Our Investing Approach
QuantStreet uses data science, machine learning, and research in financial economics to create a systematic and rigorous asset allocation process. We invest in ETFs and other investment products that balance low fees (whenever possible) with liquidity. Since QuantStreet has no economic incentive to favor one asset manager over another, we select only the investments that we believe are appropriate for our clients.
Our clients typically custody their assets at Schwab and Interactive Brokers which, in some cases, restricts the product set to which clients have access.
Two Approaches to Portfolio Construction
Our investors can choose from two approaches to portfolio management.
1. Tactical Portfolios
Tactical Portfolios are based on 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).
2. Target-Date Replicating Portfolios
Target-Date Replicating Portfolios intend to replicate the average performance of target-date funds operating at different risk levels. Read about these.
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 industry-informed 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 typically invest in major liquid asset classes using ETFs. We can also create customized strategies based on your goals.
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 (e.g., Vanguard, BlackRock, State Street, etc.).
We use ETFs to access various asset classes including US stocks, international and emerging market stocks, US government and corporate bonds, and real estate investment trusts, among a number of others.
For more information about the asset classes in which we invest, please contact us.
The ETFs in which we typically invest are highly liquid. They allow us to dynamically reposition our tactical portfolios in response to changing market conditions and opportunities, at low cost to our clients.
We do not use excessive leverage or short-selling in our investments.