Modeling financial instruments using bid and ask prices

• US 8,156,035 B2
• Filed: 04/13/2009
• Issued: 04/10/2012
• Est. Priority Date: 10/31/2005
• Status: Expired due to Fees

• Current Assignee: Penson Worldwide, Inc.
• Original Assignee: Penson Worldwide, Inc.
• Inventors: Boyd, Ronald Scott, Ferguson, Ralph Bruce, Cheung, Liam
• Primary Examiner(s): Patel, Jagdish
• Application Number:
  US12/422,615
• Publication Number:
  US 20090198634A1
• Time in Patent Office: 1,093 Days
• Field of Search: 705/35, 705/36.R, 705/37
• US Class Current: 705/37
• CPC Class Codes: G06Q 20/10 specially adapted for electronic funds transfer [EFT] systems; specially adapted for home banking systems
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis

Abstract

A method for modeling an investment significant parameter of a financial instrument, using a computer. At least one series of historical bid prices of the financial instrument or historical ask prices of the financial instrument is provided. A financial model type that has at least one variable parameter is selected. The variable parameter(s) of the selected financial model type is initialized. The series of historical bid prices and/or historical ask prices is applied to the initialized financial model type to estimate the variable parameter(s). The resulting model of the financial instrument may be used to predict future values of the investment significant parameter of the financial instrument. These predicted future values may be used to determine whether to perform automated trades of the financial instrument.

Claims

1. A method for performing automated trades of at least one financial instrument, using a computer, the method comprising the steps of:

a) predicting by the computer at least one future value of a numerical investment significant parameter of each of the at least one financial instrument, the at least one future value of the numerical investment significant parameter of each financial instrument predicted using at least one of a bid stream of the bid prices of a corresponding financial instrument or an ask stream of the ask prices of the corresponding financial instrument;

b) for each of the at least one financial instrument, using the computer, determining trend data of the corresponding financial instrument by comparing the at least one future value of the numerical investment significant parameter predicted in step (a) to at least one most recent actual value of the numerical investment significant parameter of the corresponding financial instrument;

c) automatically placing a buy order for one of the financial instruments modeled in step (a) if the corresponding trend data determined in step (b) meets a buy criterion for the one of the financial instruments; and

d) automatically placing a sell order for one of the financial instruments modeled in step (a) if the corresponding trend data determined in step (b) meets a sell criterion for the one of the financial instruments.

2. The method according to claim 1, wherein for each financial instrument, the at least one of the bid stream or the ask stream used in step (a) is at least one of a real time bid stream of the bid prices of the corresponding financial instrument or a real time ask stream of the ask prices of the corresponding financial instrument.

3. The method according to claim 1, wherein, for each financial instrument, step (a) includes the steps of:

a1) providing with the computer a model of a behavior of the at least one numerical investment significant parameter of the financial instrument based on a set of historical quotes of at least one of bid prices or ask prices of each financial instrument;

a2) selecting at least one of a corresponding real time bid stream or a corresponding real time ask stream based on the at least one of bid prices or ask prices of the financial instrument modeled by the corresponding model;

a3) applying the selected at least one of the corresponding bid stream or the corresponding ask stream to the corresponding model; and

a4) operating the corresponding model to predict the at least one future value of the numerical investment significant parameter of the financial instrument.

4. The method according to claim 3, wherein, for each of the financial instruments, step (a3) includes the steps of:

a3a) providing the corresponding bid stream of the bid prices of the financial instrument, including corresponding bid times, and the corresponding ask stream of the ask prices of the financial instrument, including corresponding ask times;

a3b) calculating a corresponding spread stream of a spread between the bid prices and the ask prices of the financial instrument from the corresponding bid stream and the corresponding ask stream;

a3c) identifying outlier bids in the corresponding bid stream of the bid prices using the corresponding spread stream;

a3d) removing the identified outliers bids and corresponding bid times from the corresponding bid stream before applying the corresponding bid stream to the corresponding model;

a3e) identifying outlier asks in the corresponding ask stream of the ask prices using the corresponding spread stream; and

a3f) removing the identified outliers asks and corresponding ask times from the corresponding ask stream before applying the corresponding ask stream to the corresponding model.

5. The method according to claim 3, wherein, for each model corresponding to one of the financial instruments, step (a1) includes the steps of:

a1a) providing the corresponding set of historical quotes of at least one of bid prices or ask prices;

a1b) selecting a corresponding financial model type having at least one variable parameter;

a1c) initializing the at least one variable parameter of the selected financial model type; and

a1d) generating the model of the at least one future value of the numerical investment significant parameter of the corresponding financial instrument by applying the corresponding set of historical quotes to the initialized financial model type and estimating the at least one variable parameter.

6. The method according to claim 5, wherein, for each model corresponding to one of the financial instruments:

step (a1a) includes providing at least one of;

a corresponding historical time series of the bid prices of the financial instrument, including corresponding bid times;

or

a corresponding historical time series of the ask prices of the financial instrument, including corresponding ask times;

step (a1d) includes applying the at least one of the corresponding historical time series of bid prices or the corresponding historical time series of ask prices to the initialized financial model type to estimate the at least one variable parameter;

step (a3) includes the steps of;

a3a) providing the selected at least one of;

the corresponding bid stream of the financial instrument, including the bid prices and corresponding bid times;

or

the corresponding ask stream of the financial instrument, including the ask prices and corresponding ask times; and

a3b) applying the selected at least one of the corresponding bid stream or the corresponding ask stream to the model; and

step (a4) includes operating the model to predict one or more corresponding future values of the numerical investment significant parameter of the financial instrument including a predicted time of each of the one or more future values.

7. The method according to claim 6, wherein, for each model corresponding to one of the financial instruments, the predicted time of each corresponding future value of the numerical investment significant parameter is within a predetermined period of time after its prediction.

8. The method according to claim 5, wherein, for each model corresponding to one of the financial instruments:

step (a1a) includes the steps of;

a1a1) providing a corresponding historical time series of the bid prices of the financial instrument, including corresponding bid times, and a corresponding historical time series of the ask prices of the financial instrument, including corresponding ask times; and

a1a2) calculating a corresponding historical time series of a spread between the bid prices and the ask prices of the financial instrument from the corresponding historical time series of the bid prices and the corresponding historical time series of the ask prices; and

step (a1d) includes applying the corresponding historical time series of the bid prices, the corresponding historical time series of the ask prices, and the corresponding historical time series of the spread between the bid prices and the ask prices to the initialized financial model type to estimate the at least one variable parameter.

9. The method according to claim 8, wherein, for each model corresponding to one of the financial instruments, step (a3) includes:

a3a) providing the corresponding bid stream of the bid prices of the financial instrument, including corresponding bid times, and the corresponding ask stream of the ask prices of the financial instrument, including corresponding ask times;

a3b) calculating a corresponding spread stream of a spread between the bid prices and the ask prices of the financial instrument from the corresponding bid stream and the corresponding ask stream; and

a3c) applying the corresponding bid stream, the corresponding ask stream, and the corresponding spread stream to the model.

10. The method according to claim 5, wherein, for each model corresponding to one of the financial instruments, step (a1b) includes selecting the corresponding financial model type to be one of:

an expert system model;

a linear analytic model;

a non-linear analytic model;

a chaotic model;

a neural network model;

a time delay neural network model;

a Markov-chain Monte Carlo model;

a wavelet transformation model;

a regression model;

a fractal model;

a support vector machine model;

or a Bayesian model.

11. The method according to claim 1, wherein, for each financial instrument, step (a) includes the steps of:

a1) providing a corresponding model of at least one of bid prices or ask prices of the financial instrument based on a corresponding set of historical quotes of the at least one of bid prices or ask prices of each financial instrument;

a2) selecting at least one of a corresponding real time bid stream or a corresponding real time ask stream based on the at least one of bid prices or ask prices of the financial instrument modeled by the corresponding model;

a3) applying the selected at least one of the corresponding bid stream or the corresponding ask stream to the corresponding model; and

a4) operating the corresponding model to predict at least one of corresponding future bid prices of the financial instrument or corresponding future ask prices of the financial instrument.

12. The method according to claim 11, wherein, for each model corresponding to one of the financial instruments, step (a1) includes the steps of:

a1a) providing the corresponding set of historical quotes of at least one of bid prices or ask prices;

a1b) selecting a corresponding financial model type having at least one variable parameter;

a1c) initializing the at least one variable parameter of the selected financial model type; and

a1d) generating the model of the at least one of bid prices or ask prices of the corresponding financial instrument by applying the corresponding set of historical quotes to the initialized financial model type and estimating the at least one variable parameter.

13. The method according to claim 12, wherein, for each model corresponding to one of the financial instruments:

step (a1a) includes providing at least one of;

a corresponding historical time series of the bid prices of the financial instrument, including corresponding bid times;

or

a corresponding historical time series of the ask prices of the financial instrument, including corresponding ask times;

step (a1d) includes applying the at least one of the corresponding historical time series of bid prices or the corresponding historical time series of ask prices to the initialized financial model type to estimate the at least one variable parameter;

step (a3) includes the steps of;

a3a) providing the selected at least one of;

the corresponding bid stream of the financial instrument, including the bid prices and corresponding bid times;

or

the corresponding ask stream of the financial instrument, including the ask prices and corresponding ask times; and

a3b) applying the selected at least one of the corresponding bid stream or the corresponding ask stream to the model; and

step (a4) includes operating the model to predict at least one of;

one or more corresponding future bid prices of the financial instrument including a predicted bid time of each of the one or more future bid prices;

or

one or more corresponding future ask prices of the financial instrument including a predicted ask time of each of the one or more future ask prices.

14. The method according to claim 13, wherein, for each model corresponding to one of the financial instruments, the predicted bid time of each corresponding future bid price and the predicted ask time of each corresponding future ask price are within a predetermined period of time after their prediction.

15. The method according to claim 1, wherein the at least one financial instrument is at least one publicly traded financial instrument.

16. The method according to claim 1, wherein the at least one financial instrument are selected from the group consisting of stocks, bonds, commodities, currencies, equities, derivatives, and futures.

17. The method according to claim 1, wherein, for each of the financial instruments, step (a) includes predicting one or more corresponding future values of the numerical investment significant parameter of the financial instrument including a corresponding parameter confidence level of each of the one or more corresponding future values.

18. The method according to claim 17, wherein the trend data determined in step (b) for each of the financial instruments includes a corresponding trend confidence level based on at least one of the corresponding parameter confidence level.

19. The method according to claim 18, wherein the buy criterion and the sell criterion for each of the financial instruments varies based on the corresponding trend confidence level determined in step (b).

20. The method according to claim 18, wherein:

step (c) includes the steps of;

c1) determining if the corresponding trend data determined in step (b) meets the buy criterion for the one of the financial instruments;

c2) determining a buy size of the buy order based on the corresponding trend confidence level determined in step (b) when the corresponding trend data is determined to meet the buy criterion in step (c1); and

c3) automatically placing the buy order for the one of the financial instruments when the corresponding trend data is determined to meet the buy criterion in step (c1); and

step (d) includes the steps of;

d1) determining if the corresponding trend data determined in step (b) meets the sell criterion for the one of the financial instruments;

d2) determining a sell size of the sell order based on the corresponding trend confidence level determined in step (b) when the corresponding trend data is determined to meet the sell criterion in step (d1); and

d3) automatically placing the sell order for the one of the financial instruments when the corresponding trend data is determined to meet the sell criterion in step (d1).

21. The method according to claim 1, wherein:

the at least one investment significant parameter of the financial instrument includes at least one of a future bid price or a future ask price; and

for each of the financial instruments, step (a) includes predicting at least one of;

one or more corresponding future bid prices of the financial instrument including a corresponding bid confidence level of each of the one or more corresponding future bid prices;

or

one or more corresponding future ask prices of the financial instrument including a corresponding ask confidence level of each of the one or more corresponding future ask prices.

22. The method according to claim 1, wherein:

the at least one financial instrument is a plurality of financial instruments; and

step (b) includes the steps of;

b1) for each of the at least one financial instrument, comparing the at least one investment significant parameter predicted in step (a) to at least one most recent most recent value of the numerical investment significant parameter of the corresponding financial instrument to determine a predicted change of the corresponding financial instrument;

b2) analyzing the plurality of predicted changes determined in step (b1) to formulate a joint trade strategy for the plurality of financial instruments over a predetermined period time; and

b3) setting the trend data corresponding to each of the financial instruments based on the joint trade strategy.

23. The method according to claim 22, wherein step (b2) includes analyzing the plurality of predicted changes determined in step (b1) to formulate the joint trade strategy using one of:

an expert system model;

a linear analytic model;

a non-linear analytic model;

a chaotic model;

a neural network model;

a time delay neural network model;

a Markov-chain Monte Carlo model;

a wavelet transformation model;

a regression model;

a fractal model;

a support vector machine model;

or a Bayesian model.

24. The method according to claim 1, wherein:

the at least one investment significant parameter of the financial instrument includes at least one of a future bid price or a future ask price;

the at least one financial instrument is a plurality of financial instruments; and

step (b) includes the steps of;

b1) for each of the at least one financial instrument, comparing the at least one future bid price or future ask price predicted in step (a) to at least one most recent bid price or at least one most recent ask price of the corresponding financial instrument to determine a predicted quote change of the corresponding financial instrument;

b2) analyzing the plurality of predicted quote changes determined in step (b1) to formulate a joint trade strategy for the plurality of financial instruments over a predetermined period time; and

b3) setting the quote trend data corresponding to each of the financial instruments based on the joint trade strategy.

25. The method according to claim 1, wherein:

the at least one financial instrument is a plurality of financial instruments;

step (c) includes the steps of;

c1) determining the buy criterion for each of the financial instruments based on at least one trend data determined in step (b) corresponding to another of the financial instruments;

c2) for each financial instrument, determining if the corresponding trend data determined in step (b) meets the corresponding buy criterion determined in step (c1); and

c3) automatically placing the buy order for each financial instrument for which the corresponding trend data is determined to meet the corresponding buy criterion in step (c2); and

step (d) includes the steps of;

d1) determining the sell criterion for each of the financial instruments based on at least one trend data determined in step (b) corresponding to another of the financial instruments;

d2) for each financial instrument, determining if the corresponding trend data determined in step (b) meets the corresponding sell criterion determined in step (d1); and

d3) automatically placing the sell order for each of the financial instruments for which the corresponding trend data is determined to meet the corresponding buy criterion in step (d2).

26. The method according to claim 1, wherein:

step (c) includes the steps of;

c1) comparing the corresponding trend data determined in step (b) to the buy criterion for the one of the financial instruments;

c2) determining a buy size of the buy order based on the comparison of the corresponding trend data and the buy criterion in step (c1);

c3) automatically placing the buy order for the one of the financial instruments when the buy size determined in step (c2) is greater than zero; and

step (d) includes the steps of;

d1) comparing the corresponding trend data determined in step (b) to the sell criterion for the one of the financial instruments;

d2) determining a sell size of the sell order based on the comparison of the corresponding trend data and the sell criterion in step (d1);

d3) automatically placing the sell order for the one of the financial instruments when the sell size determined in step (d2) is greater than zero.

27. The method according to claim 1, wherein the investment significant parameter includes at least one of:

a future trade price;

a future bid price;

a future ask price;

a future spread;

a fair market value (FMV);

an expected profit;

a change in trade price between two times;

a change in bid price between two times;

a change in ask price between two times;

a change in spread between two times;

a change in FMV between two times;

a change in profit between two times;

a rate of change of trade price;

a rate of change of bid price;

a rate of change of ask price;

a rate of change of spread;

a rate of change of FMV;

a rate of change of profit;

a prediction of winners and losers;

or a buy/sell instruction.