System and method for emulating a long/short hedge fund index in a trading system

A system comprises a memory operable to store a compound index that is based at least in part on a plurality of component indices. The plurality of component indices comprise an international developed markets equity index, a U.S. large-cap equity index, and a U.S. small-cap equity index. The compound index is further based at least in part on a plurality of weights, wherein each weight is associated with a respective one of the plurality of component indices. The system further comprises a processor communicatively coupled to the memory and operable to update the plurality of weights according to a regression analysis. The regression analysis is based at least in part on a respective set of returns associated with each of the plurality of component indices and with a hedge fund index. The plurality of weights are updated such that the compound index emulates the hedge fund index. The processor is further operable to determine a current compound index value based at least in part on the plurality of component indices and on the updated plurality of weights. The processor is further operable to transmit the current compound index value to one or more clients.

TECHNICAL FIELD OF THE INVENTION

The present invention relates generally to electronic trading and more specifically to a system and method for emulating a long/short hedge fund index in a trading system.

BACKGROUND OF THE INVENTION

Traditional trading systems allow traders to pursue various investment schemes, including mutual funds and hedge funds. Some traders perceive hedge funds as providing greater returns than other types of investments. However, because hedge funds are actively managed, hedge funds are generally associated with higher fees than other types of investments. In addition, investments in hedge funds are generally not as liquid as investments in other types of assets.

SUMMARY OF THE INVENTION

In accordance with the present invention, the disadvantages and problems associated with prior trading systems have been substantially reduced or eliminated.

In some embodiments, a system comprises a memory operable to store a compound index that is based at least in part on a plurality of component indices. The plurality of component indices comprise an international developed markets equity index, a U.S. large-cap equity index, and a U.S. small-cap equity index. The compound index is further based at least in part on a plurality of weights, wherein each weight is associated with a respective one of the plurality of component indices. The system further comprises a processor communicatively coupled to the memory and operable to update the plurality of weights according to a regression analysis. The regression analysis is based at least in part on a respective set of returns associated with each of the plurality of component indices and with a hedge fund index. The plurality of weights are updated such that the compound index emulates the hedge fund index. The processor is further operable to determine a current compound index value based at least in part on the plurality of component indices and on the updated plurality of weights. The processor is further operable to transmit the current compound index value to one or more clients.

In certain embodiments, a method comprises storing a compound index that is based at least in part on a plurality of component indices. The plurality of component indices comprise an international developed markets equity index, a U.S. large-cap equity index, and a U.S. small-cap equity index. The compound index is further based at least in part on a plurality of weights, wherein each weight is associated with a respective one of the plurality of component indices. The method continues by updating the plurality of weights according to a regression analysis. The regression analysis is based at least in part on a respective set of returns associated with each of the plurality of component indices and with a hedge fund index. The plurality of weights are updated such that the compound index emulates the hedge fund index. The method continues by determining a current compound index value based at least in part on the plurality of component indices and on the updated plurality of weights. The method concludes by transmitting the current compound index value to one or more clients.

The invention has several important technical advantages. Various embodiments of the invention may have none, some, or all of these advantages. One advantage is that the trading system provides a weighted compound index associated with various component indices. In some embodiments, each component index is associated with assets having intraday liquidity. The transaction costs of trading these assets are generally lower than the transaction costs associated with hedge funds. Thus, the compound index offers more liquidity and lower fees than a hedge fund index.

Another advantage is that the trading system periodically updates the weights of the component indices that underlie the compound index. The trading system may configure the weights so that the compound index emulates the performance of a hedge fund index. Thus, the compound index may provide traders with returns similar to those provided by a hedge fund index.

Other advantages of the present invention will be readily apparent to one skilled in the art from the description and the appended claims.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1illustrates a trading system10, according to certain embodiments. Trading system10may comprise one or more clients20, an index server30, one or more market data servers40, and one or more market centers50communicatively coupled by one or more networks60.

Trading system10is operable to execute trading orders12submitted by traders14. Trading system10is further operable to provide a financial indicator that emulates a hedge fund index22. The financial indicator may be referred to as compound index18. Compound index18is based at least in part on component indices24that are proportioned according to a particular weighting scheme. The particular weighting scheme allows compound index18to emulate hedge fund index22. Component indices24may be associated with assets having intraday liquidity.

In conjunction with determining compound index18, trading system10may provide compound index fund16. In some embodiments, compound index fund16represents a liquid and tradable asset that is available to the trading public. According to certain embodiments, because compound index18emulates hedge fund index22, compound index fund16provides traders14with both daily liquidity and hedge-fund-like returns26.

As explained above, compound index18is based at least in part on a plurality of component indices24. Each component index24is predicated on various investment instruments28such as, for example, equities, debt, currencies, commodities, stocks, bonds, futures contracts, derivatives, and/or any suitable instrument. A particular component index24is generally an indicator regarding the market value and/or performance of the particular investment instruments28that underlie the particular component index24. Examples of component indices24include, but are not limited to, the Dow Jones Industrial Average, the German DAX, the British FTSE 100, the S&P 500 Total Return Index, the U.S. Dollar Index, the MSCI Emerging Markets Free Total Return Index, the MSCI EAFE U.S. Dollar Net Total Return Index, and the Russell 2000 Total Return Index.

Component indices24may be categorized according to various attributes. For example, the NASDAQ index may be categorized as a technology index because it is primarily based on securities associated with technology companies. As another example, the MSCI Emerging Markets Free Total Return Index, which is based on securities from global emerging markets, may be categorized as an international emerging markets equity index. In some embodiments, component indices24may be categorized as international developed markets equity indices, U.S. large-cap equity indices, U.S. small-cap equity indices, commodity indices, debt indices, currency indices, and/or any suitable type of index.

In addition, or as an alternative, to component indices24, compound index18may be based at least in part on one or more interest rates32. In some embodiments, interest rate32may be a short-term interbank lending rate. For example, compound index18may be based at least in part on the BBA One Month USD Libor. In other embodiments, interest rate32may be a prime rate, federal funds rate, mortgage rate, wholesale rate, retail rate, discount rate, and/or any number and combination of suitable lending rates.

Using current values of component indices24, trading system10may determine a current value of compound index18. As explained above, each of the component indices24associated with compound index18may be weighted such that compound index18emulates a particular hedge fund index22. Generally, a hedge fund index22is predicated on multiple constituent hedge funds and represents an indicator of the market value of the multiple hedge funds associated with the particular hedge fund index22. Compound index18may be configured to emulate any suitable hedge fund index22. Examples of hedge fund indices22include, but are not limited to, the HFRI Fund Weighted Composite Index, the CSFB Credit Suisse/Tremont Hedge Fund Index, the FTSE Hedge Index, the DOW Jones Hedge Fund Index, the Eurekahedge Hedge Fund Index, the HFRI Equity Hedge Index, and/or any suitable hedge fund index22.

According to certain embodiments, hedge fund index22represents an index of multiple hedge funds that employ long/short investment strategies (e.g., long/short equity strategies). An example of such hedge fund index22is the HFRI Equity Hedge Index. In some embodiments, a long/short investment strategy involves establishing a core holding of long equities that are hedged with short sales of stocks and/or stock index options. In other embodiments, a long/short investment strategy involves establishing a long position in currencies, debt, commodities, stocks, bonds, futures contracts, derivatives, and/or any suitable investment instrument28hedged with a short position in any suitable number and combination of investment instruments28. The holdings of a hedge fund that employs a long/short investment strategy may be selected based on an analysis of individual companies as well as risks and opportunities offered by particular industries, sectors, and/or countries. In some embodiments, a fund manager associated with a hedge fund that employs a long/short investment strategy may attempt to achieve neutrality and/or reduce volatility by diversifying and/or hedging positions across individual regions, industries, sectors, and/or market capitalization bands. By configuring compound index18to replicate hedge fund index22that is based on hedge funds that employ long/short investment strategies (such as, for example, the HFRI Equity Hedge Index), compound index18may replicate the performance of long/short investment strategies.

In some embodiments, the respective weights34of component indices24may be updated periodically (e.g., weekly, bi-weekly, monthly, and/or according to any suitable time period). Weights34may be determined based at least in part on returns26of the respective component indices24and on returns26of the particular hedge fund index22that compound index18is configured to emulate. In some embodiments, a regression analysis may be performed to determine the respective weights34of the component indices24. The respective weights34of component indices24may be determined such that compound index18emulates the performance of the particular hedge fund index22. Compound index18may emulate the performance of hedge fund index22by tracking or replicating the movements of hedge fund index22. Because compound index18may emulate hedge fund index22, returns26of compound index18may be similar to returns26of hedge fund index22.

As explained above, trading system10comprises one or more clients20. Client20represents any suitable local or remote end-user device that may be used by traders14to access one or more elements of trading system10, such as index server30. Trader14may use client20to submit deposits, make withdrawals, request information, and/or communicate with various components of trading system10. In some embodiments, trader14may use client20to invest in funds that are managed by index server30. A particular client20may comprise a computer, workstation, telephone, Internet browser, electronic notebook, Personal Digital Assistant (PDA), pager, or any other suitable device (wireless, wireline, or otherwise), component, or element capable of receiving, processing, storing, and/or communicating information with other components of trading system10. Client20may also comprise any suitable user interface such as a display, microphone, keyboard, or any other appropriate terminal equipment according to particular configurations and arrangements. It will be understood that trading system10may comprise any number and combination of clients20. In some embodiments, client20may comprise a graphical user interface (GUI)36.

GUI36is generally operable to tailor and filter data presented to trader14. GUI36may provide trader14with an efficient and user-friendly presentation of trading orders12, market data38, and/or other suitable information. GUI36may comprise a plurality of displays having interactive fields, pull-down lists, and buttons operated by trader14. In one example, GUI36presents relevant market data38to trader14and conceals the remaining information to reduce visual clutter. Then, upon receiving a request from trader14, GUI36expands the visual representation of market data38to display account information, market information, and/or other suitable information. GUI36may include multiple levels of abstraction including groupings and boundaries. It should be understood that the term graphical user interface may be used in the singular or in the plural to describe one or more graphical user interfaces36and each of the displays of a particular graphical user interface36.

Although clients20are described herein as being used by “traders”, it should be understood that the term “trader” is meant to broadly apply to any user of trading system10, whether that user is an agent acting on behalf of a principal, a principal, an individual, a legal entity (such as a corporation), or any machine or mechanism that is capable of participating in transactions in trading system10.

Trader14may use client20to communicate with index server30. Index server30is generally operable to monitor component indices24. Based at least in part on the movement of component indices24, index server30is operable to update compound index18. In some embodiments, index server30is operable to manage compound index fund16associated with compound index18. (Compound index fund16is described in detail with respect toFIG. 2.)

Index server30is operable to update compound index18periodically (e.g., hourly, daily, weekly, and/or according to any suitable time period). In some embodiments, index server30re-calculates compound index18on a daily basis. The daily value of a particular indicator (e.g., component index24, compound index18, interest rate32, and/or hedge fund index22) may be referred to as the closing level42of that indicator. In some embodiments, closing level42refers to the official value of an indicator as published by market data server40at a configurable time on a given business day. Index server30is operable to transmit closing level42of compound index18to market data server40.

Index server30may comprise any suitable combination of hardware and/or software implemented in one or more modules to provide the described functions and operations. In some embodiments, index server30may comprise a general-purpose personal computer (PC), a Macintosh, a workstation, a Unix-based computer, a server computer, or any suitable processing device. In some embodiments, the functions and operations described above may be performed by a pool of multiple index servers30. A particular index server30may comprise an index memory44and an index processor46.

Index memory44comprises any suitable arrangement of random access memory (RAM), read only memory (ROM), magnetic computer disk, CD-ROM, or other magnetic or optical storage media, or any other volatile or non-volatile memory devices that store one or more files, lists, tables, or other arrangements of information such as market data38. AlthoughFIG. 1illustrates index memory44as internal to index server30, it should be understood that index memory44may be internal or external to index server30, depending on particular implementations. Also, index memory44may be separate from or integral to other memory devices to achieve any suitable arrangement of memory devices for use in trading system10.

Index memory44is generally operable to store index logic48. Index logic48generally comprises rules, algorithms, code, tables, and/or other suitable instructions for updating compound index18and managing compound index fund16. Index memory44is further operable to store market data38, compound index fund16, and compound index18.

Index memory44is communicatively coupled to index processor46. Index processor46is generally operable to execute index logic48stored in index memory44to calculate compound index18and to manage compound index fund16. Index processor46may comprise any suitable combination of hardware and software implemented in one or more modules to provide the described function or operation.

Index server30may transmit trading orders12to one or more market centers50. Market center50is generally operable to receive and execute trading orders12. Once a particular trading order12is executed, market center50is operable to generate and transmit a trade confirmation message to index server30. Market center50is further operable to transmit trading data52to market data server40. Trading data52may comprise information regarding trading activities in market center50. In particular, trading data52may comprise information regarding best bid prices, best offer prices, trading volumes, volatility, and/or any other suitable information regarding trading activity in market center50. In some embodiments, trading data52represents raw data regarding conditions in market center50.

Market centers50may comprise all manner of order execution venues including exchanges, Electronic Communication Networks (ECNs), Alternative Trading Systems (ATSs), market makers, or any other suitable market participants. Each market center50may maintain a bid and offer price for at least one investment instrument28by standing ready, willing, and able to buy or sell that investment instrument28at publicly quoted prices, also referred to as market center prices. Different market centers50may provide different market center prices for particular investment instruments28. For example, a particular market center50may offer a particular bid price and/or offer price for a particular investment instrument28, while another market center50may offer a different bid price and/or offer price for the same investment instrument28.

Market center50may be communicatively coupled via network60to market data server40. Market data server40is generally operable to receive and process trading data52from market center50. Market data server40may process trading data52to generate market data38. Market data38may comprise current and/or historical information regarding any suitable index, financial instrument, mutual fund, hedge fund, exchange traded fund (“ETF”), interest rate32, investment instrument28, trader14, and/or any suitable number and combination of indicators regarding trading system10. In particular, market data38may comprise current and/or historical values of component indices24, interest rates32, and hedge fund indices22. In some embodiments, market data server40may be operated by a financial news service organization such as, for example, Bloomberg, L.P. In other embodiments, market data server40may be operated by a market maker, brokerage firm, bank, market center50, and/or any suitable financial services entity.

Market data server40may comprise any suitable combination of hardware and/or software implemented in one or more modules to provide the described functions and operations. In some embodiments, market data server40may comprise a general-purpose personal computer (PC), a Macintosh, a workstation, a Unix-based computer, a server computer, or any suitable processing device. In some embodiments, the functions and operations described above may be performed by a pool of multiple market data servers40. A particular market data server40may comprise a market data memory54and a market data processor56.

Market data memory54comprises any suitable arrangement of random access memory (RAM), read only memory (ROM), magnetic computer disk, CD-ROM, or other magnetic or optical storage media, or any other volatile or non-volatile memory devices that store one or more files, lists, tables, or other arrangements of information. AlthoughFIG. 1illustrates market data memory54as internal to market data server40, it should be understood that market data memory54may be internal or external to market data server40, depending on particular implementations. Also, market data memory54may be separate from or integral to other memory devices to achieve any suitable arrangement of memory devices for use in trading system10.

Market data memory54is generally operable to store trading data52from market centers50. Market data memory54is further operable to store market data logic58. Market data logic58generally comprises rules, algorithms, code, tables, and/or other suitable instructions for generating market data38based at least in part on trading data52.

Market data memory54may be communicatively coupled to market data processor56. Market data processor56is generally operable to execute market data logic58to generate market data38. Market data processor56comprises any suitable combination of hardware and software implemented in one or more modules to provide the described function or operation.

As explained above, clients20, index server30, market data servers40, and market centers50may be communicatively coupled via one or more networks60. Network60may represent any number and combination of wireline and/or wireless networks suitable for data transmission. Network60may, for example, communicate internet protocol packets, frame relay frames, asynchronous transfer mode cells, and/or other suitable information between network addresses. Network60may include one or more intranets, local area networks, metropolitan area networks, wide area networks, cellular networks, all or a portion of the Internet, and/or any other communication system or systems at one or more locations.

It should be understood that the internal structure of trading system10and the servers, processors, and memory devices associated therewith is malleable and can be readily changed, modified, rearranged, or reconfigured to achieve the intended operations of trading system10.

In operation, compound index18is based at least in part on component indices24that are proportioned according to a particular weighting scheme. Index server30is operable to determine a respective weight34for each component index24that underlies compound index18. The respective weights34may be determined such that compound index18emulates a particular hedge fund index22. In some embodiments, index server30may re-calculate the respective weights34on a periodic basis (e.g., weekly, monthly, bimonthly, etc.). The day on which index server30re-calculates the respective weights34may be referred to as the rebalancing day62.

To re-calculate the respective weights34, index server30may determine, based at least in part on market data38, returns26associated with component indices24and hedge fund index22. The determined returns26may be weekly returns26, monthly returns26, and/or returns26associated with any suitable time period. Return26of a particular indicator (e.g., component index24, interest rate32, and hedge fund index22) refers to the change in value of the particular indicator over a particular time period. For example, a monthly return26of component index24represents the increase or decrease in value of component index24over a given month. In some embodiments, return26may be expressed as a percentage, as a currency amount, and/or according to any suitable metric.

Based at least in part on the determined returns26, index server30is operable to determine a respective weight34for each component index24and/or for interest rate32. According to certain embodiments, the respective weights34may be determined based at least in part on a regression analysis. The respective weights34may be determined such that compound index18emulates the performance of the particular hedge fund index22.

According to certain embodiments, the regression analysis may be based at least in part on multiple returns26from a configurable sampling period64. Sampling period64refers to one or more intervals of time for which returns26are input into the regression analysis. For example, if sampling period64is twenty-four months, then monthly returns26for each of the past twenty-four months may be input into the regression analysis to update weights34of component indices24. The sampling period64may be twelve months, twenty-four months, thirty-six months, and/or any suitable period of time.

After updating the respective weights34of component indices24, index server30may periodically determine closing level42of compound index18. In some embodiments, index server30updates closing level42of compound index18on a daily basis. Index server30may determine closing level42of compound index18based at least in part on closing levels42of component indices24and on the current weights34of component indices24. Closing level42of compound index18may be further based at least in part on interest rate32.

As explained above, weights34may be updated periodically (e.g., monthly, bimonthly, etc.). Because weights34are updated based at least in part on a particular hedge fund index22, the performance of compound index18emulates the particular hedge fund index22.

FIG. 2illustrates an example compound index fund16, according to certain embodiments. Compound index fund16generally holds a plurality of investment instruments28from each component index24associated with compound index18. The overall performance of compound index fund16depends, at least in part, on the particular investment instruments28held by compound index fund16. The proportions of investment instruments28in compound index fund16depend, at least in part, on weights34associated with component indices24.

An example illustrates certain embodiments. In this example, compound index fund16is associated with three component indices24—Component Index X, Component Index Y, and Component Index Z. Component Index X is associated with Securities A-D, Component Index Y is associated with Notes E-J, and Component Index Z is associated with Commodities K-M. Compound index fund16is associated with compound index18, which is configured to emulate a particular hedge fund index22. In this example, based at least in part on a regression analysis of Component Indices X, Y, and Z and on the particular hedge fund index22, index server30determines that Component Index X is associated with Weight S, Component Index Y is associated with Weight T, and Component Index Z is associated with Weight U.

In the present example, compound index fund16holds each of Securities A-D, each of Notes E-J, and each of Commodities K-M. The number of Securities A-D in compound index fund16is proportional to Weight S. The number of Notes E-J in compound index fund16is proportional to Weight T. The number of Commodities K-M in compound index fund16is proportional to Weight U.

Index server30may re-calculate Weights S, T, and U periodically. If the re-calculation causes a change in any of Weights S, T, and U, index server30may adjust the proportions of investment instruments28in compound index fund16accordingly. To adjust the proportions of investment instruments28in compound index fund16, index server30may generate and transmit trading orders12to market centers50.

It should be understood that, in a particular component index24, the underlying investment instruments28(e.g., securities, notes, etc.) may be represented in different proportions. In other words, a particular component index24may internally weigh the investment instruments28that underlie that particular component index24. Investment instruments28in some indices may be price weighted, market-value weighted, and/or capitalization weighted. Index server30may configure compound index fund16such that the proportions of investment instruments28in compound index fund16reflect weights34of component indices24as well as any internal weightings of a particular component index24.

In the foregoing example, compound index fund16holds each investment instrument28from each of Component Indices X, Y, and Z. In other embodiments, compound index fund16may hold representative investment instruments28from each component index24according to a statistical sampling of the market.

FIGS. 3-6illustrate, in part, sample data and calculations regarding an example compound index18. In particular,FIGS. 3-6illustrate example returns26of component indices24, example weights34of component indices24, and example closing levels42of compound index18, according to certain embodiments.

In the present example, compound index18is configured to emulate a particular hedge fund index22—namely, the HFRI Fund Weighted Composite Index (“the HFRI Index”). In this example, compound index18is based at least in part on five component indices24—namely, the S&P 500 Total Return Index (“the SPTR index”), the Russell 2000 Total Return Index (“the RU20 index”), the MSCI EAFE U.S. Dollar Net Total Return Index (“the INT index”), the MSCI Emerging Markets Free Total Return Index (“the EMG index”), and the U.S. Dollar Index (“the USD index”). In addition, compound index18is based at least in part on a particular interest rate32—the BBA One Month USD Libor (“the Libor”).

FIG. 3illustrates example market data38that is stored in index memory44and that is used to determine compound index18, according to certain embodiments. Index server30receives market data38from market data server40on a substantially continuous basis. In this example, market data38comprises closing levels42of the five component indices24, the Libor, and the HFRI index. Index server30is operable to store this information in index memory44. As illustrated inFIG. 3, for Nov. 30, 2006, index server30determines, based at least in part on market data38, that the SPTR index is valued at 2155.885254, the RU20 index is valued at 3317.79004, the INT index is valued at 4388.808, the EMG index is valued at 302.957, and so forth.

In some embodiments, market data server40does not publish each day a particular closing level42for hedge fund index22. In certain embodiments, closing level42for hedge fund index22may be published monthly.

According to some embodiments, returns26of the various indicators (e.g., component indices24, interest rate32, and hedge fund index22) may be calculated for configurable intervals (e.g., weeks, months, etc.). In certain embodiments, the last day of a given interval may be referred to as the observation day66. Trading system10may be configured such that observation day66corresponds with the day on which market data server40publishes closing level42of hedge fund index22.

In the present example, returns26of the various indicators are determined on a monthly basis. In this example, observation day66is the last day of each calendar month.

FIGS. 4A and 4Billustrate monthly returns26associated with the five component indices24, the Libor, and the HFRI index. In this example, index server30determines monthly returns26as follows:
Libor return=Libor closing levelOD-1*(ACTUAL/360)/100The returns of the respective indices (e.g., the SPTR, RU20, INT, EMG, USD, and HFRI indices) are determined according to the following formula: return of respective index=(respective index closing levelOD/respective index closing levelOD-1)−1

In the foregoing formulas, “closing levelOD” refers to closing level42of the particular indicator (e.g., index or Libor) on a given observation day66. “Closing levelOD-1” refers to closing level42of the particular indicator (e.g., index or Libor) one calendar month prior to the given observation day66. With respect to the Libor return26, “ACTUAL” refers to the actual number of days in the calendar month in which the given observation day66resides.

In the present example, index server30determines the monthly Libor return26for November 2006. In particular, based at least in part on market data38fromFIG. 3, index server30determines that Libor closing levelOD-1=5.32 (e.g., closing level42of the Libor on the prior observation day66). Index server30further determines that ACTUAL=30 (the actual number of days in November). Thus, index server30determines that the monthly Libor return26for November 2006 is 0.004433333. Index server30stores the determined Libor return26in index memory44.

In the present example, index server30further determines the monthly SPTR index return26for November 2006. Based at least in part on market data38illustrated inFIG. 3, index server30determines that the SPTR index closing levelOD=2155.885254 (e.g., closing level42of the SPTR index as of Nov. 30, 2006). Index server30further determines that SPTR index closing levelOD-1=2115.653809 (e.g., closing level42of the SPTR index as of Oct. 31, 2006). Accordingly, index server30determines that the monthly SPTR index return26for November 2006 is 0.019016081. Index server30stores the determined monthly return26of SPTR index in index memory44. In the present example, index server30repeats the foregoing procedure with respect to the RU20, INT, EMG, USD, and HFRI indices.

In the present example, index server30stores monthly returns26for sampling period64of twenty-four months. Monthly returns26from sampling period64are input into a regression calculation for updating weights34associated with component indices24. Each month, returns26from the earliest month in sampling period64may be discarded and returns26from the most recent month may be added to returns26associated with sampling period64.

In some embodiments, market data server40may not publish closing level42of hedge fund index22for a particular observation day66until one or more days after the particular observation day66. Accordingly, in some embodiments, index server30may not determine return26of hedge fund index22for a particular month until sometime during the following month.

In the present example, index server30is configured to rebalance weights34associated with the five component indices24once each month. The day on which index server30rebalances the respective weights34is referred to as rebalancing day62. In this example, rebalancing day62is the second business day following the day on which market data server40publishes the monthly closing level42(e.g., “end update”) of the HFRI index. As explained above, index server30may, on each rebalancing day62, re-calculate the respective weights34associated with component indices24. Although the present example illustrates rebalancing day62as the second business day following the publication of the end update of the HFRI index, it should be understood that rebalancing day62may be any suitable day (e.g., last day of the month, first day of the month, first day of the week, etc.).

FIG. 5illustrates the results of an example linear regression analysis based at least in part on returns26illustrated inFIGS. 4A and 4B. The respective weights34of the five component indices24are determined in this example by performing a multiple linear regression according to the following formula:
HFRI index return−Libor return=Constant+WeightA*(SPTR index return−Libor return)+WeightB*(RU20 return−Libor return)+WeightC*(INT index return−Libor return)+WeightD*(EMG index return−Libor return)+WeightE*USD index return
In the foregoing formula, “return” refers to the determined monthly return26of the respective indicator (i.e., Libor or index) for the second month preceding the current rebalancing day62. Thus, if the current rebalancing day62is Jan. 4, 2007, “return” refers to return26for November 2006. In some embodiments, the reason for not including returns26from December 2006 is that market data server40may not publish the December return26of hedge fund index22until the end of January or the beginning of February. In other embodiments, however, returns26from the most recent month may be included in the regression analysis.

In this example, the value of “Constant” may be determined by executing the multiple linear regression according to a least squares method. Like Weights A-E, the actual value of “Constant” may be solved for by executing the linear regression.

In this example, sampling period64for the regression analysis is the twenty-four month period ending on the second month preceding the current rebalancing day62. Thus, if the current rebalancing day62is Jan. 4, 2007, sampling period64is from December 2004 through November 2006.

In the present example, on Jan. 4, 2007, index server30performs the foregoing linear regression based at least in part on returns26illustrated inFIGS. 4A and 4B. According to the regression analysis, index server30determines that Weight A is −0.198, Weight B is 0.176, Weight C is 0.219, Weight D is 0.090, and Weight E is −0.009. Index server30stores Weights A-E in index memory44.

After updating Weights A-E on a given rebalancing day62, index server30may use Weights A-E during the ensuing month to determine closing level42of compound index18on a daily basis.FIGS. 6A and 6Billustrate a table comprising example closing levels42of compound index18, according to certain embodiments. In the present example, index server30is configured to determine closing level42of compound index18on each business day. To determine closing level42of compound index18on a given day, index server30first determines the accumulated total return (“ATR”) associated with the Libor and the component indices24. ATR is determined according to the following formula:
ATR=WeightX*(LiborRD*(DAYS/365))+WeightA*((SPTR index closing levelICD/SPTR index closing levelRD)−1)+WeightB*((RU20 index closing levelICD/RU20 index closing levelRD)−1)+WeightC*((INT index closing levelICD/INT index closing levelRD)−1)+WeightD*((EMG index closing levelICD/EMG index closing levelRD)−1)+WeightE*((USD index closing levelICD/USD index closing levelRD)−1)
In the foregoing formula, “ICD” refers to the current day. “RD” refers to the most recent rebalancing day62. “DAYS” refers to the actual number of days from (but excluding) the most recent rebalancing day62to (and including) the current day. “Weight X” equals (1−(the sum of Weights A through D)).

In the present example, the current day is Jan. 8, 2007. On that day, index server30determines, based at least in part on market data38, that SPTR index closing levelICD=2178.80249. Based at least in part on market data38stored in index memory44, index server30determines that SPTR index closing levelRD=2186.602783 (i.e., closing level42of the SPTR index on the most recent rebalancing day62—Jan. 4, 2007). Index server30determines that Weight A is equal to −0.198. Index server30repeats the foregoing procedure for the other component indices24. Based at least in part on the foregoing formula, index server30determines that the ATR is equal to −0.0066.

After determining the ATR, index server30determines closing level42of compound index18for the current day. In the present example, index server30is configured to determine the closing level42of compound index18according to the following formula:
Compound index closing levelICD=(ATR+1)*compound index closing levelRD
In the foregoing formula, “ICD” refers to the current day. “RD” refers to the most recent rebalancing day62. In the present example, index server30determines from data stored in index memory44that compound index closing levelRDis 1460.15 (i.e., the compound index closing level42on Jan. 4, 2007). Based at least in part on the determined ATR, index server30then determines that the compound index closing level42for the current calculation day is 1450.56. In the present example, index server30transmits the determined compound index closing level42to clients20and to market data server40. Market data server40may then disclose the determined compound index closing level42to market centers50and/or to other traders14in trading system10.

In some embodiments, weights34of component indices24may be subject to constraints. In some embodiments, constraints represent limits that are configured to maintain compound index18within configurable thresholds. In the event that index server30imposes a particular constraint for a particular component index24, the regression analysis may continue with respect to the other component indices24as if no constraints had been imposed. In the foregoing example, the respective weights34of the SPTR, INT, and USD indices may be constrained to have a value of greater than or equal to minus one and less than or equal to one. In this example, weight34of the EMG index may be constrained to be greater than or equal to zero and less than or equal to one, and weight34of the RU20 index may be constrained to be greater than or equal to −0.3 and less than or equal to one. Although particular constraint values are described herein, it should be understood that index server30may be configured to impose any suitable number and combination of constraints.

In the foregoing example, Weight A associated with the SPTR index has a negative value. In some embodiments, any negative weight value has the same effect on compound index18as if a short position had been created in the applicable component index24.

In some embodiments, the sum of weights34of component indices24may exceed one. In certain embodiments, if the sum of weights34exceeds one, the computation of compound index18is associated with an element of leverage exposure.

In the foregoing example, compound index18is associated with five component indices24. It should be understood, however, that compound index18may be associated with any number and combination of component indices24.

Component indices24in the foregoing example comprise the SPTR, RU20, INT, EMG, and USD indices. In other embodiments, however, component indices24may comprise some or none of the foregoing indices. In certain embodiments, component indices24may comprise one or more commodity indices, one or more debt indices, one or more currency indices, one or more equity indices, and/or other indices associated with any suitable class of investment instruments28.

In the foregoing example, compound index18emulates the HFRI index. The HFRI index generally represents an index of a plurality of constituent hedge funds. In some embodiments, the HFRI index includes both U.S. domestic and off-shore hedge funds. Although the foregoing example illustrates a particular compound index18that emulates the HFRI index, it should be understood that compound index18may be configured to emulate any suitable hedge fund index22and/or any number and combination of hedge fund indices22. For example, compound index18may be configured to emulate the CSFB Credit Suisse/Tremont Hedge Fund Index, the FTSE Hedge Index, the DOW Jones Hedge Fund Index, the Eurekahedge Hedge Fund Index, and/or any suitable hedge fund index22. As another example, compound index18may be configured to emulate the HFRI Equity Hedge Index and/or any suitable hedge fund index22that represents the performance of multiple hedge funds that employ long/short investment strategies.

In the foregoing example, component indices24comprise at least the SPTR index. In some embodiments, the SPTR index is the total return version of the S&P 500 Index. The S&P 500 Index is associated with the stocks of five hundred large-cap companies (mostly U.S. companies). According to certain embodiments, dividends may be reinvested on a daily basis. In some embodiments, Standard & Poor's acts as the index sponsor for the SPTR index. Although the foregoing example illustrates compound index18associated with the SPTR index, it should be understood that, in some embodiments, compound index18may not be associated with the SPTR index. According to certain embodiments, the SPTR index is an example of a U.S. large-cap equity index. In certain embodiments, compound index18may be based at least in part on any suitable component index24associated with securities of large-cap U.S. companies.

Component indices24in the foregoing example further comprise the RU20 index. According to certain embodiments, the RU20 index may be based at least in part on the Russell 2000 Index, which measures the performance of the 2,000 smallest companies in the Russell 3000 Index. The Russell 3000 Index is generally formed by listing U.S. companies in descending order by market capitalization. The top 3,000 stocks (those of the 3,000 largest U.S. companies) make up the Russell 3000 Index. The top 1,000 of those companies make up the large-cap Russell 1000 Index, and the bottom 2,000 (the smallest companies) make up the Russell 2000 Index. According to certain embodiments, the RU20 index is an example of a U.S. small-cap equity index. In some embodiments, the Russell Investment Group acts as the index sponsor for the RU20 index. Although the foregoing example illustrates compound index18associated with the RU20 index, it should be understood that, in some embodiments, compound index18may not be associated with the RU20 index. In certain embodiments, compound index18may be based at least in part on any suitable component index24associated with securities of small-cap U.S. companies.

In the foregoing example, component indices24further comprise the INT index. In some embodiments, the INT index is based at least in part on the MSCI EAFE Index (Europe, Australia, Far East) (the “EAFE Index”). According to certain embodiments, the EAFE Index is a free float-adjusted market capitalization index that is designed to measure developed market equity performance, excluding the U.S. and Canada. In some embodiments, Morgan Stanley Capital International acts as the index sponsor of the INT index. Although the foregoing example illustrates compound index18associated with the INT index, it should be understood that, in some embodiments, compound index18may not be associated with the INT index. In some embodiments, the INT index is an example of an international developed markets equity index. In certain embodiments, compound index18may be based at least in part on any suitable component index24associated with equity performance in developed markets.

Component indices24in the foregoing example further comprise the EMG index. In some embodiments, the EMG index is based at least in part on the MSCI EMF U.S. Dollar Index (“the EMF Index”). According to certain embodiments, the EMF Index is a free float-adjusted market capitalization index that is designed to measure equity market performance in global emerging markets. In some embodiments, Morgan Stanley Capital International acts as the index sponsor of the EMG index. Although the foregoing example illustrates compound index18associated with the EMG index, it should be understood that, in some embodiments, compound index18may not be associated with the EMG index. According to certain embodiments, the EMG index is an example of an international emerging markets equity index. In certain embodiments, compound index18may be based at least in part on any suitable component index24associated with equity market performance in global emerging markets.

In the foregoing example, component indices24further comprise the USD index. According to certain embodiments, the USD index indicates the general international value of the U.S. dollar. In particular, the USD index may average the exchange rates between the U.S. dollar and a plurality of major world currencies. Although the foregoing example illustrates compound index18associated with the USD index, it should be understood that, in some embodiments, compound index18may not be associated with the USD index. In certain embodiments, compound index18may be based at least in part on any suitable component index24associated with one or more currencies and/or one or more exchange rates.

In the foregoing example, compound index18is based at least in part on the Libor (e.g., BBA One Month USD Libor). The Libor, which is published by the British Bankers Association, generally represents a particular interest rate32that is applicable to the short-term international interbank market. In some embodiments, the Libor applies to large loans borrowed for anywhere from one day to five years. The short-term international interbank market associated with the Libor allows banks with liquidity requirements to borrow from other banks with surpluses, enabling banks to avoid holding excessively large amounts of their asset base as liquid assets. In some embodiments, the Libor is officially fixed once a day. Although the foregoing example illustrates interest rate32associated with the Libor, it should be understood that, in some embodiments, compound index18may not be associated with the Libor. In certain embodiments, compound index18may be based at least in part on any number and combination of interest rates32.

In the foregoing example, weights34of component indices24are determined according to a linear regression. In other embodiments, however, weights34of component indices24may be determined according to a nonlinear regression, kernel regression, simple linear regression, multiple linear regression, polynomial interpolation, numerical integration, and/or any suitable number and combination of formulas, equations, tables, and/or algorithms.

In some embodiments, trading system10is operable to detect a market disruption event. A market disruption event may comprise a failure of the sponsor of component index24to publish closing level42of component index24. In some embodiments, a market disruption event may comprise a disruption and/or failure associated with one or more market centers50. In some embodiments, if index server30detects a market disruption event that affects a particular component index24, index server30may determine closing level42of that particular component index24based at least in part on prevailing market conditions, last reported trading prices, and/or other information that is relevant to the valuation of the affected component index24. According to certain embodiments, if index server30detects a market disruption event associated with a closure of one or more market centers50, index server30may set closing level42of compound index18to be equal to closing level42of compound index18on the previous business day. In such embodiments, once market centers50reopen, index server30may determine a current closing level42of compound index18.

The invention has several important technical advantages. Various embodiments of the invention may have none, some, or all of these advantages. One advantage is that trading system10provides a weighted compound index18associated with various component indices24. In some embodiments, each component index24is associated with assets having intraday liquidity. The transaction costs of trading these assets are generally lower than the transaction costs associated with hedge funds. Thus, compound index18offers more liquidity and lower fees than hedge fund index22.

Another advantage is that trading system10periodically updates weights34of component indices24that underlie compound index18. Trading system10may configure weights34so that compound index18emulates the performance of hedge fund index22. Thus, the compound index18may provide traders14with returns26similar to those provided by hedge fund index22. In some embodiments, because compound index18emulates one or more hedge fund indices22, compound index18provides a benchmark for the performance of alternative investments such as, for example, funds of funds, hedge funds, and investable hedge fund indices22.

FIG. 7illustrates a flowchart for updating compound index18, according to certain embodiments. The method begins at step702by storing in index memory44compound index18. Compound index18may be based at least in part on interest rate32and/or on a plurality of component indices24. The plurality of component indices24may comprise an equity index, a debt index, a commodity index, a currency index, and/or an index associated with any suitable number and combination of classes of investment instruments28. In index memory44, each component index24may be associated with a respective weight34.

At step704, index server30determines whether the current day is rebalancing day62. If index server30determines at step704that the current day is not rebalancing day62, the method continues to step720. If, however, index server30determines at step704that the current day is rebalancing day62, then at step706index server30may determine one or more monthly returns26for each of the plurality of component indices24. In some embodiments, index server30may determine the monthly returns26based at least in part on market data38from market data server40.

At step708, index server30determines one or more monthly returns26for a particular interest rate32. At step710, index server30determines one or more monthly returns26for a particular hedge fund index22that is emulated by compound index18.

At step712, index server30may execute a linear regression to determine updated weights34. Each of the updated weights34may be associated with a respective component index24. The linear regression may be based at least in part on the determined returns26associated with component indices24, the particular interest rate32, and/or the particular hedge fund index22. The linear regression may use monthly return data for a configurable sampling period64of time (e.g., twelve months, twenty-four months, etc.). The linear regression may be executed such that compound index18emulates the particular hedge fund index22. At step714, index server30may store the updated weights34in index memory44.

In certain embodiments, compound index18may be associated with compound index fund16. Compound index fund16may comprise a plurality of investment instruments28and may be managed by index server30. At step716, index server30may, based at least in part on the updated weights34, adjust the allocation of investment instruments28in compound index fund16. As an example, a particular compound index18may comprise a first set of investment instruments28corresponding to a first component index24associated with a first weight34, a second set of investment instruments28corresponding to a second component index24associated with a second weight34, and a third set of investment instruments28corresponding to a third component index24associated with a third weight34. Upon updating the first, second, and third weights34, index server30may adjust the number and/or type of investment instruments28in compound index fund16in proportion to the updated first, second, and third weights34. In some embodiments, to adjust the proportions of investment instruments28, index server30may generate and transmit to market center(s)50one or more trading orders12.

At step718, index server30determines a current closing level42for each component index24. Index server30may determine the current closing levels42of component indices24based at least in part on market data38from market data server40. At step720, index server30determines closing level42of compound index18. The determination may be based at least in part on the most recently determined set of weights34associated with component indices24. The determination of closing level42of compound index18may be further based at least in part on the plurality of current closing levels42of component indices24. At step722, index server30transmits closing level42of compound index18to one or more clients20and/or to market data server40. In some embodiments, index server30and/or market data server40may transmit closing level42of compound index18to one or more market centers50. The method then ends.

Although the present invention has been described in detail, it should be understood the various changes, substitutions, and alterations can be made hereto without departing from the scope of the invention as defined by the appended claims.