Multi-Symbol Indicator for Normalized Neural Network Inputs

Summary

This indicator gathers values from up to ten combinations of symbols, timeframes, and signal variants, synchronizing them to the symbol on which the indicator is installed. Its original purpose is to provide normalized inputs to a neural network, though the document suggests other uses without specifying them. Available calculations include a high-low range ratio, open-price changes, RSI, Stochastic, moving-average differences, and time of day. Some price-difference calculations are normalized to a range from -1 to +1 when new data arrives.

The document describes parameters for selecting each instrument, calculation variant, timeframe, and period. It also recommends setting the maximum bars to calculate at twice the required data amount. It provides no performance results, validation, or evidence that the inputs improve a trading model. The method is a data preparation and indicator utility, so its usefulness depends on downstream modeling and careful handling of synchronization, scaling, and historical data.

Key ideas

• The indicator can display up to ten data series drawn from different symbols, timeframes, and signals.
• Its stated purpose is to prepare synchronized, normalized values for neural network inputs.
• Available features include price changes, RSI, Stochastic, moving-average differences, a range ratio, and time of day.
• Several price-based outputs are normalized to the range from -1 to +1 when new data arrives.
• The document gives configuration guidance but no evidence of trading performance.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.