WO2016178217A1

WO2016178217A1 - Interactive probability visualization user interface for real time data

Info

Publication number: WO2016178217A1
Application number: PCT/IL2016/050458
Authority: WO
Inventors: Yariv MATHOV; Alon FINE; Peleg MICHAELI
Original assignee: M.B. Visualtrade Ltd.
Priority date: 2015-05-03
Filing date: 2016-05-03
Publication date: 2016-11-10

Abstract

A method of generating an interactive user interface adapted to visualize a time- series of values in relation to a user defined geometric object. The method comprises receiving a plurality of consecutive values of at least one irregular time varying parameter, iteratively updating a visualization of a dynamic graph of the of at least one irregular time varying parameter according to the consecutive values to reflect a current change, identifying at least one time dependent threshold at a future period according to user instructions to reshape or relocate at least one geometric object presented in the visualization, calculating a probability that a future value of the time varying parameter exceeds or descends the at least one time dependent threshold during the future period, and causing a device presenting the visualization to present an indication of the probability in association with the at least one geometric object.

Description

INTERACTIVE PROBABILITY VISUALIZATION USER INTERFACE FOR REAL

TIME DATA

BACKGROUND

The present invention, in some embodiments thereof, relates to visualization and, more specifically, but not exclusively, to a tool for visualization of current values of one or more irregular time varying parameters in relation to a user defined prediction.

Prediction, sometimes referred to as forecast, is an estimation of an uncertain numeric quantity. Prediction plays a crucial role in many aspects of life. Statistical inference is used in many disciplines. Some applications of statistical inference move from a visual level of a phenomenon (such as the height of a wave or the location of a particle) to an abstract level of the phenomena (mathematical formulae). Making a prediction more rigorous may reduce advantages of visualizing especially when an experienced observer (also referred to as a user) is involved. SUMMARY

According to some embodiments of the present invention, there is provided a method of generating an interactive user interface adapted to visualize a time-series of values in relation to a user defined geometric object. The method comprises receiving a plurality of consecutive values of at least one irregular time varying parameter, iteratively updating a visualization of a dynamic graph of the of at least one irregular time varying parameter according to the consecutive values to reflect a current change, identifying at least one time dependent threshold at a future period according to user instructions to reshape or relocate at least one geometric object presented in the visualization, calculating a probability that a future value of the time varying parameter exceeds or descends the at least one time dependent threshold during the future period, and causing a device presenting the visualization to present an indication of the probability in association with the at least one geometric object.

Optionally, the plurality of consecutive values are acquired over a network from at least one data feed. Optionally, the defining , the calculating and the causing are iteratively repeated each based on different instructions to reshape or relocate the at least one geometric object so as to allow the user to iteratively receive a plurality probabilities derived from a plurality of shapes or a plurality of shapes locations of the at least one geometric object.

Optionally, calculating is performed based on a model describing a time dependent phenomena.

Optionally, the geometric object is selected from a group consisting of an ellipse, a rectangular, a triangular, a circle and a curved line.

Optionally, the at least one time dependent threshold comprises a time dependent range defining a range of values as a threshold.

Optionally, the method comprises identifying an additional user input indicative of a prediction that is based on the probability and causing the device to update the dynamic graph based on new consecutive values from at least one feed along a possible collision course with the geometric object to provide a visual indication of a failure or a realization of the prediction.

Optionally, the dynamic graph and the at least one geometric object are presented on a common coordinate system.

More optionally an X-axis of the common coordinate system represents time scale and a Y-axis of the common coordinate system represents a value scale for the at least one irregular time varying parameter.

Optionally, the at least one irregular time varying parameter is a value of a member selected from a financial asset, a currency ratio, a currency, a bond, an index, a stock, and a debenture.

Optionally, the user instructions comprises instructions to change a size of the geometric object.

Optionally, the user instructions comprises instructions to a location of the geometric object in relation to the dynamic graph.

According to some embodiments of the present invention, there is provided a system of generating an interactive user interface adapted to visualize a time-series of values in relation to a user defined geometric object. The system comprises a network interface adapted to receive consecutive values of at least one irregular time varying parameter from at least one data feed, at least one processor, and memory including computer-executable instructions that, based on execution by the at least one processor, configure the at least one processor to: iteratively update a visualization of a dynamic graph of the of at least one irregular time varying parameter according to the consecutive values to reflect a current change, identify at least one time dependent threshold at a future period according to user instructions to reshape or relocate at least one geometric object presented in the visualization, calculate a probability that a future value of the time varying parameter exceeds or descends the at least one time dependent threshold during the future period, and cause a device presenting the visualization to present an indication of the probability in association with the at least one geometric object.

Unless otherwise defined, all technical and/or scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the invention pertains. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of embodiments of the invention, exemplary methods and/or materials are described below. In case of conflict, the patent specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and are not intended to be necessarily limiting.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

Some embodiments of the invention are herein described, by way of example only, with reference to the accompanying drawings. With specific reference now to the drawings in detail, it is stressed that the particulars shown are by way of example and for purposes of illustrative discussion of embodiments of the invention. In this regard, the description taken with the drawings makes apparent to those skilled in the art how embodiments of the invention may be practiced.

In the drawings:

FIG. 1 is a flowchart of a method of generating an interactive user interface adapted to visualize in real time a time-series of current values of an irregular time varying parameter in relation to a geometric shape having one or more user adaptive parameters, such as a relative location, area and/or one or more boundaries, according to some embodiments of the present invention; FIG. 2 is an exemplary graphical user interface (GUI) visualizing a dynamic graph updated according to a time-series of current values and an adjustable geometric shape, according to some embodiments of the present invention;

FIG. 3 is a schematic illustration of a system for generating an interactive UI visualizing, in real time, a time-series of current values of an irregular time varying parameter and an adjustable geometric shape, for instance by executing the method depicted in FIG. 1, according to some embodiments of the present invention;

FIGs. 4A-4D are a plurality of schematic illustrations of a GUI having a left portion with a dynamic graph updated in real time to reflect changes to irregular time varying parameter and a right portion with an adaptable geometric shape, according to some embodiments of the present invention;

FIG. 5 is a schematic illustration of GUI for submitting prediction on financial assets, according to some embodiments of the present invention; and

FIGs. 6 A and 6B are screenshots of a GUI having a left portion with a dynamic graph updated in real time and a right portion with an adaptable geometric shape representing a prediction, according to some embodiments of the present invention.

DETAILED DESCRIPTION

According to some embodiments of the present invention, there are provided methods and system for interactively visualizing of a probability of values of an irregular time varying parameter to exceed or descend one or more time dependent thresholds which are defined by a user by relocating and/or reshaping a geometric object. The values of an irregular time varying parameter are optionally acquired from one or more network feeds in real time.

The methods and systems provide the user with a tool for iteratively defining time dependent thresholds based on immediate feedback indicative of a current probability of an event wherein values of an irregular time varying parameter exceed or descend the time dependent threshold(s). The visualization also provides a tool for defining a prediction by locating and/or shaping the geometric object and fixating its location and/or shape. In such embodiments, the dynamic graph may be updated along a time scale such that an intersection between the dynamic graph and the geometric object is indicative of a realization of the prediction and no intersection between the dynamic graph and the geometric object is indicative of a failure of the prediction.

Before explaining at least one embodiment of the invention in detail, it is to be understood that the invention is not necessarily limited in its application to the details of construction and the arrangement of the components and/or methods set forth in the following description and/or illustrated in the drawings and/or the Examples. The invention is capable of other embodiments or of being practiced or carried out in various ways.

The present invention may be a system, a method, and/or a computer program product. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non- exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire. Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device.

Computer readable program instructions for carrying out operations of the present invention may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++ or the like, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions.

These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks.

The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks.

The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions.

Reference is now made to FIG. 1, which is a flowchart of a method 100 of generating an interactive user interface (UI) adapted to visualize in real time a time- series of current values of an irregular time varying parameter in relation to a geometric object having one or more user adaptive parameters, such as a relative location, area and/or one or more boundaries, according to some embodiments of the present invention. The geometric object defines a probability or a probability function that one or more current value dependent event(s) will occur in a user defined future period for instance by setting one or more time dependent thresholds or time dependent threshold ranges referred to, for brevity, time dependent thresholds. For example, FIG. 2 depicts an exemplary graphical user interface (GUI) visualizing a dynamic graph 151 updated according to a time-series of current values optionally acquired from one or more feeds and an adjustable geometric object 152 that defines a one or more time dependent thresholds, according to some embodiments of the present invention. The adaptable parameters of the geometric object 152 allow a user to redefine the probability of a prediction based on a visualization of the changing values.

The adaptable parameters allow the user to set a one or more time dependent thresholds such a value dependent event occurs when the values of the irregular time varying parameter exceed or descend the one or more time dependent thresholds at a future period. The changes a probability that represents a prediction by visually redefining the adjustable parameters of the geometric object. This can be done iteratively to test different events. As the method 100 does not require from the user to define or update mathematical formulae, the user is avoiding abstract definition of his prediction. The visualization exemplifies to the user how a change in a threshold or a future period affects the probability of occurrence of an event.

For example, the user may investigate a distribution of heights of ocean waves by changing a probability that in a period of 5 minutes from now there will be a wave larger than the ones in a previous period, for instance an hour, to a probability that in such a wave occurs in a period of 10 minutes from a current time, for instance a time for verifying a prediction selected as described below. Additionally or alternatively, the user may investigate a distribution of heights of ocean waves by changing a probability that in a period of 5 minutes from a user selected time there is a 1 meter height wave to a probability that in a period of 5 minutes from now there is a 2 meter height wave. Changing the period may be done be adjusting the width of the geometric object and changing the height may be done by relocating the geometric object.

Optionally, the visualization is based on updating a graph according to the time- series of current values. In use, the user may fix a selected probability, for instance by fixing boundaries of the geometric object and trigger the initiation of a validation process wherein an occurrence or a non-happening of an event is tested.

Reference is also made to FIG. 3, which is a schematic illustration of a system 200 for generating an interactive UI visualizing, in real time, a time-series of current values of an irregular time varying parameter and an adjustable geometric object, for instance by executing the method depicted in FIG. 1, according to some embodiments of the present invention. The system 200 includes a server 201 or a virtual machine executed on one or more servers and optionally a client module 202 executed for rendering a GUI such as the GUI depicted in FIG. 2 on an on-premises device 203, for example a client terminal, such as a personal computer, smartphone, and/or the like. The client module 202 stored in a memory 220 of the client terminal 203 and executed by processor(s) 209 of the client terminal 203 may be a script executed by a browser or an application installed in the client device 203. The server 201 and the client module 202 are connected to a network 205, such as a wide area network (WAN) and/or one or more local area networks (LANs), either wired and/or wireless. The system 200 includes a simulation module 204, for instance software component, stored in memory 206 of the server 201 and executed by the processor(s) 219 of the server 201. The system 200 further includes one or more network interfaces 220 adapted to receive data feeds from one or more sources 210 via the network 205. For example, the data feed includes data which consists of one or more vertical values which are changing over time, for instance a sequence of numerical values each marked with a timestamp. For example, the feed may be ratio between currencies, such as a EURO/DOLLAR currency feed consist of a rate, and a timestamp. In another example, the feed includes sequence of numerical values such as particle coordinate values, particle concentration values, wave height values, people count values and a measurement timestamp.

In use, as shown at 101, the server 201 acquires feed(s) of consecutive values of one or more irregular time varying parameter(s), for example using the one or more network interfaces 220. The data feed may include sensor data, such as a current wave height, a current particle location, a current people meter data, a current social media status and/or the like. The data feed may include financial data such as a current currency value or currencies ratio and/or a trading volume of the security(ies), equity(ies) and/or any tradable.

Now, as shown at 102, a visualization that includes a dynamic graph of the irregular time varying parameter is updated in real time by the client module 202 and/or the simulation module 204 according to the acquired consecutive values to reflect a current value change.

The dynamic graph is optionally based on an underlying mathematical model to describe a numerical 1 -dimensional phenomenon over time. As shown at 99 the dynamic graph is continuously or iteratively updated, for instance every 1 second, 1 minute, 1 hour or any intermediate or shortly period. The dynamic graph may be updated in irregular times, for instance randomly and/or upon detected change.

As shown at 103, user input(s) indicative of reshaping and/or relocating of a geometric object presented in a visualization are detected, for instance by the client module 202, for example user inputs made using a GUI presented on a display of the client device 103, for instance a touchscreen. Optionally, the dynamic graph and the geometric object are presented on a common coordinate system. While in a planning stage (e.g. 101-106) the dynamic graph is updated in a left side of the common coordinate system and the x-axis is updated to represent a fixed time difference between the dynamic graph and an area in which the geometric object can be relocated and/or reshaped (e.g. in size and/or shape ) in a prediction verification stage (e.g. 108 and 109) the dynamic graph is updated along the x-axis, into the right portion wherein the geometric object is present and optionally fixated as described below.

For example, FIGs. 4A-4D depict a GUI having a left portion with a dynamic graph updated in real time to reflect changes to irregular time varying parameter and a right portion with an adaptable geometric object. While the left portion is based on the feed values, the right portion includes a geometric object that represents a hypostasis about the future where x-axis optionally represents time and y-axis optionally represents thresholds. The location in a used coordinate system and the height of the geometric object may represent a selected range of numerical values and the width of the geometric object represents a selected period. While FIG. 4A depicts a narrow ellipse that defines the probability that the irregular time varying parameter will cross a width range of numerical values, e.g. between about 112.372 and about 112.388 during a short period, e.g. 23:00:04-23:00:0335, FIG. 4D depicts a wide ellipse that defines the probability that the irregular time varying parameter will cross a narrow range of numerical values, e.g. between about 112.38 and about 112.381, during a long period, e.g. 22:59:35-23:00:034. FIGs. 4C and 4D respectively depict a rectangular and a triangular as geometric objects.

The geometric object can be described by a mathematical formula.

Optionally, a number of graphic objects are adapted by the user, each handled as described herein, either together or separately. For example, the geometric object is a visual representation of a trading formula and the dynamic graph is a currency/financial asset trading graph. In this example, the location and the height of a geometric object such as a square represent a range of prices and the width of the geometric object represents a period.

In use, the user relocates and/or reshapes the adaptable geometric object by using a man machine interface, for instance by finger gesture motions. Mouse maneuvering and/or any keyboard or keypad usage. In one example the visualization is presented on a touch screen and the user relocate (e.g. finger tapping, holding and dragging) the adaptable geometric object by sliding one or more fingers against the touchscreen and/or reshape the adaptable geometric object by pinch and/or spread by tapping the screen with two fingers and pinching and/or spreading them.

As shown at 104, in response to the relocation and/or reshaping of the adaptable geometric object, one or more time dependent thresholds are identified. The time dependent thresholds are thresholds for the irregular time varying parameter(s) at a future period. The time dependent thresholds are optionally calculated based on the geometric object and by the simulation module 204. It should be noted that although reference is done herein to a two dimensional (2D) geometric object in a 2D coordinate system, a three dimensional (3D) geometric object may be used in a 23 coordinate system.

Now, as shown at 105, a probability or a probability function referred to herein as a probability is calculated by the simulation module 204 according to the time dependent thresholds. The probability is of a future value of the time varying parameter imaged in the dynamic graph to exceed or descend, during a future period, the one or more time dependent thresholds defined by the adaptable geometric object as currently located and/or shaped. The shape is located relatively to a present value of the irregular time varying parameter (on the time axis and the value axis).

For example, new thresholds defining ranges of wave heights during a new period and a new formula representing a probability that heights of waves will cross the new thresholds are calculated according to reshaping and/or relocating instructions and/or as an outcome of creating a new geometric object. In another example, a new thresholds and a new trading formula representing a probability that currency values will cross the new thresholds are calculated.

The probability is optionally predicted by a model calculated according to the values of the irregular time varying parameter which is optionally an irregular time varying parameter. The underlying model is continuous or at least almost continuous (in time), so at any given time there is a single optionally nonnegative value. The model constructs an explicit probability space on possible outcomes, optionally all possible outcomes of a modeled phenomenon within a fixed future timeframe, given real data from the past, limited to another fixed timeframe.

For example, a model of a location of a particle suspended in fluid is a 1- dimensional projection of the location of a particle suspended in a fluid is modeled by Brownian motion. The parameters for the model are physical attributes of the fluid and general settings. For example, a mathematical model describing a location of particles having a drift μ and an infinitesimal variance σ given that at time t = 0 its value is 0, is as follows:

where B_t denotes a Brownian motion. In another example, a model modeling social network behavior is used. Networks are often modeled by random graph model(s) (such as preferential attachment graphs). Some measures of the network (such as density or diameter) or of a single node (such as betweenness) may be modeled by a conditional formula. As a specific example, the following model may be used. Given a dimension d, intensity parameter _ > 0 and a temperature parameter λ > 0, where the (spatial) Poisson point process on the d- dimensional hyper-cube [0; l]^d with intensity λ _t. In addition, at time t, every two points x; y in the hypercube are connected with an arc independently with probability p(dist(x; y)), where dist(x; y) denotes an Euclidean distance between x and y, and

Parameters of this model are a number of nodes, and a number of arcs, m (t )■-·-^■ y Bernoulli (p (dist (x_t, x_j )) ) .

l<-j<j <«■((_·

As both are monotone, another parameter is density.

In another example, the model is of a height of an ocean wave at specific location(s) or area(s). The model is modeled by a sine wave (with a given amplitude) and optionally a random noise (usually normal, with a given standard deviation), and the parameters may be estimated (in short timescales) quite accurately using the near past. Suppose an envelope wave height is h(t) and parameters a, μ and σ are given , a height may be modeled by the following formula: h(t)— N_t ÷ a (N_t f ,

where JY A^r(/t, σ¹ ) .

The geometric object may be a rectangle or a line parallel to axes of the dynamic graph in coordinate system with the parameters xo and xj representing leftmost and rightmost times respectively and yo and yj representing bottommost and topmost values respectively. The geometric object may be an ellipse with radii parallel to the axes and with c_x and c_y representing coordinates of the ellipse center (time, value), and r_x and r_y representing a radii lengths along time and value axes. The geometric object may be a Convex hull of a finite set of points, described by x and y coordinates ((¾ yi); (x„; y„)).

Optionally, by placing or reshaping the geometric object the user submits a query for a probability that a future value of the irregular time varying parameter will exceed or descend threshold defined by the geometric object. Optionally, the geometric object is placed on a coordinate system that includes the dynamic graph such that updating the dynamic graph with future values along the x axis that represents time will intersect with the geometric object at the probability which is calculated as described above.

Optionally, the probability is calculated by executing the simulation module 204 based on a function that receives as input a mathematical model, values from a timeframe of the feed, and a representation of the geometric object. The function is executed by the simulation module 204 quickly outputs a value representing the probability that the values of the irregular time varying parameter exceed or descend thresholds defined by the geometric object (e.g. graphically intersect with boundary(ies) of the geometric object). As a generalization, the simulation module 204 may estimate a probability of not exceeding or descending the thresholds (e.g. hitting the geometric object).

For example, when the irregular time varying parameter is a temperature of a particle which changes every second to a value, optionally normalized to represent a uniform value between a and b, regardless of the past. For example, the probability is calculated by an estimating function generated using the following template:

Input: model; parameters; feed; shape

Output: probability (p€ [0, 1])

if pamm iersg feed of shape, are wrong then

j throw;

else

estimate hit probability;

return kit pmbabiliig;

end where the geometric object is a rectangle and χο,χι, yo, yi respectively denote leftmost, rightmost, bottommost and topmost thresholds by. An exemplary estimating function is provided herein: Input: a: b ;¾; «·_; I

O tpu : p€ |0, 1

if b < then

J throw;

else

end

As shown at 106, an indication of the probability is presented in the visualization, in association with the geometric object. For example, the probability is presented inside an area defined by geometric object, presented in response to a selection of the area by the user, for instance by mouse hovering and/or the like.

As shown at 107, the probability and the threshold defined by the geometric object, for instance the one or more time dependent thresholds, may be iteratively calculated, each time based on a current location or shape of the adaptable geometric object. When recalculated, the indication of the probability is optionally updated as well, providing the user immediate feedback about the effect of the geometric object adaptation on the probability that an event occurs.

Optionally, as shown at 108, the probability is used to make a prediction. The prediction is optionally taken based a user input designating the presented probability as a basis for the prediction. For example, a prediction may be set by locking the geometric object, for instance by clicking or tapping on a button.

Optionally, when the predication is validated, for instance as depicted in 109, an indication is presented to the user. For example, the dynamic graph may be updated along the x-axis that represents time with current values. FIGs. 6A and 6B exemplify how the dynamic graph intersects with the geometric object when the prediction is realized. When the dynamic graph does not intersect with the geometric object but rather passes it along the x-axis, the prediction fails and not realized.

In some embodiments of the present invention, the current values are values of a currency and/or currencies ratio and/or, an index, a financial asset, such as a bond, a debenture, and a stock and/or financial assets ratio and the probability set by the geometric object is the probability that the value of the financial asset and/or the currency exceeds one or more thresholds during a defined future period. In such embodiments, a prediction embodied in the probability is estimation that the financial asset and/or the currency exceed one or more thresholds during a defined future period. In these embodiments, once a prediction is made and the geometric object is fixed, the prediction may be validated by locking the geometric object and updating the dynamic graph with current values of the financial asset and/or the currency along the x-axis that represents time. When the dynamic graph intersects with the geometric object the prediction is realized and when the dynamic graph does not intersect with the geometric object but rather passes it along the x-axis, the prediction fails and not realized.

For example, FIG. 5 is a schematic illustration of GUI 500 for submitting prediction on financial assets, according to some embodiments of the present invention. Optionally, the GUI 500 includes information extracted from a trading platform. For example, the GUI 500 includes a sales quotation window 506 for indicating a current sale price in the market, a buying quotation window 505 for indicating a current buy price in the market, a contract window 503 for indicating prediction terms, for instance the cost of making a prediction, a window 504 indicating a position of a current user in a trade, a window 501 indicating an amount of a financial asset in a traders possession, a window 502 indicating the amount of a tradable in play, a window 507 indicating the average transaction rate, a window 508 indicating parallel trading processes at hand, and a window visualizing coordinate system 509 wherein a dynamic graph of current values of the financial asset and a geometric object as described above are presented.

Optionally, the GUI 500 includes a window 509 for allowing a user to select one of a plurality of optional geometric objects, for instance a rectangular, a triangular, an ellipse, a circle, a curved line, a polygon and/or the like.

The methods as described above are used in the fabrication of integrated circuit chips. The descriptions of the various embodiments of the present invention have been presented for purposes of illustration, but are not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein was chosen to best explain the principles of the embodiments, the practical application or technical improvement over technologies found in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

It is expected that during the life of a patent maturing from this application many relevant methods and systems will be developed and the scope of the term a module, a processor, and a network is intended to include all such new technologies a priori.

As used herein the term "about" refers to ± 10 %.

The terms "comprises", "comprising", "includes", "including", "having" and their conjugates mean "including but not limited to". This term encompasses the terms "consisting of" and "consisting essentially of".

The phrase "consisting essentially of" means that the composition or method may include additional ingredients and/or steps, but only if the additional ingredients and/or steps do not materially alter the basic and novel characteristics of the claimed composition or method.

As used herein, the singular form "a", "an" and "the" include plural references unless the context clearly dictates otherwise. For example, the term "a compound" or "at least one compound" may include a plurality of compounds, including mixtures thereof.

The word "exemplary" is used herein to mean "serving as an example, instance or illustration". Any embodiment described as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments and/or to exclude the incorporation of features from other embodiments.

The word "optionally" is used herein to mean "is provided in some embodiments and not provided in other embodiments". Any particular embodiment of the invention may include a plurality of "optional" features unless such features conflict.

Throughout this application, various embodiments of this invention may be presented in a range format. It should be understood that the description in range format is merely for convenience and brevity and should not be construed as an inflexible limitation on the scope of the invention. Accordingly, the description of a range should be considered to have specifically disclosed all the possible subranges as well as individual numerical values within that range. For example, description of a range such as from 1 to 6 should be considered to have specifically disclosed subranges such as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numbers within that range, for example, 1, 2, 3, 4, 5, and 6. This applies regardless of the breadth of the range.

Whenever a numerical range is indicated herein, it is meant to include any cited numeral (fractional or integral) within the indicated range. The phrases "ranging/ranges between" a first indicate number and a second indicate number and "ranging/ranges from" a first indicate number "to" a second indicate number are used herein interchangeably and are meant to include the first and second indicated numbers and all the fractional and integral numerals therebetween.

It is appreciated that certain features of the invention, which are, for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of the invention, which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable subcombination or as suitable in any other described embodiment of the invention. Certain features described in the context of various embodiments are not to be considered essential features of those embodiments, unless the embodiment is inoperative without those elements.

Although the invention has been described in conjunction with specific embodiments thereof, it is evident that many alternatives, modifications and variations will be apparent to those skilled in the art. Accordingly, it is intended to embrace all such alternatives, modifications and variations that fall within the spirit and broad scope of the appended claims.

All publications, patents and patent applications mentioned in this specification are herein incorporated in their entirety by reference into the specification, to the same extent as if each individual publication, patent or patent application was specifically and individually indicated to be incorporated herein by reference. In addition, citation or identification of any reference in this application shall not be construed as an admission that such reference is available as prior art to the present invention. To the extent that section headings are used, they should not be construed as necessarily limiting.

Claims

WHAT IS CLAIMED IS:

1. A method of generating an interactive user interface adapted to visualize a time- series of values in relation to a user defined geometric object, comprising:

receiving a plurality of consecutive values of at least one irregular time varying parameter;

iteratively updating a visualization of a dynamic graph of said of at least one irregular time varying parameter according to said consecutive values to reflect a current change;

identifying at least one time dependent threshold at a future period according to user instructions to reshape or relocate at least one geometric object presented in said visualization;

calculating a probability that a future value of said time varying parameter exceeds or descends said at least one time dependent threshold during said future period; and

causing a device presenting said visualization to present an indication of said probability in association with said at least one geometric object.

2. The method of claim 1, wherein said plurality of consecutive values are acquired over a network from at least one data feed.

3. The method of claim 1, wherein said defining , said calculating and said causing are iteratively repeated each based on different instructions to reshape or relocate said at least one geometric object so as to allow said user to iteratively receive a plurality probabilities derived from a plurality of shapes or a plurality of shapes locations of said at least one geometric object.

4. The method of claim 1, wherein calculating is performed based on a model describing a time dependent phenomena.

5. The method of claim 1, wherein said geometric object is selected from a group consisting of an ellipse, a rectangular, a triangular, a circle and a curved line.

6. The method of claim 1, wherein said at least one time dependent threshold comprises a time dependent range defining a range of values as a threshold.

7. The method of claim 1, further comprising identifying an additional user input indicative of a prediction that is based on said probability and causing said device to update said dynamic graph based on new consecutive values from at least one feed along a possible collision course with said geometric object to provide a visual indication of a failure or a realization of said prediction.

8. The method of claim 1, wherein said dynamic graph and said at least one geometric object are presented on a common coordinate system.

9. The method of claim 8, wherein an X-axis of said common coordinate system represents time scale and a Y-axis of said common coordinate system represents a value scale for said at least one irregular time varying parameter.

10. The method of claim 1, wherein said at least one irregular time varying parameter is a value of a member selected from a financial asset, a currency ratio, a currency, a bond, an index, a stock, and a debenture.

11. The method of claim 1, wherein said user instructions comprises instructions to change a size of said geometric object.

12. The method of claim 1, wherein said user instructions comprises instructions to a location of said geometric object in relation to said dynamic graph.

13. A system of generating an interactive user interface adapted to visualize a time- series of values in relation to a user defined geometric object, comprising:

a network interface adapted to receive consecutive values of at least one irregular time varying parameter from at least one data feed;

at least one processor; and memory including computer-executable instructions that, based on execution by the at least one processor, configure the at least one processor to:

iteratively update a visualization of a dynamic graph of said of at least one irregular time varying parameter according to said consecutive values to reflect a current change;

identify at least one time dependent threshold at a future period according to user instructions to reshape or relocate at least one geometric object presented in said visualization;

calculate a probability that a future value of said time varying parameter exceeds or descends said at least one time dependent threshold during said future period; and cause a device presenting said visualization to present an indication of said probability in association with said at least one geometric object.

14. A software program product, comprising:

a non-transitory computer readable storage medium;

first program instructions to receive consecutive values of at least one irregular time varying parameter from at least one data feed;

second program instructions to update iteratively a visualization of a dynamic graph of said of at least one irregular time varying parameter according to said consecutive values to reflect a current change;

third program instructions to identify at least one time dependent threshold at a future period according to user instructions to reshape or relocate at least one geometric object presented in said visualization;

fourth program instructions to calculate a probability that a future value of said time varying parameter exceeds or descends said at least one time dependent threshold during said future period; and

fifth program instructions to cause a device presenting said visualization to present an indication of said probability in association with said at least one geometric object;

wherein the first, second, third, fourth and fifth program instructions are executed by at least one computerized processor from the non-transitory computer readable storage medium.