At QuantStreet, our values and ethical culture guide how we approach investing and client service. The information below describes the principles we follow and the approach we take in managing client portfolios.
Our investing process draws on our CIO’s extensive experience at major financial institutions and incorporates rigorous academic research.
We strive for transparency in our investing approach. Our individual clients can see their portfolio any time by logging into the custodial account (usually on Schwab). You can also read our ongoing market updates and analysis.
We manage portfolios using a proprietary machine-learning algorithm that underlies our research-driven approach. The model’s outputs are vetted by industry-informed professional judgment.
We design portfolios with the goal of achieving the highest expected return at each client’s level of risk. Please see the disclaimer below. All our strategies are designed to be dynamic and respond to changing market conditions. We don’t use short selling, speculative options trading, and other high risk strategies, unless you specifically ask us to.
We believe that ethical behavior is the key to long-term success.
Transparency
We share our investing strategies and research insights with clients through conversations, articles, and reports. Clients are also welcome to call anytime to ask questions.
Sophisticated Analytical Resources
We give you access to sophisticated and rigorously-researched strategies. We use data and analytics to inform our investment decisions and rationale for your account.
Reasonable cost
We charge a reasonable management fee and attempt to invest in low-cost products whenever possible (balancing product fees with considerations such as liquidity).
Respect
We respect our clients and personnel. Our goal is for every person who engages with us to feel heard and valued.
Our research-driven investment process incorporates machine learning and other analytical tools to build customized client portfolios. We leverage technology and data on the asset allocation side and in our risk management approach.
Through years of industry experience, we’ve seen how real-world markets can behave outside the scope of any model. This is why we use human judgment to oversee, and sometimes override, the model’s outputs.