From Charts to Circuits: How TINs Rewire Technical Analysis for the AI Era
In a field where LSTMs, transformers, and black-box agents often dominate the conversation, a new framework dares to ask: What if our old tools weren’t wrong, just under-optimized? That’s the central premise behind Technical Indicator Networks (TINs) — a novel architecture that transforms traditional technical analysis indicators into interpretable, trainable neural networks. Indicators, Meet Neural Networks Rather than discarding hand-crafted indicators like MACD or RSI, the TIN approach recasts them as neural network topologies. A Moving Average becomes a linear layer. MACD? A cascade of two EMAs with a subtractive node and a smoothing layer. RSI? A bias-regularized division circuit. The resulting neural networks aren’t generic function approximators; they’re directly derived from the mathematical structure of the indicators themselves. ...