WO2010003137A1 - Systèmes et procédés pour fournir des données de performance d’investissement à des investisseurs - Google Patents
Systèmes et procédés pour fournir des données de performance d’investissement à des investisseurs Download PDFInfo
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- WO2010003137A1 WO2010003137A1 PCT/US2009/049641 US2009049641W WO2010003137A1 WO 2010003137 A1 WO2010003137 A1 WO 2010003137A1 US 2009049641 W US2009049641 W US 2009049641W WO 2010003137 A1 WO2010003137 A1 WO 2010003137A1
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Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/06—Asset management; Financial planning or analysis
Definitions
- FIG. 1 is a block diagram of the investment data sharing system (IDSS), under an embodiment
- Figure 9 is a flow diagram for generating a skill score using the Sharpe Ratio (SR) and Information Ratio (IR), under an alternative embodiment.
- SR Sharpe Ratio
- IR Information Ratio
- Figure 10 is a flow diagram for generating a persistence score
- Figure 11 is a flow diagram for generating a confidence score
- Figure 26 is an example output of the mutual fund engine of the recommendation engine, under an embodiment
- Figure 27 shows sample results of derived asset allocation models, derived under an embodiment, in view of results from major brokerage firms and mutual fund companies
- Figure 29 is an example output showing application of the asset allocation target models to identify sector-level allocations for investors, under an embodiment.
- Figure 30 is an example output showing the Fit Score for a particular stock, under an embodiment
- the processing system of an embodiment includes at least one processor and at least one memory device or subsystem
- the processing system can also include or be coupled to at least one database
- the term "processor” as generally used herein refers to any logic processing unit, such as one or more central processing units (CPUs), digital signal processors (DSPs), application-specific integrated circuits (ASIC), etc
- the processor and memory can be monolithically integrated onto a single chip, distributed among a number of chips or components of the IDSS, and/or provided by some combination of algorithms
- the IDSS methods described herein can be implemented in one or more of software algorithm(s), programs, firmware, hardware, components, circuitry, in any combination
- the ranking component 104 of an embodiment is configured to perform a weighting of members using results of the calculations and data of numerous weighting parameters or member attributes as described above
- the parameters include the risk-adjusted performance of each member
- the risk-adjusted performance is generated from data of historical performance and risk
- the ranking component 104 also adjusts the base score according to data validity or verification. For example, the input base score, whether unadjusted or previously adjusted, is not adjusted for a fully verified account, but is adjusted down (e.g., reduced 50%, reduced 30%, etc ) for an unverified account
- the adjustments for data validity are not limited to linear adjustments or multiplication operations
- the IDSS through the ranking component, identifies skilled (not leveraged) investors who win most of the time (persistent) and win big (win big lose small, confident in their choices).
- the ranking component of an embodiment functions to identify the skilled investors who are persistent and confident, as described in detail below.
- the ranking component functions to remove investors that achieved high returns because of leverage through the use of the Information Ratio (IR) as a ranking criterion. Similar to the Sharpe Ratio, the Information Ratio measures risk adjusted active return The active return is return (alpha) over a benchmark (e.g , S&P 500).
- the IR is used in the IDSS of an embodiment instead of the Sharpe Ratio and, in an alternative embodiment of the IDSS the IR is used along with the Sharpe Ratio
- Figure 7 is a flow diagram for ranking an investor 700, under an embodiment.
- the investor is one buying an investment position in the description that follows.
- the investor ranking of an embodiment comprises generating a skill score 702 for each investor of a plurality of investors.
- the skill score of an embodiment represents an Information Ratio (IR) of the investor, as described below with refeience to Figure 8.
- the skill score of an alternative embodiment represents a combination of an IR and a Sharpe Ratio (SR) of the investor, as described below with reference to Figure 9.
- IR Information Ratio
- SR Sharpe Ratio
- Figure 11 is a flow diagram for generating a confidence score 1100, under an embodiment.
- Generating the confidence score of an embodiment comprises calculating a weighted average win percentage 1 102 for a portfolio of each investor
- Generating the confidence score of an embodiment comprises calculating a weighted average loss percentage 1 104 for a portfolio of each investor.
- Generating the confidence score of an embodiment comprises generating the confidence score 1 106 as a ratio of the weighted average win percentage to the weighted average loss percentage.
- the IDSS of an embodiment applies the ranking algorithm of the ranking component to the mutual funds and ETFs In so doing, an embodiment uses returns adjusted for expenses when calculating the Information Ratio of the mutual fund or exchange-traded fund (ETF). Furthermore, the variable ⁇ in the rank score formula is set equal to 1.0 Moreover, an embodiment considers additional factors such as the fund manager's historical performance, number of years investing, underlying holdings, turnover, and fund inflows and outflows, for example.
- the plurality of categories of an embodiment comprise a second category following the first category, the second category comprising a first subsequent two (2) percent of investment positions according to the rating score, wherein the second category has a rating score of 14
- the plurality of categories of an embodiment comprise a third category following the second category, the third category comprising a second subsequent two (2) percent of investment positions according to the rating score, wherein the third category has a rating score of 13
- the plurality of categories of an embodiment comprise a fourth category following the third category, the fourth category comprising a third subsequent 3.5 percent of investment positions according to the rating score, wherein the fourth category has a rating score of 12
- the plurality of categories of an embodiment comprise a fifth category following the fourth category, the fifth category comprising a fourth subsequent 3 5 percent of investment positions according to the rating score, wherein the fifth category has a rating score of 1 1.
- the plurality of categories of an embodiment comprise an eighth category following the seventh category, the eighth category comprising a seventh subsequent five (5) percent of investment positions according to the rating score, wherein the eighth category has a rating score of 8
- the plurality of categories of an embodiment comprise a ninth category following the eighth category, the ninth category comprising an eighth subsequent five (5) percent of investment positions according to the rating score, wherein the ninth category has a rating score of 7
- the plurality of categories of an embodiment comprise a tenth category following the ninth category, the tenth category comprising a ninth subsequent nine (9) percent of investment positions according to the rating score, wherein the tenth category has a rating score of 6.
- the IDSS of an embodiment provides recommendations including an index for all or a subset of IDSS members, their portfolio holdings and performance for the purposes of measuring certain stock market performance Similar to the Dow Jones Industrial Average, Russell 5000, and the Standard and Poor's 500 to name a few, the index, also referred to as the "individual investor index,” can provide relevant insights into the state of the stock market at a particular time.
- the index illustrates the relative performance of the IDSS members across various cross- sections of the IDSS membership, for example, all members, or across a group based on rank
- the index can be based on member data like current holdings, positions bought, and/or positions sold, but is not so limited
- the Index could be licensed to third parties who might be interested in the real-time and daily sentiment of the individual investing community
- each investment security can be substituted into a portfolio and a srmulation run that calculates allocation level, risk and diversification measures for the new portfolio.
- the IDSS can then automatically determine the "fit score", or, how appropriate (or not) is the chosen position and what dollar value constitutes the ideal allocation.
- the trading API automatically issues a command to the broker-dealer to initiate authentication of the trade. Then, the trading API issues a command to execute the trade order The trading API automatically issues a periodic command to check the status of the trade order. Upon receiving a trade order response confirming the execution of the trade order, the trading API automatically notifies the individual of the status. If the trade order gets rejected (e g , selling more security than held), then the trading API automatically notifies the customer of the status and the reason.
- the second action of an embodiment involves a second investment position that is equivalent to the first investment position
- the second action of an embodiment involves a second investment position that is identical to the first investment position
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- Human Resources & Organizations (AREA)
- Entrepreneurship & Innovation (AREA)
- Economics (AREA)
- Marketing (AREA)
- Strategic Management (AREA)
- Technology Law (AREA)
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- Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
Abstract
La présente invention concerne des systèmes et procédés pour générer un indice de performance. Une note de rang est générée pour chaque investisseur par rapport à un groupe d'investisseurs dont l'investisseur est une génération de membre de la note de rang qui utilise des données d'investissement d’un portefeuille de l’investisseur, et le portefeuille comprend au moins une position d’investissement. Un jeu d’investisseurs est choisi parmi le groupe d’investisseurs, et la sélection est basée sur la note de rang de chaque investisseur. L’indice de performance est généré pour fournir une mesure de performance d’investisseur individuel supérieure au cours du temps par rapport à un indice de marché. La génération de l’indice de performance comprend la génération d’un portefeuille composite comprenant des positions d’investissement de chaque portefeuille de chaque investisseur du jeu d’investisseurs.
Applications Claiming Priority (10)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US7785308P | 2008-07-02 | 2008-07-02 | |
| US7785208P | 2008-07-02 | 2008-07-02 | |
| US61/077,853 | 2008-07-02 | ||
| US61/077,852 | 2008-07-02 | ||
| US16751909P | 2009-04-07 | 2009-04-07 | |
| US61/167,519 | 2009-04-07 | ||
| US12/420,043 US20090265283A1 (en) | 2007-04-30 | 2009-04-07 | Systems and Methods for Ranking Investors and Rating Investment Positions |
| US12/420,040 | 2009-04-07 | ||
| US12/420,040 US20090240574A1 (en) | 2007-04-30 | 2009-04-07 | Systems and Methods for Ranking Investors and Rating Investment Positions |
| US12/420,043 | 2009-04-07 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2010003137A1 true WO2010003137A1 (fr) | 2010-01-07 |
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ID=41466347
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/US2009/049641 WO2010003137A1 (fr) | 2008-07-02 | 2009-07-02 | Systèmes et procédés pour fournir des données de performance d’investissement à des investisseurs |
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| Country | Link |
|---|---|
| WO (1) | WO2010003137A1 (fr) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10783457B2 (en) | 2017-05-26 | 2020-09-22 | Alibaba Group Holding Limited | Method for determining risk preference of user, information recommendation method, and apparatus |
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| US20020156722A1 (en) * | 2001-03-21 | 2002-10-24 | Greenwood Ken M. | Automated securities trading system |
| US20040133497A1 (en) * | 2002-12-18 | 2004-07-08 | Spear Gregory R. | System and methods for determining performance-weighted consensus |
| US20070282730A1 (en) * | 2006-05-01 | 2007-12-06 | Carpenter Steven A | Consolidation, sharing and analysis of investment information |
| US20080040250A1 (en) * | 2004-06-01 | 2008-02-14 | Transcon Securities Pty Ltd., A Corporation | System and Method for Analysing Risk Associated with an Investment Portfolio |
| US20080082435A1 (en) * | 2006-09-12 | 2008-04-03 | O'brien John | Ratio index |
-
2009
- 2009-07-02 WO PCT/US2009/049641 patent/WO2010003137A1/fr active Application Filing
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20020156722A1 (en) * | 2001-03-21 | 2002-10-24 | Greenwood Ken M. | Automated securities trading system |
| US20040133497A1 (en) * | 2002-12-18 | 2004-07-08 | Spear Gregory R. | System and methods for determining performance-weighted consensus |
| US20080040250A1 (en) * | 2004-06-01 | 2008-02-14 | Transcon Securities Pty Ltd., A Corporation | System and Method for Analysing Risk Associated with an Investment Portfolio |
| US20070282730A1 (en) * | 2006-05-01 | 2007-12-06 | Carpenter Steven A | Consolidation, sharing and analysis of investment information |
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| US20080082435A1 (en) * | 2006-09-12 | 2008-04-03 | O'brien John | Ratio index |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| US10783457B2 (en) | 2017-05-26 | 2020-09-22 | Alibaba Group Holding Limited | Method for determining risk preference of user, information recommendation method, and apparatus |
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