ECML

ECML targets stocks perceived to be undervalued and underappreciated by the market. Investments could be of any size across various sectors, excluding financials. Through a multi-step approach and quantitative screening process, the fund employs proprietary models to estimate a company's intrinsic value. It starts by screening all publicly traded stocks on the NYSE and Nasdaq, excluding non-US based and financial sector companies. It then applies machine learning to map each company's historical data to future earnings while estimating uncertainties in its forecast. Stocks are then ranked by how inexpensive they are relative to the forecast with consideration to potential "value-traps” or stocks that are currently considered inexpensive but likely to underperform over the next year. The top 60-70 companies are reviewed, with the actively managed fund having full discretion to override the model. The portfolio is rebalanced quarterly, with securities allocated with equal weights.