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on Market Microstructure |
| By: | Rama Cont; Adrien De Larrard |
| Abstract: | We propose and study a simple stochastic model for the dynamics of a limit order book, in which arrivals of market order, limit orders and order cancellations are described in terms of a Markovian queueing system. Through its analytical tractability, the model allows to obtain analytical expressions for various quantities of interest such as the distribution of the duration between price changes, the distribution and autocorrelation of price changes, and the probability of an upward move in the price, {\it conditional} on the state of the order book. We study the diffusion limit of the price process and express the volatility of price changes in terms of parameters describing the arrival rates of buy and sell orders and cancelations. These analytical results provide some insight into the relation between order flow and price dynamics in order-driven markets. |
| Date: | 2011–04 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1104.4596&r=mst |
| By: | Nobuhiro Hosoe (National Graduate Institute for Policy Studies); Shingo Takagi (Graduate School of Economics and Business Administration, Hokkaido University) |
| Abstract: | Deregulation in the electric power industry has been aimed at promoting competition and thereby enhancing the industry's efficiency. We use the auction data of public power procurements to study the impact of the reform on the retail power market in Japan. We quantify this impact by measuring a decline in power charges, controlling for the endogeneity bias caused by the entrants' bid-submission decisions. Our results suggest that power charges would decline by about 0.48 yen/kWh on average when two or more providers bid at an auction. |
| Keywords: | electric power industry, auction data, public procurement, sample selection bias |
| Date: | 2011–04 |
| URL: | http://d.repec.org/n?u=RePEc:ngi:dpaper:11-01&r=mst |
| By: | Olesia Verchenko (Kyiv School of Economics, Kyiv Economic Institute) |
| Abstract: | This paper examines the empirical performance of several complete and incomplete market models of stock price dynamics using S&P 500 options and stock market data. The main contribution of this work is that it suggests and implements an empirical approach to estimating a complete model with uncertain volatility, and then judges it against other popular option pricing processes. The performance of alternative models is evaluated from four perspectives: (1) in-sample fit to stock returns data, (2) in-sample fit to options data, (3) consistency of physical and risk-neutral parameter estimates and (4) out-of-sample option pricing. Overall, the complete model with uncertain volatility is found to .t the data much better than models with constant and price-level-dependent volatilities, and the variance gamma process, and its performance is comparable to that of a stochastic volatility model. |
| Keywords: | Option pricing, complete and incomplete markets, stochastic volatility |
| JEL: | G13 |
| Date: | 2011–04 |
| URL: | http://d.repec.org/n?u=RePEc:kse:dpaper:38&r=mst |