nep-mst New Economics Papers
on Market Microstructure
Issue of 2018‒05‒07
four papers chosen by
Thanos Verousis

  1. Relationship between tick size reduction and price information of open limit order book By Kenji Hatakenaka
  2. Chasing Private Information By Kacperczyk, Marcin; Pagnotta, Emiliano
  3. Quantifying macroeconomic expectations in stock markets using Google Trends By Johannes Bock
  4. The price impact of liquidity in international office markets By Steven Devaney; Nicola Livingstone; Pat McAllister; Anupam Nanda

  1. By: Kenji Hatakenaka (Graduate School of Economics, Osaka University)
    Abstract: In this study, I examine the effects from tick size reduction in 2014 at Tokyo Stock Ex- change to price discovery of the limit order book by using tick-by-tick data from TOPIX100 stocks. Typically, both spreads and depths decline after tick size reduction. This fact has been confirmed in this study too. I examine the effects of changes in trader fs behavior which is caused by changes in the shape of limit order book. The results suggest that the information of an efficient price became more likely to be reflected by market orders than limit orders after tick size reduction.
    Keywords: equity market; price discovery; market microstructure; high frequency trading.
    JEL: G14
    Date: 2018–05
  2. By: Kacperczyk, Marcin; Pagnotta, Emiliano
    Abstract: Using over 5000 equity and option trades unequivocally based on nonpublic information about firm fundamentals, we find that widely used adverse selection signals display abnormal values on days with informed trading. Volatility and volume values are abnormally high, whereas illiquidity values are low, both in equity and options markets. Signals are more sensitive to informed trading in options markets and before unscheduled corporate announcements. We characterize cross-sectional responses based on the sign, type, and duration of private information. Evidence from the U.S. Securities and Exchange Commission (SEC) Whistleblower Reward Program addresses potential selection concerns.
    Date: 2018–04
  3. By: Johannes Bock
    Abstract: Among other macroeconomic indicators, the monthly release of U.S. unemployment rate figures in the Employment Situation report by the U.S. Bureau of Labour Statistics gets a lot of media attention and strongly affects the stock markets. I investigate whether a profitable investment strategy can be constructed by predicting the likely changes in U.S. unemployment before the official news release using Google query volumes for related search terms. I find that massive new data sources of human interaction with the Internet not only improves U.S. unemployment rate predictability, but can also enhance market timing of trading strategies when considered jointly with macroeconomic data. My results illustrate the potential of combining extensive behavioural data sets with economic data to anticipate investor expectations and stock market moves.
    Date: 2018–05
  4. By: Steven Devaney; Nicola Livingstone; Pat McAllister; Anupam Nanda
    Abstract: This paper investigates the relationship between market liquidity, as indicated by transaction activity, and real estate asset pricing. Prior research has typically focused on the US or UK markets, but this study draws upon office market data for 36 cities situated in 20 countries over the period Q1 2007 to Q2 2015. Prime office yield is used as the dependent variable when the effects on pricing of transaction activity are modelled. Transaction activity is captured in absolute terms using volumes and in relative terms through the measurement of turnover rates. Turnover rates are measured in two ways: as the proportion of stock in terms of physical area that traded and as the proportion of stock in terms of total value that traded. A range of econometric techniques are then applied in order to control for well-known endogeneity problems when estimating the impacts of trading on prices, and vice versa. The results indicate the extent to which transaction activity has a significant effect on pricing after controlling for other fundamental drivers. In addition, the research provides further insights into variations in transaction activity between major global office markets.
    Keywords: Capitalization rates; Liquidity; Transaction activity; Turnover rates; Yield modelling
    JEL: R3
    Date: 2017–07–01

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