New Economics Papers
on Market Microstructure
Issue of 2009‒11‒27
six papers chosen by
Thanos Verousis

  1. Liquidity cycles and make/take fees in electronic markets By Foucault, Thierry; Kadan, Ohad; Kandel, Eugene
  2. Jump-Robust Volatility Estimation using Nearest Neighbor Truncation By Torben G. Andersen; Dobrislav Dobrev; Ernst Schaumburg
  3. Short-Selling Bans around the World: Evidence from the 2007-09 Crisis By Beber, Alessandro; Pagano, Marco
  4. "Forecasting Realized Volatility with Linear and Nonlinear Models" By Michael McAleer; Marcelo C. Medeiros
  5. Optimal Clearing Arrangements for Financial Trades By Thorsten Koeppl; Cyril Monnet; Ted Temzelides
  6. Dynamic Trading with Predictable Returns and Transaction Costs By Garleanu, Nicolae Bogdan; Pedersen, Lasse Heje

  1. By: Foucault, Thierry; Kadan, Ohad; Kandel, Eugene
    Abstract: We develop a dynamic model of a market with two specialized sides: traders posting quotes ("market makers") and traders hitting quotes ("market takers"). Traders monitor the market to seize profit opportunities, generating high frequency liquidity cycles. Monitoring decisions by market-makers and market-takers are self-reinforcing, generating multiple equilibria with differing liquidity levels and duration clustering. The trading rate is typically maximized when makers and takers are charged different fees or even paid rebates. The model yields several empirical implications regarding the determinants of make/take fees, the trading rate, the bid-ask spread, and the effects of algorithmic trading on liquidity and welfare.
    Keywords: algorithmic trading; duration clustering; Liquidity; make/take fees; monitoring; two-sided markets
    JEL: G12 G20 L14
    Date: 2009–11
  2. By: Torben G. Andersen; Dobrislav Dobrev; Ernst Schaumburg
    Abstract: We propose two new jump-robust estimators of integrated variance based on high-frequency return observations. These MinRV and MedRV estimators provide an attractive alternative to the prevailing bipower and multipower variation measures. Specifically, the MedRV estimator has better theoretical efficiency properties than the tripower variation measure and displays better finite-sample robustness to both jumps and the occurrence of "zero'' returns in the sample. Unlike the bipower variation measure, the new estimators allow for the development of an asymptotic limit theory in the presence of jumps. Finally, they retain the local nature associated with the low order multipower variation measures. This proves essential for alleviating finite sample biases arising from the pronounced intraday volatility pattern which afflict alternative jump-robust estimators based on longer blocks of returns. An empirical investigation of the Dow Jones 30 stocks and an extensive simulation study corroborate the robustness and efficiency properties of the new estimators.
    JEL: C14 C15 C22 C80 G10
    Date: 2009–11
  3. By: Beber, Alessandro; Pagano, Marco
    Abstract: Most stock exchange regulators around the world reacted to the financial crisis of 2007-2009 by imposing bans or regulatory constraints on short-selling by market participants. We use the large amount of evidence generated by these regime changes to investigate their effects on liquidity, price discovery and stock returns. Since bans were enacted and lifted at different dates in different countries, and in some countries applied to financial stocks only, we identify their effects with panel data techniques, and find that bans (i) were detrimental for liquidity, especially for stocks with small market capitalization and high volatility; (ii) slowed down price discovery, especially in bear market phases, and (iii) failed to support stock prices.
    Keywords: ban; crisis; liquidity; price discovery; short selling
    JEL: G12 G14 G18
    Date: 2009–11
  4. By: Michael McAleer (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute and Center for International Research on the Japanese Economy (CIRJE), Faculty of Economics, University of Tokyo); Marcelo C. Medeiros (Department of Economics, Pontifical Catholic University of Rio de Janeiro)
    Abstract: In this paper we consider a nonlinear model based on neural networks as well as linear models to forecast the daily volatility of the S&P 500 and FTSE 100 indexes. As a proxy for daily volatility, we consider a consistent and unbiased estimator of the integrated volatility that is computed from high frequency intra-day returns. We also consider a simple algorithm based on bagging (bootstrap aggregation) in order to specify the models analyzed in the paper.
    Date: 2009–10
  5. By: Thorsten Koeppl (Queen's University); Cyril Monnet (Federal Reserve Bank of Philadelphia); Ted Temzelides (Rice University)
    Abstract: Clearinghouses support financial trades by keeping records of transactions and by providing liquidity through short-term credit that is periodically cleared by participants. We study efficient clearing arrangements for formal exchanges, where traders must clear with a clearinghouse, and for over-the-counter (OTC) markets, where trades can be cleared bilaterally. When clearing is costly, we show that it can be efficient to subsidize the clearing process for OTC transactions by charging a higher price for the clearing of transactions in exchanges. This necessitates a clearinghouse that operates across both markets. As a clearinghouse offers credit, intertemporal incentives are needed in order to ensure settlement. An increase in the costs of liquidity provision worsens the incentives to settle. Hence, when liquidity costs increase, concerns about default must lead to a tightening of liquidity provision.
    Keywords: Clearing, OTC vs Exchanges, Private Information, Liquidity Costs, Default
    JEL: G14 G23 E42
    Date: 2009–11
  6. By: Garleanu, Nicolae Bogdan; Pedersen, Lasse Heje
    Abstract: This paper derives in closed form the optimal dynamic portfolio policy when trading is costly and security returns are predictable by signals with different mean-reversion speeds. The optimal updated portfolio is a linear combination of the existing portfolio, the optimal portfolio absent trading costs, and the optimal portfolio based on future expected returns and transaction costs. Predictors with slower mean reversion (alpha decay) get more weight since they lead to a favorable positioning both now and in the future. We implement the optimal policy for commodity futures and show that the resulting portfolio has superior returns net of trading costs relative to more naive benchmarks. Finally, we derive natural equilibrium implications, including that demand shocks with faster mean reversion command a higher return premium.
    Keywords: dynamic trading; portfolio choice; predictability; transaction costs
    JEL: G11 G12
    Date: 2009–08

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