Machine learning on tick data: separating hype from reality
Posted: Tue Oct 27, 2026 7:16 am
Machine learning in trading has a glamorous image. Feed in tick data, let a neural network find patterns, collect profits. The reality is harsher.
Financial data has a very low signal-to-noise ratio. Models easily fit noise, producing gorgeous backtests that collapse in live trading. Markets are also non-stationary, meaning patterns shift over time, so a model trained on last year's behaviour may have little relevance next year.
Costs are the other killer. A model predicting 0.3 pips of movement over the next few seconds may be statistically significant and still unprofitable after a half-pip spread.
That doesn't mean machine learning is useless. Simple models used carefully, with proper validation, honest cost modelling and strict out-of-sample testing, can add value, especially for classification tasks like regime detection or spread prediction.
The red flags are familiar: tiny test periods, no costs, tuning on the test set, and claims of astonishing accuracy.
What has been tried with machine learning, and did anything survive realistic testing?
Financial data has a very low signal-to-noise ratio. Models easily fit noise, producing gorgeous backtests that collapse in live trading. Markets are also non-stationary, meaning patterns shift over time, so a model trained on last year's behaviour may have little relevance next year.
Costs are the other killer. A model predicting 0.3 pips of movement over the next few seconds may be statistically significant and still unprofitable after a half-pip spread.
That doesn't mean machine learning is useless. Simple models used carefully, with proper validation, honest cost modelling and strict out-of-sample testing, can add value, especially for classification tasks like regime detection or spread prediction.
The red flags are familiar: tiny test periods, no costs, tuning on the test set, and claims of astonishing accuracy.
What has been tried with machine learning, and did anything survive realistic testing?