How Columbus Investment Strategy Works

The engineering behind our data-intelligent investment strategy

Delivering Compelling Returns and Stability for the Long Term

Columbus is a proven, data-intelligent strategy that:

  • Uses the intelligence of data and the analytical power of robust statistical methods to take the emotion out of investing decisions
  • Finds the most optimal asset mix from a universe of 15 highly liquid, low costs ETFs, each representing a major asset class
  • Adapts its portfolio every month to prudently protect your clients’ wealth

Advisors receive the monthly Columbus Strategy Report, which includes insights on the state of the market with some explanation on how Columbus arrived at its current asset allocations. In turn, you can use these insights to form your view of the market, trade client portfolios based on the Columbus recommended allocations, and improve long-term client returns.

Columbus Report Sent at Month-End

ETFs to hold and exact allocations

Insights to support client dialogues

Trade Client Portfolio

Apply recommended allocations

Use as portfolio insights

Powered by Our Robust AI Platform

Columbus runs on the proprietary Laplace Platform, which has been developed using the R statistical programming language. R is used by some of the top hedge funds in finance, academia, and for machine learning and artificial intelligence research in the high-tech industry, including at Microsoft, Facebook, and Google. The Laplace Platform is 100% algorithm based and has been extensively tested using hundreds of different investment universe combinations ranging from 13 to over 80 assets each over a 20-year period, along with proven live trading performance

Burned by Quant ?

Many RIAs have had an experience with a quant strategy that showed great historically modeled returns, but when it started trading live it wasn’t impressive and prone to suffer from volatility and risks. This happens because the strategy has been “overfitted,” where the algorithm is built to give results based on real historical data that may not be how the market behaves in the future. Columbus takes a different approach. It is statistically tested over thousands of potential scenarios in an attempt to try to break the algorithm and ensure robustness across a huge range of possible market conditions, including unlikely ones, so we can gain confidence that the strategy’s level of risks will not go outside our norms during future market situations. Need more details?

Better Performance at Lower Risks

One of Columbus’ key strengths is delivering positive returns even during major bear markets such as the Dotcom crash and the Financial Crisis, while also producing compelling returns during stable bull markets.

Columbus in Bull Markets

During a stable bull market, Columbus will generally stay invested in stocks to capture the upside from the stock market. It will typically stay mostly invested even during small corrections.

Columbus in Uncertain Markets

When uncertainty kicks in, Columbus will move away from stocks, preferring to find opportunities elsewhere. Columbus evaluates all 15 ETFs in its investment universe every month and compares the risk/return equation for each of them to figure out a relative score for each. It then uses this information, along with relative correlation between each asset to rebalance the portfolio for the upcoming month. This means that when risks start to escalate in one asset class (e.g., stocks) relative to other assets, such as gold, the US dollar, or fixed income assets, Columbus will shift the portfolio away from the riskier assets (stocks) to emphasize those assets which are less risky.

In practice, Columbus generally follows the flow of big, smart institutional money because it essentially detects these movements as large institutions tend to move the market as they buy or sell specific assets. Columbus can sense that move and essentially follows the “smart money.”

Michael-Himmel-300x280

" I've been very impressed by the comprehensive approach used to ensure the Columbus algorithm is robust under a wide range of market situations. The depth of analysis and statistical rigor gives me the confidence I need to use it with my clients. " 

Michael Himmel

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Founding Partner Essex Asset Management

The White Paper

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