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on Market Microstructure |
| By: | John Cotter (University College Dublin) |
| Abstract: | Key to the imposition of appropriate minimum capital requirements on a daily basis requires accurate volatility estimation. Here, measures are presented based on discrete estimation of aggregated high frequency UK futures realisations underpinned by a continuous time framework. Squared and absolute returns are incorporated into the measurement process so as to rely on the quadratic variation of a diffusion process and be robust in the presence of fat tails. The realized volatility estimates incorporate the long memory property. The dynamics of the volatility variable are adequately captured. Resulting rescaled returns are applied to minimum capital requirement calculations. |
| Date: | 2011–07–21 |
| URL: | http://d.repec.org/n?u=RePEc:ucd:wpaper:200418&r=mst |
| By: | Guglielmo Maria Caporale; Alessandro Girardi |
| Abstract: | This paper proposes new metrics for the process of price discovery on the main electronic trading platform for euro?denominated government securities. Analysing price data on daily transactions for 107 bonds over a period of twenty?seven months, we find a greater degree of price leadership of the dominant market when our measures (as opposed to the traditional price discovery metrics) are used. We also present unambiguous evidence that a market's contribution to price discovery is crucially affected by the level of trading activity. The implications of these empirical findings are discussed in the light of the debate about the possible restructuring of the regulatory framework for the Treasury bond market in Europe. |
| Keywords: | Price discovery, liquidity, MTS system |
| JEL: | G10 C21 C32 |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:diw:diwwpp:dp1139&r=mst |
| By: | Zoltan Eisler; Jean-Philippe Bouchaud; Julien Kockelkoren |
| Abstract: | We propose a general framework to describe the impact of different events in the order book, that generalizes previous work on the impact of market orders. Two different modeling routes can be considered, which are equivalent when only market orders are taken into account. One model posits that each event type has a temporary impact (TIM). The "history dependent impact" model (HDIM), on the other hand, assumes that only price-changing events have a direct impact, itself modulated by the past history of all events through an "influence matrix" that measures how much, on average, an event of a given type affects the immediate impact of a price-changing event of the same sign in the future. We find in particular that aggressive market orders tend to reduce the impact of further aggressive market orders of the same sign (and increase the impact of aggressive market orders of opposite sign). We discuss the relative merits of TIM and HDIM, in particular concerning their ability to reproduce accurately the price diffusion pattern. We find that in spite of theoretical inconsistencies, TIM appears to fare better than HDIM when compared to empirical data. We ascribe this paradox to an uncontrolled approximation used to calibrate HDIMs, calling for further work on this issue. |
| Date: | 2011–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1107.3364&r=mst |
| By: | Michele Tumminello; Fabrizio Lillo; Jyrki Piilo; Rosario N. Mantegna |
| Abstract: | We use statistically validated networks, a recently introduced method to validate links in a bipartite system, to identify clusters of investors trading in a financial market. Specifically, we investigate a special database allowing to track the trading activity of individual investors of the stock Nokia. We find that many statistically detected clusters of investors show a very high degree of synchronization in the time when they decide to trade and in the trading action taken. We investigate the composition of these clusters and we find that several of them show an over-expression of specific categories of investors. |
| Date: | 2011–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1107.3942&r=mst |