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on Market Microstructure |
| By: | Moinas, Sophie |
| Abstract: | This paper analyzes the rationale for the submission of hidden limit orders, and compares opaque and transparent limit order books. In my sequential model, the limit order trader may be informed with some probability. Both informed and large uninformed liquidity suppliers submit hidden orders in order to decrease the informational impact of their large orders, while ensuring a large trading volume. As they cannot adopt such a strategy in the transparent market, I find that pre-trade opacity improves market liquidity, and the welfare of the participants. My model further yields empirical predictions on the use and revelation of hidden orders in opaque markets. |
| JEL: | G10 G14 G18 |
| Date: | 2010–03 |
| URL: | http://d.repec.org/n?u=RePEc:ide:wpaper:22438&r=mst |
| By: | Moinas, Sophie |
| Abstract: | This paper analyzes the rationale for the submission of hidden limit orders, and compares opaque and transparent limit order books. In my sequential model, the limit order trader may be informed with some probability. Both informed and large uninformed liquidity suppliers submit hidden orders in order to decrease the informational impact of their large orders, while ensuring a large trading volume. As they cannot adopt such a strategy in the transparent market, I find that pre-trade opacity improves market liquidity, and the welfare of the participants. My model further yields empirical predictions on the use and revelation of hidden orders in opaque markets. |
| JEL: | G10 G14 G18 |
| Date: | 2010–03 |
| URL: | http://d.repec.org/n?u=RePEc:tse:wpaper:22439&r=mst |
| By: | Bertrand B. Maillet (ABN AMRO Advisors, Variances and University of Paris-1 (CES/CNRS and EIF)); Jean-Philippe R. Médecin (Paris School of Economics, University of Paris-1 and Variances) |
| Abstract: | Following Bali and Weinbaum (2005) and Maillet et al. (2010), we present several estimates of volatilities computed with high- and low frequency data and complement their results using additional measures of risk and several alternative methods for Tail-index estimation. The aim here is to confirm previous results regarding the slope of the tail of various risk measure distributions, in order to define the high watermarks of market risks. We also produce synthetic general results concerning the method of estimation of the Tail-indexes related to expressions of the L-moments. Based on estimates of Tail-indexes, retrieved from the high frequency 30’ sampled CAC40 French stock Index series from the period 1997-2009, using Non-parametric Generalized Hill, Maximum Likelihood and various kinds of L-moment Methods for the estimation of both a Generalized Extreme Value density and a Generalized Pareto Distribution, we confirm that a heavy-tail density specification of the Log-volatility is not necessary. |
| Keywords: | Financial Crisis, Realized Volatility, Range-based Volatility, Extreme Value Distributions, Tail-index, L-moments, High Frequency Data. |
| JEL: | G10 G14 |
| URL: | http://d.repec.org/n?u=RePEc:ven:wpaper:2010_10&r=mst |
| By: | Xinghua Zheng; Yingying Li |
| Abstract: | We consider the estimation of integrated covariance matrices of high dimensional diffusion processes by using high frequency data. We start by studying the most commonly used estimator, the realized covariance matrix (RCV). We show that in the high dimensional case when the dimension p and the observation frequency n grow in the same rate, the limiting empirical spectral distribution of RCV depends on the covolatility processes not only through the underlying integrated covariance matrix Sigma, but also on how the covolatility processes vary in time. In particular, for two high dimensional diffusion processes with the same integrated covariance matrix, the empirical spectral distributions of their RCVs can be very different. Hence in terms of making inference about the spectrum of the integrated covariance matrix, the RCV is in general \emph{not} a good proxy to rely on in the high dimensional case. We then propose an alternative estimator, the time-variation adjusted realized covariance matrix (TVARCV), for a class of diffusion processes. We show that the limiting empirical spectral distribution of our proposed estimator TVARCV does depend solely on that of Sigma through a Marcenko-Pastur equation, and hence the TVARCV can be used to recover the empirical spectral distribution of Sigma by inverting the Marcenko-Pastur equation, which can then be applied to further applications such as portfolio allocation, risk management, etc.. |
| Date: | 2010–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1005.1862&r=mst |
| By: | Su, Yongyang |
| Abstract: | This paper analyzes the impact of changes in the securities transaction tax (STT) rate on the local A-shares market in China. We find that, on average, a 22-base-point- increase in the STT rate is associated with about a 28% drop in trading volume, while a 17-base-point- reduction in the STT rate is associated with about a 89% increase in trading volume in the Chinese A-shares market. Both the increases and reductions in the STT rate result in a significant increase in the market return volatility. Besides, the increases in the STT rate have mixed effects on market efficiency, either improving or curbing it. The reductions usually either make the market less efficient or have not effect on it. The empirical results together show that levying the STT on trading is not an effective tool to regulate stock market, at least in this emerging market. |
| Keywords: | Securities transaction taxes; stock market;volatility; trading volume |
| JEL: | G10 |
| Date: | 2010 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:22695&r=mst |