Reasons Why Retail Investors Ought Not Copy the Endowment Model —–

The legendary David Swensen took over Yale University’s endowment in 1985 when it was worth $1.5 billion and grew it to $31 billion. He revolutionized endowment investing and recently passed at the age of 67. Is there a place for the retail implementation of an endowment investing approach? 

The demonstrated outperformance of some endowments, especially Yale, naturally begs the question of its applicability in a retail setting. Although some aspects of endowment style investing are transferable, there are factors unique to retail investors that we need to be aware of while considering implementations of this approach. A financial endowment is a transfer of money or property donated to an institution, usually with the stipulation that it be invested, and the principal remain intact for a defined time period. Endowments have limited liquidity needs, significantly long investment horizons and the ability to pursue less liquid asset classes more aggressively. In contrast, individuals have higher liquidity preferences and a finite investment horizon that is closely linked to one’s particular unique circumstances.

The goal should not be to simply copy the leading university endowments for these differ from individual investors in many important respects. Here is why.

Liquidity

Liquidity needs for traditional endowments are vastly different than for individual investors. Endowments and the institutions they benefit are managed on the basis that they will exist in perpetuity. As a result, liquidity is not a major priority as the endowment is tasked to provide enough inflation-adjusted annual income to support operations. These distributions are determined by very specific spending policies. Because these limited spending policies dampen the consequences of portfolio volatility, portfolio managers gain the freedom to accept greater investment risk with the expectation of achieving higher returns without exposing the institution to unreasonably large probabilities of significant budgetary shortfalls. Individuals do not operate in this manner. They have a limited life span and spending needs can be highly uncertain, thereby resulting in very different liquidity preferences. In a retail application, advisors tend to address individual liquidity needs through four, and perhaps more, mechanisms:

a) An increase in allocation to investments in liquid absolute-return alternative mutual fund and hedge fund like vehicles;

b) Use of a tender process to control and dampen the volatility associated with uncontrolled redemption pressures;

c) Letters of credit to meet temporary shortfalls in liquidity in the case of private bank sponsors; and

d) Utilization of subscriptions to offset redemptions.

These mechanisms are not needed in a traditional endowment, but are essential components in a retail setting.

Asset Allocation

Traditional endowment portfolio fiduciaries place asset allocation at the heart of the investment process, emphasizing policy portfolio decisions over market timing and security selection activities. Satisfaction of long-term institutional goals depends in large part on the underpinnings of successful asset allocation: an equity bias to provide high returns, and diversification to produce an acceptable level of risk. In a retail setting, however, individual client needs necessitate the re-tooling of the purist endowment model to meet liquidity preferences and finite time horizons.

Pricing & Valuation

Another major issue in a retail platform is pricing. Endowment trustees do not manage their portfolios on a month-to-month basis. As such, the reliability of an NAV in any given month is not of critical importance. However, in a retail solution, the need to produce reliable NAVs is crucial if one is to drive a successful client experience. Even when a reporting procedure is decided, fund sponsors are burdened with the challenge of striking a reliable NAV each month. Retail investors and their advisors would rightfully ask questions such as “are they averaging up or averaging down? How will the NAV be adjusted to reflect this and at what intervals?” These are very practical questions that one must be prepared to answer. Unreliable, pro-forma NAVs undermine the client service experience so essential in the retail segment.

Valuations of portfolio assets also present another hurdle. The combination of liquid and illiquid asset classes in the traditional endowment make accurately valuing such assets very difficult and costly. Traditional endowments have vastly different investments across an unlimited time horizon with different risk and return characteristics. Trustees are well aware of this fact as policy portfolios are constructed to take this into account. In contrast current and precise valuation is of particular importance when the retail investor has to undergo tax and/or estate planning – issues endowment trustees do not have to grapple with.

Transparency

A corollary to the pricing and valuation issue is investor transparency. Because of the highly illiquid and proprietary nature of endowment portfolio investments, it is exceedingly difficult to ascertain precise allocations. Underlying manager secrecy, in the retail world, can create information asymmetry between investment advisors and their clients – something that is frowned upon. 

Taxation and Tax Reporting

Endowments do not pay income tax. Taxation and tax reporting are concerns that retail investment advisors and their investors are not only tasked to do, but obligated to perform under state and federal laws. Folks invested in alternatives already accept a delayed K-1 due to private equity investments. The addition of real assets, such as land and timber, oil and gas, would delay this mandatory reporting even more which has the possibility of eroding valuable client relationships. Of particular importance in regards to taxation is the generation and subsequent reporting of income sourced via investments in multiple states. A high level of transparency is needed, especially in regards to real estate and private equity investments, to identify income earned for nonresident partners. Investors need to know two seemingly basic facts: a) do they need to file a composite return? and b) are multiple state filings required? This issue is not a significant concern to educational endowments due to their tax exempt status, but can have major operational implications for investment advisors that have to determine this in the most timely and efficient way possible. 

Size

Endowments, given their large size can negotiate special arrangements with investment managers. Retail investors, unless they are part of aggregated pools in feeder vehicles cannot usually have access as well as strike preferential agreements with product sponsors.

Longer lives

In theory, universities can live forever and therefore have a much longer investment horizon than an individual. Harvard, for instance, has been around since shortly after the Pilgrims landed on Plymouth Rock. Because of that longer view, elite endowments typically depart from the traditional liquid stock and bond mix by allocating a significant portion of their assets to less liquid, often non-publicly-traded alternative investments such as venture capital, private real estate, managed futures, natural resource partnerships as well as oil and gas.  

Conclusion

This piece explored the applicability of an endowment style approach to investors in the retail investing space, discussed specific issues unique to retail and suggested how multi-asset class model portfolios may be constructed. Understanding the differences between endowments and individual investors allows discerning advisors to determine the tools, vehicles and techniques that can successfully translate the success of endowment investing down to the household level – thereby better addressing retail investors’ special investing needs. In general, for the reasons outlined earlier the endowment approach is not easily transportable to retail investing. 

Author: Sameer Jain

Lightly excepted from a previous article by the author “The Household Endowment Model – Adopting Lessons Learned from the Nation’s Top Education Endowments”

Model Portfolios. One Size Fits All. Bad Bad Idea During Coronacrisis.

The notion of putting retail investors in cookie-cutter mass-produced standardized buckets of allocations, referred to as model portfolios, is remnant of antiquated ‘90s thinking. In 2020, during the coronacrisis it is akin to paying a doctor expensive (very typically over 1% of assets) fees for an over-the-counter pain medicine prescription.

Bespoke allocation goes far beyond conventional passive risk and return trade-off found in model portfolios. It personalizes for unique investor preferences including accommodating a desire or aversion to alternative investments, expressing preferences for desired levels of illiquidity, considering different investing horizons, incorporating time varying risk preferences as well imposing constraints on specific asset classes to reflect unique investor circumstances.

Departing from model portfolios has potential to foster greater transparency. Moreover, it raises the quality of discourse an advisor has with her client. It encourages a conversation not on historical, but around forward looking risk- return expectations. It also brings nuance in investment decision making, conspicuous by absence in model portfolios.

Rather than persist with the historical notion of putting clients in coarse model portfolios, a far better approach is to begin by analyzing the forward-looking statistical properties and expected behavior of a client’s existing portfolio. This helps to arrive at the best combination of asset sub-types that improve existing allocations on a variety of chosen metrics.

ActiveAllocator.com lets you create bespoke portfolios in 10 clicks, in 10 minutes and at 1/10th cost.

ActiveAllocator is a digital asset allocation platform with technology-enabled customized advice capabilities. It is the world’s first portal that seamlessly integrates traditional, illiquid and alternative investments within portfolios. It helps investors analyze existing allocations, discover inefficiencies and create bespoke portfolios in minutes.

 

Transcend Cookie Cutter ‘Model Portfolios’ in 10 clicks, 10 minutes, 1/10th Cost

ActiveAllocator helps you go beyond traditional model portfolios by utilizing disruptive technology driven personalization. Create directional, semi-directional and non-directional market exposures in minutes.

  • Aggregate your holdings in seconds across your banks, financial advisors and custodians. Arrive at your true economic exposure. Go beyond financial products, and funds and securities you own. Understand why you may be sub optimally allocated.

 

  • Then, in seconds, optimize your portfolio on by linking your brokerage accounts and send order messages to your broker directly from ActiveAllocator’s platform. Once done, import real-time portfolio data from your brokerage firm, and see the most current picture of your portfolio’s – not historical but rather,  forward facing characteristics.

 

  • Compare your portfolio with others’. Including those, supposedly bespoke, being created by private banks and wire-houses at huge fees with attendant product driven conflicts of interest.

 

  • Increase your asset class universe to over 50 sub asset-classes including alternative investments, automate implementation, trading and periodic re-balancing.

 

  • Express your own investment views while making strategic allocation decisions.

 

Put Allocation Horse Before Product Cart

Just another example of continuous innovation at ActiveAllocator.com

ActiveAllocator’s proprietary technology searches, recognizes, classifies and instantly maps more than 4 million traded financial instruments to 50 granular asset sub-classes. By doing so, we shift focus from financial products to asset classes that drive portfolio performance. If you believe that a given financial product should belong in a different asset class, we provide the ability to change the mapping to your liking.

At the end of the mapping process, you have a comprehensive picture of your investments across multiple asset sub-classes.

 

 

Advisor Fees and Inefficient Asset Allocation to Destroy $400 bn in 2018

We estimate that retail investors lose around $400 billion annually in advisory fees and inefficient model portfolios. This value destruction is both explicit in typical 1% or higher fees charged and implicit in  further 0.5% or more model portfolio asset allocation inefficiency. This is in addition to other contracting frictions, product commissions and costs.

At ActiveAllocator we are driven by an authentic mission. To increase expected returns for millions of investors by eliminating the loss that’s built into the way the retail financial advice and investment management industry is currently structured. To remove the dead-weight costs of $130 billion from strategic asset allocation inefficiency and to drastically reduce the $260-$300 billion in advisory fees. One portfolio at a time, across 33 million individual portfolios.

 

Compare Your Own Mid-Year Capital Market Assumptions with Wall Street

Optimization for strategic asset allocation involves the forecasts of  at least three types of information:

  • Expected returns of different asset classes
  • Expected risk (volatility) of different asset classes
  • Correlations of different asset classes

We recommend that investors avoid recency bias. Since the expected returns of all assets classes vary over time, we estimate expected return of an asset class by combining the following information:

  • Long-term historical average return over multiple economic cycles
  • Key drivers of historical returns and market forecasts of future performance of such drivers
  • Consensus estimate of reputable wealth management companies

Investors may be inclined to take the long-term average return of an asset class as the expected future return. Such an approach likely will not work as the market environment mid 2017 is substantially different from the average of the past decades. Instead, historical returns give us information on the range of the possible returns. More importantly, historical returns help investors understand the key drivers that have determined realized historical long-term returns.

The following equation shows one way to decompose S&P returns:

  • S&P return = equity risk premium + long-term bond return + noise

The first two terms explain the expected return:

Expected S&P return = equity risk premium + long-term bond return

= equity risk premium + short-term interest rate + term premium

= equity risk premium + (inflation + real short-term interest rate) + term premium

The last term explains the volatility in S&P returns. It is a random variable centered around zero.

We expect the inflation rate to stay at low level in the future as it did in the past decade. The real short-term interest rate depends on the Federal Reserve’s policy. In recent years, Federal Reserve has kept short-term interest to be below inflation rate. We do not expect dramatic policy change. The term premium depends on investors’ long-term view on economic growth. Market consensus is that the U.S. economy will grow at an average of ~2% in the next decade. All these factors indicate long-term bond returns are likely to be below historical average. As a result, return of S&P is likely to be below historical average as well. Consensus view: Estimates from wealth management firms suggest an expected return of +6%.

You can now compare and contrast your own views across +50 asset sub-classes with others.

 

 

 

 

Conventional Firms May Destroy +30% of Retail Investor Returns Annually

In a low returns environment, private banks and conventional financial advice firms continue to charge 1% to 2% in fees, irrespective of portfolio performance. Common sense suggests that the lower the costs are for investors, the higher their share of an investment’s returns will be. In addition, what remains invisible is the implicit fees on returns caused by inefficient model portfolios and poor asset allocation decisions. This further detracts another 0.5% annually from investor returns, which investors don’t see.

A +1.5% cost over a typical 5% annualized return suddenly becomes a meaningful number. It suggests a +30% value destruction for the price of having a ‘personalized’ relationship with a friendly financial advisor.

Probably much too high a price to pay?

 

 

How Inefficient is Your Portfolio?

Here is how you figure out.

  • Aggregate your investment accounts.

We aggregate your held away assets by linking your investment accounts. A holistic view of your holdings is the place to begin to discover strategic asset allocation inefficiencies.

  • Discover your economic and market risks.

Our proprietary technology searches, recognizes, classifies and instantly maps more than four million traded financial instruments to over fifty asset sub-classes. This helps you cut through funds and securities and see the world in terms of asset classes.

  • Compare your market views with others.

We monitor research from wirehouses, investment banks, consulting firms to help you arrive at consensus long term capital market assumptions. This becomes a valuable starting point for you to validate and express your own market beliefs.

  • Express your investing preferences.

We help you impose your constraints on specific asset type exposure, aversion or preference for illiquidity and alternative investments, your investing horizon, time varying risk preferences and other choices. This creates personalization.

  • Analyze and optimize your portfolio.

We highlight strategic asset allocation inefficiencies to enable comparison between recommended choices with your current allocation. This provides detached objective portfolio analysis.

  • Implement your portfolio.

Our proprietary order management system securely routes trade orders to your broker to execute. We further provide real-time portfolio data from your brokerage firm. This provides the most current picture of your portfolio’s forward-facing characteristics.

Constructing Bespoke Allocations

It is our belief that in the digital age individual personalization is going to be a key weapon in the battle against irrelevance and disintermediation for financial advisors.

We provide, for the first time ever, a way to utilize disruptive technology driven personalization and mass-customization. Our proprietary Strategic Asset Allocation framework and technologies allow one to aggregate held away assets and diagnose existing portfolio holding. It maps fund products and securities to precise granular asset sub-classes, offers consensus capital market assumptions as a useful starting point, personalizes investor preferences, demonstrates inefficiency in portfolios, optimizes and allows for multi broker securities execution.

All in under 10 minutes and within 10 mouse clicks!

Consolidation and Aggregation

Our first step is to arrive at a complete picture of securities, fund holdings and other finances held in a client portfolio. With permission, we securely retrieve such data from thousands of financial institutions and brokerages on behalf of clients and their financial advisors.  We reduce repetitive data collection and data entry and provide our clients with a simple, interactive data-capturing experience.

Mapping  Financial Products to Asset Sub-classes

We, in seconds, analyze the forward-looking statistical properties and expected behavior of a client’s existing portfolio. This done, we recommend the best combination of asset subtypes that improves it on a variety of chosen metrics. Our, to be patented, proprietary methodology and scalable technology searches, recognizes, classifies and instantly maps more than four million traded financial instruments to over fifty asset sub-classes to improve strategic asset allocation and portfolio construction. Within equities ActiveAllocator scrutinizes and maps nearly all global stocks, depositary receipts, certificates, ETFs, mutual funds, investment trusts, preference shares, rights, royalty trusts and other equity-linked products. This universe is comprised of more than two million equity securities including, 665,000 stocks, 163,000 exchange traded products, 51,000 closed end funds, 31,000 fund of funds, 18,000 ADRs, 7,600 Unit Investment Trusts, 6,500 preferred stocks, as well as 1,600 private equity and 10,000 hedge funds. Within fixed income, ActiveAllocator’s technology encompasses over one million U.S. government and agency bonds, collateralized loan obligations, collateralized mortgage obligations and other types of commercial mortgage backed securities and structured products. Within money market instruments, our system recognizes more than 42,000 instruments across fifty categories of bankers’ acceptance, bills of exchange, call loans, certificates of deposit, commercial paper, time deposits, discount notes and monetary bills. Within municipal securities, we distinguish between 1.1 million instruments across original issue discount munis, fixed, adjustable, tax credit, floating, zero coupon, intermediate appreciation and consumer price index linked products, amongst others.

Capital Markets Assumptions

Each wealth management firm, each wire house, often each broker-dealer periodically arrives at their own future view of asset class expected risk and return. Sometimes clients too have strong viewpoints that they may want to discuss. Yet financial advisors have no easy way to test such comparative views within the specific context of their particular client’s portfolio. We allow advisors to do this this in minutes; our portal helps advisors quickly simulate such scenarios and allow them to quantify revision in views, triggering valuable dialog. We constantly monitor research from wirehouses, investment banks, consulting firms to arrive at consensus long term capital market assumptions such as  expected risk, return and correlation within asset classes. This becomes a useful starting point for an asset allocator or an investment committee to accept or over ride generally accepted market views. In addition to traditional liquid assets we also generate such assumptions for illiquid assets such as private equity, real estate and hedge funds. These serve as inputs into allocation optimization.

Preferences

We go far beyond conventional risk and return tradeoffs, whilst personalizing for unique investor preferences including allowing for or aversion to alternatives or illiquidity, accommodating different investing horizons, time varying risk preferences as well imposing constraints on specific asset type exposure. We integrate passive and active, liquid & illiquid, traditional and alternative investments analysis personalized to particular investor preferences, constraints and situations. For example, each investor can override consensus expected future risks and returns in any asset class and generate personalized, forward looking portfolios.

Optimization

Our new approach is ahead of that built around Modern Portfolio Theory. We allocate simultaneously across multidimensional return sources including alpha (skills), beta (marketexposure accessible inexpensively), downside risk (extreme but rare market movements) and illiquidity (whose time premiums can be purposively unlocked). We analyze the statistical properties of existing portfolios and improve strategic asset allocation by finding the best combinations of liquid and illiquid asset classes to improve existing portfolios. We enable strategic asset allocation across over 50 asset subclasses. We integrate passive and active, liquid & illiquid, traditional and alternative investments analysis personalized to particular investor preferences, constraints and situations. We allocate to non-traded assets. We account for non-tradability, illiquidity premium as well as marked to market risk. We also allocate to actively managed structures while a) appropriately calibrating returns; b) accounting for factor exposures and their implications for returns in the future; c) removing survivorship and selection bias in historical returns; d) appropriately estimating risk including skewness, kurtosis gleaned from historic returns; e) incorporating pricing distortions, serial correlation and the impact on risk; f) managing strategy drift and unstable histories; and g) optimizing downside risk.

Trade Execution

To implement  the recommended portfolio and associated changes in security holdings we utilize a proprietary order management system which securely routes trade orders to brokers. This enables investors to optimize their existing portfolios on ActiveAllocator by linking their brokerage account and sending order messages to their broker directly from ActiveAllocator’s platform. We further provide real-time portfolio data from the user’s brokerage firm, which is imported into ActiveAllocator to provide the most current picture of their portfolio’s forward facing characteristics.

 

 

Instant Multi-Asset Portfolio Diagnosis

ActiveAllocator’s proprietary technology now enables multi-asset portfolio diagnosis in less than three minutes.

New proprietary methodology and scalable technology searches, recognizes, classifies and instantly maps more than four million financial instruments to fifty asset sub-classes to improve strategic asset allocation and portfolio construction.

The movement to multi-asset investing is a dominant trend. This allows investors to quickly analyze and invest their capital in the full panoply of assets that exist today: public securities, private securities, commodities, real estate and other hard assets, loans, leases, insurance and other types of contingent claims and intellectual property.

Traditionally, each of these classes of assets and fund products have been the province of a different manager at a distinct shop. A firm either ran a hedge fund that held predominantly public securities, a private equity fund that acquired control or strategic positions in businesses, a commodity pool that traded commodities futures, or a real estate fund that invested in real property. Often, clients own their assets in different firms and have no way of knowing what their expected portfolio characteristics are likely to be. Now, they can.

Everything changes with ActiveAllocator.com