • Chair: Haoxiang Zhu, Massachusetts Institute of Technology

The Price Effects of Liquidity Shocks: A Study of SEC's Tick-Size Experiment

Rui Albuquerque
,
Boston College
Shiyun Song
,
University of Warwick
Chen Yao
,
Chinese University of Hong Kong

Abstract

Do stock prices of publicly listed companies respond to changes in transaction costs? Using the SEC's pilot program that increased the tick size for approximately 1,200 randomly chosen stocks, we find a stock price decrease between $1.75% and $3.2% for small spread stocks affected by the larger tick size relative to a control group. We find that the increase in the present value of transaction costs accounts for a small percentage of the price decrease. We study channels of price variation due to changes in expected returns: information risk, investor horizon, and liquidity risk. The evidence suggests that trading frictions affect the cost of capital.

What Moves Stock Prices? The Role of News, Noise, and Information

Jonathan Brogaard
,
University of Utah
Huong Nguyen
,
University of Technology Sydney
Talis Putnins
,
University of Technology Sydney
Eliza Wu
,
University of Sydney

Abstract

We develop a return variance decomposition model to separate the role of different types of information and noise in stock price movements. We disentangle four components: market-wide information, private firm-specific information revealed through trading, firm-specific information revealed through public sources, and noise. Overall, 31% of the return variance is from noise, 37% from public firm-specific information, 24% from private firm-specific information, and 8% from market-wide information. Since the mid-1990s, there has been a dramatic decline in noise and an increase in firm-specific information, consistent with increasing market efficiency.

Identifying Price Informativeness

Eduardo Davila
,
Yale University
Cecilia Parlatore
,
New York University

Abstract

We show that outcomes (parameter estimates and R-squareds) of regressions of prices on fundamentals allow us to recover exact measures of the ability of asset prices to aggregate dispersed information. We formally show how to recover absolute and relative price informativeness in dynamic environments with rich heterogeneity across investors (regarding signals, private trading needs, or preferences), minimal distributional assumptions, multiple risky assets, and allowing for stationary and non-stationary asset payoffs. We implement our methodology empirically, finding stock-specific measures of price informativeness for U.S. stocks. We find a right-skewed distribution of price informativeness, measured in the form of the Kalman gain used by an external observer that conditions its posterior belief on the asset price. The recovered mean and median are 0.05 and 0.02 respectively. We find that price informativeness is higher for stocks with higher market capitalization and higher trading volume.
Discussant(s)
Ingrid Werner
,
Ohio State University
Joel Hasbrouck
,
New York University
Harry Mamaysky
,
Columbia University
JEL Classifications
  • G1 - General Financial Markets