Model Portfolio Subscriptions
We use data science, machine learning, and research in financial economics to create a dynamic asset allocation process that responds to changing market conditions. While investors pay a fee for our models, we select funds that balance low fees (whenever possible) with liquidity. Since we have no economic incentive to favor one asset manager over another, we select only the funds that we believe are appropriate for our clients.
Dynamic Asset Allocation
Let’s consider the asset allocation landscape. Many large asset managers offer model portfolios at no cost to investors. Why? Because their models are generally designed to use their own financial products. The models are technically “free,” but they often invest in ETFs and other financial products that are run by the asset manager providing the models, and the underlying products often have significant fees. Also, research has found that this structure can limit the range of investment options that end up being used in the portfolios.*
At QuantStreet, our model portfolio clients receive research-driven dynamic portfolios that respond to changing market conditions. Our models invest in ETFs that are low cost (whenever possible) and liquid. Since we are independent and have no financial incentive to use one ETF over another, we prioritize choosing liquid and low cost investments for our clients. We also believe in the value of tactical asset allocation — that’s why dynamic asset allocation is at the heart of our investing process.
*Edwin Elton, Martin Gruber, Andre de Souza, Christopher Blake, Target Date Funds: Characteristics and Performance. The Review of Asset Pricing Studies (March 2015).
Our Model Portfolios
QuantStreet focuses on asset allocation as the core component of our approach. We use data science, machine learning, and financial economics to create active asset allocation strategies. Our strategies are intended to respond to changing investment opportunities and evolving market conditions. While investors pay a fee for our model portfolios, we only select ETFs and other investing products that we believe are appropriate for our clients. The investments we choose must be liquid, and we use low-fee products whenever possible.
We have no economic relationships with the funds in which we invest. Our incentive is to choose funds that are right for our clients.
What models does QuantStreet offer? QuantStreet offers tactical and strategic model portfolios at a range of risk levels. Our model portfolios allow our clients to implement either an ETF-based asset allocation strategy based on QuantStreet’s proprietary machine learning process, or a portfolio intended to replicate the average performance of target-date funds operating at different risk levels.
What will you receive each month? Each month, you’ll receive our latest model portfolios at a range of risk levels, from conservative to aggressive. Once you identify your own client’s risk preference, you will have access to a model portfolio allocation at the corresponding risk level that can be customized by your investment team to fit the client’s specific needs. QuantStreet’s model portfolios can be used for the asset allocation component of your strategy, or they can serve as a full OCIO-style solution. Please note that these model portfolios are tools that you can apply at your discretion, and you remain responsible for determining suitability for your own clients.
Our rationale, explained. Each month, we’ll share a report with the rationale for our investment decisions, so you can explain them to your own clients. If you have questions, our CIO is just a phone call away.
Benefits of Model Portfolios
1. More time for client relationship building, business development, and work-life balance.
2. Confidence that your clients are invested based on an academically rigorous and disciplined approach.
3. Multiple risk levels to meet individualized client needs.
4. Access to two sets of portfolios – Strategic and Tactical – allowing you to customize portfolio turnover to client needs.
5. Regular market analysis and commentary that empower you to explain the investing strategies to your clients.
6. Access to a sophisticated and research-informed investment process.
7. Training for your wealth advisers on how to best use QuantStreet’s model portfolios to address clients needs.
8. Direct access to QuantStreet’s CIO for in-depth economic and market analysis.
Technology and data drive the process.
QuantStreet’s models help advisers manage their own clients’ portfolios in a rigorous and analytically consistent manner. Our models are implemented using liquid, low-cost ETFs. On a monthly basis, subscribers receive two sets of ETF-based model portfolios:
Target-Date Replicating Portfolios intend to replicate the average performance of target-date funds operating at different risk levels. Read about these.
Tactical Portfolios use QuantStreet’s proprietary machine learning forecasting model. These react dynamically to changing market conditions and have monthly turnover in the 5-15% range (though sometimes lower or higher).
Both sets of portfolios reflect position limits that (in our view) prevent undue concentration risk and idiosyncratic exposures.
The Target-Date Replicating Portfolios represent a largely passive allocation, which is appropriate for some investors. However, passive allocations do not account for the fact that some assets are more or less attractive at different points in the economic cycle.
Our Tactical Portfolios address this through an active portfolio construction approach. First, we use a machine learning algorithm to forecast asset class returns. Then, we combine those forecasts with historical returns to produce portfolios at a range of risk levels, which can be customized to client risk preferences and liquidity needs.
Our Tactical Portfolio Investing Process
We use machine learning algorithms to forecast asset class returns based on a range of economic and market data. The asset allocation model then combines these forecasts with a trend signal to produce portfolios at a range of risk levels. We rebalance portfolios regularly to reflect changing opportunities and risks as market conditions evolve. Our Chief Investment Officer applies judgment and oversight to the model outputs to ensure that portfolios remain grounded in real-world market conditions.
QuantStreet’s model forecasts reflect model-based estimates and may differ materially from actual market outcomes.
Algorithmically generated using economic and market data
Qualitative analysis
Portfolio Implementation
We primarily invest in major liquid asset classes using ETFs.
We typically choose ETFs that are low cost and highly diversified. Purchasing a single ETF can be like buying hundreds or thousands of individual stocks and bonds.
Many of our ETF providers are leading global asset managers (Vanguard, BlackRock, State Street, etc.).
We use ETFs to access asset classes include US stocks, international and emerging market stocks, US government and corporate bonds, and real estate investment trusts, among others.
We also invest in value and momentum ETFs.
- Value is a strategy that involves buying stocks with relatively attractive valuations.
- Momentum involves buying past winning stocks, and avoiding past losing stocks.
ETFs are highly liquid. They allow us to dynamically reposition the portfolio in response to changing market conditions and opportunities, at low cost to our clients.
We do not typically use leverage or short-selling in our investments.
Sample Portfolio
According to our model’s assessment during this particular sample period, the assets offering the most attractive reward/risk tradeoffs are S&P 500 stocks, value stocks, high-yield bonds, and an ETF tracking real estate investment trusts.
The portfolio can also maintain some amount of cash, in this case 2.5% of portfolio value.
The portfolio is highly diversified and owns thousands of individual securities via the ETFs.
We rebalance investment portfolios regularly.
Portfolio weights change over time to reflect changing opportunities and risks.
Assets with zero current allocation may have allocations in the future.
For technical details of our strategy, please contact us and we’ll be glad to provide additional information.