FACTOR RISK MODEL BASED SYSTEM, METHOD, AND COMPUTER PROGRAM PRODUCT FOR GENERATING RISK FORECASTS

• US 20110004567A1
• Filed: 07/02/2010
• Published: 01/06/2011
• Est. Priority Date: 10/17/2002
• Status: Active Grant

• Current Assignee: Virtu ITG Software Solutions LLC
• Original Assignee: ITG Software Solutions, Inc. (Virtu Financial, Inc.)
• Inventors: Yang, Jian, MADHAVAN, Ananth, Asriev, Artem V., Serbin, Vitaly, Kartinen, Scott J., Gosier, Kenneth E., Domowitz, Ian
• Granted Patent: US 8,019,670 B2
• Time in Patent Office: Days
• US Class Current: 705/36.R
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis
• CPC Class Codes: G06Q 40/08 Insurance

Abstract

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.

Claims

1. A method for generating risk forecasts in financial securities, comprising the steps of:

selecting a set of securities;

selecting at least two risk factors associated with investment risk in the securities;

determining, for each selected risk factor, the risk factor'"'"'s return;

constructing a risk factor covariance matrix corresponding to the selected risk factors;

constructing an idiosyncratic variance matrix corresponding to the securities in the selected set of securities;

determining, for each selected risk factor, a risk factor loading coefficient for each security in the set by, at the least, performing a time series regression to obtain the sensitivity of each security'"'"'s return to variations in the risk factor'"'"'s return;

projecting the risk factor covariance matrix into a future forecast, thereby producing a future forecast of the risk factor covariance matrix, wherein the step of projecting the risk factor covariance matrix into a future forecast comprises utilizing information in implied volatility; and

projecting the idiosyncratic variance matrix into a future forecast, thereby producing a future forecast of the idiosyncratic variance matrix, wherein

the determined risk factor loading coefficients, the future forecast of the risk factor covariance matrix, and the future forecast of the idiosyncratic variance matrix can be used together to determine a forecast of the variance-covariance matrix for all securities in the selected set of securities.

2. The method of claim 1, wherein the step of projecting the risk factor covariance matrix into a future forecast comprises utilizing implied volatility in the Chicago Board of Options Exchange VIX option contract to capture market expectations of future volatility.

3. The method of claim 1, wherein the step of selecting the set of securities comprises the step of selecting securities from the group of substantially all relatively active securities in a selected market.

4. The method of claim 3, wherein the selected market is the U.S. market and the set of securities includes substantially all securities traded on the New York Security Exchange, the American Security Exchange, and the NASDAQ National Market.

5. The method of claim 1, where the step of selecting at least two risk factors comprises the step of selecting the following risk factors:

market, industry, sector, size and growth.

6. The method of claim 1, where the step of selecting at least two risk factors comprises the step of selecting the following risk factors:

market, industry, size and U.S. market.

7. The method of claim 1, wherein the step of determining a risk factor loading for each security in the set comprises performing a time series regression to obtain the sensitivity of each securities'"'"' return to variations in the risk factor'"'"'s return.

8. The method of claim 1, wherein the step of determining the factor loadings for the securities in the selected set of securities comprises the step of estimating the equation:

9. The method of claim 1, wherein the step of determining the risk factor loading coefficients comprises the step of adjusting risk factor loading estimates using a predetermined adjustment process to reduce estimation error.

10. The method of claim 1, further comprising the step of determining the forecast of the variance-covariance matrix for all securities in the selected set of securities.

31. The method of claim 1, wherein the step of projecting the risk factor covariance matrix into a future forecast comprises utilizing information in implied volatility.

11. A system, comprising:

determining means for determining risk factor return for each risk factor in a set of selected risk factors;

first estimating means for estimating a risk factor covariance matrix of the selected risk factors;

second estimating means for estimating an idiosyncratic variance matrix corresponding to a set of selected securities;

third estimating means for estimating, for each risk factor in the set of selected risk factors, a risk factor loading coefficient for each security in a set of selected securities;

first projecting means for projecting the risk factor covariance matrix into a future forecast, thereby producing a future forecast of the risk factor covariance matrix, wherein the first projecting means utilizes information in implied volatility in projecting the risk factor covariance matrix into a future forecast; and

second projecting means for projecting the idiosyncratic variance matrix into a future forecast, thereby producing a future forecast of the idiosyncratic variance matrix, wherein

the estimated risk factor loading coefficients, the future forecast of the risk factor covariance matrix, and the future forecast of the idiosyncratic variance matrix can be used together to determine a forecast of the variance-covariance matrix for all securities in the selected set of securities.

12. The system of claim 11, wherein the first projecting means utilizes implied volatility in the Chicago Board of Options Exchange VIX option contract in projecting the risk factor covariance matrix into a future forecast, thereby capturing market expectations of future volatility.

13. The system of claim 11, wherein the set of selected securities is selected from the group of substantially all relatively active securities in a selected market.

14. The system of claim 13, wherein the selected market is the U.S. market and the set of securities includes substantially all securities traded on the New York Security Exchange, the American Security Exchange, and the NASDAQ National Market.

15. The system of claim 11, wherein the set of selected risk factors comprises the following risk factors:

market, industry, sector, size and growth.

16. The system of claim 11, wherein the set of selected risk factors comprises the following risk factors:

market, industry, size and U.S. market.

17. The method of claim 11, wherein the third estimating means estimates a risk factor loading for a selected risk factor and a security in the set of selected securities by, at the least, performing a time series regression to obtain the sensitivity of the security'"'"'s return to variations in the selected risk factor'"'"'s return.

18. The system of claim 16, wherein the third estimating means estimates a risk factor loading for a security in the set of selected securities by, at the least, estimating the equation:

19. The system of claim 11, further comprising risk factor loading adjusting means for adjusting the risk factor loading estimates using a predetermined adjustment process to reduce estimation error.

20. The system of claim 11, further comprising determining means for determining the forecast of the variance-covariance matrix for all securities in the selected set of securities using the estimated risk factor loading coefficients, the future forecast of the risk factor covariance matrix, and the future forecast of the idiosyncratic variance matrix.

32. The system of claim 11, wherein the first projecting means utilizes information in implied volatility in projecting the risk factor covariance matrix into a future forecast.

21. A computer program product including a machine readable medium having stored therein instructions, the instructions comprising:

instructions for determining a risk factor'"'"'s return, wherein the risk factor is from a set of two or more selected risk factors;

instruction for constructing a risk factor covariance matrix corresponding to the selected risk factors;

instruction for constructing an idiosyncratic variance matrix corresponding to securities in a selected set of securities;

instructions for determining, for each risk factor in the set of risk factors, a risk factor loading coefficient for each security in the set of securities;

instructions for projecting the risk factor covariance matrix into a future forecast, thereby producing a future forecast of the risk factor covariance matrix, wherein the instructions for projecting the risk factor covariance matrix into a future forecast comprise instructions for utilizing information in implied volatility in projecting the risk factor covariance matrix into a future forecast; and

instructions for projecting the idiosyncratic variance matrix into a future forecast, thereby producing a future forecast of the idiosyncratic variance matrix, wherein

the determined risk factor loading coefficients, the future forecast of the risk factor covariance matrix, and the future forecast of the idiosyncratic variance matrix can be used together to determine a forecast of the variance-covariance matrix for all securities in the selected set of securities.

22. The computer program product of claim 21, wherein the instructions for utilizing information in implied volatility comprise instructions for utilizing implied volatility in the Chicago Board of Options Exchange VIX option contract in projecting the risk factor covariance matrix into a future forecast to capture market expectations of future volatility.

23. The computer program product of claim 21, wherein the selected set of securities includes securities selected from the group of substantially all relatively active securities in a selected market.

24. The computer program product of claim 23, wherein the selected market is the U.S. market and the set of securities includes substantially all securities traded on the New York Security Exchange, the American Security Exchange, and the NASDAQ National Market.

25. The computer program product of claim 24, wherein the set of risk factors comprises the following risk factors:

market, industry, sector, size and growth.

26. The computer program product of claim 21, wherein the set of risk factors comprises the following risk factors:

market, industry, size and U.S. market.

27. The computer program product of claim 21, wherein the instructions for determining the risk factor loading coefficient for a security and a risk factor comprise instructions for performing a time series regression to obtain the sensitivity of the security'"'"'s return to variations in the risk factor'"'"'s return.

28. The computer program product of claim 27, wherein the instructions for estimating the factor loading coefficients comprise instructions for estimating the equation:

29. The computer program product of claim 21, wherein the instructions for determining the risk factor loading coefficients comprise instructions for adjusting estimated risk factor loading coefficients using a predetermined adjustment process to reduce estimation error.

30. The computer program product of claim 21, further comprising instructions for determining the forecast of the variance-covariance matrix for all securities in the selected set of securities.

33. The computer program product of claim 21, wherein the instructions for projecting the risk factor covariance matrix into a future forecast comprise instructions for utilizing information in implied volatility in projecting the risk factor covariance matrix into a future forecast.