We have a minimum account size of $25,000 so we can trade 2 different index ETFs, but our recommended account size is $50,000 or higher for a more diversified portfolio.

We charge a flat 2% annual fee, calculated daily, paid monthly - based on the end of day account value. For example if you had $100,000 in your account for a full month, your monthly fee would be ~$167.

The broker also charges a minimum of $0.35 per transaction. This equates to approximately just under 1% annually.

Our 2024 return of 65.6% was net of all fees.†

Neither. Unlike hedge funds or traditional pooled investments, each client opens their own brokerage account. Our software executes trades on their behalf, ensuring full transparency.

We are a fully managed strategy, not just signals. Many quant firms sell trade signals as a subscription service. We don’t provide signals - we place every trade, manage the strategy, and report real-time results in our custom-built portal. The broker also provides their own portal as an additional opinion on a portfolio's performance.

No Options, No Margin, No Complexity: Options and margins add risk and complexity. Our philosophy as engineers is simplicity and precision, ensuring stable and predictable execution to meet our modeled results.

Our core strategy is harvesting profits from market volatility. With an innovative combination of Dollar-Cost and Value Averaging, we incrementally buy during dips and incrementally sell during rises. Captured profits can be pocketed to augment personal income and/or reinvested to fuel expontential growth.

We have yet to meet another strategy that allows you to take small profitable wins as personal income while still fueling portfolio growth in this manner. It truly is a win/win strategy.

No lock in periods, and since we are only buying exchange-traded funds - all accounts are fully liquid at their market value.

We prioritize precision, transparency, and deterministic execution - three things that AI struggles to provide in financial decision-making. While AI has revolutionized many industries, its application in investing comes with inherent risks. The biggest issue? Lack of transparency. AI-driven strategies often operate as "black boxes," making decisions that even their creators struggle to explain. If something goes wrong, there’s no clear way to diagnose the issue beyond tweaking inputs and hoping for better results. As engineers, we demand to know exactly what went wrong and why — without relying on trial-and-error adjustments.

Our Quantelligent strategy is built on structured, rules-based quantitative analysis, ensuring that every decision is rooted in hard data, backtested rigorously, and fully understood before implementation. Unlike AI, which can introduce unpredictable risks due to overfitting, noise sensitivity, or market anomalies, our strategy allows us to personally verify and refine stable models of investing.

Additionally, there’s little public evidence that AI-driven investment strategies outperform traditional quantitative models. Our results speak for themselves — 65.6% returns in 2024 versus the S&P500's return of 24.89%.†

Ultimately, we don’t trust AI to do what we can do better. Instead of relying on opaque generative decision trees, we harness the power of quantitative analysis, algorithmic precision, and human expertise to unlock consistent, scalable, and risk-managed returns.

The simple answer? Implementation.

LymanWealth is a team of three highly skilled engineers who specialize in quantitative analysis and software development — a rare combination in the investment world. Large investment firms lack the ability to pivot to new tech-based strategies due to bureaucracy, outdated processes, and resistance to change. The industry mindset is largely "why change what works?" — but we believe that firms not evolving with current technology will quickly fall behind.

Additionally, our strategy, Quantelligent, is designed to harvest market volatility, a concept that many firms refuse to consider. Traditional investment strategies focus on passive growth or complex derivatives like options and margin trading, but we take a simpler, more efficient approach — capturing profits from market movement using data-driven execution.

Another reason no one else is doing this? Mindset. Institutional investors often hesitate to embrace a strategy that actively captures profits rather than just riding market waves. It takes a shift in thinking to see why this works better than traditional buy-and-hold models. We openly share our strategy’s principles, but our proprietary quantitative analysis and execution models remain unique to us. Other firms simply don’t have the expertise, the agility, or the perspective to develop something like Quantelligent.

We've even been told that our strategy is too simple to generate our reported returns. And to that we have no answer other than to share the data as proof it works both in back-testing and our real-world results.

And lastly, automation. We are an active strategy. We buy into dips and sell into spikes on a daily cadence. An investor may be able to handle this workload on their own account, but as of this writing we have 183 accounts with 487 allocations. That's a minimum of 487 trades per day. Without automation this would be impossible and not scalable. Our strategy is fully automated to both remove the burden of manual execution and also remove all human error, bias, and emotion. We quantitatively verify the models are stable and we engineer the automated algorithm to perform.

We have decades of quantitatively backtested data and (so far) 5 years of real numbers including the bear market of 2022. We execute our Quantelligent strategy with unwavering precision, staying perfectly aligned with our models for consistent and profitable stability.

Join us and become a part of the Quantelligent investing revolution.