OANDA Corporation v. Stonex Group Inc

CourtDistrict Court, N.D. Illinois
DecidedFebruary 14, 2024
Docket1:20-cv-07785
StatusUnknown

This text of OANDA Corporation v. Stonex Group Inc (OANDA Corporation v. Stonex Group Inc) is published on Counsel Stack Legal Research, covering District Court, N.D. Illinois primary law. Counsel Stack provides free access to over 12 million legal documents including statutes, case law, regulations, and constitutions.

Bluebook
OANDA Corporation v. Stonex Group Inc, (N.D. Ill. 2024).

Opinion

IN THE UNITED STATES DISTRICT COURT FOR THE NORTHERN DISTRICT OF ILLINOIS EASTERN DIVISION OANDA Corporation, ) Plaintiff, No. 20-cv-07785 Vv. Judge John J. Tharp, Jr. StoneX Group, Inc., Defendant. MEMORANDUM OPINION AND ORDER Plaintiff OANDA Corporation and defendant StoneX Group, Inc. are both providers of online foreign currency trading and information services. OANDA has sued StoneX for patent infringement pursuant to 35 U.S.C. § 1 et seq, alleging that StoneX’s trading platform infringes three of OANDA’s patents: U.S. Patents Nos. 7,356,504 (the 504 Patent) (Ex. A to Compl., ECF No. 1-1), 7,702,548 (the °548 Patent) (Ex. B to Compl., ECF No. 1-2), and 7,742,959 (the Patent) (Ex. C to Compl., ECF No. 1-3). StoneX has filed a motion to dismiss for failure to state a claim on the ground that a claim against it for patent infringement cannot proceed because the asserted patents are invalid under 35 U.S.C. § 101 as comprising ineligible subject matter. For the reasons set forth below, StoneX’s motion is granted. OANDA’s claims are dismissed with prejudice. BACKGROUND OANDA is the assignee of the three patents at issue in this case. The innovations claimed in the patents, which the inventors filed with the Patent Office in the early 2000s, enabled OANDA to overcome certain limitations in the nascent years of online foreign currency exchange.

The ‘504 and ‘548 Patents The ‘504 and ‘548 Patents address methods for determining statistical values based on inhomogenous (i.e., arriving at irregular, “tick by tick,” intervals), high-volume time series data. The ’504 Patent teaches systems and methods “for determining value-at-risk,”! see ‘504 Patent, Abstract, while the ‘548 Patent teaches systems and methods “for obtaining predictive information (e.g., volatility),” see ‘548 Patent, Abstract. Risk measurement and management are fundamental parts of any coherent trading strategy. Obviously, many of the relevant metrics are data driven. At the time that the ‘504 and ‘548 Patents were filed, “[t]he state of the art [was] measuring risk by analyzing daily data: using one market price per working day and per financial instrument.” ‘504 Patent, Background. Given the advent of computers, however, dramatically more data became available; in fact, certain data vendors could transmit “more than 275,000 prices per day for foreign exchange spot rates alone.” Ex. D to Compl., ECF No. 1-4. And, as the patent authors explained, using only one market price per day did not provide terribly helpful predictive information: There is no reason to think that an asset’s market price at a given time of day is any more representative of the asset’s movements throughout the day than if it were selected at a different time of day. Why rely on only one price point per asset per day when such greater quantities of data were available? The problem was that deriving helpful statistical information from such high-frequency financial data arriving at random, and thus irregular, intervals (‘“tick-by-tick data”) posed some challenges. Because the prior art used a single daily transaction, the data points were regularly spaced from a temporal standpoint, i.e., they produced “homogenous time series.” And the

' Value-at-risk (“VaR”) is, as the name implies, a metric reflecting the potential loss on an investment, the probability that that potential loss may occur, and the relevant time frame over which such a loss is calculated to potentially occur. “There is a 95% chance that you don’t lose more than 4% of the current value of your holding over the next two days,” is an example.

relatively low volume of data was wieldier for conducting complicated statistical operations for on-the-spot decision making. The tick-by-tick data, on the other hand, arrived at a higher frequency and in irregularly spaced intervals, thus producing “inhomogeneous time series,” from which it was more difficult to derive meaningful statistical information. Further, the sheer volume/frequency of ticks posed issues; the tick-by-tick data sets were “100 or even 10,000 times denser than daily data,” thus requiring much more efficient computation processes to provide timely metrics for quick trading decisions. ‘548 Patent, Summary. The ‘504 and ‘548 Patents helped OANDA meet these challenges. ‘504 Claim 1, the only independent claim of the ’504 Patent, recites nine steps: (1) electronically receiving financial market transaction data over an electronic network; (2) electronically storing in a computer-readable medium said received financial market transaction data; (3) constructing an inhomogeneous time series z that represents said received financial market transaction data; (4) constructing an exponential moving average operator; (5) constructing an iterated exponential moving average operator based on said exponential moving average operator; (6) constructing a time-translation-invariant, causal operator Q[z] that is a convolution operator with kernel @ and that is based on said iterated exponential moving average operator; (7) electronically calculating values of one or more predictive factors relating to said time series z, wherein said one or more predictive factors are defined in terms of said operator Q[z]; (8) electronically storing in a computer readable medium said calculated values of one or more predictive factors; (9) and electronically calculating value-at-risk from said calculated values. ‘504 Patent, Claim J. The major steps of the ‘548 Patent are similar and as follows:

(1) financial market transaction data is electronically recetved by a computer over an electronic network; (2) the received financial market transaction data is electronically stored in a computer-readable medium accessible to the computer; (3) a time series z is constructed that models the received financial market transaction data; (4) an exponential moving average operator is constructed; (5) an iterated exponential moving average operator is constructed that is based on the exponential moving average operator; (6) a linear, time-translation-invariant, causal operator Q[z] is constructed that is based on the iterated exponential moving average operator; (7) values of one or more predictive factors relating to the time series z and defined in terms of the operator Q[z] are calculated by the computer; and (8) the values calculated by the computer are stored in a computer readable medium. ‘548 Patent, Abstract.” The ‘548 Patent has five independent claims, 1, 9, 17, 20, and 25, which all similarly involve the same concept of receiving data and constructing a time series from it, applying various operators to the time series, and deriving predictive information. The ‘959 Patent The ’959 Patent teaches “a method and apparatus for filtering high frequency time series data using a variety of techniques implemented on a computer.” ‘959 Patent, Abstract. As discussed in the ’959 Patent, data errors are a recurring problem when using high frequency time series data to derive predictive information. A data error exists “if a piece of quoted data does not conform to the real situation of the market. We have to identify a price quote as being a data error if it is neither a correctly reported transaction price nor a possible transaction price at the reported time.” ‘959 Patent, 2:25-31. The ‘959 Patent identifies various causes of data errors, ? The Court understands that the Abstract sets forth a preferred embodiment and not a specific claim. It is referenced here for brevity.

including “human errors” and “system errors.” Id. at 2:33-41, 2:56-3:45. The ‘959 Patent teaches ways to construct computerized filtering software to detect and identify errors in data streams. Id. at 5:45-60.

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Bluebook (online)
OANDA Corporation v. Stonex Group Inc, Counsel Stack Legal Research, https://law.counselstack.com/opinion/oanda-corporation-v-stonex-group-inc-ilnd-2024.