Itg Software Solutions, Inc.

Scott Kartinen

Hitesh Mittal

Ryan Lee

Ronald Taur

Ananth Madhavan

Ian Domowitz

Artem Asriev

Jian Yang

Vitaly Serbin

Kenneth E Gosier

Systems and methods are provided for maintaining neutrality while trading a list of securities using an algorithmic trading facility coupled with at least one destination. This destination includes at least one alternative trading system (ATS). This facility is coupled, via an electronic data network, to a plurality of trading clients, and configured to receive a trade request to trade a list of securities from a trading client. This request includes user defined trading constraints that are used to generate and transmit trade orders to at least one ATS. The orders are transmitted based on trading data related to the destinations, the trade list, and the trading constraints. The facility can identify each executed trade corresponding to the trade orders and calculate a trade imbalance. The facility can determine whether the trade imbalance exceeds the trading constraints, and reallocate one or more of said submitted orders based on this determination.

Systems and methods for trading a trade list in financial markets

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 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.

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New York, NY, United States of America

Scott Kartinen