System and method for providing an investment direction for operating a public / private real estate investment fund

Abstract

A method for providing an investment direction for operating an investment fund comprised of investments in public and private real estate. A computer model contains information including economic market data, weighted percentages of the investments in public and private real estate funds held by the investment fund, and data characterizing the underlying assets held by the public and private funds. The data is periodically updated to reflect changes in the underlying assets and economic market data over time. The model calculates a plurality of indicators and executes a plurality of algorithms based upon the indicators to define a valuation factor, a capital markets factor, and a volatility factor. A weighting algorithm is executed embodying the valuation factor, the capital markets factor, and the volatility factor to provide the investment direction as an output in the form of a future weighted percentage target to be achieved at a future time.

Description

[0001]2103669-000033 -1- SYSTEM AND METHOD FOR AN INVESTMENT DIRECTION FOR OPERATING A PUBLIC / PRIVATE REAL ESTATE INVESTMENT FUND CROSS-REFERENCE TO RELATED APPLICATIONS The present application claims priority to U.S. Patent Application No. 63 / 571,831, entitled “SYSTEM AND METHOD FOR PROVIDING AN INVESTMENT DIRECTION FOR OPERATING A PUBLIC / PRIVATE REAL ESTATE INVESTMENT FUND” filed March 29, 2024, the contents of which are incorporated herein by reference in their entirety. BACKGROUND OF THE INVENTION The public real estate market, as referred to herein, comprises a plurality of securities, such as Real Estate Investment Trusts (REITs) and index funds comprising investments in a plurality of REITs, which are accessible to receiving investment from the general public (e.g., traded on a public exchange). The private real estate market, as referred to herein, comprises securities or funds available to qualified investors for investment on an individual basis and having investments in real estate, but which are not accessible to receiving investment from the general public (e.g., not traded on a public exchange). U.S. Patent No.10,977,724, titled “REAL ESTATE PRIVATE INDEX FUND SYSTEMS AND METHODS,” assigned to the common assignee of the present application and incorporated herein by reference, details system, methods, and related computer program products for creating and managing investment in a real estate private index fund that replicates an open end, unlisted, private, transparently-reported real estate index. A commercial embodiment of the foregoing is offered by IDR Investment Management, and is known as the ODCE Index Fund, which tracks a non-investible fund created by the National Council of Real Estate Investment Fiduciaries (NCREIF), known as the “NCREIF Fund Index – Open End Diversified Core Equity” (NFI-ODCE) Index. It should be understood that despite the label of “public” and “private” as used herein, this label refers only to the public or private accessibility of the investment vehicles, not to the any characteristic of the underlying assets. In fact, in many cases, the public funds and private funds may embody investments in substantially the same or 210369-000033 - 2 - similar assets (typically commercial real . Likewise, reference to the “public real estate market” refers to the universe of publicly-accessible investment vehicles in real estate and the “private real estate market” refers to the universe of privately-accessible investment vehicles in real estate. The term “public real estate investments” as used herein refers to the actual investments held by a particular fund comprised of investments in the public real estate market, and “private real estate investments” refers to actual investments in the public real estate market. Over time it has been observed that the valuation of the public real estate market and the private real estate market may have a gap in market value (referred to herein as the “Cap Rate Spread”), such as is illustrated in FIG.7, wherein the market value in one may lag or lead the market value in the other for substantially the same assets or same types of assets. On average, REIT Cap Rates are 60-70 basis points (0.6-0.7%) higher than ODCE Cap Rates, as illustrated by the “Long Term Average” line in Fig.7, but the gap varies over time, as illustrated by the Cap Rate Spread line of FIG.7. This gap may be exploited to increase or decrease investment in public relative to private investments based upon the better returns or performance of one relative to the other and the movement toward equilibrium in the markets over time. Thus, there is a desire in the art for managers (e.g., fund managers or portfolio managers) or of real estate investment funds comprising investments in both public real estate funds and private real estate funds, to identify gaps and prospective future such gaps in market valuation and weight their portfolios accordingly. In particular, because private real estate funds tend to be relatively less liquid than public real estate funds, there is a desire to identify such gaps with sufficient lead time to reposition the assets to match the investment direction. SUMMARY OF THE INVENTION One aspect of the invention relates to a computer-implemented method for providing an investment direction for operating an investment fund comprised of investments in real estate. The method includes the steps of creating a computer model, comprising machine-readable instructions stored in computer memory for modeling the investment fund, and inputting into the computer model asset data corresponding to information characterizing underlying assets held by one or more public real estate funds comprising investments in real estate and characterizing underlying assets held by one or 210369-000033 - 3 - more private real estate funds investments in real estate. Steps include inputting into the computer model economic market data relevant to the public real estate market and the private real estate market; inputting into the model a current public weight percentage (B%) corresponding to a weighted percentage of the investment fund comprising the investments in the public real estate market and a current private weight percentage of assets (V% = 1-B%) corresponding to a weighted percentage of the investment fund comprising the investments in the private real estate market; and periodically updating the asset data to reflect changes in the underlying assets and changes in the information characterizing the underlying assets over time and updating the economic market data to reflect changes over time. The model is configured to calculate a plurality of indicators and to execute a plurality of algorithms based upon the plurality of indicators. The plurality of calculated indicators includes a valuation factor, a capital markets factor, and a volatility factor. The valuation factor defines an incremental public market exposure percentage shift calculated using a valuation factor algorithm based upon a z-score for a current value for a cap rate spread (CRS) between public and private real estate as compared to an average CRS. The capital markets factor is calculated based upon a z-score of a treasury spread, comprising a difference in yield between a first treasury bond duration and a second treasury bond duration, wherein the first duration is longer than the second duration. The volatility factor comprises a binary signal indicating whether to shift the weighted percentages based upon a month-over- month (MoM) price change in the public real estate market above a predetermined threshold. The method then includes executing a weighting algorithm comprising the valuation factor, the capital markets factor, and the volatility factor as inputs, and providing an output of the weighting algorithm embodying an investment direction comprising a future weighted percentage target for B% to be achieved after a predetermined period of time. The output of the model may comprise a human readable output. In embodiments, the predetermined period of time comprises two quarters of a year. In embodiments, the method further comprises executing redemptions and purchases in accordance with the predicted future weighting direction so as to achieve the future weighted percentage within the predetermined period of time. In some embodiments, the output of the model is transmitted to a computer processor configured to execute the redemptions and purchases. 210369-000033 - 4 - The valuation factor may by a valuation factor algorithm that considers whether the z-score is less than or equal to a negative threshold, greater than the negative threshold or less than a positive threshold, or greater than or equal to the positive threshold number of standard deviations, wherein the negative and positive threshold have the same absolute value. The valuation factor algorithm may further consider the valuation factor of a previous quarter relative to a valuation factor change limit, wherein the valuation factor output comprises the valuation factor of the previous quarter, the valuation factor of the previous quarter minus a change limit, or the valuation factor of the previous quarter plus the valuation factor change limit. A maximum valuation factor may be set to twice the valuation factor change limit, which may be 5%. The capital markets factor may be computed by a capital markets factor algorithm that considers whether the z-score of the treasury spread is less than or equal to a negative threshold, greater than a negative threshold or less than a positive threshold, or greater than or equal to the positive threshold number of standard deviations, wherein the negative and positive threshold have the same absolute value. The capital markets factor algorithm may further consider if the capital markets factor of a previous quarter is greater than, equal to, or less than an initial capital markets factor value (e.g.30%-70%, typically 50%) limit, and the capital markets factor output may comprise the capital markets factor of the previous quarter, the capital markets factor of the previous quarter minus a capital markets change limit, or the capital markets factor of the previous quarter plus the capital markets change limit. The capital markets change limit may be 5%, and / or the predetermined threshold for the volatility factor may be 0.15. The volatility signal at a point in time may be dependent upon the volatility factor of a current time period in which the point of time is defined and in which one of a plurality of subperiods of time the point of time is defined. For example, the current time period may be a quarter, and the plurality of subperiods may include a first month, a second month, and a third month within the quarter. The future weighted percentage target for B% may be defined between a maximum public overweight and a minimum public overweight, such as wherein the maximum public overweight is 65% and / or the minimum public overweight is 35%. The maximum public overweight value is not limited to 65%, however, and may range from 90- 210369-000033 - 5 - 37.5% (e.g. when the initial, equilibrium is 30% and the change limit is 2.5%, wherein the model is constrained to the capital markets initial value + / - 3 times the change limit) and the corresponding minimum public overweight may range from 10-62.5% depending upon other factors. The cap rate spread (CRS) between public and private real estate is preferably computed on a normalized sector-weighted basis, such as wherein the normalized sector-weighted basis uses sector weightings from the investments in the private real estate market and / or wherein the sector-weighted basis includes weightings from sectors selected from the group consisting of: apartment, office, industrial, and retail. In preferred embodiments, the private real estate investments comprise an Index Fund that tracks the NFI-ODCE Index and / or the public real estate investments comprise one or more REITs or an Index Fund of REITs. Another aspect of the invention includes non-transitory computer memory media programmed with machine-readable instructions for causing a computer processor to perform the method steps as described herein. Yet another aspect of the invention includes a computer system comprising at least one processor in communication with computer memory, the at least one processor configured to read machine-readable instructions stored in the computer memory, which instructions are configured to cause the processor to perform the method steps as described herein. BRIEF DESCRIPTION OF THE DRAWINGS FIG.1 schematically depicts an exemplary algorithm relating to determination of a valuation factor as described herein. FIG.2A schematically depicts a bell curve showing standard deviations illustrating the spectrum of relative value of the public real estate market and private real estate market from public overvalued to public undervalued. FIG.2B schematically depicts a bell curve showing standard deviations illustrating the spectrum of the capital markets factor from a negative outlook to a positive outlook. FIG.3 schematically depicts an exemplary algorithm relating to determination of a capital markets factor as described herein. 210369-000033 - 6 - FIG.4 schematically exemplary algorithm relating to determination of a volatility factor as described herein. FIG.5 schematically depicts an exemplary algorithm (decision tree) relating to determination of a future weighting investment direction based upon current weighting and the factors as applied to the algorithms as described herein. FIG.6 schematically depicts various states of the computer model as described herein. FIG.7 is an exemplary graph illustrating the public / private real estate market cap rate spread over time. FIG.8A is an exemplary graph illustrating market cap rates for REITs and the ODCE Index over time for the Apartment sector. FIG.8B is an exemplary graph illustrating market cap rates for REITs and the ODCE Index over time for the Office sector. FIG.8C is an exemplary graph illustrating market cap rates for REITs and the ODCE Index over time for the Industrial sector. FIG.8D is an exemplary graph illustrating market cap rates for REITs and the ODCE Index over time for the Retail sector. FIG.9 is an exemplary graph illustrating the Index Level Cap Rates for REITs and the ODCE real estate index over time. DETAILED DESCRIPTION OF THE INVENTION Described herein are a plurality of indicators and algorithms for processing those indicators using a computer model to provide investment direction for an investment fund. A first indicator described herein is referred to as a Valuation Factor. A purpose of the valuation factor is to quantify the difference in relative valuation between the public and private real estate markets. The variables used for determining the Valuation Factor include property sector implied capital (“cap”) rates for the public and private investments contained within 210369-000033 - 7 - the fund portfolio. As used herein, the sector” refers to the different property types within the commercial real estate market (e.g., apartment, industrial, office, retail, other). The “implied cap rate” refers to the in-place net operating income (NOI) generated by a property during the quarter multiplied by 4 and divided by the gross asset value of the property. The respective public and private funds may have different sector weightings. As used herein, the term “sector weighting(s)” refers to the gross $ exposure to a given sector (in this case apartment, industrial, office, retail & other) divided by the total gross asset value across all sectors. For example, the public real estate funds may have a first weighting of property sectors (i.e.25% apartment, 25% industrial, 20% office, 15% retail, 15% other), and the private real estate funds may have a different weighting of property sectors represented by the investments in the funds (i.e.35% apartment, 15% industrial, 30% office, 10% retail, 10% other). Therefore, in order to properly compare the funds for calculation of the valuation factor, the relative weightings of the funds are normalized to adopt the property sector weightings of one or the other. In the examples as discussed herein, the private property sector weightings have been adopted for normalization purposes. Normalizing the public and private cap rates make them comparable on an apples-to-apples basis; otherwise, the valuation signal may have excess noise arising from the differences in property sector composition on the public and private side. To illustrate this principle, FIGS.8A-8D depict graphs of the cap rates over time for each of the apartment, office, industrial, and retail sectors over time for REITs and the ODCE, showing the differences in cap rates vary by sector. FIG.9 illustrates the difference between a comparison over time of the index level cap rates for the REITs (unadjusted) and the REITs (with ODCE weightings) against the ODCE rates, showing the significant difference that the normalization of ratings may provide, at least during certain periods of time. A key metric for determining the valuation factor is the composite cap rate. A composite cap rate is calculated for both public and private real estate by taking the implied cap rates by property sector from each and calculating the weighted average of the cap rates using private real estate market sector weightings (e.g., the ODCE property sector weightings) for both sets of cap rates. After calculating the two composite cap 210369-000033 - 8 - rates, the private real estate market is subtracted from the public real estate market composite to find the spread. Understanding the difference in relative valuation between public and private real estate markets helps the manager determine which direction the portfolio needs to shift investments between the public and private markets. Steepening, flattening, or inversion of the yield curve is often used as an indicator for the capital markets forward outlook of the economy. A signal of potential economic weakness in the future can inform a fund manager of when to start tilting away from public market investments and towards private market investments, with enough lead time to make the switch. Accordingly, a second indicator described herein is referred to as the Capital Markets Factor. The purpose of the Capital Markets Factor is to determine the forward outlook of the economy according to the capital markets using an indicator of whether the yield curve is steepening, flattening, or inverting. Variables used for determining the Capital Markets Factor include the treasury yield spread, also typically referred to as the Treasury Spread. The Treasury Spread (e.g., 10Y-2Y) typically refers to the difference in yield between the (e.g., 10-year) treasury notes and (e.g., 2-year) treasury notes, which is a common metric used by economists when determining steepening, flattening or inversion of the yield curve. Other business cycle indicators may also be incorporated into the determination of the Capital Markets Factor, and this factor is not limited to only using the 10Y-2Y spread. For example, a 10Y-1Y, a 10Y-3M(onth), 5Y- 1Y, 5Y-3M may be used. Also, the Near-Term forward Spread (the 6 quarter ahead 3 month treasury yield minus the current 3 month treasury yield) may be used. A third indicator described herein is the Volatility Factor, which is used to look at large spikes in month-over-month volatility to signal market capitulation. Variables used to determine the Volatility Factor include the monthly price change in the public real estate market index. The monthly price change of a public real estate market index (e.g., NAREIT All Equity REITs Index) may be used as a gauge of momentum shifts in the broader public real estate market. The volatility factor looks at volatility spikes in the rate of change of monthly price change to signal a potential market bottom. Understanding when the public real estate market may have bottomed out can help the manager capitalize on a rapid shift in conditions that would otherwise be missed with a static lag. CALCULATION OF FACTORS 210369-000033 - 9 - For simplicity, all factors herein from the perspective of the weighting to public real estate. For example, adding 5% to a given factor translates to increasing public market exposure by 5% and decreasing private market exposure by 5%. The public real estate component of the fund may be embodied using an active strategy or a passive strategy. One option is to invest in an already-available, publicly investible REIT index fund such as the Vanguard Real Estate ETF (Ticker: VNQ), iShares U.S. Real Estate ETF (Ticker: IYR), or Schwab U.S. REIT ETF (Ticker: SCHH) that tracks a REIT market index such as the FTSE Nareit All Equity REITs Index, without limitation. Another option is to actively invest in a basket of all available public REITs, or a bespoke REIT index comprised of an actively selected basket of REITs, optionally selected intentionally because of a historic and continuing predictable gap relative to the selected private real estate investments for the fund. Valuation Factor Calculation of the Valuation Factor is now described in more detail. The valuation factor uses the cap rate spread (see below equation) to determine which direction the portfolio should shift incrementally. Characterizing the factor in terms of incremental shifts rather than an absolute level is meant to mirror marginal decisions a portfolio manager might make depending on market conditions. Valuation Factor Signal Calculation A general equation for calculating the cap rate spread (crs) in period t is set forth as Equation 1. ^^^^^^ ൌ ^^^^௨^^^^௧ ൫^^^ ൈ ^^^^^൯ െ^൫^^^ ൈ ^^^^^൯ ^1^ ^ ൌ ^^^^^^^^^^^^^^^^^^^^ ^^ ^^^^^^^^^^^^^^^^^^ ^^^^^^^^^^^^ ^^ℎ^^ ^^^^^^^^^^^^^^ ^^^^^^^^^^^^ ^^^^^^^^^^^^^^^^ ^^^^^^^^^^^^^^ ^^^^ ^^^^^^^^^^^^ ^^^ ^^^^ ^^^^^^^^^^^^^^ ^^^^^^^^^^^^ ^^^^^^^^^^^^^^^^ ^^^^^^^^^^^^ ^^^^ ^^^^^^^^^^^^ ^^^^1^ ^ 210369-000033 - 10 - ^^^^^^^ ൌ ^^^^^^^^^^^^^^ ^^^^^^^^^^^^ ^^^^^^^^^^^^^^^^ ^^^^^^^^^^^^ ^^^^^^ ^^^^^^^^^^ ^^^^ ^^^^^^^^^^^^ ^^The result of Equation 1 is the spread between the weighted average public real estate cap rate (weighted with private weightings) and the weighted average private real estate cap rate. The z-score of the cap rate spread (Equation 2, below) is the valuation signal (VS) ^^^^^^ െ ^^^^^^ ௧ ^^^௧ ൌ^2^ ^^^^^ ^^^^^^௧ ൌ ^^^^^^ ^^^^^^^^ ^^^^^^^^^^^^ ^^^^ ^^^^^^^^^^^^ ^^^^^^^ ൌ ^^^^^^^^^^^^^^ ^^^^^^ ^^^^^^^^ ^^^^^^^^^^^^^^^^^ ൌ ^^^^^^^^^^^^^^^^ ^^^^^^^^^^^^^^^^^^ ^^^^ ^^^^^^ ^^^^^^^^ ^^^^^^^^^^^^A z-score represents the number of standard deviations the current value is above or below the average. A threshold “x” as referenced in the discussion of the Algorithm below is used for a comparison to the z-score to determine whether certain decision tree statements of the algorithm are true or false. An exemplary value for “x” is preferably in a range of 0.3 - 1.1, more preferably 0.5 – 0.9, most preferably 0.7 + / - 0.05, and as used herein is 0.675, but the invention is not limited to any particular value for this threshold. Valuation Factor Algorithm An exemplary Valuation Factor Algorithm 100 for calculating the Valuation factor is now described with reference to FIG.1. For purposes of this example, the Valuation Factor’s initial value is 0%, and the Change Limit = 5%. The ‘Change Limit’ represents the maximum amount the model would switch quarter-over-quarter. The 5% constant was selected as a maximum based on the observed minimum liquidity of the ODCE index fund. However, the change limit may vary as a function of the expected liquidity of the ODCE index fund and is not limited to any particular value. However, the value is preferably in a range of 2.5-10%, more preferably 5 - 7.5%. In other examples, the initial valuation factor may be a value other than 0%, such as 5%, or -10%. The 210369-000033 - 11 - Valuation Factor output by the algorithm be an integer (i.e., -2, -1, 0, 1, 2, without limitation) multiple of the change limit. Starting with a current valuation signal 102 (VSt), the algorithm steps through the following first level decision nodes: 112 = Is VStless than or equal to -x standard deviations? 114 = Is VStgreater than -x and less than x standard deviations? 116 = Is VStgreater than or equal to x standard deviations? These decision nodes correspond to evaluating where on bell curve 200 VStcurrently resides. If the answer to node 112 is “Yes,” the public real estate market is overvalued relative to the private real estate market (i.e., the value is in the left shaded portion of bell curve 200). If the answer to node 116 is “yes”, the public real estate market is undervalued relative to the private real estate market (i.e., the value is in the right shaded portion of bell curve 200). If the answer to node 114 is “yes”, the public real estate market value is within x (e.g., 0.675, per the example) standard deviations of its average comparative value relative to the private real estate market (i.e., the value is in the middle unshaded portion of curve 200). A “yes” decision in node 112, leads the algorithm to decision nodes 121 and 122. Decision node 121 posits whether the previous quarter Valuation Factor was greater than -2 times the Change Limit, in which case the output Valuation Factor will equal the Previous Quarter Valuation Factor minus the Change Limit. Decision node 122 posits whether the previous quarter Valuation Factor was equal to -2 times the Change Limit, in which case the output Valuation Factor will equal the Previous Quarter Valuation Factor. A “yes” decision in node 114, leads the algorithm to decision nodes 124, 125 and 126. Decision node 125 posits whether the previous quarter Valuation Factor was less than zero, in which case the output Valuation Factor will equal the Previous Quarter Valuation Factor plus the Change Limit. Decision node 125 posits whether the previous quarter Valuation Factor was equal to 0, in which case the output Valuation Factor will equal the Previous Quarter Valuation Factor. Decision node 126 posits whether 210369-000033 - 12 - the previous quarter Valuation Factor than zero, in which case the output Valuation Factor will equal the Previous Quarter Valuation Factor minus the Change Limit. A “yes” decision in node 116, leads the algorithm to decision nodes 128 and 129. Decision node 128 posits whether the previous quarter Valuation Factor was less than 2 times the Change Limit, in which case the output Valuation Factor will equal the Previous Quarter Valuation Factor plus the Change Limit. Decision node 129 posits whether the previous quarter Valuation Factor was equal to 2 times the Change Limit, in which case the output Valuation Factor will equal the Previous Quarter Valuation Factor. Capital Markets Factor The capital markets factor uses the treasury spread to determine which direction the portfolio should tilt. A flat or inverted treasury spread may signal potential future market distress and would therefore warrant a portfolio manager to tilt exposure of the fund away from the more volatile, quicker-to-revalue public markets towards the private markets. Conversely, a steep yield curve may signal potential future market recovery or strength and would warrant a portfolio manager to lean away from the private markets and into the public markets. Capital Markets Signal Calculation The z-score of the treasury spread (ts) is the capital markets signal (CMS) The z-score of the treasury spread (ts) is the capital markets signal (CMS), as set forth in Equation 3^^^^^^௧^^ି ఓ^ೞ௧ ൌ[3] ^^^^^^௧ ൌ ^^^^^^^^^^^^^^ ^^^^^^^^^^^^^^ ^^^^^^^^^^^^ ^^^^ ^^^^^^^^^^^^ ^^^^^^௧ ൌ ^^^^^^^^^^^^^^^^ ^^^^^^^^^^^^ ^^^^ ^^^^^^^^^^^^ ^^^^௧^ ൌ ^^^^^^^^^^^^^^ ^^^^^^^^^^^^^^^^ ^^^^^^^^^^^^^^௧^ ൌ ^^^^^^^^^^^^^^^^ ^^^^^^^^^^^^^^^^^^ ^^^^ ^^^^^^^^^^^^^^^^ ^^^^^^^^^^^^ 210369-000033 - 13 - A z-score represents the number deviations the current value is above or below the average. A threshold “y” as referenced in the discussion of the Algorithm below is used for a comparison to the z-score to determine whether certain decision tree statements of the algorithm are true or false. An exemplary value for “y” is preferably in the range of 0.5- 1.5, more preferably 0.75-1.25, and as used herein is 1, but the invention is not limited to any particular value for this threshold. Capital Markets Factor Algorithm An exemplary Capital Markets Factor Algorithm 300 for calculating the Valuation factor is now described with reference to FIG.3. For purposes of the example as discussed herein, the initial value of the capital markets factor is 50%, with a Change Limit = 5%. However, the capital markets initial factor may range anywhere from 30-70%, more preferably 40-60%, and typically 50%, depending upon the desired equilibrium of a particular fund. The ‘Change Limit’ represents the maximum amount the model would switch quarter-over-quarter, and may be in a range of 2.5-10%, preferably 5-7.5%, and 5% selected as a typical maximum based on the observed minimum liquidity of the ODCE index fund. The change limit is not limited to any particular value and may vary as a function of the expected liquidity of the ODCE index fund. In other examples, the initial Capital Markets Factor may be a value other than 50%, such as anywhere in a range of 30-70%, e.g., 30, 35, 40, 50.55, 60, 65, or 70, %. The Capital Markets Factor output by the algorithm will typically be an integer (i.e., -2, -1, 0, 1, 2, without limitation) multiple of the change limit. Starting with a current Capital Markets signal 302 (CMSt), the algorithm steps through the following first level decision nodes: 312 = Is CMStless than or equal to -y standard deviations? 314 = Is CMStgreater than -y and less than y standard deviations? 316 = Is CMStgreater than or equal to y standard deviations? These decision nodes correspond to evaluating where on bell curve 250 CMStcurrently resides. If the answer to node 312 is “Yes,” the CMS corresponds to a relatively negative outlook based to the average (i.e., the value is in the left shaded 210369-000033 - 14 - portion of bell curve 250). If the answer 316 is “yes”, the CMS corresponds to a relatively positive outlook based to the average (i.e., the value is in the right shaded portion of bell curve 250). If the answer to node 314 is “yes”, the CMS has a value within 1 standard deviation of its average comparative value (i.e., the value is in the middle unshaded portion of curve 250). A “yes” decision in node 312, leads the algorithm to decision nodes 321 and 322. Decision node 321 posits whether the previous quarter Capital Markets Factor was greater than or equal to the capital markets factor initial value (e.g., 50%), in which case the output Capital Markets Factor will equal the Previous Quarter Capital Markets Factor minus the Change Limit. Decision node 322 posits whether the previous quarter Capital Markets Factor was less than the capital markets factor initial value (e.g., 50%), in which case the output Capital Markets Factor will equal the Previous Quarter Capital Markets Factor. A “yes” decision in node 314, leads the algorithm to decision nodes 324, 325 and 326. Decision node 324 posits whether the previous quarter Capital Markets Factor was less than the capital markets factor initial value (e.g., 50%), in which case the output Capital Markets Factor will equal the Previous Quarter Capital Markets Factor plus the Change Limit. Decision node 325 posits whether the previous quarter Capital Markets Factor was equal to the capital markets factor initial value (e.g., 50%), in which case the output Capital Markets Factor will equal the Previous Quarter Capital Markets Factor. Decision node 326 posits whether the previous quarter Capital Markets Factor was greater than the capital markets factor initial value (e.g., 50%), in which case the output Capital Markets Factor will equal the Previous Quarter Capital Markets Factor minus the Change Limit. A “yes” decision in node 316, leads the algorithm to decision nodes 328 and 329. Decision node 328 posits whether the previous quarter Capital Markets Factor was less than or equal to the capital markets factor initial value (e.g., 50%), in which case the output Capital Markets Factor will equal the Previous Quarter Capital Markets Factor plus the Change Limit. Decision node 329 posits whether the previous quarter Capital Markets Factor was greater than the capital markets factor initial value (e.g., 50%), in 210369-000033 - 15 - which case the output Capital Markets will equal the Previous Quarter Capital Markets Factor. Volatility Factor The volatility factor utilizes the month-over-month (MoM) price change in the public real estate market index to look for statistically significant reversals in the price change of the index. Volatility Factor Signal Calculation The first difference of the public real estate market index MoM price change is the volatility signal (VolS) as set forth in Equation 4. ^^ ^^^^^ ௧^^^^^ ௧ି^௧ ൌെ ^4^ ^^௧ି^^^௧ିଶ Wherein:^^^^^^^^௧ ൌ ^^^^^^^^^^^^^^^^^^^^ ^^^^^^^^^^^^ ^^^^ ^^^^^^^^^^^^ ^^ ^^^^^^^^^ℎ^^^^^^^௧ ൌ ^^^^^^^^^^^^^^ ^^^^^^^^^^^^ ^^^^^^^^ ^^^^^^^^^^^^ ^^^^^^^^^^ ^^^^^^^^^^^^௧ି^ ൌ ^^^^^^^^^^^^ ^^^^^^^^ ^^^^^^^^^^^^ ^^^^^^^^^^ ^^^^^^^^^^ ^^^^^^^^ ^^^^^^^^ℎ ^^^^^^^ ^^^^ ^^^^^^^^ℎ^^^௧ିଶ ൌ ^^^^^^^^^^^^ ^^^^^^^^ ^^^^^^^^^^^^ ^^^^^^^^^^ ^^^^^^^^^^ ^^^^^^^^ ^^^^^^ ^^^^^^^^ℎ^^ ^^^^^^ ^^^^^^^ ^^^^ ^^^^^^^^ℎ^A threshold “z” as referenced in the discussion of the Algorithm below is used for a comparison to the volatility signal to determine whether certain decision tree statements of the algorithm are true or false. An exemplary value for “z” is preferably in a range of 10-25%, preferably 15-20%, and as used herein is 15%, but the invention is not limited to any particular value for this threshold. Volatility Factor Algorithm An exemplary Volatility Factor Algorithm 400 for calculating the Volatility Factor is now described with reference to FIG.4. The Volatility Factor is a binary signal (Yes or No) that is meant to indicate if the portfolio should diverge from the simple weight and shift towards public real estate based on a dramatic shift in returns. For purposes of 210369-000033 - 16 - the example as discussed herein, the of the Volatility Factor is “No,” but in other examples, the initial value may be “Yes.” Starting with a current Volatility Signal 302 (VSt), the algorithm steps through the following first level decision nodes: 412 = Is the Current Period the first month of the quarter? 414 = Is the Current Period the second month of the quarter? 416 = Is the Current Period the third month of the quarter? If the answer to node 412 is “Yes” (i.e., it is the first month of the quarter) then the decision tree looks at blocks 421 and 422. In output block 421, if the Current Quarter Volatility Factor is already “yes”, then the value stays the same (“yes”). In node 422, if the Current Quarter Volatility Factor is currently “no”, then the decision tree looks at nodes 431 and 432. At node 431, if the Volatility Signal is less than z threshold, then the Current Quarter Volatility Factor output value will be set to “No” in output block 441. At node 432, if the Volatility Signal is greater than or equal to z threshold, then the Current Quarter Volatility Factor output value will be set to “Yes” in output block 442. If the answer to node 414 is “Yes” (i.e., it is the second month of the quarter) then the decision tree looks at blocks 424 and 425. In output block 424, if the Current Quarter Volatility Factor is already “yes”, then the value stays the same (“yes”). In node 425, if the Current Quarter Volatility Factor is currently “no”, then the decision tree looks at nodes 434 and 435. At node 434, if the Volatility Signal is less than z threshold, then the Current Quarter Volatility Factor output value will be set to “No” in output block 444. At node 435, if the Volatility Signal is greater than or equal to z threshold, then the Current Quarter Volatility Factor output value will be set to “Yes” in output block 445. If the answer to node 416 is “Yes” (i.e., it is the third month of the quarter) then the decision tree looks at blocks 427 and 428. In output block 427, if the Current Quarter Volatility Factor is already “yes”, then the value stays the same (“yes”). In node 428, if the Current Quarter Volatility Factor is currently “no”, then the decision tree looks at nodes 437 and 438. At node 437, if the Volatility Signal is less than z threshold, then the Current Quarter Volatility Factor output value will be set to “No” in output block 446. At node 438, if the Volatility Signal is greater than or equal to z threshold, then the Current 210369-000033 - 17 - Quarter Volatility Factor output value will to “No” in output block 448 and the Next Quarter Volatility Factor will be set to Yes in output block 449. Notably, the algorithm as described in the example herein is based upon considering volatility periodically at each of a first, relatively smaller period of time (month) within a second, relatively larger period of time (quarter), but the invention is not limited to the use of a volatility factor over any particular periods of relatively smaller or relatively larger periods of time, nor to any number of smaller periods within a larger period. Accordingly, for example, analogous algorithms may be used for considering volatility week by week within a month, quarter by quarter within a year, or the like, without limitation. The calculations, underlying data, and algorithms as described herein come together to form a computer model in the form of machine-readable instructions stored in computer memory with access to a computer memory in which input data is stored, wherein the instructions cause a computer processor to process the data in accordance with the instructions to provide a computer output. The machine-readable instructions may be embodied as a computer readable medium (or multiple computer readable media) (e.g., a computer memory, one or more compact discs, optical discs, magnetic tapes, flash memories, or other semiconductor devices, servers or other tangible computer storage medium of a computer or accessed by a computer network) encoded with one or more programs and models that, when executed on one or more computers or other processors, perform methods that implement the various embodiments of the invention discussed herein. The computer readable medium or media can be stationary or transportable, such that the program or programs stored thereon can be loaded onto one or more different computers or other processors to implement various aspects of the present invention as discussed herein. The computer memory can be hardware / physical memory that may include volatile and / or non-volatile memory. The computer processor includes hardware CPU(s), operatively connected to the hardware / physical memory and an input / output (UO) interface. The memory; processor(s); user interfaces, such as keyboards, touchscreens, mouse or joystick controls; output devices, such as displays and printers; as well as communication links, switches, and any other components of an operative computer system may reside in a single location or may be distributed among 210369-000033 - 18 - multiple locations, may be physically connected, and may together define a specially programmed computer network, such as but not limited to a local or global network, or a portion thereof configured to perform the relevant methods steps as described herein. The computer output may be a human readable output in the form of information displayed on a human readable display connected to the computer, printed on a physical substrate by a printer connected to the computer, or transmitted in the form of a signal that is received by another computer or device and displayed on a display connected to or integrated therein. In embodiments, the computer output may also be received by an execution processor, which may comprise a computer programmed instructions for executing purchases and redemptions of shares in the underlying index funds or component funds that constitute the public and private market investments. In other embodiments, the output of the model may be used by a human fund manager to execute purchases and redemptions at the manager’s discretion. The model as discussed herein can be characterized with reference the chart 600 in FIG.6 as having four states: reposition public 610 (in which the fund manager increases investment in the public funds towards a public overweight target from a neutral position); hold 620 (in which the fund manager keeps the weighted ratio constant); drift to neutral 630 (in which the fund manager increases investment in private funds when overweighted public or increases investment in public funds when overweighted private), and reposition private 640 (in which the fund manager increases investment in private funds toward a private overweight target from a neutral position). Embodiments of the invention include computer-implemented methods and portions thereof as described herein for implementing the computer model as described and / or any additional or optional steps, non-transitory computer memory media programmed with machine-readable instructions for causing the processor to implement the instructions for performing the methods and portions of as described herein and / or any additional or optional steps, and systems comprising computer processors and associated memory embodying the computer model as described herein programmed with the machine-readable instructions for causing the processor to implement the instructions for performing the methods and portions of as described herein and / or any additional or optional steps. Suitable computer processors, memory, and memory media may have any 210369-000033 - 19 - form known in the art. The systems may multiple processors and / or computer memories communicatively connected to one another, including processors located remotely to one another and connected by a global communications network. References to “a computer processor” or “a computer memory” should be understood to refer to one or a plurality of such processors or memory, respectively, collectively configured to perform the operations as described. PORTFOLIO WEIGHT ALGORITHM In an exemplary embodiment, prior to running iterations of the model, the Capital Markets factor starts at a capital markets factor initial value (e.g.50%) and the Valuations Factor starts at 0%, adding to a total weighting of 50% for the public market portion (and corresponding total weighting of 50% for the private market portion). For simplicity, the weight referenced below refers to the weight of public real estate in the portfolio (the private weighting can be considered 1 minus the referenced weight). For purposes of the examples as described herein, a Change Limit of 5% is used. The ‘Change Limit’ represents the maximum amount the model would switch quarter-over-quarter. The 5% constant was selected as the maximum based on the observed minimum liquidity of the ODCE index fund. However, the change limit may vary as a function of the expected liquidity of the ODCE index fund. Notably, the change limit for the algorithm as a whole, as for each of the change limits as described as part of any of the foregoing algorithms for calculation of the various factors, is not limited to any particular percentage or to any particular percentage interval (e.g. integers, multiples of 5, multiples of 5, etc.). For purposes of the illustrated weighting examples as described herein, a Max Volatility Signal Overweight of 10% is used. The Max Volatility Signal Overweight is the maximum amount the current weighting can diverge from the Simple Weight when the volatility factor is signaling a “Yes,” where the Simple Weight is equal to the Capital Markets Factor in the current quarter plus the Valuation Factor 1 quarter ago and represents the target weight of public / private two quarters into the future, ignoring the volatility factor and change limit. The Max Signal Overweight is not limited to any particular value, but a preferred range is between 5-15%, more preferably 7.5-12.5%. 210369-000033 - 20 - For purposes of the a described herein, a Max Public Overweight of 65% and a Max Public Underweight of 35% are used. The invention is not limited to any particular values for overweight and underweight, however. The result of running the collection of algorithms as described herein is provide an output comprising investment guidance in the form of a target portfolio weight of public / private real estate two (2) quarters into the future. In order to shift the portfolio in time to capitalize on public / private real estate market dislocation, it is beneficial for the portfolio manager to know the weighting of the portfolio two quarters in advance to be within the redemption request windows of private index fund (i.e., the ODCE) component funds. While the present example is designed to provide investment guidance comprising a future weighting target that is two quarters in advance, embodiments of the invention may provide future weighting targets that are fewer or more quarters (or any period of time) in advance. Examples Below are examples, labeled as Scenarios A – L, with reference to the decision tree 500 provided in Fig.5, of how the aforementioned factors may be combined to create the guidance target future weighting of public and private real estate 2 quarters in advance. Consistent with the discussion above, the factors in the below examples are written from the perspective of public real estate, and private real estate can be thought of as 1 minus the weighting of public real estate. Each scenario below follows the decision tree to each output block as shown in the diagram. SCENARIO A This example outlines a scenario where the volatility factor signals YES but there is no valuation factor present in the current quarter or 1 quarter ago. 1. Start by calculating the Valuation Factor for 1 quarter ago and the current quarter, the Capital Markets Factor for the current quarter, and the Volatility Factor for 1 quarter ago and current quarter. Scenario A assumes the following calculation / algorithm results. a. Valuation Factor (1 Quarter Ago) = 0% b. Valuation Factor (Current Quarter) = 0% 210369-000033 - 21 - c. Capital Markets Factor Quarter) = 45% d. Volatility Factor (Current Quarter) = Yes e. Volatility Factor (1 Quarter Ago) = No f. Weight 1 Quarter ahead = 45% 2. Starting at block (or node) 502 of decision tree 500, calculate the Simple Weight: a. Simple Weight = Valuation Factor (1 Quarter Ago) + Capital Markets Factor (Current Quarter) b. Simple Weight = 0% + 45% = 45% 3. In block 512, the Volatility Factor Current or 1 Quarter Ago = Yes 4. In block 522, if the Valuation Factor for the current quarter or 1 quarter ago is equal to 0, then node 522 is TRUE, and the model proceeds to block 531. 5. In block 531, the Weight 2 Quarters ahead is set as the Weight 1 Quarter ahead, which in the example as set forth herein = 45% SCENARIO B This example outlines a scenario where the volatility factor signals YES and there is a valuation factor. This scenario is generally the beginning of the actual weight deviating from the simple weight. 6. Start by calculating the Valuation Factor for 1 quarter ago & current quarter, the Capital Markets Factor for the current quarter, and the Volatility Factor for 1 quarter ago & current quarter. Scenario B assumes the following calculation / algorithm results. a. Valuation Factor (1 Quarter Ago) = 10% b. Valuation Factor (Current Quarter) = 10% c. Capital Markets Factor (Current Quarter) = 45% d. Volatility Factor (Current Quarter) = Yes e. Volatility Factor (1 Quarter Ago) = No 2. Starting at block 502 Calculate the Simple Weight. a. Simple Weight = Valuation Factor (1 Quarter Ago) + Capital Markets Factor (Current Quarter) b. Simple Weight = 10% + 45% = 55% 3. In block 512, the Volatility Factor Current or 1 Quarter Ago = Yes 210369-000033 - 22 - 4. In block 524, check if the for the current quarter or 1 quarter ago is not equal to 0 (in this case the valuation factor is not equal to zero for both periods mentioned). 5. In block 532, check that the weight 1 quarter ahead + change limit is less than the simple weight + max volatility signal overweight a. Max Volatility Signal Overweight = 10% b. Weight 1 Quarter Ahead = 55% c. Change Limit = 5% d. Simple Weight = 55% e. 55% + 5% < 55% + 10% is TRUE 6. In block 542, check that the weight 1 quarter ahead + change limit is less than the max public overweight a. Weight 1 Quarter ahead = 55% + change limit (5%) = 60% b. Max Overweight = 65% c. 60% < 65% is TRUE 7. In block 552, the target Weight 2 Quarters ahead is set to the Weight 1 Quarter ahead + Change Limit a. Weight 2 Quarters ahead = 55% + 5% = 60% SCENARIO C This example outlines a scenario where the volatility factor signals YES and there is a valuation factor, but the weight 1 quarter ahead is already at the max. 1. Start by calculating the Valuation Factor for 1 quarter ago & current quarter, the Capital Markets Factor for the current quarter, and the Volatility Factor for 1 quarter ago & current quarter. Scenario C assumes the following calculation / algorithm results. a. Valuation Factor (1 Quarter Ago) = 10% b. Valuation Factor (Current Quarter) = 10% c. Capital Markets Factor (Current Quarter) = 55% d. Volatility Factor (Current Quarter) = Yes e. Volatility Factor (1 Quarter Ago) = No 2. In block 502, calculate the Simple Weight 210369-000033 - 23 - a. Simple Weight = (1 Quarter Ago) + Capital Markets Factor (Current Quarter) b. Simple Weight = 10% + 55% = 65% 3. In block 512, the Volatility Factor Current or 1 Quarter Ago = Yes 4. In block 524, check if the Valuation Factor for the current quarter or 1 quarter ago is not equal to 0 (in this case the valuation factor is not equal to zero for both periods mentioned) 5. In block 532, check that the weight 1 quarter ahead + change limit is less than the simple weight + max volatility signal overweight. a. Max Volatility Signal Overweight = 10% b. Weight 1 Quarter Ahead = 65% c. Change Limit = 5% d. Simple Weight = 65% e. 65% + 5% < 65% + 10% is TRUE 6. In block 542, check that the weight 1 quarter ahead + change limit is less than the max public overweight. a. Weight 1 Quarter ahead = 65% + change limit (5%) = 70% b. Max Overweight = 65% c. 70% < 65% is FALSE (i.e., in block 543, the weight 1 quarter ahead is greater than or equal to the Max Public Overweight = TRUE) 7. In block 553, the Weight 2 Quarters ahead is set at the Max Overweight a. Weight 2 Quarters ahead = 65% SCENARIO D This example outlines a scenario where the volatility factor signals YES and there is a valuation factor, and the weight 1 quarter ahead has already deviated from the simple weight by 5%. This scenario occurs after the actual weight has deviated from the simple weight due to the volatility factor and is about to reach the max volatility signal overweight (max deviation from simple weight) but is still below the max public overweight. 1. Start by calculating the Valuation Factor for 1 quarter ago & current quarter, the Capital Markets Factor for the current quarter, and the Volatility Factor for 1 210369-000033 - 24 - quarter ago & current quarter. D assumes the following calculation / algorithm results. a. Valuation Factor (1 Quarter Ago) = 5% b. Valuation Factor (Current Quarter) = 0% c. Capital Markets Factor (Current Quarter) = 45% d. Volatility Factor (Current Quarter) = No e. Volatility Factor (1 Quarter Ago) = Yes 2. In block 502, calculate the Simple Weight a. Simple Weight = Valuation Factor (1 Quarter Ago) + Capital Markets Factor (Current Quarter) b. Simple Weight = 5% + 45% = 50% 3. In block 512, the Volatility Factor Current or 1 Quarter Ago = Yes 4. In block 524, check if the Valuation Factor for the current quarter or 1 quarter ago is not equal to 0 (in this case the valuation factor is not equal to zero for both periods mentioned) 5. In block 532, check that the weight 1 quarter ahead + change limit is less than the simple weight + max volatility signal overweight a. Max Volatility Signal Overweight = 10% b. Weight 1 Quarter Ahead = 55% c. Change Limit = 5% d. Simple Weight = 50% e. 55% + 5% < 50% + 10% is FALSE 6. In block 534, check if the weight 1 quarter ahead + change limit is greater than or equal to the simple weight + max volatility signal overweight a. Simple weight + max volatility signal overweight = 50% + 10% = 60% b. Max Public Overweight = 65% c. 60%<65% is TRUE in block 544 7. In block 560, the Weight 2 Quarters ahead is set to the Simple Weight + Max Volatility Signal Overweight. a. Weight 2 quarters ahead = 50% + 10% = 60% SCENARIO E 210369-000033 - 25 - This example outlines a where the volatility factor signals YES and there is a valuation factor, and the weight 1 quarter ahead has already deviated from the simple weight by 5%. This scenario occurs after the actual weight has deviated from the simple weight due to the volatility factor and is about to reach the max volatility signal overweight (max deviation from simple weight) but is at the max public overweight. 1. Start by calculating the Valuation Factor for 1 quarter ago & current quarter, the Capital Markets Factor for the current quarter, and the Volatility Factor for 1 quarter ago & current quarter. a. Valuation Factor (1 Quarter Ago) = 10% b. Valuation Factor (Current Quarter) = 10% c. Capital Markets Factor (Current Quarter) = 45% d. Volatility Factor (Current Quarter) = No e. Volatility Factor (1 Quarter Ago) = Yes ( 2. Calculate the simple weight (this represents the weight to public / private two quarters into the future, ignoring the volatility factor and change limit) a. Simple Weight = Valuation Factor (1 Quarter Ago) + Capital Markets Factor (Current Quarter) b. Simple Weight = 10% + 45% = 55% 3. Volatility Factor Current or 1 Quarter Ago = Yes (Block 512 is true) 4. Check if the Valuation Factor for the current quarter or 1 quarter ago is not equal to 0 (in this case the valuation factor is not equal to zero for both periods mentioned) (Block 524 is true) 5. Check that the weight 1 quarter ahead + change limit is less than the simple weight + max volatility signal overweight a. Max Volatility Signal Overweight = 10% b. Weight 1 Quarter Ahead = 60% c. Change Limit = 5% d. Simple Weight = 55% e. 60% + 5% < 55% + 10% is FALSE (Block 532 is FALSE, go to Block 534) 6. Check that the Simple Weight + Max Volatility Signal Overweight is less than the Max Public Overweight 210369-000033 - 26 - a. Simple Weight + Max Signal Overweight = 55% + 10% = 65% b. Max Public Overweight = 65% c. 65% < 65% is FALSE (Block 544 is False, go do Block 544a) 7. Weight 2 Quarters ahead = Max Public Overweight a. Weight 2 quarters ahead is set to 65% in Block 561 SCENARIO F This example outlines a scenario where the volatility signal is NO and the capital markets and valuation factors have shifted simultaneously creating a quarter-over- quarter change in the simple weight that is greater than the change limit, but the weight a quarter ahead plus the change limit is less than the max public overweight. 1. Start by calculating the Valuation Factor for 1 quarter ago & current quarter, the Capital Markets Factor for the current quarter, and the Volatility Factor for 1 quarter ago & current quarter. Scenario E assumes the following calculation / algorithm results. a. Valuation Factor (1 Quarter Ago) = 5% b. Valuation Factor (Current Quarter) = 10% c. Capital Markets Factor (Current Quarter) = 50% d. Volatility Factor (Current Quarter) = No e. Volatility Factor (1 Quarter Ago) = No 2. In block 502, calculate the simple weight. a. Simple Weight = Valuation Factor (1 Quarter Ago) + Capital Markets Factor (Current Quarter) b. Simple Weight = 5% + 50% = 55% 3. In block 514, the Volatility Factor Current (0) or 1 Quarter Ago = No 4. In block 526, check if the absolute value of the simple weight minus the weight 1 quarter ahead is greater than the change limit (in this case it is greater than the change limit) a. Weight 1 quarter ahead = 45% b. Change Limit = 5% c. ABS(55% – 45%) > 5% is TRUE 210369-000033 - 27 - 5. In block 536, check if the simple minus the weight 1 quarter ahead is greater than 0 (in this case the simple weight which represents the potential weight 2 quarters ahead is greater than the weight 1 quarter ahead) (Block 536 is TRUE) 6. Check that the Weight 1 Quarter ahead + Change limit is less than the Max Public Overweight a. Weight 1 Quarter ahead + Change Limit = 45% + 5% = 50% b. Max Public Overweight = 65% c. 50% < 65% is TRUE, meaning that the statement in block 545 is TRUE). 7. In block 546, the Weight 2 quarters ahead is set to the weight 1 quarter ahead plus the change limit. a. Weight 2 quarters ahead = 45% + 5% = 50% b. Weight 2 quarters ahead = 65%. SCENARIO G This example outlines a scenario where the volatility signal is NO and the capital markets and valuation factors have shifted simultaneously creating a quarter-over- quarter change in the simple weight that is greater than the change limit, but the weight a quarter ahead plus the change limit is greater than or equal to the max public overweight. For purposes of illustration, the Max Public Overweight was adjusted to illustrate other potential configurations of the model. 1. Start by calculating the Valuation Factor for 1 quarter ago & current quarter, the Capital Markets Factor for the current quarter, and the Volatility Factor for 1 quarter ago & current quarter. a. Valuation Factor (1 Quarter Ago) = 10% b. Valuation Factor (Current Quarter) = 10% c. Capital Markets Factor (Current Quarter) = 55% d. Volatility Factor (Current Quarter) = No e. Volatility Factor (1 Quarter Ago) = No 2. In Block 502, calculate the simple weight (this represents the weight to public / private two quarters into the future, ignoring the volatility factor and change limit) 210369-000033 - 28 - a. Simple Weight = (1 Quarter Ago) + Capital Markets Factor (Current Quarter) b. Simple Weight = 10% + 55% = 65% 3. Volatility Factor Current or 1 Quarter Ago = No (Block 514 is true) 4. Check if the absolute value of the simple weight minus the weight 1 quarter ahead is less than or equal to the change limit (in this case it is greater than the change limit) a. Weight 1 quarter ahead = 55% b. Change Limit = 5% c. ABS(65% – 55%) <= 5% is FALSE (Block 526 is True) 5. Check if the simple weight minus the weight 1 quarter ahead is greater than 0 (in this case the simple weight which represents the potential weight 2 quarters ahead is greater than the weight 1 quarter ahead) (Block 536 is TRUE) 6. Check that the Weight 1 Quarter ahead + Change limit is less than the Max Public Overweight a. Weight 1 Quarter ahead + Change Limit = 55% + 5% = 60% b. Max Public Overweight = 60% c. 60% < 60% is FALSE (Block 545 is FALSE, but Block 545a is TRUE) 7. Weight 2 quarters ahead = Max Public Overweight a. Weight 2 quarters ahead is set to 60%in Block 562 SCENARIO H This example outlines a scenario where the volatility signal is NO and the capital markets and valuation factors have shifted simultaneously creating a quarter-over- quarter change in the simple weight that is greater than the change limit and the weight 1 quarter ahead minus the change limit is greater than the Max Public Underweight. 1. Start by calculating the Valuation Factor for 1 quarter ago & current quarter, the Capital Markets Factor for the current quarter, and the Volatility Factor for 1 quarter ago & current quarter. Scenario F assumes the following calculation / algorithm results. a. Valuation Factor (1 Quarter Ago) = 5% b. Valuation Factor (Current Quarter) = 0% 210369-000033 - 29 - c. Capital Markets Factor Quarter) = 50% d. Volatility Factor (Current Quarter) = No e. Volatility Factor (1 Quarter Ago) = No 2. In block 502, calculate the simple weight (this represents the weight to public / private two quarters into the future, ignoring the volatility factor and change limit) a. Simple Weight = Valuation Factor (1 Quarter Ago) + Capital Markets Factor (Current Quarter) b. Simple Weight = 5% + 50% = 55% 3. In block 514, Volatility Factor Current or 1 Quarter Ago = No 4. In block 526, check if the absolute value of the simple weight minus the weight 1 quarter into the future is greater than the change limit (in this case it is greater than the change limit) a. Weight 1 quarter ahead = 65% b. Change Limit = 5% c. ABS(65% – 55%) > 5% is TRUE 5. In block 536, check if the simple weight minus the weight 1 quarter ahead is greater than 0 (in this case the simple weight which represents the potential weight 2 quarters ahead is less than the weight 1 quarter ahead) (Block 538 is TRUE) 6. Check if the Weight 1 quarter ahead – Change Limit is greater than the Max Public Underweight a. Weight 1 quarter ahead – Change Limit = 65%-5% = 60% b. Max Public Underweight = 35% c. 60% > 35% is TRUE, meaning that the statement in block 547 is TRUE. 7. In block 548, set the weight 2 quarters ahead = weight 1 quarter ahead minus the change limit a. Weight 2 quarters ahead = 65% - 5% = 60%, per Block 548 (Scenario H). SCENARIO I This example outlines a scenario where the volatility signal is NO and the capital markets and valuation factors have shifted simultaneously creating a quarter-over- quarter change in the simple weight that is greater than the change limit, but the weight 1 210369-000033 - 30 - quarter ahead minus the change limit is or equal to the Max Public Underweight. For purposes of illustration, the Max Public Underweight was adjusted to illustrate other potential configurations of the model. 1. Start by calculating the Valuation Factor for 1 quarter ago & current quarter, the Capital Markets Factor for the current quarter, and the Volatility Factor for 1 quarter ago & current quarter. a. Valuation Factor (1 Quarter Ago) = -10% b. Valuation Factor (Current Quarter) = -10% c. Capital Markets Factor (Current Quarter) = 45% d. Volatility Factor (Current Quarter) = No e. Volatility Factor (1 Quarter Ago) = No 2. Calculate the simple weight (this represents the weight to public / private two quarters into the future, ignoring the volatility factor and change limit) a. Simple Weight = Valuation Factor (1 Quarter Ago) + Capital Markets Factor (Current Quarter) b. Simple Weight = -10% + 45% = 35% 3. Volatility Factor Current or 1 Quarter Ago = No (Block 514 is TRUE) 4. Check if the absolute value of the simple weight minus the weight 1 quarter into the future is less than or equal to the change limit (in this case it is greater than the change limit) a. Weight 1 quarter ahead = 45% b. Change Limit = 5% c. ABS(35% – 45%) <= 5% is FALSE (Block 526 is TRUE) 5. Check if the simple weight minus the weight 1 quarter ahead is greater than 0 (in this case the simple weight which represents the potential weight 2 quarters ahead is less than the weight 1 quarter ahead) (Block 538 is TRUE) 6. Check if the Weight 1 quarter ahead – Change Limit is greater than the Max Public Underweight (Block 547a is TRUE) a. Weight 1 quarter ahead – Change Limit = 45%-5% = 40% b. Max Public Underweight = 40% c. 40% > 40% is FALSE 210369-000033 - 31 - 7. Weight 2 quarters ahead = Max Underweight a. Weight 2 quarters ahead = 40%, per Block 563. SCENARIO J This example outlines a scenario where the volatility signal is NO and the change from the weight 1 quarter ahead to the simple weight (which represents the potential weight 2 quarters ahead) is less than or equal to the change limit. This is the normal state of the model. 1. Start by calculating the Valuation Factor for 1 quarter ago & current quarter, the Capital Markets Factor for the current quarter, and the Volatility Factor for 1 quarter ago & current quarter. Scenario G assumes the following calculation / algorithm results. a. Valuation Factor (1 Quarter Ago) = 10% b. Valuation Factor (Current Quarter) = 10% c. Capital Markets Factor (Current Quarter) = 45% d. Volatility Factor (Current Quarter) = No e. Volatility Factor (1 Quarter Ago) = No 2. In block 502, calculate the simple weight. a. Simple Weight = Valuation Factor (1 Quarter Ago) + Capital Markets Factor (Current Quarter) b. Simple Weight = 10% + 45% = 55% 3. In block 514, the Volatility Factor Current or 1 Quarter Ago = No 4. In block 526, check if the absolute value of the simple weight minus the weight 1 quarter into the future is greater than the change limit (in this case it is not greater than, but rather equal to the change limit, meaning that the statement in block 526 is FALSE and the statement in block 528 is TRUE) a. Weight 1 quarter into the future = 55% b. Change Limit = 5% c. ABS(55% – 55%) > 5% is FALSE (<= 5% is TRUE) 5. Check if the simple weight is less than the Max Public Overweight and greater than the Max Public Underweight a. Simple Weight = 55% 210369-000033 - 32 - b. Max Public Overweight = c. Max Public Underweight = 35% d. 35% < 55% < 65% is TRUE (Block 539 is TRUE) 6. In block, 539, set the Weight 2 quarters ahead = Simple Weight a. Weight 2 quarters ahead = 55%, per the block 564. SCENARIO K This example outlines a scenario where the volatility signal is NO and the change from the weight 1 quarter ahead to the simple weight (which represents the potential weight 2 quarters ahead) is less than or equal to the change limit, but the simple weight is greater than or equal to the max public overweight. For illustration purposes, the Max Public Underweight was adjusted to illustrate other potential configurations of the model. 1. Start by calculating the Valuation Factor for 1 quarter ago & current quarter, the Capital Markets Factor for the current quarter, and the Volatility Factor for 1 quarter ago & current quarter. a. Valuation Factor (1 Quarter Ago) = 10% b. Valuation Factor (Current Quarter) = 10% c. Capital Markets Factor (Current Quarter) = 50% d. Volatility Factor (Current Quarter) = No e. Volatility Factor (1 Quarter Ago) = No 2. Calculate the simple weight (this represents the weight to public / private two quarters into the future, ignoring the volatility factor and change limit) a. Simple Weight = Valuation Factor (1 Quarter Ago) + Capital Markets Factor (Current Quarter) b. Simple Weight = 10% + 50% = 55% c. Volatility Factor Current or 1 Quarter Ago = No (Block 514 is TRUE) 3. Check if the absolute value of the simple weight minus the weight 1 quarter into the future is greater than the change limit (in this case it is not greater than the change limit) a. Weight 1 quarter into the future = 60% b. Change Limit = 5% 210369-000033 - 33 - c. ABS(60% – 60%) <= 5% (Block 528 is TRUE) 4. Check if the simple weight is greater than or equal to the Max Public Overweight a. Simple Weight = 60% b. Max Public Overweight = 60% c. 60% >= 60% is TRUE (Block 539a is TRUE) 5. Weight 2 quarters ahead = Max Public Overweight Weight 2 quarters ahead = 60%, per Block 565. SCENARIO L This example outlines a scenario where the volatility signal is NO and the change from the weight 1 quarter ahead to the simple weight (which represents the potential weight 2 quarters ahead) is less than or equal to the change limit, but the simple weight is less than or equal to the Max Public Underweight. For illustration purposes, the Max Public Underweight was adjusted to illustrate other potential configurations of the model. 1. Start by calculating the Valuation Factor for 1 quarter ago & current quarter, the Capital Markets Factor for the current quarter, and the Volatility Factor for 1 quarter ago & current quarter. a. Valuation Factor (1 Quarter Ago) = -10% b. Valuation Factor (Current Quarter) = -10% c. Capital Markets Factor (Current Quarter) = 50% d. Volatility Factor (Current Quarter) = No e. Volatility Factor (1 Quarter Ago) = No 2. Calculate the simple weight (this represents the weight to public / private two quarters into the future, ignoring the volatility factor and change limit) a. Simple Weight = Valuation Factor (1 Quarter Ago) + Capital Markets Factor (Current Quarter) b. Simple Weight = -10% + 50% = 40% 3. Volatility Factor Current or 1 Quarter Ago = No (Block 514 is TRUE) 4. Check if the absolute value of the simple weight minus the weight 1 quarter into the future is greater than the change limit (in this case it is not greater than the change limit) 210369-000033 - 34 - a. Weight 1 quarter into the = 40% b. Change Limit = 5% c. ABS(40% – 40%) <= 5% is TRUE (Block 528 is TRUE) 5. Check if the simple weight is less than or equal to the Max Public Underweight a. Simple Weight = 40% b. Max Public Underweight = 40% c. 40% <= 40% is TRUE (Block 539b is TRUE) 6. Weight 2 quarters ahead = Max Public Underweight a. Weight 2 quarters ahead = 40%, per Block 566. It should be understood that the decision tree has been represented schematically in FIG.5 and referenced herein in one embodiment, but that the logic represented therein may be expressed in different ways without departing from the functionality as described herein. Although the invention is illustrated and described herein with reference to specific embodiments, the invention is not intended to be limited to the details shown. Rather, various modifications may be made in the details within the scope and range of equivalents of the claims and without departing from the invention.

Claims

210369-000033 - 35 - What is Claimed:

1. A computer-implemented method for providing an investment direction for operating an investment fund comprised of investments in a public real estate market and a private real estate market: creating a computer model, comprising machine-readable instructions stored in computer memory for modeling the investment fund; inputting into the computer model asset data corresponding to information characterizing underlying assets held by one or more public real estate index funds comprising the investments in the public real estate market and characterizing underlying assets held by one or more private real estate index funds comprising the investments in the private real estate market; inputting into the computer model economic market data relevant to the public real estate market and the private real estate market; inputting into the model a current public weight percentage (B%) corresponding to a weighted percentage of the investment fund comprising the investments in the public real estate market and a current private weight percentage of assets (V% = 1-B%) corresponding to a weighted percentage of the investment fund comprising the investments in the private real estate market; periodically updating the economic market data and the asset data to reflect changes over time; configuring the model to calculate a plurality of indicators and to execute a plurality of algorithms based upon the plurality of indicators, wherein the plurality of calculated indicators includes: a valuation factor defining an incremental public market exposure percentage shift calculated using a valuation factor algorithm based upon a z- score for a current value for a cap rate spread (CRS) between public and private real estate as compared to an average CRS; a capital markets factor calculated based upon a z-score of a capital markets yield curve indicator;210369-000033 - 36 - a volatility factor signal indicating whether to shift the weighted percentages based upon a month-over-month (MoM) price change in the public real estate market above a predetermined threshold; executing a weighting algorithm comprising the valuation factor, the capital markets factor, and the volatility factor as inputs, and providing an output of the weighting algorithm embodying an investment direction comprising a future weighted percentage target for B% to be achieved after a predetermined period of time.

2. The method of claim 1, wherein the capital markets yield curve indicator comprises a treasury spread, comprising a difference in yield between a first treasury bond duration and a second treasury bond duration, wherein the first duration is longer than the second duration.

3. The method of claim 1 or claim 2, further comprising executing redemptions and purchases in accordance with the predicted future weighting direction so as to achieve the future weighted percentage within the predetermined period of time.

4. The method of any one of claims 1 - 3, wherein the output of the model comprises a human readable output.

5. The method of claim 3, wherein the output of the model is transmitted to a computer processor configured to execute the redemptions and purchases.

6. The method of any one of the foregoing claims, wherein the predetermined period of time comprises two quarters of a year.

7. The method of any one of the foregoing claims, wherein the valuation factor is computed by a valuation factor algorithm that considers whether the z- score is less than or equal to a negative threshold, greater than the negative threshold or less than a positive threshold, or greater than or equal to the positive threshold number of standard deviations, wherein the negative and positive threshold have the same absolute value.

8. The method of claim 7, wherein valuation factor algorithm further considers the valuation factor of a previous quarter relative to a valuation factor change limit, and the valuation factor output comprises the valuation factor of the previous quarter,210369-000033 - 37 - the valuation factor of the previous a change limit, or the valuation factor of the previous quarter plus the valuation factor change limit.

9. The method of claims 7 or 8 wherein a maximum valuation factor comprises twice the valuation factor change limit.

10. The method of any one of claims 7-9, wherein the valuation factor change limit is 5%.

11. The method of any one of the foregoing claims, wherein the capital markets factor is computed by a capital markets factor algorithm that considers whether the z-score of the treasury spread is less than or equal to a negative threshold, greater than a negative threshold or less than a positive threshold, or greater than or equal to the positive threshold number of standard deviations, wherein the negative and positive threshold have the same absolute value.

12. The method of claim 11, wherein capital markets factor algorithm further considers if the capital markets factor of a previous quarter is greater than, equal to, or less than an initial capital markets factor value, and the capital markets factor output comprises the capital markets factor of the previous quarter, the capital markets factor of the previous quarter minus a capital markets change limit, or the capital markets factor of the previous quarter plus the capital markets change limit.

13. The method of claim 11 or claim 12, wherein the capital markets initial value is in a range of 30-70% with a change limit in a range of 2.5%- 10%.

14. The method of claim 1, wherein the predetermined threshold for the volatility factor is in a range of 0.1-0.

25.

15. The method of claim 14, wherein the volatility signal at a point in time is dependent upon the volatility factor of a current time period in which the point of time is defined and in which one of a plurality of subperiods of time the point of time is defined.

16. The method of claim 15, wherein the current time period is a quarter, and the plurality of subperiods comprise a first month, a second month, and a third month within the quarter.

17. The method of any one of the foregoing claims, wherein the future weighted percentage target for B% is between a maximum public overweight and a minimum public overweight.210369-000033 - 38 - 18. The method of wherein the maximum public overweight is in a range of 90-37.5% and the minimum public overweight is in a range of 10 to 62.5 %.

19. The method of any one of the foregoing claims, wherein the cap rate spread (CRS) between public and private real estate is computed on a normalized sector-weighted basis.

20. The method of claim 19, wherein the normalized sector-weighted basis uses sector weightings from the investments in the private real estate market.

21. The method of claim 19, wherein the sector-weighted basis includes weightings from sectors selected from the group consisting of: apartment, office, industrial, and retail.

22. The method of any one of the foregoing claims, wherein the investments in the private real estate market comprise an Index Fund that tracks the NFI- ODCE Index.

23. The method of any one of the foregoing claims, wherein the investments in the public real estate market comprise one or more REITs or an Index Fund of REITs.

24. Non-transitory computer memory media programmed with machine- readable instructions for causing a computer processor to perform the method steps of any one of the foregoing claims.

25. A computer system comprising at least one processor in communication with computer memory, the at least one processor configured to read machine-readable instructions stored in the computer memory, the machine-readable instructions configured to cause the processor to perform the method steps of any one of claims 1-23.

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