Abstract: A system and method of determining a model default swap spread for a firm which includes the following steps: (i) determining a calibration group of the firm, wherein the calibration group comprises other firms having a region, a sector and a coarse quality related to the firm; (ii) setting firm leverage variables through combining observable data with a value of at least one model parameter; (iii) calibrating variables based on the calibration group; (iv) calculating the model default swap spread based on at least one of calibration variables; and (v) storing the model default swap spread.

Abstract: Systems and methods for attributing return, risk, and risk-adjusted performance for an investment portfolio. Residual factors for the investment portfolio may be determined based on a matrix of custom factors. The residual factors may correspond to a matrix of factor exposures for the portfolio that may be obtained by orthogonalizing true factors for the portfolio to the matrix of custom factors. The return of the portfolio may be attributed to the custom factors, the residual factors, and idiosyncratic effects. The risk of the portfolio may be attributed to the custom factors, the residual factors, and the idiosyncratic effects. The risk-adjusted performance may be attributed to the custom factors, the residual factors, and idiosyncratic effects based on the return attributions and the risk attributions. The return attribution, risk attribution and risk-adjusted performance attribution for each of the custom factors, the residual factors, and the idiosyncratic effects may be stored.

Abstract: A computer system, which may comprise a processor, a memory and a database, may implement a loss surface determining software module that forecasts a portfolio's loss surface. Daily loss histories may be collected from actual data or may be generated using a factor model. A model may generate a sequence of iid high frequency loss innovations that can be temporally aggregated with a Fourier transform. For each portfolio, the loss surface may be forecasted and 95% and 99% value-at-risk and expected shortfall forecasts may be derived for various time horizons.

Abstract: Systems and methods for determining a value for a global market index based on market data of publicly traded companies in a plurality of markets are disclosed. In one embodiment, indices may target a desired market coverage range subject to a universal minimum size range. In another embodiment, the indices may combine elements of percentile, number of companies, and market capitalization cutoff approaches.

Abstract: A method of constructing a value index and a growth index is disclosed. The method includes, determining a value of each variable in a group of variables for each security in a group of securities, determining a standardized score of each variable for each security, and determining an overall value standardized score and an overall growth standardized score for each security. The method further includes positioning each security in a two-dimensional style space and allocating each security to at least one of the growth index and the value index based on each security's distance from an origin of the two-dimensional style space.

Abstract: A method of generating a financial market index. The method includes selecting a plurality of constituent securities to comprise the index and determining a weight for each of the securities based on at least one forecasted parameter that is determined for each of the plurality of constituent securities that comprise the index. The method also includes generating the financial market index based on the weights.

Abstract: Systems and methods for attributing return, risk, and risk-adjusted performance for an investment portfolio. Residual factors for the investment portfolio may be determined based on a matrix of custom factors. The residual factors may correspond to a matrix of factor exposures for the portfolio that may be obtained by orthogonalizing true factors for the portfolio to the matrix of custom factors. The return of the portfolio may be attributed to the custom factors, the residual factors, and idiosyncratic effects. The risk of the portfolio may be attributed to the custom factors, the residual factors, and the idiosyncratic effects. The risk-adjusted performance may be attributed to the custom factors, the residual factors, and idiosyncratic effects based on the return attributions and the risk attributions. The return attribution, risk attribution and risk-adjusted performance attribution for each of the custom factors, the residual factors, and the idiosyncratic effects may be stored.