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on Market Microstructure |
| By: | Bruno Biais; Pierre-Olivier Weill |
| Abstract: | We propose a dynamic competitive equilibrium model of limit order trading, based on the premise that investors cannot monitor markets continuously. We study how limit order markets absorb transient liquidity shocks, which occur when a significant fraction of investors lose their willingness and ability to hold assets. We characterize the equilibrium dynamics of market prices, bid-ask spreads, order submissions and cancelations, as well as the volume and limit order book depth they generate. |
| JEL: | G12 |
| Date: | 2009–05 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:15009&r=mst |
| By: | Yuko Hashimoto; Takatoshi Ito |
| Abstract: | Market impacts of Japanese macroeconomic announcements within minutes on the dollar/yen foreign exchange are analyzed. High-frequency data collected from the actual trading platform, EBS, are used. First, impacts on returns are analyzed. Macroeconomic statistics releases that consistently had significant effects on exchange rate returns include Tankan survey (a short-term business survey conducted by Bank of Japan), GDP, industrial production (preliminary), PPI, CPI (Tokyo area), the unemployment rate and Balance of Payment statistics. Macroeconomic statistics releases that did not have impacts on returns include Trade Balance, Retail Sales and Housing start indicators. Second, for most of macroeconomic news items whose surprise components have return impacts also have impacts on deals and volatility. The announcement itself, in addition to the magnitude of surprise, is found to increase the deals and price volatility in the immediately after the announcement. In addition, some other items have no return impacts but deals and volatility impacts. These facts are consistent with a view that market participants have heterogeneous information, so that even without any price change, trades take place. Price discovery process may require some transactions with price fluctuations around new price level consistent with statistical announcement |
| JEL: | E44 F31 F41 G15 |
| Date: | 2009–05 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:15020&r=mst |
| By: | Julien Chevallier (EconomiX - CNRS : UMR7166 - Université de Paris X - Nanterre); Benoît Sévi (GRANEM LEMNA - Université d'Angers - Université de Nantes) |
| Abstract: | The recent implementation of the EU Emissions Trading Scheme (EU ETS) in January 2005 created new financial risks for emitting firms. To deal with these risks, options are traded since October 2006. Because the EU ETS is a new market, the relevant underlying model for option pricing is still a controversial issue. This article improves our understanding of this issue by characterizing the conditional and unconditional distributions of the realized volatility for the 2008 futures contract in the European Climate Exchange (ECX), which is valid during Phase II (2008-2012) of the EU ETS. The realized volatility measures from naive, kernel-based and subsampling estimators are used to obtain inferences about the distributional and dynamic properties of the ECX emissions futures volatility. The distribution of the daily realized volatility in logarithmic form is shown to be close to normal. The mixture-of-distributions hypothesis is strongly rejected, as the returns standardized using daily measures of volatility clearly departs from normality. A simplified HAR-RV model (Corsi, 2009) with only a weekly component, which reproduces long memory properties of the series, is then used to model the volatility dynamics. Finally, the predictive accuracy of the HAR-RV model is tested against GARCH specifications using one-step-ahead forecasts, which confirms the HAR-RV superior ability. Our conclusions indicate that (i) the standard Brownian motion is not an adequate tool for option pricing in the EU ETS, and (ii) a jump component should be included in the stochastic process to price options, thus providing more efficient tools for risk-management activities. |
| Keywords: | CO2 Price; Realized Volatility; HAR-RV; GARCH; Futures Trading; Emissions Markets; EU ETS; Intraday data; Forecasting |
| Date: | 2009–05–25 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:halshs-00387286_v1&r=mst |