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on Market Microstructure |
| By: | Timotheos Angelidis; Alexandros Benos |
| Abstract: | We analyze the components of the bid-ask spread in the Athens Stock Exchange (ASE), which was recently characterized as a developed market. For large and medium capitalization stocks, we estimate the adverse selection and the order handling component of the spreads as well as the probability of a trade continuation on the same side of either the bid or the ask price, using the Madhavan et al.~(1997) model. We extend it by incorporating the traded volume and we find that the adverse selection component exhibits U-shape patterns, while the cost component pattern depends on the stock price. For high priced stocks, the usual U-shape applies, while for low-priced ones, it is an increasing function of time, mainly due to the order handling spread component. Furthermore, the expected price change and the liquidity adjustment to Value-at-Risk that is needed is higher in the low capitalization stocks, while the most liquid stocks are the high priced ones. Moreover, by estimating the Madhavan et al.~(1997) model for two distinct periods we explain why there are differences in the components of the bid-ask spread. |
| Keywords: | Bid-Ask Spread, Asymmetry Information, Transaction Costs, Price Impact |
| JEL: | D4 C1 |
| URL: | http://d.repec.org/n?u=RePEc:crt:wpaper:0615&r=mst |
| By: | Wing Lon Ng |
| Abstract: | This paper applies a non- and a semiparametric copula-based approach to analyze the first-order autocorrelation of returns in high frequency financial time series. Using the EUREX D3047 tick data from the German stock index, it can be shown that the temporal dependence structure of price movements is not always negatively correlated as assumed in the stylized facts in the finance literature. Depending on the sampling frequency, the estimated copulas exhibit some kind of overreaction phenomena and multiple tail dependence, revealing patterns similar to the compass rose. |
| Keywords: | High Frequency Data, Non- and Semiparametric Copulas, Overreaction, Tail Dependence, Compass Rose |
| JEL: | C14 C22 G14 |
| Date: | 2006–12 |
| URL: | http://d.repec.org/n?u=RePEc:hum:wpaper:sfb649dp2006-086&r=mst |
| By: | Hurvich, Cliiford; Wang, Yi |
| Abstract: | We propose a new transaction-level bivariate log-price model, which yields fractional or standard cointegration. To the best of our knowledge, all existing models for cointegration require the choice of a fixed sampling frequency Delta t. By contrast, our proposed model is constructed at the transaction level, thus determining the properties of returns at all sampling frequencies. The two ingredients of our model are a Long Memory Stochastic Duration process for the waiting times tau(k) between trades, and a pair of stationary noise processes ( e(k) and eta(k) ) which determine the jump sizes in the pure-jump log-price process. The e(k), assumed to be iid Gaussian, produce a Martingale component in log prices. We assume that the microstructure noise eta(k) obeys a certain model with memory parameter d(eta) in (-1/2,0) (fractional cointegration case) or d(eta) = -1 (standard cointegration case). Our log-price model includes feedback between the shocks of the two series. This feedback yields cointegration, in that there exists a linear combination of the two components that reduces the memory parameter from 1 to 1+d(eta) in (0.5,1) and (0). Returns at sampling frequency Delta t are asymptotically uncorrelated at any fixed lag as Delta t increases. We prove that the cointegrating parameter can be consistently estimated by the ordinary least-squares estimator, and obtain a lower bound on the rate of convergence. We propose transaction-level method-of-moments estimators of several of the other parameters in our model. We present a data analysis, which provides evidence of fractional cointegration. We then consider special cases and generalizations of our model, mostly in simulation studies, to argue that the suitably-modified model is able to capture a variety of additional properties and stylized facts, including leverage, portfolio return autocorrelation due to nonsynchronous trading, Granger causality, and volatility feedback. The ability of the model to capture these effects stems in most cases from the fact that the model treats the (stochastic) intertrade durations in a fully endogenous way. |
| Keywords: | Tick Time; Long Memory Stochastic Duration; Information Share; Granger causality. |
| JEL: | C00 C01 |
| Date: | 2006–12–04 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:1413&r=mst |
| By: | Olli Castrén (European Central Bank, Kaiserstrasse 29, 60311 Frankfurt am Main, Germany.); Chiara Osbat (European Central Bank, Kaiserstrasse 29, 60311 Frankfurt am Main, Germany.); Matthias Sydow (European Central Bank, Kaiserstrasse 29, 60311 Frankfurt am Main, Germany.) |
| Abstract: | We apply the Campbell-Shiller return decomposition to exchange rate returns and fundamentals in a stationary panel vector autoregression framework. The return decomposition is then used to analyse how different investor segments react to news as captured by the different return components. The results suggest that intrinsic value news are dominating for equity investors and speculative money market investors while investors in currency option markets react strongly to expected return news. The equity and speculative money market investors seem able to distinguish between transitory and permanent FX movements while options investors mainly focus on transitory movements. We also find evidence that offsetting impact on the various return components can blur the effect of macroeconomic data releases on aggregate FX excess returns. JEL Classification: C23, F31, F32, G15. |
| Keywords: | FX return prediction, investor flows, news surprises, panel estimation, stationary VAR. |
| Date: | 2006–12 |
| URL: | http://d.repec.org/n?u=RePEc:ecb:ecbwps:20060706&r=mst |