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on Market Microstructure |
| By: | Dobrislav Dobrev; Pawel Szerszen |
| Abstract: | We demonstrate that the parameters controlling skewness and kurtosis in popular equity return models estimated at daily frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information content of realized volatility measures extracted from high-frequency data. For this purpose, we introduce asymptotically exact volatility measurement equations in state space form and propose a Bayesian estimation approach. Our highly efficient estimates lead in turn to substantial gains for forecasting various risk measures at horizons ranging from a few days to a few months ahead when taking also into account parameter uncertainty. As a practical rule of thumb, we find that two years of high frequency data often suffice to obtain the same level of precision as twenty years of daily data, thereby making our approach particularly useful in finance applications where only short data samples are available or economically meaningful to use. Moreover, we find that compared to model inference without high-frequency data, our approach largely eliminates underestimation of risk during bad times or overestimation of risk during good times. We assess the attainable improvements in VaR forecast accuracy on simulated data and provide an empirical illustration on stock returns during the financial crisis of 2007-2008. |
| Date: | 2010 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedgif:1005&r=mst |
| By: | K. Al Dayri; E. Bacry; J. F. Muzy |
| Abstract: | By studying all the trades and best bids/asks of ultra high frequency snapshots recorded from the order books of a basket of 10 futures assets, we bring qualitative empirical evidence that the impact of a single trade depends on the intertrade time lags. We find that when the trading rate becomes faster, the return variance per trade or the impact, as measured by the price variation in the direction of the trade, strongly increases. We provide evidence that these properties persist at coarser time scales. We also show that the spread value is an increasing function of the activity. This suggests that order books are more likely empty when the trading rate is high. |
| Date: | 2010–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1010.4226&r=mst |
| By: | Alessandro Beber (University of Amsterdam); Marco Pagano (Universita di Napoli Federico II, CSEF, EIEF and CEPR) |
| Abstract: | Most stock exchange regulators around the world reacted to the 2007-2009 crisis by imposing bans or regulatory constraints on short-selling. Short-selling restrictions were imposed and lifted at different dates in different countries, often applied to different sets of stocks and featured different degrees of stringency. We exploit this considerable variation in short-sales regimes to identify their effects with panel data techniques, and find that bans (i) were detrimental for liquidity, especially for stocks with small market capitalization, high volatility and no listed options; (ii) slowed down price discovery, especially in bear market phases, and (iii) failed to support stock prices, except possibly for U.S. financial stocks. |
| Keywords: | short selling; ban; crisis; liquidity; price discovery |
| JEL: | G12 G14 G18 |
| Date: | 2010–10–19 |
| URL: | http://d.repec.org/n?u=RePEc:dgr:uvatin:20100106&r=mst |