nep-mst New Economics Papers
on Market Microstructure
Issue of 2015‒11‒21
seven papers chosen by
Thanos Verousis
University of Bath

  1. A Stochastic Model of Order Book Dynamics using Bouncing Geometric Brownian Motions By Xin Liu; Qi Gong; Vidyadhar G. Kulkarni
  2. Price Impact and the Recovery of the Limit Order Book: Why Should We Care About Informed Liquidity Providers? By Daniel Havran; Kata Varadi
  3. Strategic liquidity provision in a limit order book By Julius Bonart; Martin Gould
  4. Information Asymmetry and Market Fragmentation By Cecilia Parlatore; Ana Babus
  6. Econometric Analysis of 15-minute Intraday Electricity Prices By Kiesel, Ruediger; Paraschiv, Florentina
  7. Expectations and risk premia at 8:30am: Macroeconomic announcements and the yield curve By Peter Hördahl; Eli M Remolona; Giorgio Valente

  1. By: Xin Liu; Qi Gong; Vidyadhar G. Kulkarni
    Abstract: We consider a limit order book, where buyers and sellers register to trade a security at specific prices. The largest price the buyers on the book are willing to pay to buy the security is called the market bid price, and the smallest price the sellers on the book are willing to receive to sell the security is called the market ask price. Market ask price is always greater than the market bid price, and these prices move upwards and downwards due to new arrivals, market trades, and cancellations. When the two prices become equal, a trade occurs, and immediately after the trade, these prices bounce back, that is, the market bid price decreases and the market ask price increases. We model these two price processes as ``bouncing geometric Brownian motions (GBM)'': that is, the price processes evolve according to two independent GBMs between trading times. We show that, under this model, the inter-trading times follow an inverse Gaussian distribution, and the logarithmic returns between consecutive trading times follow a normal inverse Gaussian distribution. We show that the logarithmic trading price process is a renewal reward process, and that, under a suitable scaling, this renewal reward process converges to a standard Brownian motion. Finally, we develop a GBM asymptotic model for trading prices, and derive a simple and effective prediction formula. We illustrate the effectiveness of the prediction methods with an example using real stock price data.
    Date: 2015–11
  2. By: Daniel Havran (Institute of Economics, Centre for Economic and Regional Studies, Hungarian Academy of Sciences); Kata Varadi (Department of Finance, Corvinus University of Budapest)
    Abstract: We examine the dynamics of the limit order book recovery in the purely order-driven markets. The configuration of the current limit placements in the order book determines the costs over the mid-quote for the buy and sell trades. By analyzing the relationship between the costs of the possible trades and market order-flows, we find that bid and ask side trade costs have significant impact on the direction of future market orders. Moreover, bid and ask side trade costs revert to their characteristic state. For the further analysis of limit order placement strategies, we extend the cost of trade approach by several attributes of the entire limit order book. Using snaphots about cost of round trip indicators from Budapest Stock Exchange stocks, we decompose the shape of the immediate price impact function to main three components, slope, convexity and hump-shape. By running impluse response simulations, we document the typical temporary movements of the trade costs curves and we find empirical evidences about the "pegging to the current mid-quote" behavior of the liquidity providers.
    Keywords: market liquidity, resiliency, informed liquidity providers, immediate price impact function, order-driven market
    JEL: C32 C51 G10 G17
    Date: 2015–08
  3. By: Julius Bonart; Martin Gould
    Abstract: We perform an empirical analysis of how trades influence liquidity in a limit order book (LOB). Using a recent, high-quality data set from Nasdaq, we calculate the mean net flow of limit orders before and after the arrival of a market order. We find strong evidence to suggest that liquidity providers dynamically adapt their limit order flow to the arrivals of market orders. By examining the temporal evolution of this net order flow, we argue that strategic liquidity providers consider both adverse selection and expected waiting costs when deciding how to act. We also note that our results could be consistent with an alternative hypothesis: that liquidity providers successfully forecast market order arrivals before they actually occur.
    Date: 2015–11
  4. By: Cecilia Parlatore (New York University, Stern School of Bus); Ana Babus (Chicago FED)
    Abstract: We explore the role of information asymmetries and learning as a source of market fragmentation. In our model, the equilibrium market structure is driven by the interaction between information asymmetries and the differences in the trading needs of investors. Dealers open trading posts and investors choose in which trading post to trade. After the market structure is decided, trade takes place sequentially. First, in each trading post, each dealer and his investors trade strategically. Second, after trading with their investors, dealers have access to a competitive inter-dealer market. Dealers learn about the fundamental value of the asset by providing liquidity to investors. Then they use this information to decide how much inventory they carry to the inter-dealer market. Although the price is fully revealing in the inter-dealer market, dealers trade to share their inventory risk. If dealers are perfectly informed trade takes place in a unique centralized market. As the degree of information asymmetry between dealers and investors increases, trading moves from a centralized market to fragmented markets. This is more likely when investor's private valuations are less dispersed. The mechanism is as follows. When choosing how to trade investors weight the gains from trade from having more market participants against their market power. As prices become more informative dealers trade more aggressively which increases the investors' market power for a given market size. Moreover, if investors' valuations are highly correlated, investors value having market power more than trading in a bigger market. This gives rise to fragmented markets. The model also has implications for price dispersion and liquidity.
    Date: 2015
  5. By: Frédéric Abergel (FiQuant - Chaire de finance quantitative - Ecole Centrale Paris, MICS - Mathématiques et Informatique pour la Complexité et les Systèmes - CentraleSupélec); Aymen Jedidi (FiQuant - Chaire de finance quantitative - Ecole Centrale Paris)
    Abstract: Hawkes processes provide a natural framework to model dependencies between the intensities of point processes. In the context of order-driven financial markets, the relevance of such dependencies has been amply demonstrated from an empirical, as well as theoretical, standpoint. In this work, we build on previous empirical and numerical studies and introduce a mathematical model of limit order books based on Hawkes processes with exponential kernels. After proving a general stationarity result, we focus on the long-time behaviour of the limit order book and the corresponding dynamics of the suitably rescaled price. A formula for the asymptotic (in time) volatility of the price dynamics induced by that of the order book is obtained, involving the average of functions of the various order book events under the stationary distribution.
    Date: 2015–11–05
  6. By: Kiesel, Ruediger; Paraschiv, Florentina
    Abstract: The trading activity in the German intraday electricity market has increased significantly over the last years. This is partially due to an increasing share of renewable energy, wind and photovoltaic, which requires power generators to balance out the forecasting errors in their production. We investigate the bidding behavior in the intraday market by looking at both last prices and continuous bidding, in the context of a fundamental model. A unique data set of 15-minute intraday prices and intraday-updated forecasts of wind and photovoltaic has been employed and price bids are modelled by prior information on fundamentals. We show that intraday prices adjust asymmetrically to both forecasting errors in renewables and to the volume of trades dependent on the threshold variable demand quote, which reflects the expected demand covered by the planned traditional capacity in the day-ahead market. The location of the threshold can be used by market participants to adjust their bids accordingly, given the latest updates in the wind and photovoltaic forecasting errors and the forecasts of the control area balances.
    Keywords: Intraday Electricity Prices, Bidding Behavior, Renewable Energy, Forecasting Model
    Date: 2015–10
  7. By: Peter Hördahl; Eli M Remolona; Giorgio Valente
    Abstract: We investigate the movements of the yield curve after the release of major U.S. macroeconomic announcements through the lenses of an arbitrage-free dynamic term structure model with macroeconomic fundamentals. Combining estimated yield responses obtained using high-frequency data with model estimates using monthly data, we show that bond yields move after announcements mostly because of revisions to expectations about short-term interest rates. Changes in risk premia are also sizable, partly offset the effects of short-rate expectations and help to account for the hump-shaped pattern across maturities. Most announcement responses are due to changes in expectations about the output gap.
    Keywords: Bond excess returns, term structure of interest rates, affine models, macroeconomic announcements
    Date: 2015–11

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