This Finforge-N3 AI model flow starts with the Nasdaq-100 as the asset universe, then chains together three AI model nodes: Screener-N3, Forecast-N3, and a second Screener-N3 before portfolio construction.
The idea is simple: first narrow the universe to more interesting candidates, then forecast their near-term return potential, then select the Top N forecasts to optimize against a benchmark before sending the results into portfolio construction. This creates a practical workflow where screening, forecasting, selection, and position sizing work together instead of as separate steps.
In this template, Screener-N3 uses data types including Total Current Assets and Price. Total Current Assets is the sum of assets the company expects to convert to cash or use within roughly the next year (for example, cash, receivables, and inventory), which helps describe near-term resources and operating flexibility. Price is the market’s current per-share value for the stock, reflecting what participants are willing to pay right now.
Together, these inputs give the screener both a balance-sheet liquidity/resources lens (what the company has available in the near term) and a market pricing lens (what the stock trades at).
Screener-N3 is an AI model node that continually learns from new market dynamics instead of relying on fixed screening rules. Its role is to filter the Nasdaq-100 toward stocks with stronger potential versus the benchmark.
The selected names are then passed to Forecast-N3, another AI model node, built for continual deep learning forecasting. Forecast-N3 focuses more directly on price dynamics and estimates near-term return direction and magnitude.
After forecasting, the second Screener-N3 ranks and selects the Top N forecasts to create a tighter candidate set for benchmark-aware optimization in portfolio construction.
Chaining the nodes is meaningful because they solve different parts of the problem. Screener-N3 helps reduce noise by finding better candidates, Forecast-N3 complements it by analyzing price behavior and short-term timing, and the second Screener-N3 concentrates the signal by selecting the strongest forecasts before optimization and position sizing.
