About the smallcase

  • This smallcase seeks to beat the market by identifying stocks which are "poised" to outperform the benchmark.
  • Historical valuations of the underlying stock are compared to current valuations using Machine Learning/ Artificial Intelligence techniques, in the context of broad market performance
  • Stocks with the highest probability of outperformance are then identified.
  • The list is further culled to select the highest quality stocks.
  • If enough number of stocks cannot be found by the system for a diversified portfolio, the rest of the capital is deployed into LIQUIDBEES.
  • Rebalancing targeted around evey six weeks unless a stock shows material change in fundamentals / quality or in case of fraud

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Understand smallcase costs and returns

Understand smallcase costs and returns