Applied wealthtech for investing

Academic knowledge is the basis for our unique Robo-Advisor

Most of our ideas are motivated by and well documented in academic literature. Keeping pace with developments in science is key. By making use of existing theory and combining it with our own ideas born of numerous interactions with experts, clients and friends, we have developed our unique investment engine.

ESTIMATING OWN CAPITAL MARKET ASSUMPTIONS (CMAs)

Estimating time-varying total returns

To often financial advice relies on historical return assumptions, which leads to overly optimistic or biased expectations from investors. We believe that more advanced methods that account for the time-varying nature of risk premiums need to be deployed.

We produce Capital Market Assumptions (CMAs) that rely on structural and reduced form econometric models with documented track-record.

BUILDING A ROBUST STRATEGIC ASSET ALLOCATION (SAA)

Creating your investment strategy portfolios

Estimating robust strategic portfolios is as much an art as it is science. Our portfolio building process is centered around a top-of-mind approach which uses three core investment vehicles accessible to everyone (domestic cash, bonds and equities).

Foreign assets (equity and inflation linked bonds) are added separately to the process, depending on the available investment amount or necessity.

DERIVING YOUR DYNAMIC INVESTMENT STRATEGY

Deriving the optimal investment strategy

Deriving the optimal dynamic investment strategy over time is the core of our innovation. By solving the investment plan recursively, we believe to apply the currently most sophisticated numerical procedure to goal based investment available today.

With a dynamic investment schedule at our disposal, clients can implement and monitor their investments with guidance over time.

Not just fintech but wealthtech

what distinguishes us from others...

We are not the first robo-advisor nor are we going to be the last one. We have profited tremendously from all the pioneer work that has been done in this field by others. At the same time we believe that it is necessary to compare existing technologies with what we believe is state-of-the-art today.

CONVENTIONAL FINTECHS

Same old, same old “one fits them all” approach but cheaper

This first generation of digital wealth advisors focused on replicating existing wealth management models at a cheaper price Applying historical returns on varying risk profiles and projecting a spectacular future is one major common feature of these first robo-advisors. Today most robo-advisors continue to follow this simplistic approach when advising clients, despite the lack of real wealth science innovation.

Static investments strategy for entire wealth
Offer automatic rebalancing (constant asset mix)
Use historical returns to simulate bright future

GOAL-BASED 1.0

Portfolio as function of final goal, but static over time

A major innovation in wealth management happened by acknowledging the specific behavioural aspects of investing, called mental accounting. This first innovators usually tailored the investment strategy along required returns and risks to reach a specific goal, therefore calling it goal-based strategies. Such strategies, however, failed to dynamically adjust the asset mix closer to goal maturity, leading to overshooting or undershooting risks.

Individual investment strategies for varying goals
Automatic rebalancing to individual but still static goal strategy (constant asset mix)

GOAL-BASED 2.0 logo

Portfolio as function of final goal but dynamic over time

The newest goal-based investment algorithms apply dynamic programming for asset allocation decisions. These algorithms control the risk of the investment strategy dynamically over time and are therefore path dependent. The asset mix is constantly adopted over time, depending on the past evolution and future outlook. This minimizes the risk of overshooting or undershooting the target, lifting as consequence the likelihood of reaching the target.

Individual investment strategies for varying goals
Dynamically adjusted asset mix, depending on goal evolution and future outlook