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on Market Microstructure |
| By: | Roxana Halbleib (European Center for Advanced Research in Economics and Statistics (ECARES), Université libre de Bruxelles, Solvay Brussels School of Economics and Management and CoFE); Valeri Voev (School of Economics and Management, Aarhus University and CREATES) |
| Abstract: | This paper proposes a new method for forecasting covariance matrices of financial returns. The model mixes volatility forecasts from a dynamic model of daily realized volatilities estimated with high-frequency data with correlation forecasts based on daily data. This new approach allows for flexible dependence patterns for volatilities and correlations, and can be applied to covariance matrices of large dimensions. The separate modeling of volatility and correlation forecasts considerably reduces the estimation and measurement error implied by the joint estimation and modeling of covariance matrix dynamics. Our empirical results show that the new mixing approach provides superior forecasts compared to multivariate volatility specifications using single sources of information. |
| Keywords: | Volatility forecasting, High-frequency data, Realized variance |
| JEL: | C32 C53 G11 |
| Date: | 2011–01–18 |
| URL: | http://d.repec.org/n?u=RePEc:aah:create:2011-03&r=mst |
| By: | Roxana Halbleib; Valerie Voev |
| Abstract: | This paper proposes a new method for forecasting covariance matrices of financial returns. the model mixes volatility forecasts from a dynamic model of daily realized volatilities estimated with high-frequency data with correlation forecasts based on daily data. This new approach allows for flexible dependence patterns for volatilities and correlations, and can be applied to covariance matrices of large dimensions. The seperate modeling of volatility and correlation forecasts considerably reduces the estimation and measurement error implied by the joint estimation and modeling of covariance matrix dynamics. Our empirical results show that the new mixing approach provides superior forecasts compared to multivariate volatility specifications using single sources of information. |
| Date: | 2011–01 |
| URL: | http://d.repec.org/n?u=RePEc:eca:wpaper:2013/73640&r=mst |
| By: | Laib, Fodil; Radjef, MS |
| Abstract: | This is an introductory work to trade automatization of the futures market, so far operated by human traders. We are not focusing on maximizing individual profits of any trader as done in many studies, but rather we try to build a stable electronic trading system allowing to obtain a fair price, based on supply and demand dynamics, in order to avoid speculative bubbles and crashes. In our setup, producers and consumers release regularly their forecasts of output and consumption respectively. Automated traders will use this information to negotiate price of the underlying commodity. We suggested a set of analytical criteria allowing to measure the efficiency of the automatic trading strategy in respect to market stability. |
| Keywords: | Automated Traders; Optimal Strategies; Futures Market; Commodities Trading |
| JEL: | D81 C63 C73 |
| Date: | 2010–05–24 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:28277&r=mst |