Discussing the article: "Bidirectional LSTM and Quantum Computing for Predicting the Direction of Price Movement"

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Check out the new article: Bidirectional LSTM and Quantum Computing for Predicting the Direction of Price Movement.

The article presents a reproducible implementation of a hybrid quantum-neural network model for algorithmic trading on Forex without using real quantum hardware. A fixed three-qubit quantum circuit in IBM Qiskit converts sliding-window statistics (mean returns, volatility, and range) into a probability distribution, from which seven quantum metrics are calculated. These features are integrated into a bidirectional LSTM architecture with regularization and mechanisms to address class imbalance, including focal loss and a sampler.

Imagine that, before the next price movement, the market is, as it were, “considering” many possible continuation scenarios at once: a strong upward impulse, a slow slide downward, a sharp reversal, a continuation of the sideways market, and so on. Classical models see only what has already happened in the historical data. They look for recurring sequences of closing prices, volumes, and indicators. But they almost never have direct access to how “concentrated” or “spread out” these possible scenarios were immediately before the market chose one of them.

Here we are attempting to model this “structure of uncertainty” using the mathematical apparatus of quantum mechanics — not because the market is physically quantum, but because quantum formalism provides very convenient and powerful tools for working with superpositions of probabilities and the correlations between them.

An important clarification right away: we are not using any real quantum computer, and there is absolutely no quantum advantage here in the computational-complexity sense. We simply take a very simple, fixed, non-trainable quantum circuit and use it as an exotic nonlinear transformer that maps a small window of price data into a set of statistical characteristics of the distribution.


Author: Yevgeniy Koshtenko

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