Financial methodology to valuate and predict the news impact of major events on financial instruments

1. A computerized method, comprising:

identifying an event having an association with a financial instrument;

classifying, by a modeling computer system, said event into at least one of a plurality of predefined event classes, each predefined event class being associated with a set of similar events;

retrieving, by the modeling computer system, media data associated with media coverage of said event and extracting data elements from said media data, wherein said data elements include at least one quantified communication parameter including at least one of a short term media coverage volume, a publication weight, a tonal balance, and an impact of available photographs;

retrieving, by the modeling computer system, current financial parameters associated with said financial instrument;

generating, by the modeling computer system as an intermediate result of the method, a prediction of upcoming media coverage of said event including a predicted volume and tonality of said upcoming media coverage, wherein said intermediate result is generated using the modeling computer system, a numerical model, said extracted data elements, information about said predefined event class, and said current financial parameters;

generating, using the modeling computer system and using a numerical model and said extracted data elements, information about said predefined event class, said current financial parameters and said intermediate result, a predicted financial impact of said event; and

outputting, from the modeling computer system, the predicted financial impact of said event.

2. The computerized method of claim 1 , wherein the event is associated with a court filing.

3. The computerized method of claim 1 , wherein the predicted financial impact of said event is associated with at least one of: (i) a price of said financial instrument, (ii) an amount of financial risk associated with the event, or (iii) an amount of revenue associated with the event.

4. The computerized method of claim 1 , wherein said generating an intermediate output of said numerical model further comprises generating a predicted business impact of said event.

5. The computerized method of claim 1 , wherein said at least one of a plurality of predefined event classes is at least one of: government probe, product safety, product approval, product recall, terrorism, resignation, industrial accident, corruption, bribe, strike, lawsuit, licensing, patent award, patent expiration, regulatory event, legislative change, boycott, accounting irregularity, prosecution, discrimination, insider trading, corporate manslaughter, injury or death related to product safety, incapacity of corporate officer, stock market delisting, stock market suspension, or resignation.

6. The computerized method of claim 1 , wherein said plurality of predefined event classes are created in a model training procedure, said model training procedure comprising:

receiving historical data associated with a plurality of events, said historical data including media data and financial data; and

analyzing said historical data to identify said plurality of predefined event classes.

7. The method of claim 6 , wherein said analyzing comprises at least one of: (i) an automated process or (ii) a manual process.

8. The computerized method of claim 6 , further comprising at least one method of measuring direction and strength of relationships and dependencies between variables and thus correlating said event and said historical data.

9. The computerized method of claim 1 , wherein said financial instrument is at least one of a company stock, a corporate bond, a government bond, a commodity, and a derivative instrument.

10. The computerized method of claim 1 , wherein said predicted financial impact of said event includes a predicted short term price movement of said financial instrument.

11. The computerized method of claim 1 , wherein said generating, using a numerical model, a predicted financial impact of said event further comprises augmenting said current financial parameters of said financial instrument with additional financial data including at least one of:

(i) financial data associated with the movement of an index associated with the industry associated with said financial instrument; and

(ii) financial data associated with the movement of an index associated with the market associated with said financial instrument.

12. The computerized method of claim 11 , further comprising:

comparing normalized price movement data across at least one of an industry, a market and an asset class; and

filtering out market influences not related to said event.

13. The computerized method of claim 8 , further comprising:

repeating said retrieving media data, said retrieving current financial parameters, said determining a correlation, said predicted business impact, and said predicted financial impact over a period of time; and

updating said numerical model based on said repeating.

14. The computerized method of claim 8 , wherein said determining a correlation uses quantitative parameters to compare and normalize different ones of said events within each of said predetermined event classes.

15. The computerized method of claim 8 , wherein said determining a correlation uses at least one of structural equation modeling (SEM), path analysis, and factor analysis.

16. The computerized method of claim 1 , wherein each of said predefined event classes includes at least a first parameter, said parameters extracted from historical data using at least one of a self-organizing map (SOM) and a clustering method.

17. The computerized method of claim 8 , wherein said determining a correlation includes learning a correlation via back-propagation and said correlation is utilized for classification and prediction using multilayered feed-forward networks.

18. A computerized method, comprising:

identifying, by a modeling computer system, an event having an association with a financial instrument;

classifying, by the modeling computer system, said event into at least one of a plurality of predefined event classes, each predefined event class being associated with a set of similar events;

retrieving, by the modeling computer system, media data associated with media coverage of said event and extracting data elements from said media data, wherein said data elements include at least one quantified communication parameter including at least one of a short term media coverage volume, a publication weight, a tonal balance, and an impact of available photographs;

generating a prediction of upcoming media coverage of said event including a predicted volume and tonality of said upcoming media coverage, wherein said prediction is generated using the modeling computer system, a numerical model, said extracted data elements, and information about said predefined event class; and

outputting, from the modeling computer system, the predication of the upcoming media coverage including the predicted volume and tonality of said upcoming media coverage.

19. The method of claim 18 , further comprising:

generating, using the modeling computer system, said extracted data elements, information about said predefined event class, current financial parameters and said prediction of upcoming media coverage, a predicted financial impact of said event.

20. The method of claim 19 , wherein the predicted financial impact is associated with at least one of: (i) product sales, (ii) a stock price, (ii) a stock option price, (iii) a bond value, or (iv) a credit default swap value.