WO2000046708A1

WO2000046708A1 - A system and method for creating a secondary trading market for a financial fund, in particular a hedge fund

Info

Publication number: WO2000046708A1
Application number: PCT/US1999/009948
Authority: WO
Inventors: Nicholas Winegardner; Kamal Ahmed Aboul Gheit
Original assignee: Plus Corporate Funds, Ltd.
Priority date: 1999-02-05
Filing date: 1999-05-05
Publication date: 2000-08-10
Also published as: AU3886899A

Abstract

Described is a method and system for creating a secondary trading market (45) for trading shares of a fund (10), in particular a hedge fund. A computing device of the system receives transaction data. The transaction data corresponds to a financial transaction which is executed by the fund. Holding position data (25) of the fund is calculated as a function of the transaction data. Statistical data of the fund (30) is determined, in real time, as a function of the holding position data. Subsequently, the statistical data is provided to at least one user in order to create the secondary trading market.

Description

A SYSTEM AND METHOD FOR CREATING A SECONDARY TRADING MARKET FOR A FINANCIAL FUND, IN PARTICULAR A HEDGE FUND

FIELD OF THE INVENTION

The present invention relates to a system and method for creating a secondary trading market for a financial fund, in particular a hedge fund. The secondary trading market is created by generating, e.g., in real time, data regarding performance of the financial fund.

BACKGROUND INFORMATION

A common way for a user (e.g., an investor) to invest money is via a mutual fund. The mutual fund is a pool of money that is managed by professional managers . The user buys shares of the mutual fund; the mutual fund then invests the user's money by buying financial instruments such as stocks, bonds, etc. A net asset value ("NAV") of a mutual fund share is typically determined only once a day, on an end of day basis. The NAV is calculated as a function of the end of day value of the mutual fund's assets divided by a number of outstanding mutual fund shares. When calculating the NAV, it is assumed that relevant fees and expenses of a mutual fund have already been accounted for and deducted. Users can buy (subscribe) or sell (redeem) their mutual fund shares typically on a daily basis and only at the end of day NAV. The ability to redeem or subscribe mutual fund shares into or out of a mutual fund provides a daily cash liquidity to users.

Mutual fund shares (e.g., of a "closed-end" mutual fund) may also be exchanged in a secondary market, such as stock exchanges, bond markets, etc. A secondary market is a market where securities (e.g., mutual fund shares) are traded after they are initially offered in a primary market (e.g., after a fund share is bought from a mutual fund) . Most trading of mutual fund shares is done in the secondary market, such as the New York Stock Exchange, as well as in all other are secondary markets. Generally, a mutual fund is organized as an investment company which is closely regulated by the Securities and Exchange Commission ("SEC") according to the Investment Company Act of 1940. A mutual fund must comply with strict reporting requirements and is limited with respect to the number of investment strategies it may utilize.

Another way for a user to invest money is by utilizing an alternative investment vehicle, such as a hedge fund, a Limited Liability Partnership ("LLP"), etc. Hedge funds are described in a report "The State of the Hedge Fund Industry, " by Cerulli Associates, Inc., Boston, MA, 1998, which is incorporated in its entirety herein by reference. A hedge fund, like a mutual fund, is a pool of money that is managed by professional managers. A user may invest in a hedge fund by buying a hedge fund share, which is analogous to a mutual fund share or a limited partnership interest and represents an ownership unit of the hedge fund. However, unlike a mutual fund, a hedge fund utilizes aggressive investment strategies (e.g., selling short, leverage, program trading, swaps, arbitrage, and derivatives) which are characterized by a willingness on the part of the hedge fund to accept above- average risks in pursuit of above-average returns. Consequently, a hedge fund is capable of producing a substantially higher return than a mutual fund.

Another characteristic of a hedge fund is that the hedge fund is less regulated than, e.g., a mutual fund, and thus, the hedge fund is more flexible in implementing aggressive investment strategies. For instance, a hedge fund may trade financial instruments that are not regulated by the SEC. In addition, a hedge fund has extremely relaxed reporting requirements .

A disadvantage of a hedge fund is that, due to the U.S. security industry regulations, it is available only to a limited types of users (e.g., accredited, high net worth individuals, institutions or non-U.S. investors). In addition, a hedge fund typically requires a large minimum investment (e.g., one million dollars) . Furthermore, a hedge fund may have "lock-up" features that specify a redemption schedule. The redemption schedule may limit when users may redeem their hedge fund shares (e.g., once a month, once a year, once every five years, once a decade, etc.). The redemption schedule may vary from one hedge fund to another, but it is fixed for all users of a particular hedge fund. This temporal inability to redeem hedge fund shares severely restricts daily cash liquidity to the user and, thus, decreases attractiveness of hedge funds as an investment option.

In addition, a user has very limited information regarding a hedge fund (e.g., performance and risk information). Furthermore, this limited information is not provided in real time and it is difficult to ascertain its reliability and accuracy because limited information is provided by the hedge funds. For instance, in today's market, information regarding the NAV of a hedge fund share is typically available only twelve times a year. The NAV of a hedge fund share is not available to the user until, e.g., fourteen days after the close of a particular period (e.g., a monthly period). This lack of real time, accurate and reliable information has a negative impact on the user's confidence in hedge funds and limits the full growth potential of the hedge fund industry.

To achieve daily cash liquidity of the users' capital, e.g., during "lock-up" periods, there is a need for a secondary trading market where a user may find another user to buy and/or sell his or her hedge fund shares. However, without reliable, accurate and timely information (e.g., performance and risk information) which is provided to the user on a continuous, independently calculated basis, it is extremely difficult for users of hedge funds to agree on a NAV of a hedge fund share. Consequently, there is a need to provide reliable and accurate information regarding hedge funds which would be available in real time to the user.

SUMMARY OF THE INVENTION The present invention relates to a method and system for creating a secondary trading market for trading shares of a fund, in particular a hedge fund. A computing device of the system receives transaction data. The transaction data corresponds to a financial transaction which is executed by the fund. Holding position data of the fund is calculated as a function of the transaction data. Statistical data of the fund is determined, in real time, as a function of the holding position data. Subsequently, the statistical data is provided to at least one user in order to create the secondary trading market.

BRIEF DESCRIPTION OF THE DRAWINGS

Figure 1 shows an exemplary embodiment of a system according to the present invention.

Figure 2 shows an exemplary embodiment of a central server according to the present invention.

Figure 3 shows a flow chart illustrating an exemplary method according to the present invention.

DETAILED DESCRIPTION

The present invention relates to a system and method for creating a secondary trading market for a financial fund ("fund"), in particular a hedge fund. Those skilled in the art would understand that the fund may also have the legal structure of an offshore corporation, a Limited Liability Partnership or other entity.

Figure 1 shows an exemplary embodiment of the system 1 according to the present invention. The system 1 includes a fund 10 which is a pool of money managed by professional managers. The user may invest in the fund 10 by buying a fund share. A price of the fund share (i.e., the NAV) is determined as a function of a value of the fund's assets and the number of outstanding fund shares .

The system 1 collects, e.g., on a real-time basis, particular data regarding the fund 10 and then generates statistical data regarding the performance of the fund 10. In particular, the system 1 generates the statistical data by closely monitoring transactions of the fund 10 in a worldwide marketplace

("marketplace") 15. The marketplace 15 may include global equity markets, global foreign currency markets, global fixed income markets and global financial derivative markets, etc. The fund's transactions include buying and/or selling of one or more financial instruments in the marketplace 15. The financial instruments may be instruments which are, or are not, regulated by the SEC. Subsequently, the system 1 provides, e.g., in real time, the statistical data to a user (e.g., an investor, a new reporting agency, a trading program, a computing device, a trading program, a governmental agency, etc.) . The statistical data may be utilized by the users to buy and/or sell the fund shares, e.g., during a "lock-up" period, on the secondary trading market.

As mentioned above, the exemplary embodiment of the system 1 of the present invention may perform particular steps in real time and/or generate particular data in real time. The term "real time" is intended to indicate the actual time in which a particular process and/or a particular transaction occurs (e.g., every second every minute, every hour, more than once a day, etc.) . For example, a real time stock or bond quote is one that states a security's most recent offer to sell or buy at the time of the quote. A most recent offer for, e.g., a share of X Corp. may be 10-15 seconds, while a most recent offer for, e.g., a share of a mutual fund may be the price at the end of a previous business day. In an exemplary embodiment of the present invention, the system 1 includes a central server 5, an output server 40 and a secondary market server 45. In an alternative embodiment of the present invention, the central server 5 may include the output server 40 and the secondary market server 45. Each server of the system 1 may include at least one processor, a memory storage device and a communication arrangement. Communication within the system 1 may be performed via a communication network (e.g., the internet, a proprietary network, a local or wide area network, a wireless network, a telephone network, etc.).

The central server 5 receives transaction data, which corresponds to the fund's transaction in the marketplace 15, from the fund 10 (e.g., from a computer utilized by the fund 10 for trading purposes) and collects holding position data regarding the financial holding of the fund 10 (e.g., all assets of the fund 10) . Based on the holding position data, the central server 5 calculates, e.g., in real time, the statistical data and provides the statistical data to the output server 40. The user may access the output server 40 via a user computer 50 to obtain the statistical data. Based on the available statistical data (which is continuously updated, e.g., in real time), the user may place an order to buy or sell the fund shares. For example, the user may trade the fund shares via the secondary market server 45 and/or the marketplace 15.

The marketplace 15 (e.g., via a computer) may also provide the transaction data to the central server 5. The central server 5 may compare the transaction data provided by the marketplace 15 to the transaction data provided by the fund 10. Thus, the transaction data provided by the fund 10 may be verified before being stored in the central server 5.

In an alternative exemplary embodiment of the present invention, the central server 5 may provide the holding position data and the statistical data to an auditor 35 (e.g., an independent external auditor, an internal auditor, a certified public accountant ("CPA"), etc.). Such transfer to the auditor 35 may occur in a periodic manner (e.g., once a week) via, e.g., a computer. The auditor 35 verifies that the statistical data, which was generated by the central server 5 and provided to the output server 40, is accurate.

Figure 2 shows an exemplary embodiment of the central server 5 according to the present invention. The central server 5 may include a processor 2, a storage device 3 and a communication arrangement 4. The storage device 3 may store a plurality of databases, e.g., a Current Transaction Database ("CTD") 20, a Holding Position Database ("HPD") 25, a Fund Statistic Database ("FSD") 30, etc.

The CTD 20 stores the transaction data regarding the last transaction executed by the fund 10 in the marketplace 15. The transaction data includes information such as, e.g., the type of the financial instrument, volume, price, etc. The HPD 25 stores the holding position data regarding holdings of the fund 10. The HPD 25 is adjustable, as a function of the transaction data, each time the fund 10 executes the transaction. The FSD 30 stores the statistical data regarding the fund 10. The statistical data may be generated as a function of the holding position data provided by the HPD 30, pricing data provided by the marketplace 15, and information regarding the fund's fees and expenses.

The statistical data may include the NAV of the fund share, a Data Reporting Error Index ("DREI"), Risk Management Data ("RMD"), etc. In particular, the NAV of the fund share is calculated by determining the asset value of the fund 10 as a function of the holding position data. Then, the asset value of the fund 10 is divided by the number of outstanding shares of the fund 10 to arrive at the NAV of the fund share. This is the NAV which may be reported, e.g., to the users, the marketplace 15 and the secondary market server 45, as a current price for one share of the fund 10.

The DREI may be calculated as a function of a difference between the transaction data provided by the fund 10 and the transaction data provided by the marketplace 15. For example, the fund 10 buys 1,000 shares of X Corp. at $181 per share in the marketplace 15. The fund 10 transmits a particular transaction data to the central server 5 reporting the above- stated information (i.e., 1,000 shares of X Corp. at $181 per share) . In addition, the marketplace 15 transmits the particular transaction data to the central server 5 which indicates that the fund 10 bought 1,000 shares of X Corp. at $181 per share. The central server 5 compares the transaction data provided to it by the fund 10 and the marketplace 15. In particular, the central server 5 may check, e.g., stock information (i.e., X Corp.), volume (i.e., 1,000 shares) and a share price (i.e., $181). Since the transaction data provided by the fund 10 and the marketplace 15 is identical, a value of the DREI is less therefore that a predetermined threshold value. However, if the fund 10 had reported that it bought 1,100 shares of X Corp., then the value of the DREI would be greater than the predetermined threshold value because the volume reported by the fund 10 does not match the volume reported by the marketplace 15. Subsequently, the central server 5 may generate a corresponding message to the fund 10 and the marketplace 15 indicating a discrepancy in the volume and requesting to resend the particular transaction data.

The RDM may include, e.g., a Value at Risk Measure ("VAR"), a Diversity Risk Measure ("DRM"), a Blockage Risk Measure ("BRM") and a Liquidity Risk Measure ("LRM") . The VAR may indicate, by examining the holding position data, a percentage of the fund's holdings that are at risk of loss based on a historical performance of the holdings. For example, if the fund 10 holds 45% of the fund's assets in a number of volatile stocks (e.g., penny stocks that have a high beta value), the VAR may reflect such volatility accordingly.

The DRM may indicate how diversified the holdings of the fund 10 are. The DRM may be determined as a function of the holding position data. For example, if the fund 10 holds most of its assets in a particular sector (e.g., internet stocks), then the DRM may be higher than the DRM of another fund 10 whose holdings are balanced among different sectors (e.g., 20% in internet stocks, 20% in financial stocks, 20% in pharmaceutical stocks, 20% in cyclical stocks, and 20% in oil stocks) .

The BRM may indicate whether the holdings have large blocks of a particular financial instrument that would have to be discounted in order to be sold or bought. For example, if the fund 10 has 1,000,000 shares of a particular stock whose daily volume does not exceed 10,000, then the BRM would be substantially higher then the BRM of the fund 10 which holds 1,000 shares of the particular stock and 1,000,000 shares of Z Corp. which average daily volume is 14,000,000 shares.

The LRM may indicate the liquidity of the fund's holdings. For example, if the fund 10 holds shares of a stock which can be easily turned into cash, then the LRM would be less then the LRM of another fund 10 which has financial instruments that are difficult to sell.

Figure 3 shows an exemplary embodiment of the method according to the present invention. In step 100, the fund 10 executes a particular transaction in the marketplace 15 (e.g., sells or buys a particular financial instrument) . The fund 10 may execute the transaction in the marketplace 15 directly or may utilize a third party institution (not shown) , such as a broker.

Each time the fund 10 executes the particular transaction, the fund 10 reports the transaction data to the central server 5 (step 105) . The marketplace 15 may also report the transaction data regarding the transaction of the fund 10. In step 110, the central server 5 may perform a verification procedure to verify that the transaction data received from the fund 10 is accurate.

The verification procedure includes the substep of comparing the transaction data reported by the fund 10 to the transaction data reported by the marketplace 15. With this verification procedure, it is possible to eliminate discrepancies between the transaction data provided by different sources. The advantage of the verification procedure is that it may minimize a risk of erroneous reporting by the fund 10 and/or the marketplace 15. In an alternative exemplary embodiment, the third party institution may also report the transaction data to the central server 5 which then performs the verification procedure using three sets of the transaction data which are independently provided by the fund 10, the marketplace 15 and the third party institution.

During the verification procedure, all sets of the transaction data are stored in the CTD 20. If the central server 5 verifies the transaction data (e.g., a difference value between the sets of the transaction data is less than a threshold value) , then the transaction data is transferred to the TPD 25 which accumulates the holding position data (step 115) . However, if the central server 5 does not verify the transaction data (e.g., the difference is greater than or equal to the threshold value) , then the central server 5 transmits a corresponding message to the fund 10, the marketplace 15, and/or the third party institution requesting that the transaction data be resent.

Based on the holding position data, the central server 5 may generate (e.g., continuously, in real time, etc.) the statistical data regarding the fund 10 which is stored in the FSD 30 (step 120) . In particular, the central server 5 determines the NAV, the DREI and the RDM as a function of the holding position data and the pricing data.

The statistical data may also include a Confident Interval Index ("CII") which is indicative of the accuracy of the statistical data. The CII is continuously and recursively determined as a function of the holding position data, the statistical data, the pricing data and information regarding the fund's fees and expenses (step 125). Unlike, the DREI which is determined by the central server 5, the CII is determined by the auditor 35. The auditor 35 may report the CII to the central server 5 to be stored in the FSD 30 and/or to the output server 40.

The statistical data may be updated continuously (i.e., in real time) throughout the day (e.g., second by second, minute by minute, more than once a day, etc.) upon receiving updates from, e.g., the fund 10, the marketplace 15, the auditor 35 and/or the HPD 25.

Subsequently, in step 130, the output server 40 receives the statistical data and generates an output report as a function of the statistical data. The output report is available to the user, e.g., in real time (step 135) . The user may access the output report via, e.g., the user computer 50. Alternatively, the user may receive the output report via fax, e-mail, pager, U.S. mail, telephone, etc.

Since the statistical data is available to the user and since their accuracy is independently verified, the exemplary embodiment of the system and method according to the present invention may enhance the user's confidence in the fund 10 and would allow the secondary trading market to be created (e.g., during the lock-up periods) so that the user may speculate on the performance of the fund 10. The user may buy and/or sell the fund share, at any time, e.g., using the SMS 45 or the marketplace 15 (step 140) . The SMS 45 facilitates a transaction of the TFI between different users and provides a way to achieve daily cash liquidity for the user.

In an alternative exemplary embodiment, the system 1 may track performance of a plurality of funds. In particular, the system 1 may generate an index which tracks performance of the plurality of the funds 10. The index may be a classified index which classifies the funds 10 according to a predetermined criteria (e.g., trading cycle, market coverage, asset size, length of track record, degree of risk, etc.).

An advantage of the system and method according to the present invention is that the statistical data may be provided to users and may allow users to track, e.g., in real time, the performance of the fund 10 where otherwise the users would not be able to obtain such statistical data. Thus, the statistical data enhances the user's confidence in the fund 10 and generates the secondary trading market for the fund 10 where otherwise the secondary trading market would not exist. In addition, the system and method of the present invention enable standardized evaluation of the performance of funds 10 so that the statistical data of one fund may be compared to the statistical data of another fund.

Claims

WHAT IS CLAIMED IS:

1. A method for creating a secondary trading market for trading shares of a fund, comprising the steps of: receiving transaction data by a computing device, the transaction data corresponding to a financial transaction which is executed by the fund; calculating holding position data of the fund as a function of the transaction data; determining, in real time, statistical data of the fund as a function of the holding position data; and providing the statistical data to at least one user in order to create the secondary trading market .

2. The method according to claim 1, wherein the at least one user includes at least one of a computing device, a trading program, an investor, a marketplace, a further hedge fund, a governmental agency and a news reporting source.

3. The method according to claim 1, wherein at least one of the receiving step, the calculating step and the providing step is performed in real time.

4. The method according to claim 1, wherein the fund is a hedge fund.

5. The method according to claim 1, wherein the fund is a limited liability partnership.

6. The method according to claim 1, further comprising the step of: continuously updating the statistical data throughout a day.

7. The method according to claim 1, wherein at least one of the receiving step, the calculating step, the determining step and the providing step is performed more than once a day.

8. The method according to claim 1, wherein at least one of the receiving step, the calculating step, the determining step and the providing step is performed at one second intervals.

9. The method according to claim 1, wherein at least one of the receiving step, the calculating step, the determining step and the providing step is performed every time the financial transaction is executed.

10. The method according to claim 1, further comprising the step of: executing a further transaction in the secondary trading market by the at least one user, the further transaction including at least one of a buying transaction and a selling transaction of the shares of the fund.

11. The method according to claim 10, wherein at least one of the receiving step, the calculating step, the determining step and the providing step is performed every time an offer to execute the further transaction is executed.

12. The method according to claim 10, wherein the executing step is performed in real time.

13. The method according to claim 1, wherein the statistical data include a net asset value of each of the shares, and the method further comprising the step of: determining the net asset value, by the computing device, as a function of the holding position data, pricing data and a number of outstanding shares of the fund, the pricing data corresponding to the holding position data.

14. The method according to claim 1, wherein the statistical data include at least one of risk measure data, diversity risk measure data, blockage risk measure data and liquidity risk measure data, and the method further comprising the step of: determining at least one of the risk measure data, the diversity risk measure data, the blockage risk measure data and the liquidity risk measure data as a function of the holding position data.

15. The method according to claim 14, wherein the statistical data include a net asset value of each of the shares, and the method further comprising the step of: determining the net asset value, by the computing device, as a function of the holding position data, pricing data and a number of outstanding shares of the fund, the pricing data corresponding to the holding position data.

16. The method according to claim 15, wherein the fund is a hedge fund.

17. The method according to claim 16, wherein at least one of the receiving step, the calculating step, the step of determining the statistical data, the providing step and the step of determining the net asset value is performed more than once a day.

18. The method according to claim 16, wherein at least one of the receiving step, the calculating step, the step of determining the statistical data, the providing step and the step of determining the net asset value is performed at one second intervals .

19. The method according to claim 16, wherein at least one of the receiving step, the calculating step, the step of determining the statistical data, the providing step and the step of determining the net asset value is performed every time the financial transaction is executed.

20. The method according to claim 1, wherein the receiving step includes the substeps of : executing the financial transaction by the fund in a marketplace, and providing the transaction data to the computing device by at least one of the fund and the marketplace, and the determining step including the substep of : determining the statistical data as a function of the holding position data, pricing data and expense data of the fund.

21. The method according to claim 20, wherein the receiving step includes the substeps of: executing the financial transaction by the fund in the marketplace via a broker, and providing the transaction data to the computing device by at least one of the fund, the marketplace and the broker.

22. The method according to claim 21, further comprising the steps of : comparing the transaction data provided by at least two of the fund, the marketplace and the broker to determine a data error value; when the data error value is greater than a predetermined threshold value, performing the following substeps:

(i) transmitting a corresponding message to at least one of the fund, the marketplace and the broker,

(ii) receiving the transaction data from the at least two of the fund, the marketplace and the broker, and

(iii) repeating the comparing step; and performing the calculating step if the data error value is less than or equal to the predetermined threshold value, wherein the statistical data include the data error value.

23. The method according to claim 21, further comprising the step of: determining a confidence value as a function of the transaction data, the holding position data, pricing data provided by at least one of the fund, the marketplace and the broker, wherein the statistical data include the confidence value .

24. The method according to claim 23, wherein the confidence value is generated by an auditor in real time.

25. The method according to claim 23, wherein the step of determining the confidence value is performed recursively.

26. The method according to claim 1, wherein the financial transaction includes at least one of a buying transaction and a selling transaction of a financial instrument, the financial instrument including an instrument which is regulated by the SEC.

27. The method according to claim 1, wherein the financial transaction includes at least one of a buying transaction and a selling transaction of a financial instrument, the financial instrument including one of an instrument which is not regulated the SEC.

28. The method according to claim 1, further comprising the step of: determining an index value as a function of corresponding statistical data of a plurality of funds.

29. The method according to claim 28, wherein the plurality of funds is selected as a function of at least one of a corresponding trading cycle, a corresponding market coverage, a corresponding asset size, a corresponding length of a track record, and a corresponding degree of risk.

30. A system for creating a secondary trading market for trading shares of a fund, comprising: a memory device; a communication arrangement; and a processor receiving, via the communication arrangement, transaction data corresponding to a financial transaction which is executed by the fund, the processor storing the transaction data in the memory device and calculating holding position data of the fund as a function of the transaction data, the processor determining, in real time, statistical data of the fund as a function of the holding position data, the statistical data being provided to at least one user in order to create a secondary trading market .

31. The system according to claim 30, wherein the processor calculates the holding position data in real time.

32. The system according to claim 31, wherein the processor provides the statistical data to the at least one user in real time.

33. The system according to claim 30, wherein the fund is a hedge fund.

34. The system according to claim 30, wherein the fund is a limited liability partnership.

35. The system according to claim 30, wherein the processor executes a further transaction in the secondary trading market for the user, the further transaction including at least one of a buying transaction and a selling transaction of the share of the fund from at least one further user.

36. The system according to claim 35, wherein the processor executes the further transaction in real time.

37. The system according to claim 30, wherein the at least one user includes at least one of a computing device, a trading program, an investor, a marketplace, a further hedge fund, a governmental agency and a news reporting source.

38. The system according to claim 30, wherein in the statistical data is reported to the at least one user via a communication network.

39. The system according to claim 38, wherein the communication network includes at least one of the Internet, a local area network, a wide area network, a virtual network and a wireless network.

40. A method for creating a secondary trading market for trading shares of a hedge fund, comprising the steps of: receiving transaction data by a computing device, the transaction data corresponding to a financial transaction which is executed by the hedge fund; calculating holding position data of the hedge fund as a function of the transaction data; determining, in real time, a particular price of the share as a function of the holding position data and corresponding price information; and providing the particular price to at least one user in order to create the secondary trading market .

41. The method according to claim 40, wherein at least one of the receiving step, the calculating step and the providing step is performed in real time.

42. The method according to claim 40, wherein the statistical data include at least one of risk measure data, diversity risk measure data, blockage risk measure data and liquidity risk measure data, and the method further comprising the step of: determining at least one of the risk measure data, the diversity risk measure data, the blockage risk measure data and the liquidity risk measure data as a function of the holding position data.

43. A computer-readable storage medium storing a set of instructions, the set of instructions capable of being executed by a processor to create a secondary trading market for trading shares of a fund, the set of instructions performing the steps of :

(a) receiving transaction data by a computing device, the transaction data corresponding to a financial transaction which is executed by the fund;

(b) calculating holding position data of the fund as a function of the transaction data;

(c) determining, in real time, statistical data of the fund as a function of the holding position data; and

(d) providing the statistical data to at least one user in order to create the secondary treading market .

44. A computer data signal embodied in a carrier wave to create a secondary trading market for trading shares of a fund, the computer data signal comprising:

(a) a receiving source code segment receiving transaction data by a computing device, the transaction data corresponding to a financial transaction which is executed by the fund;

(b) a calculating source code segment calculating holding position data of the fund as a function of the transaction data;

(c) a determining code source segment determining, in real time, statistical data of the fund as a function of the holding position data; and

(d) a providing source code segment providing the statistical data to at least one user in order to create a secondary trading market .