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. 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.


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?



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.


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.


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


Configure Bespoke Portfolios in Minutes. Model Portfolios are Passé.


custom–made (also bespoken), customcustomizedcustom-tailoredmade-to-ordertailoredtailor-made

Related Words


Every investor has preferences such as tolerance for risk, investment horizon, liquidity requirements, aspirations for a targeted return, choice of alternative assets as well as levels of annual portfolio turnover for tax planning purposes amongst others. A bespoke asset allocation approach takes these into account. ActiveAllocator allows for:

Selecting portfolio risk target range – whether one has a low, medium or high risk tolerance or one can specify a clear number.

Specifying maximum levels of illiquidity – the level of illiquidity a client is comfortable with.

Setting limits on alternative investments and types – some investors believe in passive management while many others see value in actively managed Alternative Investments as well as actively managed funds are valuable complements to traditional stock and bond holdings for affluent investors. However, including them in portfolios is extremely difficult. One reason is their heterogeneity and complexity. Another is that Modern Portfolio Theory or MPT, does not work in holistic asset allocation. But simply excluding them in model portfolios curtails investor choice and their potential benefits.

Providing for maximum turnover – some prefer to own allocations that remain largely static while others are comfortable with higher levels of turnover.

Targeting returns – clients often have a general expectation of expected target return. Most clients see historical realized returns but wish they had a way to automatically calculate the target return of their existing holdings as a useful starting point.

Setting an investment horizon – clients have different investing horizons which can heavily influence choices in both asset allocation and portfolio construction.

Asset class exposure constraints – the maximum or a minimum amount of exposure to any asset class.


All Asset Allocation is Not Created Equal

We hold these truths to be self-evident: that all strategic asset allocation is not created equal; that they are endowed by their Creator with certain unalienable characteristics ; that among these are returns that come from Market Exposure, Skills, Illiquidity Premium and taking on rare Downside Risk.

Strategic Asset Allocation is responsible for the majority of long term variation in portfolio returns. Yet, it is glossed over and subsumed to making tactical calls, products and fund manager selection. Extending the not so modern portfolio theory and variants of mean variance optimization to create ‘model portfolios’ is undifferentiated and suboptimal; moreover, it just does not work in the real world.

Make Asset Allocation Great Again!

1.           All portfolio problems—strategic asset allocation, tactical asset allocation, manager selection, portable alpha, asset-liability management—are subtle variations of the same problem; they need to be approached:

–             in holistic and integrated manner.

–             from a practical perspective analyzed sequentially.

–             understood as being driven by choices on two dimensions: (i) how does one define risk? (ii) choice of constraints to arrive at tradeoffs?

2.           All asset allocation problems boil down to one of comparison—making valid comparisons between often hard-to-compare choices.

3.           There are four primary sources of returns that investors choose from: fundamental market exposure, skill based excess returns, unlocking illiquidity premium and taking on rare, but potentially large, sudden downside risks:

–             strategic asset allocation is about picking the right mix within and between each of these.

–             each investment out to be evaluated for its degree of exposure to each of these.

4.           Risks in many asset classes are understated; getting this right is the key to successful asset allocation:

–             valuation risk (volatility of valuations) is generally higher than reported within illiquid and alternative assets.

–             forecast risk (“the risk that you are wrong”) is generally higher in skill-based investments than fundamental-based ones (this includes sampling problems,    instability of characteristics, wrong modeling choices).

–             downside risk is generally higher in non-traditional assets.

5.           Using a broad set of investments (asset classes) is generally better—even if they are all equally efficient—than a more restricted set.

6.           Non-traded assets should and do attract a premium over the long-run:

–             this suggests that liquidity tolerance, and not risk tolerance, should be the first place one starts for asset allocation.

7.           Investors are generally overly wary of illiquidity:

–             diversification in various risks of illiquid investments (eg uncertainty about cash inflows, outflows, valuations, spending requirements, rebalancing      requirements, new investment opportunities) reduces the total risk.

–             volatility of portfolio weights from illiquidity should be offset by the non-tradability premium.

8.           Skill-based returns are attractive because of diversification:

–             many sources, given thousands of managers, relative to few fundamental returns sources ( equity, bonds, real assets..)

–             low correlation.

9.           Market exposure based returns are common and accessible cheaply using ETFs; skills based returns are expensive and rare.

–             Timeo Danaos et dona ferentes – “Beware of Greeks Bearing Gifts”:

–             Distinguish between market exposure (beta) masquerading as skill (alpha).

10.         Resolve to re-invent how you have traditionally approached strategic asset allocation in 2017;

–             calculate active risk adjusted returns and measure an active manager’s skill.

–             identify and isolate characteristics of a manager’s skill (alpha); calculate average alpha of managers, correlation among alphas, the effect of changes in the  number of managers and use Bayesian statistics to arrive at degrees of confidence in future performance.

–             forecast the probability distribution of degree of uncertainty in return, volatility, correlations of a fund manager.

–             select fund managers who produce high skills-based returns and optimally combine such managers into a portfolio to diversify active risk.

–             generate relative allocations across skilled fund managers.

–             include soft qualitative views and a degree of confidence within a quantitative manager allocation framework.

–             decide on appropriate allocations to expensive skilled managers versus to inexpensive passive benchmarks.

–             calculate the marginal impact of adding a fund manager to an existing portfolio.

–             compare manager performance in a like-for-like manner.

WireHouse ‘Model Portfolios’​ are Inefficient and Sub-optimal

Tens of thousands of Financial Advisors blindly trust an investment committee’s house view and place Trillions of $ of client money in so called ‘model portfolios’. At ActiveAllocator, we analyzed and modeled many firms’ published views using their own long term Strategic Asset Class assumptions. We can now quantitatively demonstrate that such allocations are flat out wrong – this is bad advice.

Trust but verify.

Best of all, any Financial Advisor can now do this on her own in minutes at ActiveAllocator.

Better Financial Advice.