Computer-Implemented Systems and Methods for Hedging with Contractual Flows

• US 20150134501A1
• Filed: 11/10/2014
• Published: 05/14/2015
• Est. Priority Date: 11/08/2013
• Status: Abandoned Application

• Current Assignee: SAS Institute Incorporated
• Original Assignee: SAS Institute Incorporated
• Inventors: Chen, Wei, Skoglund, Klas Jimmy
• Application Number:
  US14/537,557
• Publication Number:
  US 20150134501A1
• Time in Patent Office: Days
• US Class Current: 705/35
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange

Abstract

This disclosure describes computer-program products, systems and computer-implemented methods for optimal liquidity reserve planning. Liquidity portfolio optimization models are disclosed that hedge with contractual cash flows and/or hedge with counterbalancing capacity. With respect to hedging with contractual cash flows, disclosed embodiments receive a minimum solvency rate for a simulation of future events that specifies a percentage of simulation scenarios in which a solvent stress test outcome is achieved, and a minimum cost portfolio is identified that provides solvency in a percentage of simulation scenarios that meets or exceeds the minimum solvency rate. With respect to hedging with counterbalancing capacity, a hedging portfolio is structured by executing a liquidity portfolio optimization model, which prescribes a series of liquidity execution actions related to management of the hedging portfolio with respect to at least one random simulation scenario.

Claims

1. A computer-program product comprising a non-transitory machine-readable storage medium that includes instructions operable to cause a data processing apparatus to perform operations including:

accessing information representing assets and liabilities of an entity;

accessing a representation of a time horizon specified with respect to a series of consecutive future time periods;

generating representations of multiple simulation scenarios on a computing device, wherein the multiple simulation scenarios include one or more impacts associated with hypothetical events during the time horizon, and wherein the one or more impacts are forecasted using the hypothetical events and the information representing assets and liabilities;

receiving input corresponding to a minimum rate for a simulation of future events associated with the multiple simulation scenarios, wherein the minimum rate specifies a percentage of simulation scenarios in which a stress test outcome is achieved; and

identifying a minimum plan for the entity, wherein executing the minimum plan meets or exceeds the minimum rate, wherein identifying the minimum plan includes processing the representations of the simulation scenarios by executing an optimization model subject to at least one constraint, and wherein the optimization model is executed on the computing device and corresponds to the minimum plan.

2. The computer-program product of claim 1, wherein identifying the minimum plan includes:

specifying, with respect to multiple asset classes, aggregate asset values in the minimum plan.

3. The computer-program product of claim 1, wherein at least one of the simulation scenarios further includes a series of impacts associated with a series of hypothetical events during the time horizon.

4. The computer-program product of claim 3, wherein the impacts include a cash flow impact with respect to each of the future time periods, and wherein at least one of the hypothetical events is a new loan contract hypothetically consummated by the entity during the time horizon.

5. The computer-program product of claim 1, wherein the at least one constraint includes at least one tail risk constraint.

6. The computer-program product of claim 1, wherein the at least one constraint includes Conditional Liquidity at Risk.

7. The computer-program product of claim 6, wherein the Conditional Liquidity at Risk is approximated using a cash flow mismatch optimization model with Conditional Value at Risk constraints.

8. The computer-program product of claim 7, wherein the cash flow mismatch optimization model includes a liquidity solvency probability as a deterministic parameter.

9. The computer-program product of claim 1, wherein the minimum plan is identified assuming that, during each of the future time periods, liquidity supplying capacity for hedging negative cash outflows is unavailable to the entity.

10. The computer-program product of claim 1, wherein the minimum plan is identified assuming that a positive overnight interest rate is zero throughout the time horizon.

11. The computer-program product of claim 1, wherein a representation of the minimum plan is used as a baseline condition within a hedging portfolio optimization model.

12. The computer-program product of claim 1, wherein the minimum plan provides solvency for the entity by generating positive cash inflows that replicate negative cash outflows during each of the future time periods.

13. A system comprising:

a processor configured to perform operations including;

accessing information representing assets and liabilities of an entity;

accessing a representation of a time horizon specified with respect to a series of consecutive future time periods;

generating representations of multiple simulation scenarios, wherein the multiple simulation scenarios are generated on a computing device and include one or more impacts associated with hypothetical events during the time horizon, and wherein the one or more impacts are forecasted using the hypothetical events and the information representing assets and liabilities;

receiving input corresponding to a minimum rate for a simulation of future events associated with the multiple simulation scenarios, wherein the minimum rate specifies a percentage of simulation scenarios in which a stress test outcome is achieved; and

identifying a minimum plan for the entity that meets or exceeds the minimum solvency rate, wherein identifying the minimum plan includes processing the representations of the simulation scenarios by executing an optimization model subject to at least one constraint, and wherein the optimization model is executed on the computing device and corresponds to the minimum plan.

14. The system of claim 13, wherein identifying the minimum plan includes:

specifying, with respect to multiple asset classes, aggregate asset values in the minimum plan.

15. The system of claim 13, wherein at least one of the simulation scenarios further includes a series of impacts associated with a series of hypothetical events during the time horizon.

16. The system of claim 15, wherein the impacts include a cash flow impact with respect to each of the future time periods, and wherein at least one of the hypothetical events is a new loan contract hypothetically consummated by the entity during the time horizon.

17. The system of claim 13, wherein the at least one constraint includes at least one tail risk constraint.

18. The system of claim 13, wherein the at least one constraint includes Conditional Liquidity at Risk.

19. The system of claim 18, wherein the Conditional Liquidity at Risk is approximated using a cash flow mismatch optimization model with Conditional Value at Risk constraints.

20. The system of claim 19, wherein the cash flow mismatch optimization model includes a liquidity solvency probability as a deterministic parameter.

21. The system of claim 13, wherein the minimum plan is identified assuming that, during each of the future time periods, liquidity supplying capacity for hedging negative cash outflows is unavailable to the entity.

22. The system of claim 13, wherein the minimum plan is identified assuming that a positive overnight interest rate is zero throughout the time horizon.

23. The system of claim 13, wherein a representation of the minimum plan is used as a baseline condition within a hedging portfolio optimization model.

24. The system of claim 13, wherein the minimum plan provides solvency for the entity by generating positive cash inflows that replicate negative cash outflows during each of the future time periods.

25. A computer-implemented method comprising:

accessing inputted information representing assets and liabilities of an entity;

accessing an inputted representation of a time horizon specified with respect to a series of consecutive future time periods;

using a computing device to generate representations of multiple simulation scenarios, wherein the multiple simulation scenarios are generated on the computing device and include one or more impacts associated with hypothetical events during the time horizon, and wherein the one or more impacts are forecasted using the hypothetical events and the information representing assets and liabilities;

accessing, on the computing device, an inputted minimum rate for a simulation of future events associated with the multiple simulation scenarios, wherein the minimum rate specifies a percentage of scenarios in which a stress test outcome is achieved; and

using the computing device to identify a minimum plan for the entity that meets or exceeds the minimum solvency rate, wherein identifying the minimum plan includes processing the representations of the simulation scenarios by executing an optimization model on the computing device, the optimization model subject to at least one constraint, and wherein the optimization model corresponds to the minimum plan.

26. The method of claim 25, wherein identifying the minimum plan includes:

specifying, with respect to multiple asset classes, aggregate asset values in the minimum plan.

27. The method of claim 25, wherein at least one of the simulation scenarios further includes a series of cash flow impacts associated with a series of hypothetical events during the time horizon.

28. The method of claim 27, wherein the impacts include a cash flow impact with respect to each of the future time periods, and wherein at least one of the hypothetical events is a new loan contract hypothetically consummated by the entity during the time horizon.

29. The method of claim 25, wherein the at least one constraint includes at least one tail risk constraint.

30. The method of claim 25, wherein the at least one constraint includes Conditional Liquidity at Risk.

31. The method of claim 30, wherein the Conditional Liquidity at Risk is approximated using a cash flow mismatch optimization model with Conditional Value at Risk constraints.

32. The method of claim 31, wherein the cash flow mismatch optimization model includes a liquidity solvency probability as a deterministic parameter.

33. The method of claim 25, wherein the minimum plan is identified assuming that, during each of the future time periods, liquidity supplying capacity for hedging negative cash outflows is unavailable to the entity.

34. The method of claim 25, wherein the minimum plan is identified assuming that a positive overnight interest rate is zero throughout the time horizon.

35. The method of claim 25, wherein a representation of the minimum plan is used as a baseline condition within a hedging portfolio optimization model.

36. The method of claim 25, wherein the minimum plan provides solvency for the financial entity by generating positive cash inflows that replicate negative cash outflows during each of the future time periods.