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on Market Microstructure |
| By: | Fabio C. Bagliano (Department of Economics and Public Finance "G. Prato", University of Torino); Carlo A. Favero (Innocenzo Gasparini Institute for Economic Research, Bocconi University); Giovanna Nicodano (Department of Economics and Public Finance "G. Prato", University of Torino) |
| Abstract: | Several models predict that both market liquidity and trading volume generated by less informed traders do not increase when there is insider trading. Available empirical evidence is mixed and still relatively small, because of the inherent di¢ culty to identify insider trading events. Our econometric work, based on 19 suspect insider trading events drawn from the non-public ?file of the Italian supervisory authority, provides further insight on these key implications of stock market models. The second purpose of this paper is to assess whether insider trading changes the distribution of volume and returns in a way that can be used by supervisory authorities in order to detect its presence through statistical methods. |
| Keywords: | asymmetric information, insider trading, abnormal returns, traded volume |
| JEL: | G14 G18 |
| Date: | 2011–10 |
| URL: | http://d.repec.org/n?u=RePEc:tur:wpaper:26&r=mst |
| By: | Paolo Guasoni; Johannes Muhle-Karbe |
| Abstract: | For an investor with constant absolute risk aversion and a long horizon, who trades in a market with constant investment opportunities and small proportional transaction costs, we obtain explicitly the optimal investment policy, its implied welfare, liquidity premium, and trading volume. We identify these quantities as the limits of their isoelastic counterparts for high levels of risk aversion. The results are robust with respect to finite horizons, and extend to multiple uncorrelated risky assets. In this setting, we study a Stackelberg equilibrium, led by a risk-neutral, monopolistic market maker who sets the spread as to maximize profits. The resulting endogenous spread depends on investment opportunities only, and is of the order of a few percentage points for realistic parameter values. |
| Date: | 2011–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1110.1214&r=mst |
| By: | Kentaro Iwatsubo (Graduate School of Economics, Kobe University); Ian W. Marsh (Cass Business School) |
| Abstract: | We examine the links between end-user order flows as seen by a major European commercial bank and macroeconomic fundamentals. We show that both exchange rate changes and flows are only weakly related to macroeconomic news announcements and hypothesise that gthe cat is already out of the bagh by the time the news is announced. Instead, order flows of financial and corporate customers reflect in real time the evolution of macroeconomies. The actions of the banks receiving the order flows in turn reveal the information to the market as a whole which prices the exchange rate accordingly. By the time the news is announced, the exchange rate already contains the majority of the information. |
| Keywords: | Order flows, Fundamentals, Exchange rates, News, Microstructure |
| JEL: | F31 |
| Date: | 2011–09 |
| URL: | http://d.repec.org/n?u=RePEc:koe:wpaper:1120&r=mst |
| By: | Junjie Wang; Shuigeng Zhou; Jihong Guan |
| Abstract: | In financial markets, abnormal trading behaviors pose a serious challenge to market surveillance and risk management. What is worse, there is an increasing emergence of abnormal trading events that some experienced traders constitute a collusive clique and collaborate to manipulate some instruments, thus mislead other investors by applying similar trading behaviors for maximizing their personal benefits. In this paper, a method is proposed to detect the hidden collusive cliques involved in an instrument of future markets by first calculating the correlation coefficient between any two eligible unified aggregated time series of signed order volume, and then combining the connected components from multiple sparsified weighted graphs constructed by using the correlation matrices where each correlation coefficient is over a user-specified threshold. Experiments conducted on real order data from the Shanghai Futures Exchange show that the proposed method can effectively detect suspect collusive cliques. A tool based on the proposed method has been deployed in the exchange as a pilot application for futures market surveillance and risk management. |
| Date: | 2011–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1110.1522&r=mst |
| By: | Laurent Schoeffel (CEA-Saclay) |
| Abstract: | The probability distribution of log-returns of financial time series, sampled at high frequency, is the basis for any further developments in quantitative finance. In this letter, we present experimental results based on a large set of time series on futures. Then, we show that the t-distribution with $\nu \simeq 3$ gives a nice description of almost all data series. This appears to be a quite general result that stays robust on a large set of any financial data as well as on a wide range of sampling frequency of these data, below one hour. |
| Date: | 2011–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1110.1006&r=mst |