Itg Software Solutions, Inc.

Vitaly Serbin

Ian Domowitz

Jian Yang

Ananth Madhavan

Artem Asriev

Milan Borkovec

Scott Kartinen

Robert D Sinclair

Yossef Brandes

Kenneth E Gosier

A computerized method for generating risk forecasts is provided. A set of securities is selected. A set of risk factors is selected. The risk factor returns a determined. A risk factor covariance matrix and an idiosyncratic variance matrix are constructed. For each risk factor, a factor loading coefficient is determined for each selected security. The risk factor covariance matrix is projected into a future forecast. The idiosyncratic variance matrix is projected into a future forecast. The factor loading coefficients, the future forecast of the risk factor covariance matrix, and the future forecast of the idiosyncratic variance matrix can be used to determine a forecast of the variance-covariance matrix for the selected securities.

Factor risk model based system, method, and computer program product for generating risk forecasts

A trading platform computer system for detecting an abnormal trading condition of a security uses real-time and estimated values of one or more variables associated with the condition of the security to generate one or more analytic metrics that are compared to empirical distributions based on one or more peer groups for the security. An indicator can then be displayed to a trader as an indication of the abnormal condition.

System and method for generating real-time indicators in a trading list or portfolio

A factor risk model based method for generating risk forecasts. In one embodiment, the method includes: selecting a set of securities; selecting a set of risk factors; determining the risk factor returns; constructing a risk factor covariance matrix; constructing an idiosyncratic variance matrix; determining, for each risk factor, a factor loading coefficient for each selected security; projecting the risk factor covariance matrix into a future forecast; and projecting the idiosyncratic variance matrix into a future forecast. The factor loading coefficients, the future forecast of the risk factor covariance matrix, and the future forecast of the idiosyncratic variance matrix can be used to determine a forecast of the variance-covariance matrix for the selected securities. In some embodiments, the step of estimating factor loadings includes performing a time series regression to obtain the sensitivity of each stocks' return to variations in the factor's return.

A system and method for detecting an abnormal trading condition of a security uses real-time and estimated values of one or more variables associated with the condition of the security to generate one or more analytic metrics that are compared to empirical distributions based on one or more peer groups for the security. An indicator can then be displayed to a trader as an indication of the abnormal condition.

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Boston, MA, United States of America

Vitaly Serbin