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on Market Microstructure |
| By: | John Cotter (University College Dublin) |
| Abstract: | Accurate volatility modelling is paramount for optimal risk management practices. One stylized feature of financial volatility that impacts the modelling process is long memory explored in this paper for alternative risk measures, observed absolute and squared returns for high frequency intraday UK futures. Volatility series for three different asset types, using stock index, interest rate and bond futures are analysed. Long memory is strongest for the bond contract. Long memory is always strongest for the absolute returns series and at a power transformation of k < 1. The long memory findings generally incorporate intraday periodicity. The APARCH model incorporating seven related GARCH processes generally models the futures series adequately documenting ARCH, GARCH and leverage effects. |
| Keywords: | Long Memory, APARCH, High Frequency Futures |
| Date: | 2011–05–30 |
| URL: | http://d.repec.org/n?u=RePEc:ucd:wpaper:200414&r=mst |
| By: | Katarzyna Bien (National Bank of Poland and Warsaw School of Economics) |
| Abstract: | This paper examines an intraday activity of bank trading of the EUR/PLN currency pair via the Reuters Dealing 3000 Spot Matching System in 2007. On the grounds of the sequential trade model of Easley, Engle, O’Hara & Wu (2008), we can differentiate between the time-varying patterns for the strategic behavior of informed and uninformed (liquidity) traders. We present evidence for the particular hour-of-day seasonality pattern that characterizes the arrival of uninformed and informed trades. The conditional arrival rates for both trader categories enable the assessment of their interactions and are used to forecast a time-varying probability of informed trading (PIN). The predictions of PIN are used to test the impact of information heterogeneity on the instantaneous liquidity of the market, which is proxied by the bid-ask spread and the market depth. |
| Keywords: | probability of informed trading, dynamic EKOP model, intraday liquidity modeling |
| JEL: | F31 G15 |
| Date: | 2011–05–30 |
| URL: | http://d.repec.org/n?u=RePEc:wse:wpaper:53&r=mst |
| By: | Markus Reiß |
| Abstract: | The basic model for high-frequency data in finance is considered, where an efficient price process is observed under microstructure noise. It is shown that this nonparametric model is in Le Cam's sense asymptotically equivalent to a Gaussian shift experiment in terms of the square root of the volatility function σ. As an application, simple rateoptimal estimators of the volatility and efficient estimators of the integrated volatility are constructed. |
| Keywords: | High-frequency data, integrated volatility, spot volatility estimation, Le Cam deficiency, equivalence of experiments, Gaussian shift |
| JEL: | C14 |
| Date: | 2011–05 |
| URL: | http://d.repec.org/n?u=RePEc:hum:wpaper:sfb649dp2011-028&r=mst |
| By: | Ferdinand Graf (Department of Economics, University of Konstanz, Germany) |
| Abstract: | I analyze company news from Reuters with the 'General Inquirer' and relate measures of positive sentiment, negative sentiment and disagreement to abnormal stock returns, stock and option trading volume, the volatility spread and the CDS spread. I test hypotheses derived from market microstructure models. Consistent with these models, sentiment and disagreement are strongly related to trading volume. Moreover, sentiment and disagreement might be used to predict stock returns, trading volume and volatility. Trading strategies based on positive and negative sentiment are profitable if the transaction costs are moderate, indicating that stock markets are not fully efficient. |
| Keywords: | Content Analysis, Company News, Market Microstructure |
| JEL: | G12 G14 |
| Date: | 2011–05–31 |
| URL: | http://d.repec.org/n?u=RePEc:knz:dpteco:1118&r=mst |
| By: | Andrea Monticini (Universita Cattolica - Milano); Francesco Ravazzolo (Norges Bank (Central Bank of Norway)) |
| Abstract: | Market efficiency hypothesis suggests a zero level for the intraday interest rate. However, a liquidity crisis introduces frictions related to news, which can cause an upward jump of the intraday rate. This paper documents that these dynamics can be partially predicted during turbulent times. A long memory approach outperforms random walk and autoregressive benchmarks in terms of point and density forecasting. The gains are particular high when the full distribution is predicted and probabilistic assessments of future movements of the interest rate derived by the model can be used as a policy tool for central banks to plan supplementary market operations during turbulent times. Adding exogenous variables to proxy funding liquidity and counterparty risks does not improve forecast accuracy and the predictability seems to derive from the econometric properties of the series more than from news available to financial markets in realtime. |
| Keywords: | Interbank market, Intraday interest rate, Forecasting, Density forecasting, Policy tools. |
| JEL: | C22 C53 E4 E5 |
| Date: | 2011–06–06 |
| URL: | http://d.repec.org/n?u=RePEc:bno:worpap:2011_06&r=mst |
| By: | Les Coleman (University of Melbourne); Adi Schnytzer (Bar-Ilan University) |
| Abstract: | This article uses trading data in the options market for shares in The Bear Sterns Companies (BSC) during the early stages of the US sub-prime crisis as a laboratory to examine the incidence of insider trading. We take the perspective of a regulator making use of hindsight to identify the most propitious periods for insider trades and to identify market activity indicative of insiders. Half the value of options traded were on 19 percent of the days, mostly in contracts in or close-to the money and near to expiry. We find persuasive evidence that insiders could have been active in trading Bear Sterns stock during this period. |
| Keywords: | insider trading, forensic finance, Bear Sterns |
| Date: | 2011–03 |
| URL: | http://d.repec.org/n?u=RePEc:biu:wpaper:2011-11&r=mst |