U.S. patent application number 14/756472 was filed with the patent office on 2016-01-07 for graphical representation of financial information.
The applicant listed for this patent is Cary D. Perttunen. Invention is credited to Cary D. Perttunen.
Application Number | 20160005120 14/756472 |
Document ID | / |
Family ID | 36318143 |
Filed Date | 2016-01-07 |
United States Patent
Application |
20160005120 |
Kind Code |
A1 |
Perttunen; Cary D. |
January 7, 2016 |
Graphical representation of financial information
Abstract
A programmed computer either provides a link to, provides a
user-viewable advertisement for, or receives a hit from an end user
who has hyperlinked from, a Web site that performs a method
comprising: determining, by at least one computer, which plurality
of financial items in a market sector are to be included in a
graphical representation thereof comprising a respective plurality
of contiguous regions each having a respective area based on a
respective net assets of its represented one of the financial items
and each having a respective interior color based on a respective
change in price of its represented one of the financial items; and
providing the Web site that displays the graphical representation.
Said determining comprises determining that a second financial item
in the market sector is not to be included in the graphical
representation based on its correlation with a first financial item
being less than zero.
Inventors: |
Perttunen; Cary D.; (Shelby
Township, MI) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Perttunen; Cary D. |
Shelby Township |
MI |
US |
|
|
Family ID: |
36318143 |
Appl. No.: |
14/756472 |
Filed: |
September 8, 2015 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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13999388 |
Feb 20, 2014 |
9135659 |
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14756472 |
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13986759 |
Jun 3, 2013 |
8659605 |
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13999388 |
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13573977 |
Oct 17, 2012 |
8456473 |
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13986759 |
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13507436 |
Jun 28, 2012 |
8294719 |
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13573977 |
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13136157 |
Jul 25, 2011 |
8228332 |
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13507436 |
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13066078 |
Apr 6, 2011 |
7990383 |
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13136157 |
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12925691 |
Oct 27, 2010 |
7928982 |
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13066078 |
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12592176 |
Nov 20, 2009 |
7830383 |
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12925691 |
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11820859 |
Jun 21, 2007 |
7626586 |
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12592176 |
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11431801 |
May 9, 2006 |
7239317 |
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11820859 |
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10388258 |
Mar 13, 2003 |
7046248 |
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11431801 |
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60403862 |
Aug 15, 2002 |
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60365125 |
Mar 18, 2002 |
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Current U.S.
Class: |
705/14.73 ;
705/37 |
Current CPC
Class: |
G06Q 20/10 20130101;
G06Q 40/00 20130101; G06T 11/206 20130101; G06Q 40/025 20130101;
G06Q 40/12 20131203; G06Q 30/0277 20130101; G06F 16/9558 20190101;
G06F 3/04842 20130101; G06F 3/0482 20130101; G06Q 40/04 20130101;
G06F 3/0481 20130101; G06T 2200/24 20130101; G06Q 40/06 20130101;
G06Q 50/188 20130101 |
International
Class: |
G06Q 40/04 20060101
G06Q040/04; G06T 11/20 20060101 G06T011/20; G06F 3/0484 20060101
G06F003/0484; G06F 3/0482 20060101 G06F003/0482; G06Q 30/02
20060101 G06Q030/02; G06F 17/30 20060101 G06F017/30 |
Claims
1. A computer-implemented method comprising: providing a link to a
Web site which performs a method comprising: determining, by at
least one computer, which plurality of financial items in a market
sector are to be included in a graphical representation thereof
comprising a respective plurality of contiguous regions each having
a respective area based on a respective net assets of its
represented one of the plurality of financial items and each having
a respective interior color based on a respective change in price
of its represented one of the plurality of financial items, wherein
the plurality of financial items comprises a first financial item,
and wherein said determining comprises determining that a second
financial item in the market sector is not to be included in the
graphical representation based on its correlation with the first
financial item being less than zero; and providing the Web site
that displays the graphical representation; wherein said providing
the link is performed by a computer programmed to perform same.
2. The computer-implemented method of claim 1 wherein the
respective area of a first region of the plurality of contiguous
regions is monotonically related to the respective net assets of
the first financial item.
3. The computer-implemented method of claim 2 wherein the first
region having the respective area that is monotonically related to
the respective net assets of the first financial item is
user-selectable to retrieve a quote associated with the first
financial item.
4. The computer-implemented method of claim 1 wherein the method
performed by the Web site further comprises initiating a
transaction involving one of the plurality of financial items using
the Web site.
5. The computer-implemented method of claim 1 wherein the first
financial item comprises an investment trust.
6. The computer-implemented method of claim 1 wherein the first
financial item comprises a mutual fund.
7. A computer-implemented method comprising: providing a
user-viewable advertisement for a Web site which performs a method
comprising: determining, by at least one computer, which plurality
of financial items in a market sector are to be included in a
graphical representation thereof comprising a respective plurality
of contiguous regions each having a respective area based on a
respective net assets of its represented one of the plurality of
financial items and each having a respective interior color based
on a respective change in price of its represented one of the
plurality of financial items, wherein the plurality of financial
items comprises a first financial item, and wherein said
determining comprises determining that a second financial item in
the market sector is not to be included in the graphical
representation based on its correlation with the first financial
item being less than zero; and providing the Web site that displays
the graphical representation; wherein said providing the
user-viewable advertisement is performed by a computer programmed
to perform same.
8. The computer-implemented method of claim 7 wherein the
respective area of a first region of the plurality of contiguous
regions is monotonically related to the respective net assets of
the first financial item.
9. The computer-implemented method of claim 8 wherein the first
region having the respective area that is monotonically related to
the respective net assets of the first financial item is
user-selectable to retrieve a quote associated with the first
financial item.
10. The computer-implemented method of claim 7 wherein the method
performed by the Web site further comprises initiating a
transaction involving one of the plurality of financial items using
the Web site.
11. The computer-implemented method of claim 7 wherein the first
financial item comprises an investment trust.
12. The computer-implemented method of claim 7 wherein the first
financial item comprises a mutual fund.
13. The computer-implemented method of claim 7 wherein the
user-viewable advertisement is communicated to an end user from an
advertisement provider other than the Web site.
14. The computer-implemented method of claim 7 wherein the
user-viewable advertisement is communicated to an end user from the
Web site.
15. A computer-implemented method comprising: receiving a hit from
an end user who has hyperlinked from a Web site which performs a
method comprising: determining, by at least one computer, which
plurality of financial items in a market sector are to be included
in a graphical representation thereof comprising a respective
plurality of contiguous regions each having a respective area based
on a respective net assets of its represented one of the plurality
of financial items and each having a respective interior color
based on a respective change in price of its represented one of the
plurality of financial items, wherein the plurality of financial
items comprises a first financial item, and wherein said
determining comprises determining that a second financial item in
the market sector is not to be included in the graphical
representation based on its correlation with the first financial
item being less than zero; and providing the Web site that displays
the graphical representation; wherein said receiving the hit is
performed by a computer programmed to perform same.
16. The computer-implemented method of claim 15 wherein the
respective area of a first region of the plurality of contiguous
regions is monotonically related to the respective net assets of
the first financial item.
17. The computer-implemented method of claim 16 wherein the first
region having the respective area that is monotonically related to
the respective net assets of the first financial item is
user-selectable to retrieve a quote associated with the first
financial item.
18. The computer-implemented method of claim 15 wherein the method
performed by the Web site further comprises initiating a
transaction involving one of the plurality of financial items using
the Web site.
19. The computer-implemented method of claim 15 wherein the first
financial item comprises an investment trust.
20. The computer-implemented method of claim 15 wherein the first
financial item comprises a mutual fund.
Description
COPYRIGHT NOTICE
[0001] A portion of the disclosure of this patent document contains
material which is subject to copyright protection. The copyright
owner has no objection to the facsimile reproduction by anyone of
the patent document or the patent disclosure, as it appears in the
Patent and Trademark Office patent file or records, but otherwise
reserves all copyright rights whatsoever. The following copyright
notice applies to the Claims section of this patent document:
.COPYRGT. 2015 Cary D. Perttunen.
CROSS REFERENCE TO RELATED APPLICATIONS
[0002] This application is a continuation of U.S. application Ser.
No. 13/999,388, filed Feb. 20, 2014, pending, which is a
continuation of U.S. application Ser. No. 13/986,759, filed Jun. 3,
2013, now U.S. Pat. No. 8,659,605, which is a continuation of U.S.
application Ser. No. 13/573,977, filed Oct. 17, 2012, now U.S. Pat.
No. 8,456,473, which is a continuation of U.S. application Ser. No.
13/507,436, filed Jun. 28, 2012, now U.S. Pat. No. 8,294,719, which
is a continuation of U.S. application Ser. No. 13/136,157, filed
Jul. 25, 2011, now U.S. Pat. No. 8,228,332, which is a continuation
of U.S. application Ser. No. 13/066,078, filed Apr. 6, 2011, now
U.S. Pat. No. 7,990,383, which is a continuation of U.S.
application Ser. No. 12/925,691, filed Oct. 27, 2010, now U.S. Pat.
No. 7,928,982, which is a continuation of U.S. application Ser. No.
12/592,176, filed Nov. 20, 2009, now U.S. Pat. No. 7,830,383, which
is a continuation of U.S. application Ser. No. 11/820,859, filed
Jun. 21, 2007, now U.S. Pat. No. 7,626,586, which is a continuation
of U.S. application Ser. No. 11/431,801, filed May 9, 2006, now
U.S. Pat. No. 7,239,317, which is a continuation of U.S.
application Ser. No. 10/388,258, filed Mar. 13, 2003, now U.S. Pat.
No. 7,046,248, which claims the benefit of U.S. Provisional
Application No. 60/365,125, filed Mar. 18, 2002, and U.S.
Provisional Application No. 60/403,862, filed Aug. 15, 2002. The
above-identified applications are hereby incorporated by reference
into the present application.
BACKGROUND OF THE INVENTION
[0003] 1. Field of the Invention
[0004] The present invention relates to methods and systems for
organizing and displaying financial information.
[0005] 2. Description of the Related Art
[0006] Fidelity Investments' Web site provides a visual
representation of stocks in the stock market, which is branded as
"Map of the Markets". Each of the stocks is represented by a
rectangular shape. An aggregate of the rectangular shapes is also
rectangular. Though all of the stocks are represented in a compact
form, it is unclear how a stock represented by one rectangle
specifically relates to stocks represented by neighboring
rectangles.
[0007] PCQuote.com introduced a graphical representation of a
single equity, branded as "Sniper". The representation has a bulls
eye design comprised of 13 sectors, each sector representing an
area of reconnaissance. The areas of reconnaissance include: stock
flow which indicates a relationship between a number of shares that
traded on the bid side versus a number of shares traded on the
offer side, quadrant distribution which indicates a total volume of
shares traded distributed across four quadrants to show what prices
are attracting the most activity, price rotation which numerically
indicates when price rotation activity favors buyer or sellers,
relative price rotation which visually indicates when price
rotation activity favors buyers or sellers, time rotation which
measures the acceptance of higher or lower prices, relative time
rotation which shows a current time period bias, "to target" which
indicates when a stock price is within 1/2 point of a forecast high
or low price, "to exit" which indicates a most extreme stop-out
price, buy/sell imbalance which measures where a majority of trades
are occurring, look-out signal which indicates a day's direction
for an equity, gatekeeper which provides a logical stop-out price,
stock and market direction which points out a path of least
resistance, and "center of the scope" which indicates whether
buyers or sellers are dominant across the board.
BRIEF DESCRIPTION OF THE DRAWINGS
[0008] The present invention is pointed out with particularity in
the appended claims. However, other features are described in the
following detailed description in conjunction with the accompanying
drawings in which:
[0009] FIG. 1 is a flow chart of an embodiment of a method of
relating a plurality of financial items by a tree;
[0010] FIG. 2 is a flow chart of an embodiment of a method of
determining regions to represent tree-related financial items;
[0011] FIG. 3 is a flow chart of an embodiment of a method of
determining angles to define the regions;
[0012] FIG. 4 is a flow chart of an embodiment of a method of
determining radii to define the regions; and
[0013] FIG. 5 shows an example of regions which represent
tree-related financial items;
[0014] FIGS. 6, 7(A-B) and 8 are a flow chart of an embodiment of a
method of further organizing the financial item information;
[0015] FIG. 9 shows an example of a rearrangement of the regions in
FIG. 5;
[0016] FIG. 10 is an example of a tree which relates fourteen
stocks A-N to a base stock S;
[0017] FIG. 11 is a first example of regions to represent the
fourteen stocks A-N and the base stock S related by the tree in
FIG. 10; and
[0018] FIG. 12 is a second example of regions to represent the
fourteen stocks A-N and the base stock S related by the tree in
FIG. 10.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0019] Disclosed herein are improved methods of organizing and
representing information pertaining to a plurality of financial
items. Examples of the financial items include, but are not limited
to, stocks, equities, bonds, commodities, currencies, options,
futures, mutual funds, market indices, sector indices, and
investment trusts. The financial items are organized into a tree
based on a degree of similarity between pairs of the items. The
financial items may be further organized by determining a
depth-first search of the tree having an optimum value associated
therewith. The associated value of a depth-first search is based
upon an order of considering financial items in the tree, and
similarity values between pairs of financial items in the tree.
[0020] Based on the tree and optionally the optimal depth-first
search, parameters which define regions to represent the financial
items are determined. Each region has a controlled area based upon
a predetermined value, herein referred to as a weight, associated
with the financial item. Examples of weight values associated with
any herein-mentioned financial item include, but are not limited
to, a price of the financial item, a trading volume of the
financial item, a market capitalization associated with the
financial item, a dollar-measured trading volume of the financial
item, a book value associated with the financial item, net assets
of the financial item, earnings associated with the financial item,
and other properties of the financial item.
[0021] Preferably, each region has an area monotonically related,
and more preferably proportional, to its weight. For example,
consider a first region representing a first financial item with a
first weight value, and a second region representing a second
financial item with a second weight value. If the first weight
value is greater than the second weight value, the first region has
a first area greater than a second area of the second region.
[0022] The weight values need not be determined for cases in which
each of the financial items either is unweighted or has the same
weight value. In these cases, the hereinafter-described
computations can be simplified by assigning a weight of one to each
of the financial items. A plurality of regions, each having the
same area, results in these cases.
[0023] The regions may be visibly displayed to provide a visible
representation of the financial information, and/or used to provide
an input interface to allow a user-initiated selection of a portion
of the financial information. Optionally, the regions may be
printed to produce a hard copy representation of the financial
information.
[0024] Each non-root financial item in the tree is represented by a
corresponding concave region such as an annulus sector. In
describing shapes in this patent application, the term "annulus
sector" is meant to be synonymous with "sector of an annulus". As
such, an approximately circular annulus sector is meant to describe
an approximate sector of a circular annulus. An approximately
circular annulus sector is definable by a first line segment, a
second line segment, a first approximately circular arc, and a
second approximately circular arc. The first approximately circular
arc is at least partially definable by a first focus point and a
first radius. The second approximately circular arc is at least
partially definable by a second focus point and a second radius.
Preferably, the first focus point and the second focus point are
located substantially at the same point. It is further preferred
that the first radius and the second radius differ so that the
region has a radial width.
[0025] The first approximately circular arc is further definable by
a first starting angle and either a first ending angle or a first
arc angle. The second approximately circular arc is further
definable by a second starting angle and either a second ending
angle or a second arc angle. Preferably, the first arc angle and/or
the second arc angle are non-zero so that the region has an angular
width. Also preferably, the first starting angle is substantially
the same as the second starting angle, the first ending angle is
substantially the same as the second ending angle, and the first
arc angle is substantially the same as the second arc angle.
[0026] The first line segment and the second line segment are
preferably oriented substantially radially with respect to a point.
Preferably, this point is located substantially at the first focus
point and the second focus point. In this case, it is also
preferred that the first line segment be oriented substantially
radially with respect to the point at an angle substantially the
same as the first starting angle and the second starting angle, and
that the second line segment be oriented substantially radially
with respect to the point at an angle substantially the same as the
first ending angle and the second ending angle.
[0027] The root financial item may be represented by a
substantially convex shape. Preferably, the substantially convex
shape is at least partially defined by at least a portion of an
approximate circle. Examples of the substantially convex shape
having this preferred form include, but are not limited to, an
approximate sector of a circle, and approximately an entire
circle.
[0028] It is noted that use of the terms "approximate" and
"approximately" for the herein-disclosed regions, shapes, and
curves include non-perfect representations of said regions, shapes,
and curves using a display device, a hard copy device such as a
printer, and/or an input device. For example, a pixel-based display
device can display a plurality of discrete pixels to approximate
any of the herein-disclosed regions, shapes, and curves. As another
example, a display device may distort an intended region, shape, or
curve to produce an approximation thereof. Examples of this
distortion include, but are not limited to, a distortion due to
pixel aspect ratio, a distortion due to a non-planar display
screen, and a distortion due to rasterization.
[0029] Approximations of regions, shapes, and curves may also be
generated in software or firmware. For example, a curve may be
represented by a piecewise approximation. An example of a piecewise
approximation of a curve includes, but is not limited to, a
piecewise linear approximation. Further examples include a curve
being approximated by a simplified equation therefor, and a curve
being approximated by a plurality of display points. Examples of
ways to approximate a shape or a region include, but are not
limited to, using a plurality of points to approximate the shape or
region, and using a polygon to approximate the shape or region.
[0030] Use of discrete parameter values to represent a region,
shape, or curve also may result in an approximation thereof. For
example, a circular arc may be represented by an integral center
coordinate, an integral radius, an integral start angle, and an
integral arc width. In this case, and other cases, either round-off
or truncation of parameter values to comply with a discrete
representation results in an approximation of a desired region,
shape, or curve.
[0031] It is noted that a shape need not be precisely convex to be
substantially convex. Examples of insubstantial concavities in a
substantially convex shape include, but are not limited to, those
which may result from an approximation of the shape or a curve
which at least partially defines the shape, and those present where
endpoints of two curves imprecisely meet.
[0032] Before proceeding, a review of graph-related terminology is
provided. A graph is definable by a set of nodes and a set of edges
joining or associating different pairs of distinct nodes. The edges
in the graph may be either directed or undirected. It is noted that
alternative terminology may be used to describe the graph. Examples
of synonyms of "node" include, but are not limited to, "vertex" and
"state". Examples of synonyms of "edge" include, but are not
limited to, the terms "arc" and "link". Therefore, the
herein-disclosed methods, articles, apparatus, and examples should
not be limited by the selected terminology used to describe the
graph.
[0033] A first node is said to be adjacent to a second node if
there is an edge from the first node to the second node. A path is
definable by a sequence of nodes wherein each consecutive pair of
nodes in the sequence is adjacent.
[0034] A tree is a graph having a unique path from a designated
node, called a root node, to each of its other nodes. If the tree
is undirected, then any of its nodes can be designated to be the
root node. An undirected tree can be made into a directed tree by
directing all edges away from the designated root node.
[0035] Each node in a directed tree, except for the root node, is a
child node of a unique parent node from which an edge is directed
thereto. Nodes having the same parent node are called siblings.
Nodes of a directed tree with no children are called leaf nodes.
Nodes having at least one child are called internal nodes.
[0036] A level number of a node is defined as the number of edges
in the path between the node and the root node. The height of the
tree is the largest level number of any node.
[0037] If each internal node of a rooted tree has m children, the
tree is called an m-ary tree. If m=1, the tree is unary. If m=2,
the tree is binary. If m=3, the tree is ternary.
[0038] FIG. 1 is a flow chart of an embodiment of a method of
relating a plurality of financial items by a tree. Each of the
financial items is represented by a corresponding node of the tree.
It is preferred that the tree is non-unary. By being non-unary, the
tree has at least one internal node with two or more child nodes.
It is also preferred that the tree has a height of at least two. It
is further preferred that the tree has more leaf nodes than a
number of child nodes emanating from its root node.
[0039] As indicated by block 20, the method comprises selecting one
of the financial items as a base item. The base item is assigned as
the root node of the tree. Typically, the base item is one whose
relationship with other financial items is of interest. For
example, an investor may be interested in how a particular stock
relates to other stocks. In this case, the particular stock is
selected as the base item.
[0040] As indicated by block 22, the method comprises determining a
first plurality of similarity values between the base item and a
plurality of other financial items. Each of the first plurality of
similarity values indicates a degree of similarity or correlation
between the base item and a corresponding one of the other
financial items.
[0041] As indicated by block 24, the method comprises determining a
second plurality of similarity values between a corresponding
plurality of pairs of the other financial items. Each of the second
plurality of similarity values indicates a degree of similarity or
correlation between a corresponding pair of the other financial
items.
[0042] The similarity values may be based on a correlation between
trading behaviors of two financial items. For example, the
similarity values may be based on either a correlation coefficient
between a price behavior of two financial items or a correlation
coefficient between a volume behavior of two financial items. A
more specific example is the similarity value being based on a
correlation coefficient of the end-of-day price data for two stocks
over a year. In general, the correlation coefficient may be
determined over any time length of data (e.g. a day, a week, a
month, a year-to-date, a year or multiple years) with any suitable
sampling interval of data (e.g. one minute, 5 minutes, 30 minutes,
one day, one week, one month or one year) for any type of data
(e.g. price, volume or dollar volume).
[0043] As indicated by block 26, the method comprises determining
an optimum path tree based on the first plurality of similarity
values and the second plurality of similarity values. The optimum
path tree indicates a respective optimum path between the base item
and each of the other financial items.
[0044] The optimum path between the base item and another financial
item has an optimum function value of similarity values between the
base item and the other financial item. Examples of the function
whose optimum value dictates the optimum path include, but are not
limited to, a sum of similarity values between the base item and
the other financial item, and a product of similarity values
between the base item and the other financial item. To determine an
optimum product of similarity values, an additive optimum path
algorithm may be performed on a logarithm of the similarity values.
For example, if the similarity values are numerical values between
0% and 100%, then an additive minimum path algorithm may be
performed on a negative logarithm of the non-zero similarity
values, e.g. -log(similarity value), to determine a maximum product
of similarity values.
[0045] Each similarity value may be set to a large constant if a
correlation coefficient between its two financial items is less
than or equal to zero, and set to the negative logarithm of the
correlation coefficient if the correlation coefficient is greater
than zero. In this case, an additive minimum path algorithm is
performed using the aforementioned similarity values. The large
constant is selected so that adjacent pairs of financial items in
each minimum path have a correlation coefficient greater than
zero.
[0046] As is known in the art of network algorithms, examples of
algorithms to compute the shortest paths include, but are not
limited to, Dijkstra's algorithm and Floyd's algorithm. Those
having ordinary skill can review shortest path algorithms on pp.
123-127 of A. Tucker, Applied Combinatorics, Second Edition, John
Wiley & Sons, 1984.
[0047] As an alternative to block 26, alternative types of spanning
trees may be determined based upon the first plurality of
similarity values and the second plurality of similarity values.
For example, an optimum spanning tree such as a minimum spanning
tree may be determined. The optimum spanning tree has an optimum
function value of similarity values. Examples of the function whose
optimum value dictates the optimum spanning tree include, but are
not limited to, a sum of similarity values, and a product of
similarity values. To determine an optimum product of similarity
values, an additive optimum spanning tree algorithm may be
performed on a logarithm of the similarity values.
[0048] As is known in the art of network algorithms, examples of
algorithms to compute a minimum spanning tree include, but are not
limited to, Kruskal's algorithm and Prim's algorithm. Those having
ordinary skill can review minimum spanning trees on pp. 127-131 of
A. Tucker, Applied Combinatorics, Second Edition, John Wiley &
Sons, 1984.
[0049] As indicated by block 30, the method comprises representing
the tree in a computer-readable form using a computer-readable
medium. Various computer-readable data structures can be used to
represent the tree in the computer-readable form using the
computer-readable medium. Based on the computer-readable form of
the tree, regions to represent the financial items can be
determined as described with reference to FIGS. 2 to 5.
[0050] FIG. 2 is a flow chart of an embodiment of a method of
determining regions to represent tree-related financial items. Each
financial item is represented by a corresponding node of a tree.
For each non-root node in the tree (as indicated by block 40), a
first value associated with the node is determined (as indicated by
block 42). The first value is based on (W+C1)/C2, wherein W denotes
a weight of the node, C1 denotes a cumulative weight of all
descendants of the node, and C2 denotes a cumulative weight of all
descendants of a parent of the node.
[0051] For each non-root node in the tree (as indicated by block
44), a second value associated with the node is determined (as
indicated by block 46). The second value is equal to a product of
the first values for all non-root nodes in a tree-defined path from
the root node to the node.
[0052] As indicated by block 50, the method comprises determining
angles to define the regions based on the second values. The angles
may be based on an overall angular width of an aggregation of the
regions, herein denoted by MAXIMUM_ARC_ANGLE, and an initial
starting angle of the aggregation of the regions, herein denoted by
FIRST_START_ANGLE. In general, the MAXIMUM_ARC_ANGLE value can be
any value, such as less than 180 degrees, about equal to 180
degrees, greater than 180 degrees but less than 360 degrees, or
about equal to 360 degrees. If the MAXIMUM_ARC_ANGLE is equal to
360 degrees, the region representing the root node is a circle. If
the MAXIMUM_ARC_ANGLE is less than 360 degrees, the region
representing the root node is a sector of a circle having a start
angle and an end angle.
[0053] The start angle for the root node is set to the
FIRST_START_ANGLE value. The end angle for the root node is set to
a sum of the FIRST_START_ANGLE value and the MAXIMUM_ARC_ANGLE
value. A resulting arc angle for the root node is equal to the
MAXIMUM_ARC_ANGLE value.
[0054] An embodiment of a method of determining angles associated
with non-root nodes is shown in FIG. 3. As indicated by block 60,
the method comprises initializing a variable, herein denoted by
CHILD_START_ANGLE, of the root node. The CHILD_START_ANGLE of the
root node is initialized to be equal to FIRST_START_ANGLE. As
indicated by block 62, a variable denoted as LEVEL is prepared to
increment from 1 to a height of the tree. As indicated by block 64,
the method comprises performing acts for each node having a level
number equal to the LEVEL variable. The acts comprise determining a
start angle for the node (block 66), an arc angle for the node
(block 68), and an end angle for the node (block 70). The start
angle is equal to the CHILD_START_ANGLE value of the parent of the
node. The arc angle is equal to a product of the second value of
the node and the MAXIMUM_ARC_ANGLE value. The end angle is equal to
a sum of the start angle and the arc angle. Alternatively, the end
angle may be equal to the start angle minus the arc angle.
[0055] The acts further comprise updating the CHILD_START_ANGLE of
the parent of the node (block 72), and setting the
CHILD_START_ANGLE of the node (block 74). The CHILD_START_ANGLE of
the parent of the node is updated to be equal to the end angle for
the node. The CHILD_START_ANGLE of the node is set to the start
angle for the node. Optionally, the act in block 74 is omitted if
the node is a leaf node.
[0056] As indicated by block 76, flow of the method is directed
back to block 64 if there is a further node having a level number
equal to the LEVEL variable. Otherwise, flow of the method is
directed to block 80. From block 80, if there is a further level to
process, flow of the method is directed to block 62 wherein the
LEVEL variable is incremented. If there are no further levels to
process, the method is completed.
[0057] Referring back to FIG. 2, an act of determining radii to
define the regions is performed as indicated by block 82.
Preferably, the region representing the root node is definable by a
single radius. Thus, if the MAXIMUM_ARC_ANGLE is equal to 360
degrees, the region representing the root node may be a circle; and
if the MAXIMUM_ARC_ANGLE is less than 360 degrees, the region
representing the root node may be a sector of a circle.
[0058] FIG. 4 is a flow chart of an embodiment of a method of
determining radii to define the regions. The radii may be based on
an overall radius of the aggregate of the regions, herein denoted
by MAXIMUM_RADIUS. To simplify subsequent computations, a constant
K defined as the MAXIMUM_ARC_ANGLE times the square of the
MAXIMUM_RADIUS, divided by the cumulative weight of all nodes in
the tree, is determined.
K=MAXIMUM_ARC_ANGLE*(MAXIMUM_RADIUS).sup.2/(cumulative weight of
all nodes in the tree)
[0059] As indicated by block 90, an outer radius for the root node
is determined. The outer radius for the root node is equal to the
square root of: K times the weight of the root node divided by the
arc angle for the root node.
[0060] As indicated by block 92, a variable denoted as LEVEL is
prepared to increment from 1 to a height of the tree. As indicated
by block 94, the method comprises performing acts for each node
having a level number equal to the LEVEL variable. The acts
comprise determining an inner radius for the node (block 96) and an
outer radius for the node (block 100). The inner radius for the
node is determined to be equal to the outer radius for the parent
of the node. The outer radius for the node is equal to the square
root of: the sum of square of the inner radius of the node and K
times the weight of the node divided by the arc angle for the node.
Optionally, if the node is a leaf node, the outer radius of the
node can be determined to be equal to the MAXIMUM_RADIUS value
without performing the aforementioned computation.
[0061] As indicated by block 102, flow of the method is directed
back to block 94 if there is a further node having a level number
equal to the LEVEL variable. Otherwise, flow of the method is
directed to block 104. From block 104, if there is a further level
to process, flow of the method is directed to block 92 wherein the
LEVEL variable is incremented. If there are no further levels to
process, the method is completed.
[0062] Referring back to FIG. 2, an act of providing the regions to
represent the nodes in the tree is performed, as indicated by block
110. Each non-root node is represented by a corresponding region
definable with respect to a common focus point by the start angle,
end angle, inner radius, and outer radius. The root node is
represented by a region definable with respect to the common focus
point by an outer radius, and optionally a start angle and an end
angle.
[0063] The resulting aggregation of regions has many desirable
qualities. For any tree configuration, the herein-disclosed method
provides a one-to-one correspondence between the financial items
and the regions. By one-to-one correspondence, it is meant that
each financial item is represented by one and only one of the
regions, and each of the regions represents one and only one of the
financial items.
[0064] Further, the aggregation of regions is contiguous for any
tree configuration, which in the context of this disclosure is
broadly inclusive of describing the regions as being either
neighboring or adjacent throughout the aggregation. For example,
adjacent pairs of regions which are spaced slightly apart are
considered to be contiguous.
[0065] Still further, the aggregation of regions defines an
identifiable boundary at its periphery for any tree configuration.
If the MAXIMUM_ARC_ANGLE value is 360 degrees, the boundary
comprises a circle having a radius equal to the MAXIMUM_RADIUS
value. If the MAXIMUM_ARC_ANGLE value is less than 360 degrees, the
boundary comprises an arc having a radius equal to the
MAXIMUM_RADIUS value, a start angle equal to the FIRST_START_ANGLE
value, and an arc angle equal to the MAXIMUM_ARC_ANGLE value.
[0066] Yet still further, for any tree configuration, the
herein-disclosed method provides a one-to-one correspondence
between leaf nodes and regions adjacent the circle or arc boundary.
By one-to-one correspondence, it is meant that all the leaf nodes
are represented by regions adjacent the circle or arc boundary, and
all regions adjacent the circle or arc boundary represent leaf
nodes. Thus, a user can easily identify the leaf nodes of the tree
even if the branches of the tree have different lengths.
[0067] Also, for any tree configuration, the area of each region is
proportional to the weight of its corresponding financial item. If
the nodes are either equally weighted or unweighted, each of the
regions has the same area for any tree configuration.
[0068] It is noted that there are various scenarios in which
regions having areas strictly unproportional to their weights have
areas substantially proportional to their weights. Examples of
sources of deviation in areas which still provide substantially
proportional areas, but are not limited to, approximations used to
display the regions (see the discussion herein of "approximate" and
"approximately"), approximations in the mathematical processes used
to calculate the areas and/or the parameters which define the
regions, and round-off and/or truncation errors in the mathematical
processes used to calculate the areas and/or the parameters which
define the regions.
[0069] It is noted that any values or parameters which are
herein-described as being the same or equal can be slightly
different, i.e. either about or approximately the same, either
about or approximately equal. In a particular example, the inner
radius of one or more nodes (determined in block 96 in FIG. 4) can
be modified to be slightly greater than the outer radius of its
parent to mitigate a possibility of radially-overlapping regions.
Another way to mitigate radially-overlapping regions comprises
modifying the outer radius of one or more nodes to be slightly less
than the inner radius of each of its children. In either of the
above two examples, the inner radius and the outer radius are still
considered to be about equal. Similarly, the start angle and/or end
angle of each region can be compressed toward the center of its
region to mitigate a possibility of angularly-overlapping regions.
In this case, angles of angularly adjacent regions are still
considered to be about equal. In any of the above examples, the
resulting area of the region is still considered to be about
monotonically-related and/or about proportional to the weight of
its corresponding node.
[0070] An example of regions which represent equally-weighted
tree-related financial items is shown in FIG. 5. A semicircular
region 130 represents a base financial item (i.e. a root node of a
tree). Circular annulus sectors, a representative one indicated by
reference numeral 132, represent other financial items whose
relationship with the base financial item is of interest (i.e.
non-root nodes of the tree).
[0071] All of the leaf nodes are represented by regions adjacent a
semicircular arc 134 which partially defines a periphery of the
aggregation of the regions. The regions are approximated by
rounding the start angle and the end angle to an integral number of
degrees, and rounding the outer radius to an integral number of
display units. All of the regions have approximately the same
area.
[0072] The circular annulus sectors comprise a first circular
annulus sector region 136 to represent a first financial item, a
second circular annulus sector region 140 to represent a second
financial item and a third circular annulus sector region 142 to
represent a third financial item. The second and third circular
annulus sector regions 140 and 142 are radially adjacent the first
circular annulus sector region 136. The second circular annulus
sector region 140 is angularly adjacent the third circular annulus
sector region 142. A radial width of the second circular annulus
sector region 140 differs from a radial width of the third annulus
sector region 142.
[0073] The relationship of the first, second and third financial
items to the base financial item is intuitively represented by the
juxtaposition of their associated regions. By virtue of the first
region 136 being radially interposed between the region 130 and the
regions 140 and 142, the base financial item is more similar to the
first financial item than to the second and third financial
items.
[0074] The act of providing the regions may comprise outputting a
signal to display the regions and/or outputting a signal to make
the regions user-selectable, to provide a user interface. The at
least one signal to provide the user interface may be communicated
by a computer data signal. The computer data signal may be
communicated via a computer network. Examples of the computer
network include, but are not limited to, an intranet, an internet
and an extranet. The computer data signal may include computer
program code to assist in providing the user interface. Of
particular interest are signals representative of code in a markup
language such as HTML (hypertext markup language).
[0075] The user-selectable regions can be provided in a variety of
ways. Of particular interest is use of either a client-side image
map or a server-side image map to provide the user-selectable
regions in relation to an image of the regions. Here, a
user-selectable region can be provided using HTML tags to
approximate any of the herein-disclosed shapes, including convex
shapes such as sectors and concave shapes such as annular sectors.
In particular, the polygon area definition in an AREA tag inside a
MAP tag can be used to provide a user-selectable region having one
of the herein-disclosed shapes.
[0076] It is noted that a markup language improvement is
contemplated which would provide an annular sector area definition
and a sector area definition in an AREA tag inside a MAP tag. For
example, a sector of a circle could be definable by an AREA tag
having the following form: [0077] <AREA SHAPE="circle_sector"
[0078] COORDS="x, y, x1, y1, x2, y2, x3, y3" [0079] HREF="URL">
where (x,y) are coordinates of a center point of an arc-defining
circle, (x1,y1) are coordinates of a point either on or collinear
with a first radial line segment, (x2,y2) are coordinates of a
point either on or collinear with a second radial line segment,
(x3,y3) are coordinates of a point either on or co-circular with
the circular arc, and URL is a computer address such as a uniform
resource locator which is linked to in response to a user selection
of the region. It is noted that the HREF="URL" portion can replaced
by one or more event codes (e.g. onclick, ondblclick, onmousedown,
onmousemove, onmouseover, onmouseout, onmouseup) each followed by
an associated function.
[0080] A sector of a circular annulus could be definable by an AREA
tag having the following form: [0081] <AREA
SHAPE="annulus_sector" [0082] COORDS="x, y, x1, y1, x2, y2, x3, y3,
x4, y4" [0083] HREF="URL"> where (x,y) are coordinates of a
center point of a first arc-defining circle and a second
arc-defining circle, (x1,y1) are coordinates of a point either on
or collinear with a first radial line segment, (x2,y2) are
coordinates of a point either on or collinear with a second radial
line segment, (x3,y3) are coordinates of a point either on or
co-circular with the first circular arc, (x4,y4) are coordinates of
a point either on or co-circular with the second circular arc, and
URL is a computer address such as a uniform resource locator which
is linked to in response to a user selection of the region. It is
noted that the HREF="URL" portion can replaced by one or more event
codes (e.g. onclick, ondblclick, onmousedown, onmousemove,
onmouseover, onmouseout, onmouseup) each followed by an associated
function.
[0084] With this improvement, a user interface creator can more
directly implement user-selectable regions having some of the
herein-disclosed shapes.
[0085] The at least one signal is communicated by a waveform
representative thereof through a communication medium. Examples of
the waveform and the communication medium include, but are not
limited to, an optical waveform through an optical medium, an
electronic waveform through an electronic medium, and an
electromagnetic waveform through an electromagnetic medium.
[0086] Based on the at least one signal, the regions may be
displayed by a display device. Examples of the display device
include, but are not limited to, a computer monitor, a television,
a liquid crystal display, a cathode ray tube, and a gas plasma
display. For a computer data signal, the at least one signal is
received by a computer in communication with the computer network.
The computer generates a display signal to display the region on
the display device.
[0087] Optionally, the regions representing the financial items may
be arranged to optimize or otherwise improve a function of
similarity values between pairs of financial items represented by
angularly-adjacent regions, while maintaining the radial-adjacency
between adjacent financial items in the tree. FIGS. 6, 7(A-B) and 8
provide a flow chart of an embodiment of a method of further
organizing the financial item information.
[0088] As indicated by block 152, the method comprises providing a
depth-first search sequence for considering financial items in the
tree. An initial depth-first search sequence may be provided by
initializing, for each of the internal items having at least two
child items in the tree, a respective sequence for considering its
respective child items.
[0089] As indicated by block 154, the method comprises providing a
memory which is to indicate, for each level number from one to a
height of the tree, a last-considered item associated with the
level number in the depth-first search sequence. The memory may be
initialized to indicate that no items have been considered at each
level number from one to the height of the tree.
[0090] As indicated by block 156, the method comprises considering
a first non-root item in the depth-first search sequence as a
current item. As indicated by block 160, the method comprises
determining if the current item is an internal item of the tree. If
the current item is an internal item of the tree, an act of
determining if at least one of the leaf items had been previously
considered in the depth-first search sequence is performed (block
162).
[0091] If at least one of the leaf items had been previously
considered in the depth-first search sequence, a similarity value
between the current item and the last-considered item associated
with the level number of the current item is used to determine a
value associated with the depth-first search sequence (block 164).
As indicated by block 166, the current item is indicated as the
last-considered item associated with the level number of the
current item.
[0092] Referring back to block 160, if the current item is not an
internal item of the tree, and thus is a leaf item of the tree, a
subprocess is performed for each level number L from the level
number of the current item to the height of the tree (block 170).
The subprocess comprises determining if at least one of the leaf
items had been previously considered in the depth-first search
sequence (block 172) and determining if the last-considered item
associated with level number L is the same as the last-considered
item associated with level number L-1 (block 174). Since the root
item is always the last-considered item associated with level
number 0, the last-considered item associated with level number 1
always differs from the last-considered item associated with level
number 0. Thus, block 174 may be skipped for L=1.
[0093] If at least one of the leaf items has been previously
considered in the depth-first search sequence and the
last-considered item associated with level number L differs from
the last-considered item associated with level number L-1, a
similarity value between the current item and the last-considered
item associated with the level number L is used to determine a
value associated with the depth-first search sequence (block 180).
As indicated by block 182, the subprocess is performed one or more
times for each level number indicated in block 170.
[0094] Each of the similarity values described with reference to
blocks 164 and 180 indicates a degree of similarity or correlation
between a corresponding pair of financial items. The similarity
values described with reference to blocks 164 and 180 may be the
same as the second plurality of similarity values used to determine
the tree. Alternatively, the similarity values described with
reference to blocks 164 and 180 may differ from the second
plurality of similarity values used to determine the tree.
[0095] As indicated by block 186, a subprocess is performed for
each level number L from the level number of the current item to
the height of the tree. As indicated by block 190, the current item
is indicated as the last-considered item associated with the level
number L. As indicated by block 192, the subprocess is performed
one or more times for each level number indicated in block 186.
[0096] As indicated by block 194, a subsequent item in the
depth-first search sequence is considered as the current item. Flow
of the method may be directed back to block 156 until no subsequent
items exist in the depth-first search sequence. Optionally, block
156 may be modified to further iterate, after the final item, from
the first non-root item to the first leaf item. In this case, items
from the first non-root item to the first leaf item are considered
twice.
[0097] The value associated with the depth-first search sequence is
a function of the similarity values identified in blocks 164 and
180. For example, the function may be based on a sum of the
aforementioned similarity values, a product of the aforementioned
similarity values, an average of the aforementioned similarity
values such as either an arithmetic mean or a geometric mean of the
aforementioned similarity values, a maximum of the aforementioned
similarity values, or a minimum of the aforementioned similarity
values.
[0098] The function may be partially evaluated each time a
similarity value is identified in blocks 164 and 180.
Alternatively, the function may be evaluated after all of the
similarity values have been identified in blocks 164 and 180 for
all iterations of block 156. In general, the similarity values
identified in blocks 164 and 180 may be used at any time to
evaluate the function and thus determine the value associated with
the depth-first search sequence.
[0099] As indicated by block 196, the depth-first search sequence
is modified. The depth-first search sequence may be modified by
modifying the sequence for considering child items for each of at
least one of the internal items having at least two child items in
the tree. Flow of the method is directed back to block 154 to
initiate the process of determining a value associated with the
modified depth-first search sequence. The memory provided for
indicating last-considered items in the initial depth-first search
sequence may be either different or the same as the memory provided
for indicating last-considered items for the modified depth-first
search sequence.
[0100] In this way, values associated with a plurality of
depth-first search sequences of the tree are determined.
Optionally, values associated with all possible depth-first search
sequences of the tree may be determined. The number of possible
depth-first search sequences of the tree is equal to the product of
the factorial of each internal node's number of children nodes.
[0101] Using an embodiment of the herein-disclosed method for some
functions, two depth-first search sequences have the same value
associated therewith if one has an order of considering leaf items
which is the reverse of the other. Thus, in these and other cases,
values associated with at most half of all possible depth-first
search sequences of the tree may be determined. The depth-first
search sequences which are considered may be limited by prohibiting
reverse-equivalent sequences for considering child items of the
root item. A branch-and-bound approach, for example, may be used to
limit consideration to less than half of all possible depth-first
search sequences.
[0102] Using another embodiment of the herein-disclosed method for
some functions, two depth-first search sequences have the same
value associated therewith if one has an order of considering leaf
items which is either a cyclic-equivalent or a reverse
cyclic-equivalent of the other. For example, a sequence A-B-C-D has
three cyclic-equivalent sequences B-C-D-A, C-D-A-B and D-A-B-C, and
four reverse cyclic-equivalent sequences D-C-B-A, A-D-C-B, B-A-D-C
and C-B-A-D. Thus, in these and other cases, values associated with
at most M/(2*N) sequences may be determined, where M is the number
of all possible depth-first search sequences of the tree, and N is
the number of child items of the root item. The depth-first search
sequences which are considered may be limited by prohibiting
cyclic-equivalent and reverse cyclic-equivalent sequences for
considering child items of the root item. A branch-and-bound
approach, for example, may be used to limit consideration to less
than M/(2*N) sequences.
[0103] As indicated by block 200, the method comprises determining
which evaluated depth-first search sequence has an optimum value
associated therewith. Depending on the function used to determine
values associated with depth-first search sequences, this act may
comprise either determining which depth-first search sequence has a
maximum associated value, or determining which depth-first search
sequence has a minimum associated value.
[0104] As indicated by block 202, a planar depiction of the tree is
provided in which the items are ordered according to the
depth-first search sequence having the optimum value. The planar
depiction may comprise a plurality of regions to visibly represent
the items, wherein adjacent items in the tree are represented by
radially-adjacent regions, and wherein pairs of items identified in
blocks 164 and 180 for the depth-first search sequence having the
optimum value are represented by angularly-adjacent regions. In
this case, if the acts in FIGS. 2-4 had been performed to determine
parameters defining the regions for a non-optimal arrangement, only
the angles defining the regions need to be determined for the
optimal arrangement. Thus, the acts in FIG. 3 are performed again,
where the order of the nodes considered in block 64 is dictated by
the order of the nodes in the optimum depth-first search sequence.
The optimal arrangement does not affect the inner radius and outer
radius of each region. For example, the regions in FIG. 5 may be
rearranged as shown in FIG. 9 after performing the method described
with reference to FIGS. 6-8 and recalculating the angles as
described with reference to FIG. 3. Alternatively, the acts in
FIGS. 2-4 can be performed to determine all of the parameters for
all of the regions.
[0105] If the depiction is to span an overall angular width of
about 360 degrees, it is preferred that block 156 be modified to
further iterate, after the final item, from the first non-root item
to the first leaf item.
[0106] Alternatively, the planar depiction may comprise a plurality
of regions to visibly represent the items, wherein adjacent items
in the tree are represented by a visible edge between their
corresponding regions, and wherein child items are ordered (either
left-to-right, right-to-left, top-to-bottom, bottom-to-top,
clockwise or counterclockwise, for example) according to the
sequence associated with the depth-first search sequence having the
optimum value.
[0107] An example is given to illustrate one embodiment of a method
of organizing financial information. As should be appreciated, the
scope of the present disclosure is not to be limited by this
example.
[0108] For purposes of illustration and example, consider a tree
shown in FIG. 10 which relates fourteen stocks A-N to a base stock
S. The tree may be determined as described with reference to FIG. 1
based on a correlation of price behavior of the stocks. For each of
the stocks, TABLE I shows an initial sequence for considering its
child stocks in a depth-first search of the tree. The initial
sequence is used to provide an initial depth-first search sequence
for considering stocks in the tree.
TABLE-US-00001 TABLE I Sequence for considering Stock child stocks
S A G N A B F B C D C -- D E E -- F -- G H I M H -- I J K L J -- K
-- L -- M -- N --
[0109] TABLE II illustrates one embodiment of determining a value
associated with the initial depth-first search sequence. Each row
in TABLE II represents an iteration associated with one of the
stocks. From left to right, the columns in TABLE II indicate: (a)
if at least one leaf stock had been previously considered, (b) the
current stock being considered in the depth-first search sequence
of the tree, (c) whether the current stock is an internal stock or
a leaf stock of the tree, (d) the level number of the current
stock, (e) a last-considered stock associated with level number 1,
(f) a last-considered stock associated with level number 2, (g) a
last-considered stock associated with level number 3, (h) a
last-considered stock associated with level number 4, and (i) which
similarity values are used to determine the value.
TABLE-US-00002 TABLE II At least one leaf Similarity stock values
used in previously Internal function considered? Stock or leaf?
Level 1 2 3 4 evaluation No A Internal 1 A -- -- -- -- No B
Internal 2 A B -- -- -- No C Leaf 3 A B C C -- Yes D Internal 3 A B
D C (C, D) Yes E Leaf 4 A B D E (C, E) Yes F Leaf 2 A F F F (B, F)
(D, F) (E, F) Yes G Internal 1 G F F F (A, G) Yes H Leaf 2 G H H H
(F, H) Yes I Internal 2 G I H H (H, I) Yes J Leaf 3 G I J J (H, J)
Yes K Leaf 3 G I K K (J, K) Yes L Leaf 3 G I L L (K, L) Yes M Leaf
2 G M M M (I, M) (L, M) Yes N Leaf 1 N N N N (G, N) (M, N)
[0110] As illustrated in TABLE II, fifteen similarity values are
used to determine the value associated with the initial depth-first
search sequence. The fifteen similarity values consist of a
similarity value between stocks C and D, a similarity value between
stocks C and E, a similarity value between stocks B and F, a
similarity value between stocks D and F, a similarity value between
stocks E and F, a similarity value between stocks A and G, a
similarity value between stocks F and H, a similarity value between
stocks H and I, a similarity value between stocks H and J, a
similarity value between stocks J and K, a similarity value between
stocks K and L, a similarity value between stocks I and M, a
similarity value between stocks L and M, a similarity value between
stocks G and N, and a similarity value between stocks M and N. In
this example, the function used to determine the value associated
with the initial depth-first search sequence is a sum of the
fifteen similarity values.
[0111] TABLE III shows a modified sequence for considering child
stocks of the base stock in a depth-first search of the tree. The
modified sequence is used to provide a second depth-first search
for considering stocks in the tree.
TABLE-US-00003 TABLE III Sequence for considering Stock child
stocks S G A N A B F B C D C -- D E E -- F -- G H I M H -- I J K L
J -- K -- L -- M -- N --
[0112] TABLE IV illustrates one embodiment of determining a value
associated with the second depth-first search sequence. As
illustrated, sixteen similarity values are used to determine the
value associated with the second depth-first search sequence. The
sixteen similarity values consist of a similarity value between
stocks H and I, a similarity value between stocks H and J, a
similarity value between stocks J and K, a similarity value between
stocks K and L, a similarity value between stocks I and M, a
similarity value between stocks L and M, a similarity value between
stocks A and G, a similarity value between stocks B and M, a
similarity value between stocks C and M, a similarity value between
stocks C and D, a similarity value between stocks C and E, a
similarity value between stocks B and F, a similarity value between
stocks D and F, a similarity value between stocks E and F, a
similarity value between stocks A and N, and a similarity value
between stocks F and N. In this example, the function used to
determine the value associated with the second depth-first search
sequence is a sum of the sixteen similarity values.
TABLE-US-00004 TABLE IV At least Similarity one stock values used
in previously Internal function considered? Stock or leaf? Level 1
2 3 4 evaluation No G Internal 1 G -- -- -- -- No H Leaf 2 G H H H
-- Yes I Internal 2 G I H H (H, I) Yes J Leaf 3 G I J J (H, J) Yes
K Leaf 3 G I K K (J, K) Yes L Leaf 3 G I L L (K, L) Yes M Leaf 2 G
M M M (I, M) (L, M) Yes A Internal 1 A M M M (A, G) Yes B Internal
2 A B M M (B, M) Yes C Leaf 3 A B C C (C, M) Yes D Internal 3 A B D
C (C, D) Yes E Leaf 4 A B D E (C, E) Yes F Leaf 2 A F F F (B, F)
(D, F) (E, F) Yes N Leaf 1 N N N N (A, N) (F, N)
[0113] The above process is repeated for additional depth-first
search sequences by modifying a sequence for considering child
stocks for at least one stock. Potential sequences for considering
child stocks of stock S are A-G-N, A-N-G, G-A-N, G-N-A, N-A-G and
N-G-A. Potential sequences for considering child stocks of stock A
are B-F and F-B. Potential sequences for considering child stocks
of stock B are C-D and D-C. Stock D has one potential sequence for
considering its child, namely stock E. Potential sequences for
considering child stocks of stock G are H-I-M, H-M-I, I-H-M, I-M-H,
M-H-I and M-I-H. Potential sequences for considering child stocks
of stock I are J-K-L, J-L-K, K-J-L, K-L-J, L-J-K and L-K-J.
[0114] Values associated with all possible depth-first search
sequences of the tree may be determined. The number of possible
depth-first search sequences of the tree is equal to the product of
3!, 2!, 2!, 1!, 3! and 3!, which equals 864.
[0115] Preferably, values associated with at most half of all
possible depth-first search sequences of the tree (432 in this
example) are determined. In this case, the depth-first search
sequences which are considered are limited by prohibiting
reverse-equivalent sequences for considering child stocks of the
root stock, namely the stock S. In this example, the sequences for
considering child stocks of the stock S may be limited to A-G-N,
A-N-G and G-A-N (whose reverse-equivalent sequences are N-G-A,
G-N-A and N-A-G, respectively).
[0116] Based on the values, the depth-first search sequence having
a maximum value associated therewith is determined. For purposes of
illustration and example, consider that the value associated with
the second depth-first search sequence is greater than or equal to
values associated with the other depth-first search sequences. A
signal may be outputted to display a planar depiction of the tree
in which the stocks are ordered according to the second depth-first
search sequence.
[0117] A browsing sequence may be provided in accordance with the
second depth-first search sequence. In this case, the sequence for
browsing the stocks is G-H-I-J-K-L-M-A-B-C-D-E-F-N (see the second
column of TABLE IV). The browsing sequence and the tree may be used
in accordance with the teachings in the patent application having
Ser. No. 09/533,545, now U.S. Pat. No. 6,460,033, which is hereby
incorporated by reference into the present disclosure.
[0118] In the above example, cyclic-equivalent and reverse
cyclic-equivalent sequences may be prohibited by prohibiting
cyclic-equivalent and reverse cyclic-equivalent sequences for
considering child stocks of the root stock, namely the stock S.
Thus, the sequence for considering child stocks of the stock S may
be limited to A-G-N, since G-N-A and N-A-G are cyclic-equivalent
sequences, and N-G-A, A-N-G and G-A-N are reverse cyclic-equivalent
sequences. In this case, the stocks from the first non-root stock
to the first leaf stock may be considered twice to determine a
value associated with a depth-first search sequence of the tree. In
the above example, the value associated with initial depth-first
search sequence would be further based upon a similarity value
between stocks A and N, a similarity value between stocks B and N,
and a similarity value between stocks C and N. The value associated
with the second depth-first search sequence would be further based
upon a similarity value between stocks G and N, and a similarity
value between stocks H and N. However, as explained above, the
second depth-first search sequence would not have been
considered.
[0119] An apparatus for performing embodiments of the
herein-disclosed methods and examples may comprise one or more
programmed computers. Each programmed computer may provide a
particular functionality implemented using hardware and/or software
and/or firmware.
[0120] Preferably, a programmed computer includes a computer memory
encoded with executable instructions representing a computer
program. A processor is responsive to the computer memory to
perform a series of specifically identified operations dictated by
the computer program. In this way, the computer program can cause
the computer to act in a particular fashion.
[0121] Examples of the processor include, but are not limited to, a
general purpose microprocessor, an application-specific integrated
circuit (which may be either standard or custom), one or more
discrete logic elements, a digital signal processor, an analog
signal processor, one or more circuits, or any combination thereof.
It is noted that the processor may be embodied by either a single
processing unit or a plurality of processing units. For example,
the processor may be embodied by either a single, central
processing unit or a plurality of distributed processing units.
[0122] Examples of the computer memory include, but are not limited
to, an electronic memory, a magnetic memory, an optical memory, and
a magneto-optical memory. Examples of an electronic memory include,
but are not limited to, a programmable electronic memory and a
read-only, hard-wired electronic memory. Examples of a magnetic
memory include, but are not limited to, a magnetic disk and a
magnetic tape. The magnetic disk may be embodied by a magnetic
floppy diskette or a magnetic hard drive, for example. Examples of
an optical memory include, but are not limited to, an optical disk.
The optical disk may be embodied by a compact disk or a DVD, for
example. Regardless of its form, the computer memory may be either
read-only, once-writable, or rewritable.
[0123] In general, the processor may be responsive to any data
structures, computer programs, and signals encoded on a
computer-readable medium to perform an embodiment of any of the
herein-disclosed methods and examples. Examples of the
computer-readable medium include, but are not limited to,
computer-readable storage media and computer-readable communication
media. Examples of computer-readable storage media are described
with reference to the computer memory.
[0124] The computer is coupled to a display to display the visible
representations described herein and other visible information to
an end user. Examples of the display include any of the
herein-disclosed display devices.
[0125] The computer receives user input indicating a selection of a
region from one or more input devices. Examples of the one or more
input devices include, but are not limited to, a keyboard, a touch
screen, a touch pad, a voice input device, and a pointing device
(e.g. a mouse or a pointing stick). The computer processes the user
input and/or communicates at least one signal based upon the user
input. The display and the one or more input devices facilitate
user interaction with the computer.
[0126] Embodiments of the herein-disclosed methods and examples can
be performed using either a single computer or a plurality of
computers. A plurality of computers may cooperate in a
client-server fashion, for example, wherein a server computer
outputs at least one signal to cause a client computer to display a
visible representation and/or to provide a user interface. The
plurality of computers may cooperate in a peer-to-peer fashion, for
example, wherein one peer computer acts as a server computer and
another peer computer acts as a client computer.
[0127] The teachings herein can be combined with and/or applied to
any of the teachings in U.S. application Ser. No. 09/243,595, now
U.S. Pat. No. 6,359,635, which is hereby incorporated by reference
in this application. The disclosure in Ser. No. 09/243,595
contemplates methods, articles, apparatus, and examples which
include an act of providing a link to a computer site which
performs an embodiment of any of its disclosed methods and
examples. The disclosure in Ser. No. 09/243,595 also contemplates
methods, articles, apparatus, and examples which include an act of
providing a user-viewable advertisement for a computer site which
performs an embodiment of any of its disclosed methods and
examples. The user-viewable advertisement may be communicated to
the end user from either an advertisement provider or the computer
site. The disclosure in Ser. No. 09/243,595 further contemplates
methods, articles, apparatus, and examples which include an act of
receiving a hit from an end user who has hyperlinked from a
computer site which performs an embodiment of any of its disclosed
methods and examples. Each of the aforementioned computer sites may
include an internet site, a Web site, or another site accessible
via a computer network.
[0128] As stated in the foregoing description, similarity values
may be based on a correlation between trading behaviors of two
financial items. Other examples of trading behaviors include, but
are not limited to, postings of buy or sell messages such as those
monitored by ThomsonFN.com's I-Watch.TM. service. The messages may
include super messages in which brokers/dealers specify whether
they want to buy or sell a particular stock, a size of the
particular stock to trade, and an exact price. The messages may
include interest messages which are not binding. The similarity
values may be equal to or otherwise based on a correlation
coefficient between the postings of messages for two financial
items. To determine the correlation coefficient, a time series
indicating an aggregate level of messaging for each of a plurality
of time intervals is determined for each stock. For example, the
time series for a stock may indicate the aggregate level of
messaging within 5 minute or 20 minute intervals, such as the data
provided by ThomsonFN.com's I-Watch.TM. service. The correlation
coefficient is a cross correlation between two time series for two
different stocks.
[0129] Embodiments of the present invention have many practical
applications. A financial Web site can display regions to show how
a selected financial item relates to other financial items. Each
region may be user-selectable so that a user can retrieve
information associated with its corresponding financial item.
Examples of the information include, but are not limited to, a
quote, a bid price, an offer price, trading volume, a chart,
technical analysis, fundamental analysis, historical prices,
profile information, research for the item, an income statement, a
balance sheet, a prospectus, and a message board associated with
the item. Further, a selection of a region may facilitate (e.g.
either assist or initiate) a transaction involving the financial
item (e.g. buying or selling a stock).
[0130] The financial items represented by the regions may comprise
either all financial items in an index (e.g. all stocks in the
Standard & Poors' 500 index), all financial items in a user's
watch list, only the nearest neighbors to the base financial item
based on the similarity values, all financial items in a market
sector, or all financial items in a market industry, for example.
Preferably, only financial items whose correlation with the base
financial item is greater than zero are considered for inclusion in
the graphical representation. Optionally, a criterion for including
financial items in the graphical representation may be more
stringent, for example, only financial items whose correlation with
the base financial item is greater than a positive threshold (e.g.
0.2, 0.5, 0.7) are considered for inclusion in the graphical
representation.
[0131] A mutual fund family may determine how a family of its
mutual funds are interrelated based on similarity values. The
relationship can be displayed on the mutual fund family's Web site,
displayed in an on-line version of a prospectus or an annual
report, and/or printed in a hard copy prospectus or an annual
report.
[0132] The regions may be displayed with different display
properties based on a property of the items. Examples of the
property include, but are not limited to, a sector within which the
item is contained, an industry within which the item is contained,
a change in price of the item, a change in volume of the item, a
percentage of institutional volume, a percentage of retail volume,
and an amount of institutional interest to buy or sell based on
super messages and/or interest messages. Examples of the display
property include, but are not limited to, an interior color of the
region, an interior gray scale of the region, an interior fill
pattern for the region, a color bordering the region, an image
within the region, and text within the region. For example, the
color may be a shade of green if the price is up, and a shade of
red if the price is down.
[0133] A sequence of the same graphical representation but with
time-varying display properties can be displayed in succession to
provide an animated view of the financial information over the
course of a time period. For example, a recap of the price action
of each financial item over the course of a day can be shown in an
animation that lasts much less time (e.g. under 30 seconds, or
under a minute). In this case, the colors of the regions may change
during the animation to reflect price changes in the respective
items over the course of the day.
[0134] By selecting the base item to be a newsworthy stock or
another newsworthy financial item, a financial news service can
show how buying or selling pressure in the newsworthy item is
spreading to other stocks or financial items. The financial news
service may be either a television broadcast service, a computer
network service such as an Internet service, a wireless telephone
or PDA service, or a print service.
[0135] By allowing a user to select the base item, the user can be
provided a view of the stock market that focuses on his/her own
stock of interest. For example, a user may select the base item to
be a stock that the user either owns, shorts, is interested in
buying, or is interested in selling.
[0136] Optionally, the weight value of each item can be based on
the similarity value between the item and the base item. In this
case, items which are highly-similar to the base item are displayed
with greater areas than items which are less similar to the base
item. Each weight value can be based on or equal to the correlation
between the corresponding item and the base item. For example, the
weight value may be equal to the correlation if the correlation is
greater than zero. As another example, the weight value may be
equal to the correlation squared if the correlation is greater than
zero. In both of the above examples, an item would not be
considered for and included in the graphical representation if its
correlation with the base item is less than or equal to zero.
[0137] FIG. 11 is a first example of regions to represent the
fourteen stocks A-N and the base stock S related by the tree in
FIG. 10. In this example, the regions all have approximately the
same area. The regions provide a 360-degree view of the stocks A-N
and S.
[0138] FIG. 12 is a second example of regions to represent the
fourteen stocks A-N and the base stock S related by the tree in
FIG. 10. In this example, each region has an area based on a
similarity value between its corresponding stock and the base
stock. Thus, if a first stock (e.g. stock A) is more similar to the
base stock S than a second stock (e.g. stock B) is to the base
stock S, the region representing stock A has a greater area than
the region representing stock B. The regions provide a 360-degree
view of the stocks A-N and S.
[0139] It will be apparent to those skilled in the art that the
disclosed inventions may be modified in numerous ways and may
assume many embodiments other than the preferred forms specifically
set out and described herein. For example, the acts described with
reference to FIGS. 1-4 and 6-8 may be executed in an order other
than that indicated in FIGS. 1-4 and 6-8. Further, some of the acts
may be performed in parallel. Still further, the regions may have
the herein-disclosed similarity-based areas but with
non-annulus-sector shapes in alternative embodiments.
[0140] Accordingly, it is intended by the appended claims to cover
all modifications which fall within the true spirit and scope of
the present invention.
* * * * *