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on Market Microstructure |
| By: | Carol Osler (International Business School, Brandeis University); Tanseli Savaser (Department of Economics, Williams College) |
| Abstract: | This paper investigates how active price-contingent trading contributes to extreme returns even in the absence of news. Price-contingent trading, which is common across financial markets, includes algorithmic trading, technical trading, and dynamic option hedging. The paper highlights four properties of such trading that increase the frequency of extreme returns, and then estimates the relative of these properties using data from the foreign exchange market. The four key properties we consider are: (1) high kurtosis in the distribution of order sizes; (2) clustering of trades within the day; (3) clustering of trades at certain prices; and (4) positive and negative feedback between trading and returns. Calibrated simulations indicate that interactions among these properties are at least as important as any single one. Among individual properties, the orders’ size distribution and feedback effects have the strongest influence. Price-contingent trading could account for over half of realized excess kurtosis in currency returns. |
| Keywords: | Crash, Fat Tails,Kurtosis,Exchange Rates,Order Flow,High-Frequency,Microstructure,Jump Process,Value-At-Risk,Risk Management |
| JEL: | G1 F3 |
| Date: | 2010–11 |
| URL: | http://d.repec.org/n?u=RePEc:brd:wpaper:4&r=mst |
| By: | Serge Darolles (CREST - Centre de Recherche en Économie et Statistique - INSEE - École Nationale de la Statistique et de l'Administration Économique); Gaëlle Le Fol (DRM - Dauphine Recherches en Management - CNRS : UMR7088 - Université Paris Dauphine - Paris IX); Gulten Mero (CREST - Centre de Recherche en Économie et Statistique - INSEE - École Nationale de la Statistique et de l'Administration Économique, CREM - Centre de Recherche en Economie et Management - CNRS : UMR6211 - Université de Rennes I - Université de Caen) |
| Abstract: | We develop a model of the daily return-volume relationship which incorporates information and liquidity shocks. First, we distinguish between two trading strategies, information-based and liquidity-based trading and suggest that their respective impacts on returns and volume should be modeled differently. Second, we integrate the microstructure setting of Grossman-Miller (1988) with the information flow perspective of Tauchen-Pitts (1983) and derive a modified MDH model with two latent factors related to information and liquidity. Our model explains how the liquidity frictions can increase the daily traded volume, in the presence of liquidity arbitragers. Finally, we propose a stock-specific liquidity measure using daily return and volume observations of FTSE100 stocks. |
| Keywords: | Volatility-volume relationship; mixture of distribution hypothesis; liquidity shocks; informed trading; liquidity arbitrage |
| Date: | 2010 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:halshs-00536046_v1&r=mst |
| By: | Naoki Makimoto (Professor, Graduate School of Business Sciences, University of Tsukuba (E-mail: makimoto@gssm.gsbs.tsukuba.ac.jp)); Yoshihiko Sugihara (Deputy Director and Economist, Institute for Monetary and Economic Studies, Bank of Japan (E-mail: yoshihiko.sugihara@boj.or.jp)) |
| Abstract: | In this paper, we develop a multiasset model of market liquidity and derive the optimal strategy for block order execution under both liquidity and volatility risk. The market liquidity flowing into and out of an order book is modeled as a mean-reverting stochastic process. Given the shape of the order book for each asset, we express the market impact of an execution as a recursive impact that recovers gradually with associated uncertainty. We then derive the optimal execution strategy as a closed-form solution to the mean-variance problem that optimizes the trade-off between the market impact and the volatility/liquidity risk given investor risk aversion. Using our model, we analyze some implications of the optimal execution strategy with comparative statics and simulations. We also discuss whether we avoid price manipulation with our optimal execution strategy. |
| Keywords: | optimal execution strategy, market impact, transaction cost, stochastic liquidity, limit order book, price manipulation, mean-variance optimization |
| JEL: | C61 G11 G12 |
| Date: | 2010–11 |
| URL: | http://d.repec.org/n?u=RePEc:ime:imedps:10-e-25&r=mst |
| By: | Carol Osler (International Business School, Brandeis University); Alexander Mende (Leibniz Universität); Lukas Menkhoff (Leibniz Universität) |
| Abstract: | This paper examines the price discovery process in currency markets, basing its analysis on the pivotal distinction between the customer (end-user) market and the interdealer market. It first provides evidence that the price discovery process cannot be based on adverse selection between dealers and end users, as postulated in standard equity-market models, because the spreads dealers quote to their customers are not positively related to a trade’s likely information content. The paper then highlights three hypotheses from the literature – fixed operating costs, market power, and strategic dealing – that may explain the cross-sectional variation in customers spreads. The paper finishes by proposing a price discovery process relevant to liquid two-tier markets and providing preliminary evidence that this process applies to currencies. |
| Keywords: | Bid-ask spreads, foreign exchange, asymmetric information, microstructure, price discovery, interdealer, inventory, market order, limit order |
| JEL: | F31 G14 G15 |
| Date: | 2010–06 |
| URL: | http://d.repec.org/n?u=RePEc:brd:wpaper:3&r=mst |