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The Portfolio Optimizer for Wealth Management

2-minute summary: We are a software company with two main products:

Typical usages include:

Our strengths:

We do not manage money, or sell directly to advisors / investors; we just license our software (binary or source-available), which our clients can host.

One of our risk models projected onto 3 dimensions (image loop over 1 month), and its application to a specific investing scenario. See here for an interactive version of this animation.

Sample features:

Here are some of our advantages. Click on each item to expand.

Rather than investing in an indexed ETF or mutual fund, a client can have the advantages of tax-loss harvesting for every stock in each index they hold.

Direct Indexing is quickly becoming more attractive, even for smaller accounts, with the advent of:

Even if the market as a whole is not moving, individual stocks have a wide range of returns. By holding each stock individually, there are far more tax-loss harvesting opportunities.

See our direct indexing demo for more.

There are multiple goals when choosing a good portfolio for a client, such as:

These goals sometimes conflict. For example, a client got a large gift of stock as a child, which is now at a large gain. Selling that stock would cause him to owe a lot of tax, but not selling will keep the portfolio unbalanced.

Through a unique technology that we have built (details here, here, and here), we are able to find the portfolio that gives the best combination of these goals.

Our technology relies in turn on mathematical programming - which is a well-known technique used widely across different industries - and on mature third-party software packages that solve those problems.

An advisor typically assigns a target portfolio to a client based on how much risk she can take based on her personal situation. However, the client may have accounts elsewhere for various reasons:

We understand that.

Therefore, it makes little sense to invest her $100,000 in the same proportions as the target; those proportions are instead meant to apply to her whole financial picture. For instance, if her external assets include restricted shares in her tech startup, the $100,000 in cash should be invested relatively less in the tech sector to avoid overexposure to risk.

Our system can invest optimally by incorporating a client's external assets into its investment decisions.

This can be combined with Direct Indexing to provide the benefit of tax-loss harvesting as well as customization.
There are many ways to look at a client's external assets which will not result in a better portfolio: We instead apply sophisticated techniques that are widely used by large professional trading firms - such as banks and market makers - to balance their own portfolio risk intelligently while maximizing returns. See here our factor model demo for more.

Even if a traditional advisor can incorporate external holdings correctly, we can invest better because we monitor portfolios continuously.

For example, some days may be better for rebalancing a portfolio than others from a tax savings perspective, depending on market prices. Computers are much better than humans at scanning prices continuously and making that determination. Ultimately, this enables advisors to spend less time on portfolio mechanics, and more time on high-touch and high-value work.

We have the ability to tailor a client's investments to their individual situation, such as:
We have the ability to show exactly how we would invest a client's money, tailored to their individual situation, such as: A client's exact future investing results will depend on market prices, which of course we cannot predict. However, we can show clients how their account would have been invested, had they opened the account a few years in the past. Several aspects of their investment behavior will not depend as much on prices. For example:

This is a corollary of "Preview ability" above.

How does an advisor know whether a certain investing product is good for a particular client? And how can the client (possibly a prospect) be convinced that such a product is valuable?

Advisors may sometimes publish white papers that describe the average improvement over a few scenarios (or possibly just one). For example, they may describe what happens when a client deposits $200,000 upfront & $5,000 every month, and is in a particular federal and state tax bracket. However, there is no well-defined average client situation, so results may vary a lot by client.

What if you could tell your clients what their benefit would be?

The preview ability displays the benefit customized to a client, and helps make a much more convincing argument.

The founders have previously worked in the biggest trading system in the US, and have spent most of their professional lives building highly reliable, mission-critical enterprise systems. As a result, the system is engineered well. Here are some examples:

There are also some "softer" reasons why our system was able to be built solidly:

The system is written in Java, and has almost no dependencies (database, broker connections, market data feeds, etc.), which makes integration easier. The inputs are:

The output in the production system is a set of orders. Note: in simulation, we additionally generate a rich set of metrics and graphs.

The only external dependencies are for historical data (prices, cash dividends, splits, etc.), for which we use an established third-party provider.

We architected our system from the start for one purpose only: to enable fast rollout of sophisticated investment products.

For example, the system allows the investing research team to run parallel simulations of investment algorithms and subsequently generate:

This can help researchers e.g. tweak the behavior of tax loss harvesting algorithms so as to increase after-tax returns.

Here are some products on our roadmap. While they have not been created yet, our system was specifically architected to make it much easier to build them.

target allocation target allocation asset class partitions asset class partitions asset tracking asset tracking trade amounts trade amounts details details net tax owed net tax owed portfolio type totals portfolio type totals stock totals stock totals tax lot sizes tax lot sizes tax lots tax lots asset class totals asset class totals results table results table
Automatically generated summaries of investing simulations to help build new investment products; see demos