METHOD AND SYSTEM FOR PROVIDING FINANCIAL FORECASTING ON
LISTED COMPANIES
FIELD OF THE DISCLOSURE
[0001] The present disclosure generally relates to a method and a system
for providing financial forecasting of a listed company, and more particularly, to a
method and a system for providing financial forecasting of a listed company based on
financial forecast models that may be manipulated.
BACKGROUND OF THE DISCLOSURE
[0002] It is important these days to have an adequate understanding about
business entities or companies or any business organization before making any financial
investment. One. of the primary requirements for making an informed investment decision
is not only the ease of access to historical financial data on the company in question, but
also have the ability to assess future financial performance of the company. The reliance
on historical data to drive future financial forecasts, requires a high level of accuracy and
integrity in the historical data set as well as transparency in the forecasting methodology
applied to each historical line item. This ensures that a timely and accurate financial
decision may be made within the sphere of opportunity.
[0003] Existing tools and corporate analytics systems predominantly
deliver analytical capability on merely historical financial performance of companies,
with little to no capability to run elaborate financial forecasts and estimates, in a well
structured and transparent fashion. Such existing solutions and tools also have limited
capability to generate financial forecast models related to companies without intensive
user interference and analytical throughput. More specifically, such tools may also have
limited capabilities to allow the user to manipulate the financial forecast models for
providing a financial forecast of the company. Thus, existing tools require time
consuming research inputs from their users.
SUMMARY OF THE DISCLOSURE
' 2~
[0004] In view of the foregoing disadvantages inherent in the prior-art, the
general purpose of the present disclosure is to provide a method and a system providing
financial forecasting on a range of stock exchange listed companies that is configured to
include all advantages of the prior art and to overcome the drawbacks inherent in the
prior art offering some added advantages.
[0005] An object of the present disclosure is to provide an advanced tool
for providing financial forecast model on a publicly listed company, with the view to
deliver forecast manipulation capability, via the software interface, to the user; in order
for the user to adjust the future expected financial performance of the company based on
their understanding and expectation of future performance on a series of underlying
variables that impact the performance of the company in question.
[0006] Another object of the present disclosure is to provide a tool for
providing financial forecasts on a company in a user friendly manner.
[0007] Yet another object of the present disclosure is to provide a tool,
which includes personalized features that enable a user to select stock exchange listed
companies of their interest in a manner suited to their requirements.
[0008] To achieve the above objective, in one aspect, the present
disclosure provides a method for providing financial forecasting on a listed company. The
method includes receiving name of a company from a user from a list of companies made
available to the user. Further, the method includes locating a financial forecast model
corresponding to the requested company. The financial forecast model is capable of being
manipulated by the user and the financial forecast model is capable of being utilized for
determining future expected financial performance of the company. Furthermore, the
method includes providing the financial forecast of the company based on the forecasting
capability of the financial forecast model.
[0009] In another aspect, the present disclosure provides a computer
program product embodied within a computer readable medium. The computer program
product encodes a computer program of instructions for executing a computer process for
providing financial forecasting on a range of stock exchange listed companies. The
z
computer process includes receiving name of a company from a user from a list of
companies made available to the user. Further, the computer process includes locating a
financial forecast model corresponding to the company requested, wherein the financial
forecast model is capable of being manipulated by the user, and wherein the financial
forecast model is capable of being utilized for determining future expected financial
performance of the company. Furthermore, the computer process includes providing the
financial forecast of the company based on the forecasting capability of the financial
forecast model.
[0010] In yet another aspect, the present disclosure provides a system for
financial forecasting on a listed company. The system includes a receiving module
configured to receive name of a company from a user from a list of companies made
available to the user. Further, the system includes a locating module configured to locate
a financial forecast model corresponding to the company, wherein the financial forecast
model capable of being manipulated by the user, and wherein the financial forecast model
is capable of being utilized for determining future expected financial performance of the
company. Further, the system includes an application module configured to provide the
financials of the company based on the financial forecast model and the historical data
corresponding to the company.
BRIEF DESCRIPTION OF THE DRAWINGS
[0011] The advantages and features of the present disclosure will become
better understood with reference to the following detailed description and claims taken in
conjunction with the accompanying drawing, in which:
[0012] FIG. 1 is a flow diagram of a method for providing financial
forecasting of a listed company, according to an embodiment of the present disclosure;
[0013] FIG. 2 is a flow diagram of a method for generating a financial
forecast model, according to an embodiment of the present disclosure;
H
[0014] FIG 3 is a block diagram of a system for providing financial
forecasting of a listed company, according to another embodiment of the present
disclosure;
[0015] FIG 4 is a snapshot depicting validation of the collected data and
notification of the user in case of violation;
[0016] FIG 5 is a flow diagram, which explains the process of validation
of the collected data;
[0017] FIG 6 is a snapshot depicting how a user may change assumptions
of a parameter in the method 100;
[0018] FIGS. 7 and 8 are snapshots depicting how a user may view the
financial statements as released by the company;
[0019] FIG. 9 is a snapshot depicting a summary report generated by
method 100;
[0020] FIGS. 10-13 are snapshots depicting how a user may be provided
with an option of summary report either based on predetermined estimates or based on
his/her estimates;
[0021] FIG. 14 is a snapshot depicting company screening based on a
screening criteria;
[0022] FIG. 15 is a snapshot depicting a peer group analysis of companies;
[0023] FIG 16 is a snapshot depicting analysis of impact of a change in an
independent variable on a given dependent variable in a created scenario;
[0024] FIGS. 17 and 18 are snapshots depicting summarizing of a
comparison between companies in particular portfolios/sectors/indices/regions;
[0025] FIG. 19 depicts the logical diagram of the system 200 of FIG. 3;
and
5
[0026] FIG 20 diagram depicts the architecture diagram of the system 200
of FIG 3.
DETAILED DESCRIPTION OF THE DISCLOSURE
[0027] The exemplary embodiments described herein detail for illustrative
purposes are subject to many variations in structure and design. It should be emphasized,
however, that the present disclosure is not limited to a particular method and system for
providing financial forecasting on a range of stock exchanged listed companies as shown
and described. It is understood that various omissions and substitutions of equivalents are
contemplated as circumstances may suggest or render expedient, but these are intended to
cover the application or implementation without departing from the spirit or scope of the
claims of the present disclosure. Also, it is to be understood that the phraseology and
terminology used herein is for the purpose of description and should not be regarded as
limiting. .
[0028] The use of terms "including," "comprising," or "having" and
variations thereof herein is meant to encompass the items listed thereafter and equivalents
thereof as well as additional items. Further, the terms, "a" and "an" herein do not denote a
limitation of quantity, but rather denote the presence of at least one of the referenced
item.
[0029] The present disclosure provides a method and a system for
providing financial forecasting on a range of stock exchange listed companies. The term
financial as mentioned herein includes both historical and forecasted figures of key
indicators of the company. Suitable example of the key indicators may include, but not
limited to, financial ratios, fixed working capital, income/revenues, profit/ loss, net
interest income, and the like. More specifically, the present disclosure provides a method
and a system for providing financial forecasting on a range of stock exchange listed
companies based on financial forecast models that may be manipulated by the user. It
should be understood that the term 'forecasting' as used throughout the present disclosure
relates to predicting future key performance indicators of a company. The term
'company' as described herein may refer to a public limited company (i.e., stock
exchange listed company). However, such definition of the term 'company' should not be
/
construed as a limitation to the present disclosure. Accordingly, the method and the
. system of the present disclosure may also be applicable for other entities, such as private
limited companies and limited liability partnership firms. The method and the system of
the present disclosure will now be explained with reference to FIGS. 1-3.
[0030] As shown in FIG. 1, a method 100 for providing financial
forecasting of a listed company includes receiving name of a company from a user, at
block 10. The user as mentioned herein may be a person interested in accessing financials
of the company. Accordingly, a list of companies made available to the user, and the user
may prompt the name of the company for which he desires the financials, at block 10.
More specifically, the user may enter the name of the company by inputting the name of
the company through an input device (not shown), such as a keyboard, a touchpad, or
other similar inputting devices.
[0031] Thereafter, the method 100 includes locating a financial forecast
model corresponding to the company, at block 20. It will be apparent to a person skilled
in the art that the term 'financial forecast model' as mentioned herein refers to a set of
relational parameters, which may be used to forecast key financial indicators of a
company. Further, it will be apparent to a person skilled in the art that the financial'
forecast model may be based on a plurality of assumptions. Exemplary set of financial
parameters of the financial models of the present disclosure, may include, but not limited
to,
1. EBIT Margin = EBIT/ Total Revenue
2. Gross Debt to Assets = (Long Term Debt + Short Term Debt)/ Total Assets
3. RoCE (%) = EBIT/ Avg. Capital Employed
4. Debt Service Cover = EBITDA/ (Interest +Debt Repayment)
However, it should be clearly understood that the set of financial parameters as enlisted
above should not be construed as a limitation to the present disclosure. Accordingly, the
financial forecast model may include additional set of parameters and variables.
7
[0032] More specifically, the method 100 may include retrieving the
financial forecast model corresponding to the company from a plurality of financial
forecast models stored in a database, and more particularly, uploaded in a database.
[0033] In one embodiment of the present disclosure, the method 100 may
include generating the financial forecast model, uploading the financial forecast model in
the database, and then retrieving the generated financial forecast model, at block 20. The
generation of the financial forecast model may now be explained with reference to FIG 2.
[0034] As shown in FIG. 2, the generation of the financial forecast model
may include collecting data corresponding to the company, at block 32. The data may be
collected from primary sources or secondary sources. Suitable examples of the primary
sources may include interaction of an analyst from officials of the company. Suitable
examples of the secondary sources include collection of the data from sources, such as
company databases, annual reports of the companies, websites, and other similar sources.
Further, the collecting of the data corresponding to the company may include collecting
as reported data of the company. In one embodiment, the collecting data corresponding to
the company comprises collecting analyst derived data.
[Please provide input on analyst derived data.]
[0035] After the collection of the data corresponding to the company, the
method of generating the financial forecast model includes verifying the data, at block
34. The verification of the data may involve corroborating the collected data to locate
inconsistencies and errors. The step of verification of the data, at block 34, may be
performed by the analyst or may also be computer implemented. For example, a
computer implemented code may be initiated on the collected data to determine the
inconsistencies and the errors.
[0036] After the verification of the collected data, the method of
generating financial forecast model includes analyzing the collected data to derive key
pointers, at block 36. The term analyzing the data as mentioned herein may refer to
deriving insights from the collected data about the company and the inter-relationship of
these data points and structuring these insights in form of key pointers and forecasting
formulae. Again, the analysis may be done by the analyst or may be computer
$
implemented. For example, the data may be interpreted to arrive at key pointers, such as
income, expenses, depreciation, liabilities, and other such key pointers.
[0037] After the analysis of the data, at block 36, the method of generating
the financial forecast model may include deducing the financial forecast model based on
the analyzed data, at block 38. More specifically, the method may include inputting the
key pointers derived at block 36 in the relational parameters in a forecasting sense to
deduce the financial forecast model, at block 38.
[0038] The method 100 of the present disclosure may additionally include
validating the financial forecast model. The validation of the financial forecast model
ensures that the financial forecast model may be free from inconsistencies and
reconciliation problems. The validation of the financial forecast model may be based on a
plurality of predetermined integrity checks. The validation ensures that in case any of the
values is wrongly inputted, the method 100 may not accept the value, and may intimate
the user of such inconsistencies and discrepancies. .
[0039] The validation of the collected data ensures total accuracy from an
accounting perspective. Further, if the user makes any changes that violate the internal
control parameters, these are clearly notified to the level of identification of cells where
the violation exists. This may be better understood by referring to FIG 4.
[0040] As shown in FIG. 4, if a user inputs any number in the Income
Statement sheet of the application, then on clicking model verification tab 252, the user
would be prompted a error message 255, such as, "Net interest income for FY201 1F does
not tally with the items that make up the "Net Interest Income" figure.
[0041] Moreover, FIG. 5 depicts a flow diagram 257 which explains how
the validation of the collected data works with respect to method 100. As shown in FIG.
5, if the method 100 during the validation of the collected data passes the first check, then
the forecast items in the data input sheet may be checked so that it matches the predetermined
calculations (accounting checks) that we have defined in the database. Any
violation in the number may be highlighted as error. Alternatively, if the method 100
during the validation of the collected data passes the second check, then the user may be
1
allowed to upload the numbers to the central server which may be used as estimates
anywhere in the application to run the valuation comparisons.
[0042] Now referring again to FIG 1, after the locating of the financial
forecast model, the method 100 may include providing the financial forecast of the
company based on the forecasting capability of the financial forecast model, at block 27.
[0043] It should be understood that the financial forecast model as
described herein may be manipulated by the user. More specifically, each financial
forecast model combines historical financial information with forecasting methodologies
for individual variables to determine the future expected financial performance of the
company, based on a plurality of forecast assumptions. Also, the user may be capable of
changing at least one of a plurality of forecasting assumptions, on which the financial
forecast model may be based, for manipulating the financial forecast model. Such
manipulation feature provides the user an option of customizing the forecasting
assumption according to his/ her choice. This is shown with reference to FIG 6.
[0044] As shown in FIG 6, the user may change these assumptions by
right clicking on a parameter 260. A manipulated assumption 265 may then accepted by
the method 100.
[0045] In one embodiment of the present disclosure, the method 100 may
include viewing source of the collected data. Accordingly, the user may drill down to
documents from where the collected data is sourced. Also, the user may download such
data if required. This gives the user an option of quickly verifying the authenticity and
integrity of the collected data, in terms of its sourcing, by electing to view the source
documents. For example, if the user intends to drill down to source of a key indicator,
such as operating profit, then the user may be able to view the as reported financial
statements of the company with the operating profit indicator highlighted. This viewing
source of the collected data is as shown in FIGS. 7 and 8.
[0046] As shown in FIG. 7, a user may view the financial statements as
released by the company by refeiring to associated files section 300 on right hand side of
the application. The section 300 includes all source documents like annual reports and
corporate presentations.
\°
[0047] As shown in FIG. 7 and FIG 8, a user may also "right click" on a
particular cell in the application to retrieve the source document corresponding to the
collected data. If the user clicks on the collected data, and selects drill-down to source
option 310, it brings the user to the source document 320 with the specific data
highlighted in yellow.
[0048] In one embodiment of the present disclosure, the method 100 may
further include generating analytical charts based on the fmancials of the company. In one
embodiment of the present disclosure, the method 100 may include generating analytical
charts may include generating charts based on a user defined criteria. More specifically,
the method 100 may include reorganizing data about the key indicators, and thereafter
using the data to prepare the analytical charts.
[0049] In yet another embodiment, the present disclosure provides
generating summary reports using generated forecasts of method 100. Exemplary
summary report is as shown in FIG. 9. The method may generate four kinds of reports:
Company Profile, One Pager Report, Two Pager Report, and Company Report. However,
the generation of the aforementioned reports should not be construed as a limitation to the
present disclosure.
[0050] Further, the method 100 gives an option to the user to generate the
summary reports based on his/her estimates or predetermined estimates. As shown in FIG
10, the application provides the user with two options for each type of summary report.
First, the application provides the user with an option of summary reports based on
predetermined estimates 330. Second, the application provides the user with an option of
summary report based on his/her estimates 335. If the user chooses the predetermined
estimates 330 option, a summary report similar to that shown in FIG. 9 is generated.
[0051 ] If the user chooses the option of generating summary report based
on his/her estimates, then the user may be allowed to manipulate any assumption. For
example, the user may manipulate the Total Revenue Figure 340 as shown in FIG. 11by
changing Average Revenue per Minute in the financial forecast model sheet
corresponding to the Total Revenue Figure 340 from a figure 345 of 0.7 to a figure 350 of
II
55 NT$ per minute as shown in FIG 12. The change may reflect in the summary report as
shown by figure 355 in FIG 13.
[0052] In yet another embodiment of the present disclosure, the method
100 may also include creating scenarios and view the companies that fall into the
scenario. More specifically, the user may have an option of creating new scenarios based
on plurality of filters available. This allows the user to view some of the key financial
parameters associated with companies.
[0053] The company screening may rely on fundamental and valuation
data, and may deliver a focused list of companies for the subscriber. The company
screening as described herein may be better understood in conjunction with reference to
FIG 14.
[0054] As shown in FIG 14, the company screening may include a
screening criteria section 375 and a list of companies 380.
[0055] In one embodiment of the present disclosure, the method 100 may
further include performing a peer group analysis of the company. The peer group analysis
may include comparing fmancials of the company to the fmancials of competitor
companies. Further, the peer group analysis may include presenting the result of the
comparison to the user. The peer group analysis may be shown with reference to FIG 15.
[0056] In yet another embodiment of the present disclosure, the method
100 may include analyzing impact of a change in an independent variable on a given
dependent variable in a created scenario. This analysis may be as shown in FIG. 16.
[0057] As shown in FIG. 16, a sensitivity detail section 400 presents the
user with an option to change the independent variable. The analysis of the sensitivity is
shown in the output grid section 410.
[0058] In addition, the method 100 also enables the user to summarize
comparison between companies in particular portfolios/sectors/indices/regions, which are
under coverage of the firm for various parameters. The user may select companies,
forecast items, forecast periods for summarizing the comparison. The summarizing may
be depicted by FIG. 17. The summary may be shown in FIG. 18.
I 2 -
[0059] Further, the present disclosure provides a computer program
product embodied within a computer readable medium. The computer program product
encodes a computer program of instructions for executing a computer process to provide
financial forecast of a listed company. The computer process includes receiving name of
a company from a user from a list of companies made available to the user. Further, the
computer process includes locating a financial forecast model corresponding to the
company. The financial forecast model as described herein is similar to the financial
forecast model described above. Accordingly, the financial forecast model is capable of
being manipulated by the user, and wherein the financial forecast model is capable of
being utilized for determining future expected financial performance of the company.
[0060] After, the location of the financial forecast model, the computer
process includes providing the financials of the company based on the forecasting
capability of the financial forecast model.
[0061] The computer process may further include generating the financial
forecast model. The generating of the financial forecast model is similar to the generating
of the financial forecast model as described above. Accordingly, the generating of the
financial forecast model includes collecting data corresponding to the company. The
collecting of the data corresponding to the company includes collecting as reported data
of the company. In one embodiment of the present disclosure, the collecting data
corresponding to the company comprises collecting analyst derived data. Thereafter, the
computer process may include verifying the data, analyzing the collected data, and
deducing the financial forecast model based on the analysis.
[0062] The computer process may further include validating the financial
forecast model, the validating of the data based on a plurality of predetermined integrity
checks, comprising of accounting and reconciliation checks. The validation may be
similar to the validation described above with reference to FIG 1. Further, the validation
may include intimating the user based on the result of the validation.
[0063] Also, the computer process may include viewing source of a data
element of the collected data, wherein locating the financial forecast model comprising
retrieving the model from a database of uploaded models.
[3
[0064] In an embodiment of the present disclosure, the computer process
may include screening companies based on investment criteria comprising one or more of
sector, country, investment characteristics, and fundamental and valuation filters. Further,
the computer process may include performing a peer group analysis comprising
comparing financials of the company to the financials of competitor companies. The
computer process may also include generating analytical charts based on the data of the
company. The generation of analytical charts may include generating charts based on a
user defined criteria.
[0065] In another aspect, the present disclosure provides a system for
providing financial forecasting of a listed company. The system will be explained in
details with reference to FIG .3. As shown in FIG 3, the system 200 includes a receiving
module 210 configured to receive name of a company from a user from a list of
companies made available to the user. Further, the system 200 includes a locating module
230 coupled to the receiving module 210. The locating module 230 may be configured to
locate a financial forecast model corresponding to the company in a database 235 having
a plurality of uploaded financial forecast models. It should be understood that the
financial forecast model may be capable of being manipulated by the user. Further, the
financial forecast model is capable of being utilized for determining future expected
financial performance of the company.
[0066] In one embodiment, the locating module 230 may also include a
generating module 237 configured to generate the financial forecast model. More
specifically, the generating module 237 may be configure to collect data corresponding to
the company from primary and secondary sources using a collecting module 239, verify
the data, analyze the collected data, and deduce the financial forecast model based on the
analysis.
[0067] In addition, the system 200 includes an application module 240
coupled to the locating module 230. The application module 240 may be configured to
provide the financials of the company based on the financial forecast model.
1M
[0068] The system 200 may further include a storage module (not shown
in FIG 3), which may fulfill the storage requirement of the system 200. For example, the
storage module may be configured to store the financial forecast model generated by the
locating module 230.
[0069] The system 200 may include a manipulating module (not shown)
adapted to allow a user to change at least one of a plurality of forecasting assumptions for
manipulating the financial forecast model.
[0070] The system 200 may furthermore include a validating module
configured to validate the financial forecast model, wherein the validating of the financial
forecast model is based on a plurality of predetermined integrity checks. The plurality of
predetermined integrity checks are similar to the integrity checks described above.
[0071] The system 200 may additionally include a screening module (not
shown) configured to screen companies based on investment criteria, such as, sector,
country, investment characteristic and fundamental and valuation filters. Further, the
system 200 may include a peer group analysis (not shown) module configured to perform
a peer group analysis of the company. The peer group analysis module comprises a
comparison module configured to compare financials of the company to financials of
competitor companies. Further, the system 200 includes a chart generation module
configured to generate charts based on the financials of the company. In one embodiment,
the chart generating module is configured to generate charts based on a user defined
criteria.
[0072] The system 200 may be better understood by considering the
logical diagram of the system 200 as shown in FIG. 19, and the architecture diagram of
the system 200 as shown in FIG. 20.
[0073] As shown in FIG 19, the system 200 may include multiple servers
500 (Web servers and database servers), and multiple users 502 connected to the multiple
servers 500 for data retrieval via internet. The input message, inquiry or request by one of
the multiple users 502 is transferred via standard transport protocol, such as PORT 80
using SOAP technology, to the network hardware and then finally to web servers 502.
The network hardware also checks the load between multiple web servers. It will be
I 5
apparent to a person skilled in the art that SOAP is the simple Object Access Protocol, a
way to create widely distributed, complex computing environments that run over the
Internet using the existing Internet infrastructure. It is about applications communicating
directly with each other over the Internet in a very rich way. Further, SOAP mandates the
small number of HTTP headers that facilitates firewall/proxy settings.
[0074] The web servers sends the query to the database servers which then
sends the output back to web servers to transfer via network switch to the particular user
500.
[0075] The architecture of the system 200 may be Windows based three
tiers WPF (Windows Presentation Foundation), as depicted in FIG 19. As shown in FIG
19, the first layer is the user interface and the business access layer, wherein the user
accesses the system through their workstations. The signal from user interface travels to
web server where web service are installed at port 80/443. The signal travelling to web
server via internet may be encrypted. The users are then authenticated with username and
password check, and after this the signal goes to core libraries where there is security
enabled for access rights of users. This layer may have database access where the data is
encrypted for communication with database. The database used is MS SQL Server 2005.
The encrypted signal goes to the database which contains primary and audit databases.
The database has the stored procedures and the data for the system 200. The signal travels
back to the user interface with the required information from the database.
[0076] The present disclosure therefore provides a method, such as
method 100, and a system, such as system 200, for providing financial forecasting of a
listed company. The method includes receiving name of a company from a user, and
locating a financial forecast model corresponding to the company. The financial forecast
model is capable of being manipulated by the user. Further, the method includes
providing the financials of the company based on the forecasting capability of the
financial forecast model. The system includes a receiving module configured to receive
name of a company from a user, and a locating module coupled to the receiving module.
The locating module is configured to locate a financial forecast model corresponding to
the company. Further, the system includes an application module coupled to the locating
module and the collection module. The application module configured to provide the
M
financials of the company based on the historical data and the financial forecast model.
Further, the present disclosure provides a computer process for providing financial
forecasting of a listed company. The system, the method and the computer process give
significant value to the customer in terms of reduced analysis, conversion and testing
timeframe to forecast the future financial performance of a business entity or a company
or a company listed in any stock exchange. Further, the system, the method and the
computer process lowers the total cost of ownership of the financial platform for the
client. Also, the system, the method and the computer process empowers a user of the
information to form a fundamental view on a company within hours, delivering
significant speed of decision-making. The method, system, and the computer process also
allows quick generation of reports corresponding to companies, macro screening of
companies, and peer group comparisons between companies.
[0077] In addition, the financial forecast models as described in the
present disclosure are industry and company specific, keeping in mind in mind the
specifics of each industry group and, in particular, each company's dynamics. Also, the
financial forecast models are completely transparent in terms of methodology and
information sourcing. Moreover, the financial forecast models are based on clear
methodologies, provides complete transparency on the various formulae that drive
forecasting as well as the underlying assumptions being used and the rationale for their
use.
[0078] The foregoing descriptions of specific embodiments of the present
disclosure have been presented for purposes of illustration and description. They are not
intended to be exhaustive or to limit the present disclosure to the precise forms disclosed,
and obviously many modifications and variations are possible in light of the above
teaching. The embodiments were chosen and described in order to best explain the
principles of the present disclosure and its practical application, to thereby enable others
skilled in the art to best utilize the present disclosure and various embodiments with
various modifications as are suited to the particular use contemplated. (It is understood
that various omission and substitutions of equivalents are contemplated as circumstance
may suggest or render expedient, but such are intended to cover the application or
implementation without departing from the spirit or scope of the claims of the present
disclosure).

What is claimed is:
1. A method for providing financial forecasting on a listed company, the
method comprising:
receiving name of a company from a user from a list of companies made available
to the user;
locating a financial forecast model corresponding to the company requested,
wherein the financial forecast model is capable of being manipulated by the user, and
wherein the financial forecast model is capable of being utilized for determining future
expected financial performance of the company; and
providing the financial forecast of the company based on the forecasting
capability of the financial forecast model.
2. The method of claim 1, wherein locating the financial forecast model
comprises retrieving the financial forecast model from a database of uploaded models.
3. The method of claim 1, wherein locating the financial forecast model
comprises generating the financial forecast model.
4. The method of claim 3, wherein generating the financial forecast model
comprises:
collecting data corresponding to the company;
verifying the data;
analyzing the collected data; and
deducing the financial forecast model based on the analyzed data.
5. The method of claim 4 further comprising storing the collected data.
6. The method of claim 4 further comprising viewing source of a data
element of the collected data.
IS
7. The method of claim 4, wherein collecting data corresponding to the
company comprises collecting data from primary sources.
8. The method of claim 4, wherein collecting data corresponding to the
company comprises collecting data from secondary sources.
9. The method of claim 4, wherein collecting data corresponding to the
company comprises collecting as reported data of the company.
10. The method of claim 4, wherein collecting data corresponding to the
company comprises collecting analyst derived data.
11. The method of claim 1 further comprising validating the financial forecast
model, wherein the validating of the financial forecast model is based on a plurality of
predetermined integrity checks comprising of accounting and reconciliation checks.
12. The method of claim 11 further comprising intimating result of the
validation to the user.
13. The method of claim 1, wherein each financial forecast model combines
historical financial information with forecasting methodologies for individual variables to
determine the future expected financial performance of the company, based on a plurality
of forecast assumptions.
14. The method of claim 13, wherein the user is capable of changing at least
one of the plurality of forecasting assumptions for manipulating the financial forecast
model for future time periods on expected performance.
15. The method of claim 1 further comprising generating quick reports
corresponding to the company based on the manipulated financial forecast model.
16. The method of claim 1 further comprising screening the companies
based on investment criteria comprising one or more of sector, country, investment
characteristic, and fundamental and valuation filters.
H
17. The method of claim 1 further comprising performing a peer group
analysis of the company based on the financials.
18. The method of claim 17, wherein performing the peer group analysis
comprises comparing financials of the company to financials of competitor companies.
19. The method of claim 1 further comprising generating analytical charts
based on financials of the company.
20. The method of claim 19, wherein generating analytical charts comprises
generating charts based on a user defined criteria.
21. A computer program product, the computer program product embodied
within a computer readable medium, the computer program product encoding a computer
program of instructions for executing a computer process for providing financial
forecasting on a listed company, the computer process comprising:
receiving name of a company from a user from a list of companies made available
to the user;
locating a financial forecast model corresponding to the company requested,
wherein the financial forecast model is capable of being manipulated by the user, and
wherein the financial forecast model is capable of being utilized for determining future
expected financial performance of the company; and
providing the financial forecast of the company based on the forecasting
capability of the financial forecast model.
22. The computer program product of claim 21, wherein locating the financial
forecast model comprises generating the financial forecast model.
23. The computer program product of claim 22, wherein generating the
financial forecast model comprises:
collecting data corresponding to the company;
verifying the data;
analyzing the collected data; and
deducing the financial forecast model based on the analysis.
T-O
24. The computer program product of claim 23 further comprising storing the
data.
25. The computer program product of claim 21 further comprising validating
the financial forecast model, wherein the validating of the financial forecast model is
based on a plurality of predetermined integrity checks, comprising of accounting and
reconciliation checks.
26. The computer program product of claim 25 further comprising intimating
result of the validation to the user.
27. The computer program product of claim 23 further comprising viewing
source of a data element of the collected data.
28. The computer program product of claim 23, wherein collecting data
corresponding to the company comprises collecting as reported data of the company.
29. The computer program product of claim 23, wherein collecting data
corresponding to the company comprises collecting analyst derived data.
30. The computer program product of claim 21, wherein each financial
forecast model combines historical financial information with forecasting methodologies
for individual variables to determine the future expected financial performance of the
company, based on a plurality of forecast assumptions.
31. The computer program product of claim 30, wherein the user is capable of
changing at least one of the plurality of forecasting assumptions for manipulating the
financial forecast model for future time periods on expected performance.
32. The computer program product of claim 21, wherein locating the
financial forecast model comprises retrieving the model from a database of uploaded
models.
X
33. The computer program product of claim 21 further comprising screening
companies based on investment criteria comprising one of sector, country, investment
characteristics, and fundamental and valuation filters.
34. The computer program product of claim 21 further comprising performing
a peer group analysis of the company based on the financials.
35. The computer program product of claim 34 wherein performing the peer
group analysis comprises comparing financials of the company to the financials of
competitor companies.
36. The computer program product of claim 21 further comprising generating
analytical charts based on financials of the company.
37. The computer program product of claim 36, wherein generating analytical
charts comprises generating charts based on a user defined criteria.
38. The computer program product of claim 21 further comprising generating
quick reports corresponding to the company based on the manipulated financial forecast
model.
39. A system for providing financial forecasting on a listed company, the
system comprising:
a receiving module configured to receive name of a company from a user from a
list of companies made available to the user;
a locating module configured to locate a financial forecast model corresponding
to the requested company, wherein the financial forecast model is capable of being
manipulated by the user, and wherein the financial forecast model is capable of being
utilized for determining future expected financial performance of the company; and
an application module configured to provide the financial forecast of the
company based on the forecasting capability of the financial forecast model.
40. The system of claim 39 further comprising a database configured to store
the financial forecast model.
•n41.
The system of claim 39, wherein the locating module comprises a
generating module configured to generate the financial forecast model.
42. The system of claim 41, wherein the generating module is further
configured to:
collect data corresponding to the company;
verify the data;
analyze the collected data; and
deduce the financial forecast model based on the analysis.
43. The system of claim 41, wherein the generating module is configured to
collect data from primary sources and second sources.
44. The system of claim 39, further comprising a validating module
configured to validate the financial forecast model, wherein the validating of the financial
forecast model is based on a plurality of predetermined integrity checks, comprising of
accounting and reconciliation checks.
45. The system of claim 39 further comprising a manipulating module adapted
to allow a user to change at least one of a plurality of forecasting assumptions for
manipulating the financial forecast model.
46. The system of claim 39 further comprising a screening module configured
to screen companies based on sector, country, investment characteristics, and
fundamental and valuation filters.
47. The system of claim 39 further comprising a peer group analysis module
configured to perform a peer group analysis of the company.
48. The system of claim 47, wherein the peer group analysis module is
configured to compare financials of the company to financials of competitor companies.
49. The system of claim 39 further comprising a chart generation module
configured to generate charts based on financials of the company.
23
50. The system of claim 49, wherein chart generating module is configured to
generate charts based on a user defined criteria.
51. The system of claim 50 further comprising a collecting module configured
to collect historical data corresponding to the company.