Generating And Providing Information About Expected Future Prices of Assets

• US 20110231338A1
• Filed: 04/15/2011
• Published: 09/22/2011
• Est. Priority Date: 08/18/2000
• Status: Active Grant

• Current Assignee: Athena Capital Advisors, Inc.
• Original Assignee: Athena Capital Advisors, Inc.
• Inventors: Forney, G. David JR., Scott, Leonard L. JR., Cooper, Lisette, Cooper, Philip A., Myers, Stewart
• Granted Patent: US 8,352,348 B2
• Time in Patent Office: Days
• US Class Current: 705/36.R
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis

Abstract

Data are received that represents current prices of options on a given asset. An estimate is derived from the data of a corresponding implied probability distribution of the price of the asset at a future time. Information about the probability distribution is made available within a time frame that is useful to investors, for example, promptly after the current option price information becomes available.

Claims

1. A method comprising:

receiving data representing current prices of options on a given asset,

deriving from said data an estimate of a corresponding implied probability distribution of the price of said asset at a future time, and

making information about said probability distribution available within a time frame that is useful to investors.

2. The method of claim 1 in which the data represent a finite number of prices of options at spaced-apart strike prices of the asset, and also including

calculating a set of first differences of said finite number of prices to form an estimate of the cumulative probability distribution of the price of said asset at a future time.

3. The method of claim 2 also including

calculating a set of second differences of the finite number of strike prices from the set of first differences to form an estimate of the probability distribution function of the price of said asset at a future time.

4. A method comprising:

receiving data representing current prices of options on a given asset,

deriving from said data an estimate of a corresponding implied probability distribution of the price of said asset at a future time, and

providing a real-time data feed containing information based on said probability distribution.

5. A method comprising:

providing a graphical user interface for viewing pages containing financial information related to an asset; and

when a user indicates an asset of interest, displaying probability information related to the price of the asset at a future time.

6. A method comprising:

enabling a user to identify an asset of interest, the asset being one for which data representing current prices of options on the asset are available,

deriving from said data an estimate of a corresponding implied probability distribution of the price of said asset at a future time, and

providing a display of a probability distribution of prices of the asset at future times.

7. A method comprising:

enabling a user to indicate a future time and to identify an asset of interest, the asset being one for which data representing current prices of options on the asset are available, and

displaying to the user a distribution of the probability that the asset will reach prices within a range of prices at the future time.

8. A method comprising:

receiving data representing current prices of options on a given asset, the options being associated with spaced-apart strike prices of the asset at a future time,

the data including shifted current prices of options resulting from a shifted underlying price of the asset, the amount by which the asset price has shifted being different from the amount by which the strike prices are spaced apart, and

deriving from said data an estimate of a quantized implied probability distribution of the price of said asset at a future time, the elements of the quantized probability distribution being more finely spaced than for a probability distribution derived without the shifted current price data.

9. A method comprising

receiving data representing current prices of options on a given asset, the options being associated with spaced-apart strike prices of the asset at a future time,

deriving from said data an estimate of an implied probability distribution of the price of said asset at a future time, the mathematical derivation including a smoothing operation, and

making information about said probability distribution available within a time frame that is useful to investors.

10. The method of claim 9 in which the smoothing operation is performed in a volatility domain.

11. The method of claim 9 in which the smoothing operation is performed in the domain of the option prices or in the domain of the probability distribution information.

15. The method of claim 9 also including

generating a smoothed volatility function using only data that are reliable under a predetermined measure of reliability.

16. The method of claim 9, further comprising:

generating an implied volatility function formula having a quadratic form with two variables representing a strike price and an expiration date;

wherein coefficients of the implied volatility function formula are determined by applying regression analysis to approximately fit the implied volatility function formula to each of the implied volatilities.

12. A method comprising:

receiving data representing current prices of options on a given asset, the options having strike prices at future dates,

deriving a volatility for each of the future dates in accordance with a predetermined option pricing formula that links option prices with strike prices of the asset;

generating a smoothed and extrapolated volatility function;

and using the volatility information to generate information within a time-frame that is useful for investors.

13. The method of claim 12 in which the volatility function is extrapolated to a wider range of dates than the future dates.

14. The method of claim 12 in which the volatility function is extrapolated to strike prices other than the strike prices of the options.

17. A method comprising:

receiving data representing current prices of options on assets belonging to a portfolio,

deriving from said data an estimate of an implied multivariate distribution of the price of a quantity at a future time that depends on the assets belonging to the portfolio, and

making information about said probability distribution available within a time frame that is useful to investors.

18. A method comprising:

receiving data representing values of a set of factors that influence a composite value,

deriving from said data an estimate of an implied multivariate distribution of the price of a quantity at a future time that depends on assets belonging to a portfolio, and

making information about said probability distribution available within a time frame that is useful to investors.

19. The method of claim 18 in which the mathematical derivation includes generating a multivariate probability distribution function based on correlations among the factors.

20. A graphical user interface comprising:

a user interface element adapted to enable a user to indicate a future time;

a user interface element adapted to show a current price of an asset; and

a user interface element adapted to show the probability distribution of the price of the asset at the future time.

21. A method comprising:

continually generating current data that contains probability distributions of prices of assets at future times,

continually feeding the current data to a recipient electronically, and

the recipient using the fed data for services provided to users.

22. A method comprising:

receiving data representing current prices of options on assets belonging to a portfolio,

receiving data representing current prices of market transactions associated with a second portfolio of assets, and

providing information electronically on the probability that the second portfolio of assets will reach a first value given the condition that the first portfolio of assets reaches a specified price at a future time.

23. A method comprising:

receiving data representative of actual market transactions associated with a first portfolio of assets;

receiving data representative of actual market transactions associated with a second portfolio of assets;

providing information on the expectation value of the price of first portfolio of assets given the condition that the second portfolio of assets reaches a first specified price at a specified future time through a network.

24. A method comprising

evaluating an event defined by a first multivariate expression that represents a combination of macroeconomic variables at a time T, and

estimating the probability that a second multivariate expression that represents a combination of values of assets of a portfolio will have a value greater than a constant B at time T if the value of the first multivariate expression is greater than a constant A.

25. The method of claim 24 in which the probability is estimated using Monte Carlo techniques.

26. A method comprising

defining a regression expression that relates the value of one variable representing a combination of macroeconomic variables at time T to a second variable at time T that represents a combination of assets of a portfolio, and

estimating the probability that the second variable will have a value greater than a constant B at time T if the value of the first variable is greater than a constant A at time T, based on the ratio of the probability of x being greater than A under the regression expression and the probability of x being greater than A.

27. A method comprising

defining a current value of an option as a quadratic expression that depends on the difference between the current price of the option and the current price of the underlying security, and

using Monte Carlo techniques to estimate a probability distribution of the value at a future time T of a portfolio that includes the option.

28. A method comprising

by machine, performing computations to determine a cumulative probability distribution function (cdf) for a price of an asset at a future time (T) based on prices of options on the asset, the options being at two or more strike prices x for the asset, the computations including:

determining a cumulative-distribution-function-implied volatility (CDF-implied volatility) of the asset as a function of the prices of the options by estimating a finite set of cdf values based on the prices of the options, and

for each of the estimated cdf values in the finite set, determining, as the CDF-implied volatility, a statistical measure for which probability of exercise of an option, as determined by an option pricing model, agrees with the estimated cdf value, for the time T and for an interpolated strike price corresponding to the estimated cdf value, given a current price of the asset,

the determined CDF-implied volatilities representing an estimated curve of CDF-implied volatility as a function of the prices of options at the strike prices x.

29. The method of claim 28 comprising

smoothing the estimated curve of CDF-implied volatility.

30. The method of claim 29 comprising estimating parameters in a parameterized smooth probability distribution, the parameters chosen to best fit, with the cdf of the parameterized distribution, the smoothed estimated curve of CDF-implied volatility.

31. The method of claim 28 comprising estimating parameters in a parameterized probability distribution, the parameters chosen to best fit, with the cdf of the parameterized distribution, the estimated curve of CDF-implied volatility.

32. The method of claim 29 comprising

computing a probability density function (pdf) by differentiating the smoothed CDF.

33. The method of claim 28 comprising

estimating CDF-implied volatility values at two or more future times T for which option prices are available, and interpolating and extrapolating associated variances to obtain interpolated and extrapolated values of the CDF that are implied at other future times.

34. The method of claim 28 in which the probability of exercise option, as determined by an option pricing model, is adjusted for risk aversion.

35. The method of claim 33 in which the adjustment for risk aversion comprises shifting the CDF values at a given price x to a higher price x by estimating stock returns in terms of a market return regression factor, together with standard long term estimates for market returns.

36. The method of claim 28 in which the estimated CDF values are for returns on a portfolio of assets, provided by Monte-Carlo calculations in a modeled multivariate distribution of joint returns on the assets.

37. The method of claim 28 in which the estimating of a finite set of cdf values comprises estimating by finite difference differentiation.

38. The method of claim 28 in which the statistical measure comprises a standard deviation.

39. The method of claim 38 in which the option pricing model assigns a probability of exercise at a future time based on a lognormal distribution determined by the standard deviation, adjusted for time to expiration, together with additional parameters available to an investor at a present time.

40. The method of claims 28, 38, and 39 in which the option pricing model comprises the Black-Scholes option pricing model.