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Quantamental Approach =

Data + Insights

In the age of big data, machine learning and artificial intelligence, it is imperative to fully embrace the power of statistical evidence in decisions making. However, we believe that educated human judgement is a perfect complement to data analytics, especially when dealing with uncertainty and probabilities. 

In almost every aspect of our investment process we incorporate data, evidence and facts but use our judgement to make the final call. Some, but not all instances include the following.


We use statistical measures of deviation from long-term means and assume reversion to averages.


Our analysis incorporates factors (valuation metrics, credit metrics, ...) that had the most significance in explaining returns historically. These factors may be different for each sector and market. Additionally, we use algorithms that allow us to track the filings and main positions of the most successful hedge fund managers each quarter.


We use quantitative metrics to assess the default probability of an issuer (Altman's Z-score, Piotroski's F-score, Campbell's default probability) and determine the relative value of an issue based on statistical measures compared to history and peers.


We developed our own quantitative model to value preferred securities based on the factors that historically best explained their prices.


We use macroeconomic (LEIs), financial (Yield Curve and Credit Spreads) and technical indicators (Exponential Moving Averages) to assess the probability of recessions and bear markets. We backtest these metrics to assess their statistical significance.

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