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on Market Microstructure |
| By: | Brogaard, Jonathan; Hendershott, Terrence; Riordan, Ryan |
| Abstract: | We examine empirically the role of high-frequency traders (HFTs) in price discovery and price efficiency. Based on our methodology, we find overall that HFTs facilitate price efficiency by trading in the direction of permanent price changes and in the opposite direction of transitory pricing errors, both on average and on the highest volatility days. This is done through their liquidity demanding orders. In contrast, HFTs’ liquidity supplying orders are adversely selected. The direction of buying and selling by HFTs predicts price changes over short horizons measured in seconds. The direction of HFTs’ trading is correlated with public information, such as macro news announcements, market-wide price movements, and limit order book imbalances. JEL Classification: G12 |
| Keywords: | high frequency trading, price discovery, price formation, pricing errors |
| Date: | 2013–11 |
| URL: | http://d.repec.org/n?u=RePEc:ecb:ecbwps:20131602&r=mst |
| By: | Ulrich Hounyo (Oxford-Man Institute of Quantitative Finance and CREATES) |
| Abstract: | The main contribution of this paper is to propose a new bootstrap method for statistics based on high frequency returns. The new method exploits the local Gaussianity and the local constancy of volatility of high frequency returns, two assumptions that can simplify inference in the high frequency context, as recently explained by Mykland and Zhang (2009). Our main contributions are as follows. First, we show that the local Gaussian bootstrap is firstorder consistent when used to estimate the distributions of realized volatility and ealized betas. Second, we show that the local Gaussian bootstrap matches accurately the first four cumulants of realized volatility, implying that this method provides third-order refinements. This is in contrast with the wild bootstrap of Gonçalves and Meddahi (2009), which is only second-order correct. Third, we show that the local Gaussian bootstrap is able to provide second-order refinements for the realized beta, which is also an improvement of the existing bootstrap results in Dovonon, Gonçalves and Meddahi (2013) (where the pairs bootstrap was shown not to be second-order correct under general stochastic volatility). Lastly, we provide Monte Carlo simulations and use empirical data to compare the finite sample accuracy of our new bootstrap confidence intervals for integrated volatility and integrated beta with the existing results. |
| Keywords: | High frequency data, realized volatility, realized beta, bootstrap, Edgeworth expansions |
| JEL: | C15 C22 C58 |
| Date: | 2013–09–16 |
| URL: | http://d.repec.org/n?u=RePEc:aah:create:2013-30&r=mst |
| By: | Ginglinger, Edith; Koenig-Matsoukis, Laure; Riva, Fabrice |
| Abstract: | This paper examines the impact of market liquidity on seasoned equity offerings (SEO) characteristics in France. We find that, besides blockholders’ takeup, liquidity is an important determinant of SEO flotation method choice. We document higher direct equity offering flotation costs, but also improved stock market liquidity after public offerings and standby rights relative to uninsured rights. After controlling for endogeneity in the choice of SEO flotation method, we find that pure public offerings and standby rights are comparable in terms of direct costs and liquidity improvement. Our results provide new insights as to why firms choose public offerings despite apparently higher costs. |
| Keywords: | SEO; Seasoned equity offering; flotation method; flotation costs; rights issues; public offerings; liquidity; bid-ask spread; |
| JEL: | G34 G32 |
| Date: | 2013 |
| URL: | http://d.repec.org/n?u=RePEc:dau:papers:123456789/10852&r=mst |
| By: | Simon Hagemann |
| Abstract: | This paper presents a first investigation of hourly price determinants in the German intraday market for electricity. The influence of power plant outages, forecast errors of wind and solar power production, load forecast errors and foreign demand and supply on intraday prices are explained from a theoretical perspective. Furthermore the influences of the non-linear merit-order shape, ramping costs and strategic market behavior are discussed. The empirical results from different regression analysis with data from 2010 and 2011 show that most price determinants increase and decrease intraday prices as expected. Nevertheless, only a minor share of power plant outages and solar power forecast errors are traded on the electronic intraday trading platform, thus influencing prices not as strongly as expected. Furthermore the price determinants influence intraday prices differently over the course of the day which may be explained by an alternating liquidity provision. |
| Keywords: | Intraday market for electricity, price modeling, price determinants |
| Date: | 2013–10 |
| URL: | http://d.repec.org/n?u=RePEc:dui:wpaper:1318&r=mst |