USOO86.06672B2 (12) United States Patent (10) Patent No.: US 8,606,672 B2 Varma et al. (45) Date of Patent: Dec. 10, 2013 (54) METHOD AND SYSTEM FOR ANALYZING (56) References Cited INVESTMENT INFORMATION U.S. PATENT DOCUMENTS (75) Inventors: Samir Varma, Greenwich, CT (US); 6,349,291 B1 2/2002 Varma Michael Wayne Shore, Dallas, TX (US) OTHER PUBLICATIONS (73) Assignee: Reconstructor Holdings LLC, Greenwich, CT (US) SAS Institute User Guide. Statistical Analysis of AKS, Ak Steel Holding Corp. (C) RiskPic.com, (*) Notice: Subject to any disclaimer, the term of this Sep. 22, 2010, 18 pages. patent is extended or adjusted under 35 U.S.C. 154(b) by 40 days. * cited by examiner (21) Appl. No.: 13/288,660 Primary Examiner — Richard C Weisberger (74) Attorney, Agent, or Firm — Oblon, Spivak, (22) Filed: Nov. 3, 2011 McClelland, Maier & Neustadt, L.L.P. (65) Prior Publication Data (57) ABSTRACT US 2012/O116996 A1 May 10, 2012 An information processing apparatus and associated method Related U.S. Application Data for analyzing investment information. An input unit receives a financial request and one or more investment variables (60) Provisional application No. 61/410,237, filed on Nov. relating to the financial indicator and a description vector unit 4, 2010. generates at least two vectors containing the one or more investment variables based on the financial request. A (51) Int. Cl. description vector similarity unit then calculates a similarity G06O40/00 (2012.01) value by comparing the at least two vectors and an investment (52) U.S. Cl. analysis unit analyzes the similarity value and the financial USPC ............................................... 705/35; 705/37 request, and determines investment advice based on results of (58) Field of Classification Search the analysis. USPC ...................................................... 705/35 45 See application file for complete search history. 18 Claims, 5 Drawing Sheets 'sU.S. Patent Dec. 10, 2013 Sheet 1 of 5 US 8,606,672 B2 *..****…. U.S. Patent Dec. 10, 2013 Sheet 3 of 5 US 8,606,672 B2 :* ************** U.S. Patent Dec. 10, 2013 Sheet 4 of 5 US 8,606,672 B2 | | | | | | | eolk-+apv p~~~ : ********************,*,*,*,*,*,*; ;&~~~~~-~~~~~*~*~~••••••••••• -------------------------------- ~*~~)~;~«~ | { *~~~~~••••••••••••••••••••••?•••* | | | | | | ---- | --------...-- | | U.S. Patent Dec. 10, 2013 Sheet 5 of 5 US 8,606,672 B2 Start sawaaaaaaaaaaaa. it u Receive Financial ---YYYYY. request and |investment variabies s -- - - \, ^. w S30 - % ^. * NO WA variables» . ^ ^.Received? - -- ^ Y Generate Description i.S : Wectors ------------------------------------------------s-s-s-s s's Normalize investment . Waiaries Fig. 5 * 8 * * -X . \, *Additionax: - r x YES × Financia: X -8 3. 8. s S 2^ ^ ^ US 8,606,672 B2 1. 2 METHOD AND SYSTEM FOR ANALYZING analysis unit analyzes the similarity value and the financial INVESTMENT INFORMATION request, and determines investment advice based on results of the analysis. CROSS REFERENCE TO RELATED APPLICATIONS BRIEF DESCRIPTION OF THE DRAWINGS This Application is based upon and claims the benefit of A more complete appreciation of the present advance priority from the U.S. Provisional Application No. 61/410, ments and many of the attendant advantages thereof will be 237, filed on Nov. 4, 2010; the entire contents of which are 10 readily obtained as the same becomes better understood by incorporated herein by reference. reference to the following detailed description when consid ered in connection with the accompanying drawings. How FIELD ever, the accompanying drawings and their exemplary depic tions do not in any way limit the scope of the advancements The embodiments discussed herein relate to a method and embraced by this specification. The scope of the advance 15 ments embraced by the specification and drawings are system for analyzing investment information. More specifi cally, a method and system that provides investment advice defined FIG. by the words of the accompanying claims. 1 is a schematic diagram of a system for analyzing and comparisons of investment information based on an investment information according to an exemplary embodi analysis of financial information is described. ment of the present advancement; BACKGROUND FIG. 2 is a schematic diagram of an information processing apparatus according to an exemplary embodiment of the present advancement. Financial markets. Such as the stock market, provide a FIG.3 is a schematic drawing of a mobile device according vehicle for consumers to make financial investments with the to an exemplary embodiment of the present advancement; hope of monetary gain. For example, Stocks of a corporation 25 FIG. 4 is a functional drawing of the investment analysis purchased by a consumer can provide monetary gains for the system according to an exemplary embodiment of the present consumer if the Stock value increases over time. Before mak advancement; ing an investment in the stock market, a consumer should FIG. 5 is an algorithmic flow chart of analyzing investment undertake a considerable amount of time to research the information according to an exemplary embodiment of the investment. However, consumers are easily overwhelmed by 30 present advancement; and the amount of factors that can be taken into account when attempting to make a smart investment decision and may only DETAILED DESCRIPTION wish to focus on customized factors that are most relevant to a consumer's portfolio needs. Further, it is difficult for con In the following, the present advancement will be dis Sumers to determine the risk and reward levels of various 35 cussed by describing a preferred embodiment with reference investments as well as the similarity and/or differences to the accompanying drawings. However, those skilled in the between various investments based on these factors. art will realize other applications and modifications within Financial markets can also be extremely volatile which can the scope of the disclosure as defined in the enclosed claims. result in Sudden losses with respect to a consumers invest In embodiments, any desired network configuration, hard ment. This Sudden loss can cause the consumer to dispose of 40 ware, programming architecture, or a combination of both the investment regardless of potential future gains. For may be used to implement a system for analyzing investment example, a consumer may notice a Sudden drop in a stock information. price and proceed to sell the stock to avoid further losses. FIG. 1 is a schematic diagram of a system for analyzing However, the stock price over a longer period of time may investment information according to an exemplary embodi show a significant increase thereby resulting in a missed 45 ment of the present advancement. In FIG. 1, a computer 2 is opportunity by the consumer for long-term monetary gain. connected to a server 4, a database 6 and a mobile device 8 via A need exists for a method and system for analyzing invest a network 10. The server 4 represents one or more servers ment information that allows a consumer to generate custom connected to the computer 2, the database 6 and the mobile ized investment analysis and advice based on a variety of device 8 via the network 10. The database 6 represents one or factors identified by the consumer. Further, a need exists for 50 more databases connected to the computer 2, the server 4 and providing risk and reward information as well as comparison the mobile device 8 via network 10. The mobile device 8 information between investments based on the above-noted represents one or more mobile devices connected to the com factors in a way that intelligently informs a consumer of puter 2, the server 4 and the database 6 via the network 10. investment value in the past, present and into the future. The network 10 represents one or more networks, such as the 55 Internet, connecting the computer 2, the server 4, the database SUMMARY 6 and the mobile device 8. The server 4, the computer 6 and/or the mobile device 8 can In order to solve at least the above-noted problems, the be utilized as a central hosting site for the investment analysis present advancement relates to information processing appa system. Users of the computer 6 and mobile device 8 can also ratus and associated method for analyzing investment infor 60 access the investment analysis system on the server 4 via mation relating to a financial indicator. An input unit receives network 10. Accordingly, the server 4 may notify users of the a financial request and one or more investment variables investment information through the network 10 to the com relating to the financial indicator and a description vector unit puter 6 or mobile device 8. generates at least two vectors containing the one or more Next, a hardware description of the information processing investment variables based on the financial request. A 65 apparatus for analyzing investment information according to description vector similarity unit then calculates a similarity exemplary embodiments is described with reference to FIG. value by comparing the at least two vectors and an investment 2. In FIG. 2, the information processing apparatus includes a US 8,606,672 B2 3 4 CPU200 which performs the processes described above. The iPhone from Apple, Inc. of America, includes a processor 320 process data and instructions may be stored in memory 202. used to control the functions of the mobile device 8 and to run These processes and instructions may also be stored on a applications thereon, Such as an electronic address book, storage medium disk 204 such as a hard drive (HDD) or interne browser, etc. Processor 320 may be an ARM processor portable storage medium or may be stored remotely. Further, 5 or a processor such as a Core 2 Duo from Intel Corporation of the claimed advancements are not limited by the form of the America. Alternatively, Processor 320 may be implemented computer-readable media on which the instructions of the on an FPGA, ASIC or using discrete logic circuits, as would inventive process are stored. For example, the instructions be recognized by one of ordinary skill in the art. may be stored on CDs, BLU-RAY. DVDs, in FLASH A user interface 310, which may include a microphone, memory, RAM, ROM, PROM, EPROM, EEPROM, hard disk 10 speaker, touch screen, keyboard or any combination thereof, or any other information processing device with which the allows the processor 320 to receive input from a user of the information processing device communicates, such as a mobile device 300, and a display 315 provides feedback to the server or computer. user. Display 315 may be a color or monochrome LCD dis Further, the claimed advancements may be provided as a play or any other display that would be recognized by one of utility application, background daemon, or component of an 15 ordinary skill in the art. operating system, or combination thereof, executing in con Mobile device 8 also includes a communication interface junction with CPU 200 and an operating system such as 305 and antenna 335 to communicate with other devices, such Microsoft Windows 7, UNIX, Solaris, LINUX, Apple MAC as the server 4 or another mobile device 8. Further, mobile OS and other systems known to those skilled in the art. device 8 may communicate with these other devices wire CPU200 may be a Xenon or Core processor from Intel of lessly using the cellular network (including EDGE, 3G, 4G, America or an Opteron processor from AMD of America, or etc.) a WiFi connection, a Bluetooth connection or any other may be other processor types that would be recognized by one wireless form of communication that is known. Mobile of ordinary skill in the art. Alternatively, the CPU200 may be device 8 may also communicate through a wired connection implemented on an FPGA, ASIC, PLD or using discrete logic to communication interface 305, such as a USB connection. circuits, as one of ordinary skill in the art would recognize. 25 In some embodiments, mobile device 8 includes read-only Further, CPU200 may be implemented as multiple proces memory, ROM 330, to store low-level functions and pro sors cooperatively working in parallel to perform the instruc cesses necessary to support core functionality, and re-writ tions of the inventive processes described above. able memory 325, which stores an operating system, drivers, The information processing apparatus in FIG. 2 also applications, application data and user data. Re-writable includes a network controller 208, such as an Intel Ethernet 30 memory 325 may be dynamic or static random access PRO network interface card from Intel Corporation of memory (RAM), FLASH memory, EEPROM memory, and America, for interfacing with network 10. As can be appre the like. Further, portions of the re-writable memory 325 may ciated, the network 10 can be a public network, such as the be removable. Internet, or a private network such as an LAN or WAN net For example, re-writable memory 325 may store an appli work, or any combination thereof and can also include PSTN 35 cation for communicating with server 4 to identify mobile or ISDN sub-networks. The network 10 can also be wired, device 8 and to provide the server 4 with access to data stored Such as an Ethernet network, or can be wireless such as a therein. Such application may be downloaded, via any of the cellular network including EDGE, 3G and 4G wireless cel communication methods described above, from the server 4, lular systems. The wireless network can also be WiFi, Blue from a software repository or from an online store, such as the tooth, or any other wireless form of communication that is 40 App Store from Apple, Inc. of America. Further, such an known. application may be an electronic address book, or electronic The information processing apparatus further includes a personal information manager (PIM). However, the applica display controller 210, such as a NVIDIA GeForce GTX or tion may also be a plug-in for an electronic address book or Quadro graphics adaptor from NVIDIA Corporation of PIM already installed on mobile device 8, a background America for interfacing with display 212, such as a Hewlett 45 application, driver and the like. Packard HPL2445w LCD monitor. A general purpose I/O As one of skill in the art would recognize, the above interface 214 interfaces with a keyboard and/or mouse 216 as descriptions of the server 4 and mobile device 8 are merely well as a touch screen panel 218 on or separate from display examples and other server configurations and mobile devices 212. General purpose I/O interface also connects to a variety may be used without departing from the scope of the present of peripherals 220 including printers and scanners, such as an 50 advancements. OfficeJet or DeskJet from Hewlett Packard. According to some embodiments, a “module” refers to A sound controller 226 is also provided in the information hardware architecture or one or more programming architec processing apparatus, such as Sound Blaster X-Fi Titanium tures, or a combination of both, configured to perform one or from Creative, to interface with speakers/microphone 228 more designated functions. thereby providing Sounds and/or music. 55 FIG. 4 describes the functionality of the investment analy The general purpose storage controller 222 connects the sis system according to one embodiment of the present storage medium disk 204 with communication bus 224, advancement. FIG. 4 illustrates investment variables and a which may be an ISA, EISA, VESA, PCI, or similar, for financial request 400, the database 6, the server 4, the invest interconnecting all of the components of the information ment advice 410, a description vector unit 402, normalizing processing apparatus. A description of the general features 60 unit 404, description vector similarity unit 406 and an invest and functionality of the display 212, keyboard and/or mouse ment analysis unit 408. The description vector unit 402, nor 216, as well as the display controller 210, storage controller malizing unit 404, description vector similarity unit 406 and 222, network controller 208, sound controller 226, and gen an investment analysis unit 408 are illustrated within the eral purpose I/O interface 214 is omitted herein for brevity as server 4 but in other embodiments could be included within these features are known. 65 the computer 6 or the mobile device 8. Investment variables FIG. 3 is a block diagram of the mobile device 8. The and a financial request 400 relating to an investment, or finan mobile device 8, which may be a Smart phone such as an cial indicator, are received from a user depending on the US 8,606,672 B2 5 6 investment information the user wants to obtain. Example tion determined by the investment analysis unit 408 is investment variables 400 include P/E rations, debt to equity, described later with respect to FIG. 5. total sales, and temporal resampled risk. The financial request The investment advice 410 of the investment analysis unit represents a request from the user to obtain certain financial 408 are provided to the database 6 to be stored for possible information. A variety of non-limiting examples of financial later analysis and are provided to the user via at least a requests are described in detail later. The investment variables computer 2 or mobile device 8 as described in FIG. 1. and financial request 400 are then transmitted to the server 4 FIG. 5 is a algorithmic flow chart of analyzing investment via the network 10 as described in FIG. 1. information according to an exemplary embodiment of the The description vector unit 402 of the server 4 defines a present advancement. The process of analyzing investment description vector based on the investment variables and the 10 information starts at step S500 by having a user input a financial request 400. The description vector can represent a customized ranking of factors, or investment variables 400, multidimensional point in multidimensional space and con relating to the investment (p?e ratios, debt to equity, etc), and tains the investment variables 400. The description vector a financial request 400. The system then determines whether defines what type of investment information, Such as risk or all the variables have been received at step S502. IfNO at step reward information, the user is seeking to obtain for his or her 15 S502, the system continues to accept investment variables portfolio needs. More information with respect to the descrip 400 until the user has finished. If YES at step S502, the system tion vector is provided later with respect to FIGS. 5 and 6. proceeds to step S504 to generate a description vector based The normalizing unit 404 of the server 4 normalizes all of on the investment variables and the financial request 400. the investment variables 400 of the description vector defined The description vector DV generated by the description by the description vector unit 402. Normalization is required vector unit 402 is defined as follows. DV=(s1, s2, s3, ..., Sn), so that all of the investment variables 400 have an equal where s1 through Sn are investment variables 400 that weight with respect to each other when investment calcula describe an investment or benchmark in question. Therefore, tions are performed. One type of normalization is 1/N, where if the user wanted to measure the risk of a single stock and N is the number of investment variables 400. Another type of determines that the most important factors are the p?e ratio, normalization is to use the standard deviation of all the infor 25 the 21 day resampled risk of the maximum drawdown mation in database 6. For this type of normalization, the exceeding 10%, and the Quick Ratio, then the description information analyzing system calculates the standard devia vector for this particular stock, i.e. for this particular calcu tion for each investment variable 400 contained in the data lation, would bean"Investment Risk Vector” defined as IRV= base 6 and then divides the investment variable 400 of the (p?e ratio, 21 day resampled risk of the maximum drawdown particular investment by the standard deviation. For example, 30 exceeding 10%, Quick Ratio). A corresponding “Benchmark if the user selects IBM as a particular investment and chooses Risk Vector would be defined as BRV-(p?e ratio, 21 day the P/E Ratio as one of the investment variables 400, the resampled risk of the maximum drawdown exceeding 10%, investment analysis system locates all of the P/E Ratios in the Quick Ratio). While both vectors contain the same invest database 6, calculates the standard deviation, and then divides ment variables 400, the values of the investment variables 400 the P/E Ratio of IBM by the standard deviation to obtain a 35 will likely be different based on the corresponding value of normalized value. each investment variable 400 in the database 6 with respect to The present advancement, however, does not require the the investment or benchmark. Once the description vector is input investment variables to be equally weighted. As long as defined, the process proceeds to step S506 to normalize each the sum of all the normalization weights is 1, different invest of the investment variables 400. ment variables 400 could have different weights. Any addi 40 The investment variables 400 must be normalized to ensure tional description vector being compared to the description they each provide the appropriate amount of weight to the vector defined by the description vector unit 204 would also investment analysis calculations. For example, the absolute have to be normalized to keep calculations consistent. More value of a p?e ratio is generally in the tens or twenties. The information with respect to the normalizing unit 404 is pro absolute value of a 21 day resampled risk, however, is vided later with respect to FIG. 5. 45 between Zero and 1. If the two variables were not normalized, The description vector similarity unit 406 calculates the then any future calculation would be almost entirely domi similarities between description vectors created by the nated by the p?e ratio. description vector unit 402 and normalized by the normaliz One option is for the user to specify how to normalize each ing unit 404. As described later, at least one way to determine variable based on the user's needs. However, a natural, the similarity between description vectors is to calculate the 50 default, normalization for each piece of data is Supplied for Euclidean distance between the description vectors. How the ease of the user. As noted above, one such natural normal ever, another metric for determining the similarity is to use an ization is to use the standard deviation of all such pieces of absolute value metric or any other metric defined by the user information in the database 6. So, for example, if the user of the investment analysis system. The results of the descrip requested analysis on a particular stock, and the user's tion vectors similarity unit are then transmitted to the invest 55 choices were the p?e ratio, the pf's ratio, and the chance of a 5 ment analysis unit 408. day maximum drawdown exceeding 5%, all the p?e ratios The investmentanalysis unit 408 analyzes the results of the would be located in the database 6, their standard deviation description vector similarity unit 406 to provide the user with would be calculated, and then that particular stock's p?e ratio investment advice based on the investment variables and the would be divided by this standard deviation. Then all the p/s financial request 400 defined by the user. To do this, the 60 ratios would be located in the database 6, their standard investment analysis unit 408 compares similarity information deviation would be calculated, and this stock's p?'s ratio would from the description vector similarity unit 406 based on what be divided by that standard deviation. This process is repeated type of investment information the user is interested in until all the investment variables 400 of the description vector obtaining for his or her portfolio. Non-limiting examples of are normalized. investment information includealist of a best or worst invest 65 Returning to the description vector, non-limiting examples ments, a comparison of investments, and risk and reward of the description vector include an Investment Risk Vector, information. More information on the investment informa Benchmark Risk Vector, Investment Reward Vector and an US 8,606,672 B2 7 8 Benchmark Reward Vector. The description vector can also Returning to FIG. 5, after the investment variables 400 be any other vector chosen by the user. As such, the names have been normalized at step S506, the similarities between “Benchmark Risk Vector”, “Benchmark Reward Vector, the description vectors are calculated at step S508. There are “Investment Risk Vector” and “Investment Reward Vector' different ways of defining a similarity between two descrip are for convenience and the user is free to specify any number 5 tion vectors. One option is to take the Euclidean distance of vectors with customized naming conventions so as to make between two multidimensional vectors generated by the whatever comparison the user sees fit between whatever description vector unit 402. This would be represented by, for instruments, portfolios or groups the user wants. The Invest example, IRisk-BRisk or IReward-BReward, which rep ment Risk Vector IRisk is defined as follows. IRisk=(IRisk 1, resents taking each normalized investment variable 400 from IRisk2, IRisk3,..., IRiskin), where IRisk1 through IRiskin are 10 each description vector generated by the description vector the normalized investment variables 400 that describe the unit 402, subtract one from the other, square the result, sum investment in question. For example, IRisklip?e ratio, them together, and take the square root. For example, to IRisk2–21 day resampled risk, IRisk3=total sales of com calculate the risk of an investment, the following calculation pany/total sales in industry, etc., to IRiskin. Alternatively, is performed: (IRisk1-BRisk1)2+(IRisk2-BRisk2)2+ IRisk1=5 day resampled risk of maximum drawdown >5%, 15 (IRisk3-BRisk3)2+...+(IRiskN-BRiskN)2. The square IRisk2-chance of hitting a fixed stop loss of 3% over a one root of the resulting sum is then calculated to obtain the month period, etc., to IRiskin. The investment could be any similarity value. thing from an individual financial instrument Such as a stock, Another method of calculating the similarity is by using an to a group of financial instruments such as a group of stocks, absolute value similarity metric. Using the absolute value to an entire investment portfolio made up of any number of metric, each normalized investment variable from each financial instruments such as stocks, bonds, mutual funds, description vector generated by the description vector unit commodities, options, OTC derivatives, currencies, contin 402 is subtracted from one another and the resultant values gent claims, derivatives, balance sheet items, options, futures, are added to obtain a distance between the description vec exchange traded instruments, and over the counter instru tors. The absolute value of the distance is then determined to mentS. 25 obtain a similarity value. For example, to calculate the risk of The Benchmark Risk Vector Brisk is defined as follows. an investment, the following calculation is performed: BRisk=(BRisk 1, BRisk2, BRisk3, . . . , BRiskin) where (IRisk1-BRisk1)|+| (IRisk2-BRisk2)|+| (IRisk3 BRisk1 through BRiskin are the same investment variables BRisk3)|+...+(IRiskN-BRiskN). 400 as IRisk1 through IRiskin, but for the Benchmark rather It should be noted that when more variables are added, the than the Investment if the Benchmark Risk Vector BRisk is 30 absolute value of the result will increase. While the results for used in comparison to the Investment Risk Vector. A Bench each calculation will be unaffected by this, it might cause mark is a standard against which the performance of a secu some confusion to a user. Therefore, one non-limiting rity, mutual fund or investment manager can be measured. example to keep intuition correct from one similarity calcu Generally, broad market and market-segment stock and bond lation to the next for the user, is to divide each “similarity” indexes are used for this purpose. For example, the Bench 35 result by VN, where N is the number of variables in the vector. mark could be a recognized benchmark like the S&P 500, it Investment advice is then determined by the investment could be a sector index, it could bean ETF, or it could be some analysis unit 408 based on the results of step S508 and the custom composite created by the user. types of description vectors compared. Provided below are The Investment Reward Vector IReward is defined as fol non-limiting examples of investment advice determined by lows. IReward=(IReward 1, IReward2. IReward3, IRewardn), 40 the investment analysis unit 408 based on a variety of finan where the investment variables 400 are variables that the user cial requests 400 received that relate to investment informa thinks affect the expected return of the investment. The tion. For example, upon receiving a financial request to iden investment could be for a stock, a portfolio, or a mixed bag of tify the risk of an investment, the investment analysis system various kinds of investments. It should be noted that the calculates the similarity between the investment risk vector Investment Reward Vector should not be the same vector as 45 and the benchmark risk vector. For this analysis, the greater Investment Risk Vector IRisk. The Investment Risk Vector the number calculated from the similarity between the invest IRisk represents what the user thinks of as the financial infor ment risk vector and the benchmark risk vector, the higher the mation that goes wrong, or might go wrong, or that which risk of the investment. indicates an elevated level of risk. IReward represents that An investment comparison can also be calculated to pro financial information which the user thinks might go right 50 vide the user with information on how the current investment thereby providing a favorable return for the user. compares to an ideal investment. An ideal investment is a The Benchmark Reward Vector is defined as follows. predefined investment by the user based on the user's finan BReward=(BReward1, BReward2. BReward3, . . . . cial requirements. This is determined by calculating the simi BRewardn) where the investment variables 400 correspond to larity between the investment reward vector and the bench the investment variables 400 defined in the Investment 55 mark reward vector. For this analysis, the smaller the number Reward Vector IReward if the Benchmark and the Investment calculated from the similarity between the investment reward Reward Vector IReward are being compared. It should be vector and the benchmark reward vector, the closer the cur noted that BReward represents the “ideal investment accord rent investment is to the ideal investment and therefore the ing to the user. For example, if the user is a stock investor and better the current investment. is interested in value, the user may think the best kinds of 60 For a given group of investments, a list of the best and worst investments are those where the p?e ratio is less than 10, the investments out of the group can be calculated. This list is price/book is less than 1, the current ratio is greater than 1, and determined by calculating the risk and reward for each invest the profit margin is greater than 5%. Thus, the user would ment in the database 6. Next, for each investment, the ratio create a BReward with those four investment variables 400 “(1/reward)/(risk) is calculated and the investments can be and normalize the investment variables 400. A comparison of 65 ranked by this number. Accordingly, the investments with the proposed investments to this “ideal investment will be highest ranks are the best and the investments with the lowest described later. ranks are the worst. The best or worst investments can be any US 8,606,672 B2 10 type of investment meeting predetermined constraints by the larity values between IReward1 and BReward 1, IReward2 user. For example, a best investment could be one which and BReward2 and so forth through IReward 10 and makes the most short term gain whereas the worst investment BReward 10. could be one with the quickest loss short term. Similarly, if it is believed that the most worrisome risks are Alternative investments that have a similar risk profile to such concerns as the risk that this stock will fall more than the current investment can also be calculated. This is analysis 10% in the next week, the probability that this stock will hit a is performed by calculating the risk for all the investments in stop loss placed 15% away, and the risk that this stock will fall the database 6 and finding those investments with a risk value more than 20% from a purchase price at any time over the next that is closest to the risk value of the current investment. year, the IRisk vector is defined as the normalization of the above noted risk values. Further, the BRisk vector with Similarly, alternative investments that have a similar reward 10 respect profile to the current investment can also be calculated. This investmentto the Benchmark i.e. the S&P 500 contains the same is analysis is performed by calculating the reward for all the larity values,variables 400. Again, the ten distances, or simi are then calculated as dRisk1 through dRisk10 investments in the database 6 and finding those investments by obtaining the risk similarity values between IRisk1 and with a reward value that is closest to the reward value of the 15 current investment. BRisk1, IRisk2 and BRisk2 and so forth through IRisk10 and BRisk10. For a user interested in one investment, better investments Next, the ten Reward/Risk statistics are calculated as “(1/ with similar risk profiles can be calculated. First, and as Reward Similarity Valuei)/Risk Similarity Valuei', with i explained above, all other investments that have a similar risk going from 1 to 10. Given the above-noted considerations and profile to the one investment are located from the database 6 based on the results, the highest ranked stock would be the and their reward values are calculated. These investments are best and the lowest ranked stock would be the worst. For then ranked by the equation"(1/reward value)/(risk value) to example, the highest ranked stock has the lowest calculated determine the better investments. value and the worst stock has the highest calculated value A user can also build a portfolio with an optimal risk/ based on the equation: “(1/Rewardi)/Riski.” reward. In this case, an optimization routine would find the 25 In another example according to the present advancement, portfolio that maximized the “(1/reward)/risk” ratio subject sometimes the user is not worried about risk but is instead to user defined constraints. The user defined constraints can interested in the stocks that best match a stock display Screen represent certain filters within a portfolio with respect to the of the user. In other words, the user may be interested in investment information. For example, the user could define stocks that best match a stock display screen defining that constraints such that no single investment can have more than 30 earnings growth must be >60% in the last quarter, sales a 10% weight in the portfolio, the top 5 investments must growth must be >25% in the last quarter, and average annual account for at least 25% of the total weight in the portfolio, earnings per share must be >25% over the last 3 years. currencies must represent a fraction between 3% and 5% of A problem with this scenario is that a user will typically the portfolio, and gold must represent between 1% and 3% of just adjust the values displayed on the stock display Screen the portfolio. To define best portfolio, similarity to a bench 35 screens until a certain number of stocks come up when no mark is used for optimization. stocks meet the original stock display screen criteria. This In other words, for a portfolio, there would be a weight (wi) causes problems because often the user is looking for a "com for each investment. Each variable that went into either the mon-sense' or "close-enough” match to the screen and investment risk vector or the investment reward vector would adjusts the screens, which can move the user away from be weighted by that weight (wi) as follows: 40 obtaining a meaningful screen match. In other words, there IReward=w1 IReward V1+w2*IRewardV2+ isn't much of a real difference between a stock that grew at w3*IReward V3 and so on, with the sum of the ws=1, where 25% and one that grew at 24.5%. For this case, BReward is each of the IRewardV’s is a vector. BReward is set to the defined as (60.25.25). user's idea of the ideal investment. IRiskw1*IRiskV1+ Next, all the stocks in the database 6 are processed and for w2*IRiskV2+w3*IRiskV3 and so on, while having the same 45 each one the IReward is calculated as “min(Earnings Growth, w’s as IReward. An optimization routine to maximize 60), min(Sales Growth.25), min (Average Annual Earnings, (1/IReward-BReward)/(IRisk-BRisk) by varying the 25). Therefore, criterion that are specified as “must be w’s, subject to constraints, would then be used to rank the greater than or “must be less than are replaced by any various investments based on the user constraints. numbers that exceed (are less than) the threshold by the In another example according to the present advancement, 50 threshold. In other words, if the earnings growth is more than when trying to choose amongst 10 stocks that have been 60, it is replaced with 60. As such, if there are N stocks, N identified via a stock screen or some other associated method, distances Ni are calculated between BRewardi and IRe it is important to know which of these stocks gives the most wardi. When the N distances Ni are ranked in ascending return with respect to the risk. If it is believed that the best order, the lowest N's have the best match to your criteria. stocks have Earnings Growth in the current quarter of 50% to 55 Therefore, the present advancement provides a more useful 75%, Annual earnings growth over the last 3 years of 15%- and reliable stock screen than those provided by conventional 25%, and as close to new highs as possible, the BReward methods. vector is defined as “62.5/normalization (investment vari According to another example of the presentadvancement, able-), 20/normalization (investment variable), O/normal assume that a user is a portfolio manager who owns a variety ization (investment variable). The value 62.5 represents the 60 of stocks and has the S&P 500 as a benchmark. Because of midpoint of 50 to 75, the value 20 represents the midpoint of this situation, it may seem that the user is massively correlated 15%-25%, and 0 represents a stock trading at a new high, ie, to the S&P 500 and is a closet indexer. This is a problem ((current price-highest price)/current price)/normalization because customers may ask why they are paying money for (investment variable). The same process is then repeated for services when it seems like the user is just following the S&P each of the ten stocks to get their IReward vectors. The ten 65 500. While this may just be a coincidence, there needs to be a distances, or similarity values, are then calculated as way to prove the coincidence to the customer. One solution dReward 1 through dReward 10 by obtaining the reward simi afforded by the present advancement is to pick a set of salient US 8,606,672 B2 11 12 investment variables 400 such as the PIS ratio, the P/E ratio, According to another example of the presentadvancement, average daily trading Volume, and market cap relating to a the best stocks in the “energy” sector can be calculated by financial request to determine a financial correlation. The customizing a BRisk and BReward and performing the weighted average P/S, P/E, average daily trading volume and above-noted procedures for a ranking. If a user is interested in market cap of the user's portfolio (weighted by their percent stocks that are “like', or "closest to Southern Co., the user age weight in the portfolio) is then calculated based on their determines user-customized investment variables 400 such as values in the database 6 and are compared to the values from Debt/Equity, Price/Sales, Quick Ratio, and Market Cap and the database 6 of the same input variables 400 with respect to creates a BReward with these investment variables 400 for the S&P 500. In other words, the BReward and the IReward Southern Co. These results are then compared by the invest are calculated and compared. If they’re substantially different 10 ment analysis system to all the IRewards in the database 6 and than Zero, then the high correlation to the S&P 500 has noth the top N matches can be determined Similarly, if a user is ing to do with being a “closet indexer” and the customer's interested in stocks like "RHAT', but wants Risk to be taken concerns can be allayed. into account, the user defines investment variables 400 such According to another example of the present advancement, as market cap, debt ratios, share numbers, common owners, the user may determine that a particular stock used to be a 15 financial metrics, and similar past performance for Reward “value' stock but is now a “growth' stock because the stock (call these X1,X2, X3, . . . Xn) and appropriate investment has raised in value significantly. As such, the user may have a variables (y1, y2, y3 ...,yn) for Risk. The user then creates problem convincing an investment committee to sell the stock a BRisk description vector withy 1 throughlyn and a BReward unless the user can show that the stock should not be in the description vector with x1 through xn. The normal above user's portfolio. noted ranking procedure is then applied to determine the best To solve this issue, a BReward Value and a BReward stocks that are like "RHAT” Further, if the user is interested Growth are calculated by the investment analysis system. in stocks that are like “RHAT but only within the “technol Using these calculations, the user can demonstrate that three ogy” sector, the investment analysis system follows the above years ago when the user bought the stock, its BReward Value procedure while restricting the stocks in consideration to number was much smaller than its BReward Growth number. 25 “technology’ stocks. However, now the situation is reversed in that the BReward According to another example of the presentadvancement, Value is very much larger than BReward Growth. It is impor a user may wish to determine whether his mutual fund is tant to note in this situation that the BReward Value and exhibiting “style drift' based on the managers investment BReward Growth vectors need not have the same factors strategy. Style drift is when a manager has bad performance thereby making comparisons very simple for users well 30 and changes his method of managing his fund to try to catch versed in the differences between value and growth stocks. up. This is usually a disaster for the investor. To solve this According to another example of the presentadvancement, problem, the user takes a portfolio of the fund from a past assume a user wants to invest in companies local to where the disclosure and picks the salient investment variables 400 user lives because the user believes he would have a better (these will depend on the type of fund). The investment analy understanding of information with respect to those local com 35 sis system then determines the old IReward and BReward panies from reading local newspapers, talking to local com based on these past investment variables 400 values stored in pany employees, etc. However, determining which compa the database 6 and calculates the distance. The investment nies are local can be troublesome using conventional analysis system then takes the portfolio of the fund today and methods. A user must struggle with an overwhelming amount makes the same IReward and BReward but with the current of search options to determine whether a company is local 40 values. At this point the investment analysis system can Such as a company's official address, local revenue, the num inform the user whether the distance has changed apprecia ber of employees that live near the user, the percentage of the bly. The investment analysis tool can also repeat this process company's Suppliers that are local, and the percentage of the for every past quarter to determine whether the distance cal company's customers that are local. Therefore, unless the culation Suddenly spikes up or drifts up every quarter. user take all these things into account, the user will find it 45 According to another example of the presentadvancement, difficult to get useful information with respect to his invest a user that wants to buy government debt can determine how ment needs. much riskier that government debt is as compared to other The use of description vectors of the present advancement government debt. For example, assume the user wants to buy overcomes this problem. First, all of the above-noted infor Italian government debt but believes that German govern mation with respect to each company is collected and stored 50 ment debt should be taken to be "risk free'. The user then in the database 6. For example, the distance of “headquarters' wants to know how much riskier the Italian government debt of a company from the geographic center of where the user is as compared German government debt. Here, the user lives, the percent of the company's employees that work determines that the investment variables 400 are “percent of within 25 miles of where the user lives, the percentage of the debt maturing in the next year, the “debt/GDP ratio’, the company's revenue that is generated in the State where the 55 “current account deficit as a percent of GDP, and “percent user lives, the amount of the company’s Supplies that come age of debt held by foreigners’. The investment analysis from company's in the user's state, and the percentage of the system then constructs the BRisk with German statistics and company's revenue that comes from other states can be the IRisk with Italian Statistics. The calculated distance mea included in an BReward description vector such as BReward sures show how much riskier Italian Debt is versus German (0,100,100,100,100). This value is then compared by the 60 Debt. investment analysis system to the IReward of every company According to another example of the presentadvancement, in the database 6 using the same variables as those in the the user may want to buy GE bonds and determine how much BReward description vector to calculate the distances ther riskier the GE bonds are than F bonds? If the user believes that ebetween. Based on the results and the customization and IBM bonds are almost "risk free” and should be used as the calculation by the investment analysis system, the user is 65 benchmark, the user picks salient investment variables 400 provided with information describing that the lowest dis and the investment analysis tool constructs IRiskGE, IRiskF tances represent the most “local companies. and BRiskIBM and compares the distance of IRiskGE versus US 8,606,672 B2 13 14 BRiskIBM with IRiskF versus BRiskIBM. The one with the The invention claimed is: highest distance is the riskiest. 1. An information processing apparatus for analyzing According to another example of the present advancement, investment information, comprising: the user may believe that countries with the following set of a processor programmed to characteristics (S) have currencies, or stocks, that will appre 5 receive a financial request identifying financial informa ciate. The investment analysis system can then provide the tion a user wishes to obtain relating to an investment, best investments from a list of countries in the database 6 by and one or more different types of investment vari generating BReward and IReward and ranking by ascending ables relating to at least one of the investment and a order of distance. benchmark, Referring back to FIG. 5, once the investment advice is 10 generate at least two vectors containing the one or more returned, it is determined whether there are any additional investment variables based on the financial request, financial requests at step S512. If YES at step S512, then the calculate a similarity value by calculating a distance between the at least two vectors, and process returns to step S500 to receive different investment analyze the similarity value and the financial request, variables and financial requests 400. If NO at step S512, the 15 and analysis process is completed and the process ends. determine output information, as investment advice for a According to one embodiment of the present advancement, user, correlating to the financial request and the simi any investment information determined by the analysis larity value based on results of the analysis, investment system is organized and stored virtually in a plu wherein each vector is one of the following types: rality of folders. For example, analysis results can be stored an investment reward vector containing one or more invest on a recording medium of a PC or in the database 6 connected ment variables which the user believes relate to an to the network 10. A user can then use his computer 2 or expected financial return of the investment, connect to the network 10 to obtain previously calculated an investment risk vector containing one or more invest investment information based on previously customized ment variables which the user believes relate to a level of description vectors. 25 risk of the investment, Websites hosted by servers 4 can also provide users with a benchmark reward vector containing the one or more online access to the features afforded by the analysis invest investment variables which the user believes relate to the ment system. These websites provide general access features expected return of the investment, the one or more vari to all users as well as increased access and functionality when 30 ables having values identified by the benchmark, or a user registers with the website. A user who is registered a benchmark risk vector containing the one or more could access old financial investment information based on investment variables which the user believes relate to previously customized description vectors via a search of the the level of risk of the investment, the one or more virtual folders. This old investment information could then be variables having values identified by the benchmark. compared against current values obtained by running the 35 wherein theinformation 2. The processing apparatus of claim 1, processor is further programmed to normalize the previously customized description vectors. A user can also one or more investment variables by converting the one or use customized description vectors to determine investment more investment variables into one or more normalized val information based on previous market conditions at a specific ues each having an equal weight with respect to each other. date or automatically update the old investment information 3. The information processing apparatus of claim 1, based on current market conditions. 40 wherein the processor calculates the similarity value by cal Though the above discussion has been made with reference culating the Euclidean distance between the at least two vec to the stock market, other financial markets or investment tOrS. structures may also be used without departing from the spirit 4. The information processing apparatus of claim 1, of this advancement. wherein the financial request is to determine a level of risk of Any processes, descriptions or blocks in flowcharts 45 the investment, to determine how the investment compares to described herein should be understood as representing mod an ideal investment received from the user, determine one or ules, segments, orportions of code which include one or more more investments having a similar risk profile with respect to executable instructions for implementing specific logical the investment, or to analyze a relationship of one or more functions or steps in the process, and alternate implementa 50 investments to the benchmark to identify closet indexing. tions are included within the scope of the exemplary embodi wherein 5. The information processing apparatus of claim 4. the benchmark of the benchmark reward vector and ment of the present advancements in which functions may be benchmark executed out of order from that shown or discussed, including against whichrisk vector relates to a benchmark standard the performance of the investment can be mea Substantially concurrently or in reverse order depending upon Sured. the functionality involved. 55 6. The information processing apparatus of claim 1, Obviously, numerous modifications and variations of the wherein a type of the at least two vectors generated by the present advancements are possible in light of the above teach processor is based on the financial request. ings. In particular, while the application of the present 7. The information processing apparatus of claim 4. advancement has been described with respect to events such wherein a type of the at least two vectors generated by the as conventions, sports and concerts, other applications are 60 processor is based on the financial request. within the scope of the appended claims. For example, with 8. The information processing apparatus of claim 1, out limitation, the present advancement may be applied to wherein in response to receiving a predetermined number of Video games, TV, cell phones, tablets, web applications, and investment variables, the processor divides the similarity any other platform as would be understood by one of ordinary value by a function of the number of investment variables. skill in the art. It is therefore to be understood that within the 65 9. The information processing apparatus of claim 4. Scope of the appended claims, the present advancements may wherein when the financial request is to determine a level of be practiced otherwise than as specifically described herein. risk of the investment, the processor generates an investment US 8,606,672 B2 15 16 risk vector and a benchmark risk vector, calculates the simi ing, for each financial indicator, the ratio r, where r (1/ larity value, and determines the level of risk of the investment reward similarity value)/(risk similarity value). based on the similarity value such that the higher the similar 14. The information processing apparatus of claim 4, fur ity value, the lower the level of risk and the lower the simi ther comprising: larity value the higher the level of risk. 5 a database configured to store a plurality of investments, 10. The information processing apparatus of claim 4. wherein when the financial request is to determine one or wherein when the financial request is to determine how the more investments having a similar risk profile with investment compares to an ideal investment received from the respect to the investment, user, the processor the processor 10 generates a risk investment vector and a benchmark risk receives one or more investment variables which the vector containing one or more investment variables user believes describe the ideal investment, relating to the investment, and generates an investment reward vector containing the generates, for each investment of the plurality of invest one or more investment variables describing the ments, an additional risk investment vector and an investment and a benchmark reward vector contain- 15 additional benchmark risk vector containing one or ing the one or more investment variables describing more investment variables which the user believes the ideal investment, relate to the level of risk of the investment, calculates the similarity value, and calculates the similarity value between the risk invest determines how the investment compares to the ideal ment vector and the benchmark risk vector, investment such that the higher the similarity value, for each additional financial indicator of the plurality of the further the investment is from the ideal investment additional financial indicators, calculates an addi and the lower the similarity value the closer the invest tional similarity value by comparing the additional ment to the ideal investment. risk investment vector and the additional benchmark 11. The information processing apparatus of claim 4. risk vector, and wherein when the financial request is to rank a plurality of 25 determines one or more investments having a similar financial indicators, risk profile with respect to the investment by compar the description vector unit generates, for each financial ing the similarity value of the investment to each indicator, an investment reward vector, a benchmark additional similarity value calculated for each of the reward vector, an investment risk vector, and a bench plurality of other investments. mark risk vector, each containing one or more invest 30 15. The information processing apparatus of claim 4. ment variables relating to the financial indicator, wherein when the financial request is to analyze a relationship the description vector similarity unit calculates, for each of one or more investments to the benchmark to identify financial indicator, a reward similarity value between the closet indexing, investment reward vector and the benchmark reward the processor vector and calculates a risk similarity value between the 35 generates an investment reward vector and a benchmark investment risk vector and the benchmark risk vector, reward vector containing the one or more investment and variables, the investment analysis unit determines the ranking of the calculates the similarity value, and plurality of financial indicators by comparing each determines whether closet indexing is taking place reward similarity value and each risk similarity value. 40 based on the similarity value by determining whether 12. The information processing apparatus of claim 11, the similarity value is greater than a predetermined wherein the investment analysis unit processor determines threshold. the ranking of the plurality of financial indicators by calcu 16. A method, implemented by an information processing lating and ranking, for each financial indicator, the ratio r, apparatus, for analyzing investment information, comprising: where r (1/reward similarity value)/(risk similarity value). 45 receiving, at a processor, a financial request identifying 13. The information processing apparatus of claim 4. financial information a user wishes to obtain relating to wherein when the financial request is to determine a plurality an investment, and one or more different types of invest of financial indicators adhering to predetermined constraints, ment variables relating to at least one of an investment the input device receives a plurality of weighting factors, and a benchmark; each weighting factor corresponding to a different finan 50 generating, via the processor, at least two vectors contain cial indicator of the plurality of financial indicators; ing the one or more investment variables based on the the description vector unit, for each financial indicator, financial request; generates an investment reward vector, a benchmark calculating, via the processor, a similarity value by calcu reward vector, an investment risk vector, and a bench lating a distance between the at least two vectors; and mark risk vector, each containing one or more invest 55 analyzing, via a processor, the similarity value and the ment variables relating to the financial indicator, and financial request; and multiplies a corresponding weighting factor to the determining, via the processor, output information as investment reward vector, benchmark reward vector, investment advice for the user, the output information investment risk vector, and benchmark risk vector, correlating the financial request and the similarity value the description vector similarity unit calculates, for each 60 based on results of the analysis, financial indicator, a reward similarity value between the wherein each vector is one of the following types: investment reward vector and the benchmark reward an investment reward vector containing one or more invest vector and calculates a risk similarity value between the ment variables which the user believes relate to an investment risk vector and the benchmark risk vector, expected financial return of the investment, and 65 an investment risk vector containing one or more invest the investment analysis unit determines the ranking of the ment variables which the user believes relate to a level of plurality of financial indicators by calculating and rank risk of the investment, US 8,606,672 B2 17 18 a benchmark reward vector containing the one or more generating at least two vectors containing the one or more investment variables which the user believes relate to the investment variables based on the financial request; expected return of the investment, the one or more vari calculating a similarity value by calculating a distance ables having values identified by the benchmark, or between the at least two vectors; a benchmark risk vector containing the one or more invest analyzing the similarity value and the financial request; and ment variables which the user believes relate to the level determining output information as investment advice for of risk of the investment, the one or more variables the user, the output information correlating the financial request and the similarity value based on results of the having values identified by the benchmark. analysis, 17. The method of claim 16, 10 wherein each vector is one of the following types: wherein the financial request is to determine a level of risk an investment reward vector containing one or more invest of the investment, to determinehow the investment com ment variables which the user believes relate to an pares to an ideal investment received from the user, to expected financial return of the investment, determine one or more investments having a similar risk an investment risk vector containing one or more invest profile with respect to the investment, or to analyze a 15 ment variables which the user believes relate to a level of relationship of one or more investments to the bench risk of the investment, mark to identify closet indexing. a benchmark reward vector containing the one or more 18. A non-transitory computer-readable medium storing investment variables which the user believes relate to the computer-readable instructions thereon which when expected return of the investment, the one or more vari executed by a computer cause the computer to perform a ables having values identified by the benchmark, or method for analyzing investment information, comprising: a benchmark risk vector containing the one or more invest ment variables which the user believes relate to the level receiving a financial request identifying financial informa tion a user wishes to obtain relating to an investment and of risk of the investment, the one or more variables one or more different types of investment variables relat having values identified by the benchmark. ing to at least one of an investment and a benchmark; k k k k k