nep-mst New Economics Papers
on Market Microstructure
Issue of 2017‒02‒19
nine papers chosen by
Thanos Verousis

  1. Trading Fees and Intermarket Competition By Marios Panayides; Barbara Rindi; Ingrid M. Werner
  2. Regularities and Irregularities in Order Flow Data By Martin Theissen; Sebastian M. Krause; Thomas Guhr
  3. Financial transaction taxes: Announcement effects, short-run effects, and long-run effects By Eichfelder, Sebastian; Lau, Mona; Noth, Felix
  4. Trading Lightly: Cross-Impact and Optimal Portfolio Execution By Iacopo Mastromatteo; Michael Benzaquen; Zoltan Eisler; Jean-Philippe Bouchaud
  5. Abnormal Returns from Joining Congress? Evidence from New Members By Joshua C. Hall; Serkan Karadas; Minh Tam T. Schlosky
  6. A regime-switching stochastic volatility model for forecasting electricity prices By Knapik, Oskar; Exterkate, Peter
  7. Tradable Credit Markets for Intensity Standards By Rudik, Ivan
  8. Hawkes process model with a time-dependent background rate and its application to high-frequency financial data By Takahiro Omi; Yoshito Hirata; Kazuyuki Aihara
  9. The Daily Microstructure of the Housing Market By Peter Chinloy; William D. Larson

  1. By: Marios Panayides; Barbara Rindi; Ingrid M. Werner
    Abstract: We model an order book with liquidity rebates (make fees) and trading fees (take fees) that faces intermarket competition, and use the model s insights to explain changes in market quality and market shares following changes in make-take fees. As predicted by our model, we document that fee changes by one venue a ect market quality and market shares for all venues that compete for order fl ow. Furthermore, we document cross-sectional differences in changes in market quality and market shares following a simultaneous decrease in both make and take fees consistent with traders in large (small) capitalization stocks being more sensitive to the change in make (take) fees. JEL Classifications: G10, G12, G14, G18, G20, D40, D47 Keywords: Trading Fees, Maker-Taker Pricing, Intermarket Competition, Limit Order Book
    Date: 2017
  2. By: Martin Theissen; Sebastian M. Krause; Thomas Guhr
    Abstract: We identify and analyze statistical regularities and irregularities in the recent order flow of different NASDAQ stocks, focusing on the positions where orders are placed in the orderbook. This includes limit orders being placed outside of the spread, inside the spread and (effective) market orders. We find that limit order placement inside the spread is strongly determined by the dynamics of the spread size. Most orders, however, arrive outside of the spread. While for some stocks order placement on or next to the quotes is dominating, deeper price levels are more important for other stocks. As market orders are usually adjusted to the quote volume, the impact of market orders depends on the orderbook structure, which we find to be quite diverse among the analyzed stocks as a result of the way limit order placement takes place.
    Date: 2017–02
  3. By: Eichfelder, Sebastian; Lau, Mona; Noth, Felix
    Abstract: We analyze the impact of the French 2012 financial transaction tax (FTT) on trading volumes, stock prices, liquidity, and volatility. We extend the empirical research by identifying FTT announcement and short-run treatment effects, which can distort difference-in-differences estimates. In addition, we consider long-run volatility measures that better fit the French FTT's legislative design. While we find strong evidence of a positive FTT announcement effect on trading volumes, there is almost no statistically significant evidence of a long-run treatment effect. Thus, evidence of a strong reduction of trading volumes resulting from the French FTT might be driven by announcement effects and short-term treatment effects. We find evidence of an increase of intraday volatilities in the announcement period and a significant reduction of weekly and monthly volatilities in the treatment period. Our findings support theoretical considerations suggesting a stabilizing impact of FTTs on financial markets.
    Keywords: financial transaction tax,market quality,announcement effect,short-run treatment effect
    JEL: G02 G12 H24 M41
    Date: 2017
  4. By: Iacopo Mastromatteo; Michael Benzaquen; Zoltan Eisler; Jean-Philippe Bouchaud
    Abstract: We model the impact costs of a strategy that trades a basket of correlated instruments, by extending to the multivariate case the linear propagator model previously used for single instruments. Our specification allows us to calibrate a cost model that is free of arbitrage and price manipulation. We illustrate our results using a pool of US stocks and show that neglecting cross-impact effects leads to an incorrect estimation of the liquidity and suboptimal execution strategies. We show in particular the importance of synchronizing the execution of correlated contracts.
    Date: 2017–02
  5. By: Joshua C. Hall (West Virginia University, Department of Economics); Serkan Karadas (Sewanee, The University of the South, Department of Economics); Minh Tam T. Schlosky (Sewanee, The University of the South, Department of Economics)
    Abstract: Past research shows that members of Congress are informed traders, i.e., that they earn abnormal returns while in office. This important research does not identify whether being elected leads to informed trading or whether informed traders are selected into office. We try to provide a partial answer to this question by looking at whether new members of Congress were informed traders prior to being elected and how their portfolio performance changes after election and appointment to different types of committees. Due to data limitations our analysis focus on the pre-congressional (i.e., election) and congressional (i.e., post-election) common stock trades made by newly elected members of Congress from 2004-2010. We find weak evidence of informed trading for the pre-Congress period, suggesting that informed traders are not being selected into office. When combined with our finding that the portfolios of members serving on powerful committees outperform the market during their second term in office, this provides additional evidence that serving on influential committees is the mechanism by which members of Congress earn abnormal returns.
    Keywords: informed trading, congressional trading, the STOCK Act
    Date: 2016–12
  6. By: Knapik, Oskar; Exterkate, Peter
    Abstract: In a recent review paper, Weron (2014) pinpoints several crucial challenges outstanding in the area of electricity price forecasting. This research attempts to address all of them by i) showing the importance of considering fundamental price drivers in modeling, ii) developing new techniques for probabilistic (i.e. interval or density) forecasting of electricity prices, iii) introducing an universal technique for model comparison. We propose new regime-switching stochastic volatility model with three regimes (negative jump, normal price, positive jump (spike)) where the transition matrix depends on explanatory variables. Bayesian inference is explored in order to obtain predictive densities. The main focus of the paper is on short-time density forecasting in Nord Pool intraday market. We show that the proposed model outperforms several benchmark models at this task.
    Keywords: Electricity prices, density forecasting, Markov switching, stochastic volatility, fundamental price drivers, ordered probit model, Bayesian inference, seasonality, Nord Pool power market, electricity prices forecasting, probabilistic forecasting
    Date: 2017–02
  7. By: Rudik, Ivan
    Abstract: Many environmental standards are expressed in terms of intensity rather than absolute levels. In some cases, intensity standards are associated with tradable credit markets to mitigate the firms’ compliance costs. I develop a jurisdictional model of credit trading under an intensity standard, framed in terms of a Renewable Portfolio Standard for electric utilities. I find that jurisdictions of firms with high costs of compliance may actually be better off by not allowing inter-jurisdictional credit trading. Counterintuitively, increasing the stringency of the intensity standard under credit trading can have the opposite of the intended effect and decrease renewable electricity generation.
    Date: 2016–02–02
  8. By: Takahiro Omi; Yoshito Hirata; Kazuyuki Aihara
    Abstract: A Hawkes process model with a time-varying background rate is developed for analyzing the high-frequency financial data. In our model, the logarithm of the background rate is modeled by a linear model with variable-width basis functions, and the parameters are estimated by a Bayesian method. We find that the data are explained significantly better by our model as compared to the Hawkes model with a stationary background rate, which is commonly used in the field of quantitative finance. Our model can capture not only the slow time-variation, such as in the intraday seasonality, but also the rapid one, which follows a macroeconomic news announcement. We also demonstrate that the level of the endogeneity of markets, quantified by the branching ratio of the Hawkes process, is overestimated if the time-variation is not considered.
    Date: 2017–02
  9. By: Peter Chinloy (Temple University); William D. Larson (Federal Housing Finance Agency)
    Abstract: The microstructure of the housing market includes periodic buyer liquidity constraints, high transaction costs, and bilateral negotiations on price and timing. These separately introduce daily price volatility and negative serial correlation that is suppressed at a monthly frequency. In a daily U.S. house price index, the annualized standard deviation of returns is 27 percent, versus 3 percent for monthly data. We attribute the daily volatility to repeating calendar-based liquidity price premiums (8 percentage points), transaction costs (7 pp), estimation and composition error (2 pp), and idiosyncratic shocks (10 pp). Monthly house price indices suggest housing has exceptionally high risk-adjusted returns. A daily index brings Sharpe ratios in line with other assets.
    Keywords: liquidity, market microstructure, daily house price index, mortgages, volatility
    JEL: G21 G22
    Date: 2017–02

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