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Performance & Methodology

How to interpret NeuralTrend signals and results

NeuralTrend is designed as a market-research and simulation platform. Here you can find the information needed to evaluate its signals, historical results, assumptions, and limitations.

322 publicly listed assets
300 crypto assets
22 traditional assets
Daily signal frequency

Historical simulations are not a live brokerage record

Historical simulations are not brokerage statements, real-money results, or guarantees of future performance. A separately labeled Forward Record will begin from a clearly stated date when NeuralTrend is released publicly; pre-launch testing will not be imported.

Standardized Signal Overview view

Recent one-year historical simulation

This is the same historical simulation framework available in Signal Overview, fixed to the 1Y horizon for four representative crypto assets. It is not a separate validation dataset and should not be confused with the approved, date-bounded Forward Record.

Explore all assets and horizons in Signal Overview →
Asset Coverage AI strategy Buy & Hold Return spread AI max drawdown Data freshness Latest signal
BTC-USD 366 observations 2025-09-07 – 2026-09-07 +12.9% -29.3% +42.3 pts -28.7% Current Through 2026-09-07 HOLD
ETH-USD 366 observations 2025-09-07 – 2026-09-07 +17.7% -42.8% +60.5 pts -35.4% Current Through 2026-09-07 HOLD
SOL-USD 366 observations 2025-09-07 – 2026-09-07 +54.9% -49.9% +104.8 pts -12.7% Current Through 2026-09-07 HOLD
XRP-USD 366 observations 2025-09-07 – 2026-09-07 -6.8% -51.9% +45.0 pts -6.8% Current Through 2026-09-07 HOLD

Generated from the currently deployed data files using the 1Y Signal Overview horizon. Coverage and data-through dates are shown per asset.

How signals work

Completed data becomes a BUY, HOLD, or SELL state

NeuralTrend intentionally avoids using incomplete same-day market information when producing the daily signal shown to users.

1

Completed market data

Daily price and volume data are collected after a market day is complete. Technical and other indicators are derived from that information.

2

Model evaluation

The asset’s model evaluates information available through the previous completed day. It does not use today’s price.

3

Published signal

The resulting BUY, HOLD, or SELL state is associated with the current signal date and is used by the site’s historical and live simulations.

Data freshness

Each signal shows the completed data it is based on

NeuralTrend displays a data-through date, the time the deployed site data file was updated, and a simple freshness state. These indicators describe the website data available to the model; they are not real-time exchange timestamps or trade confirmations.

Current

Within the expected cadence

Crypto is checked against calendar days. Stocks use a weekday-aware check so weekends do not automatically make data stale.

Delayed

Later than usual

The latest completed row is one update beyond the normal tolerance. Users should verify the data-through date before acting.

Stale

Materially behind

The latest completed row is several expected updates behind. The signal remains visible for transparency but should not be treated as current.

Stock-market holidays are not embedded in the lightweight freshness calculation, so an exchange holiday can occasionally make a current stock file appear delayed.

Simulation assumptions

What is included in displayed results

Execution price

Historical and current live simulations use the daily closing price stored for the relevant signal date. They are not real-time exchange executions.

Transaction costs

The current fixed assumptions are 1.00% per executed crypto side and 0.10% per executed stock side. Actual venue costs may differ.

Open positions

Positions still open at the end of a selected horizon are marked to market. No artificial final SELL or exit fee is added without a SELL signal.

Buy & Hold benchmark

The benchmark uses the same period and includes an entry cost. Residual cash is retained when a whole-share stock purchase cannot invest every dollar.

Not modeled separately

Slippage, bid–ask spread variation, DEX gas costs, liquidity-dependent price impact, market impact, taxes, borrow costs, and exchange-specific fee tiers are not modeled separately. Actual trading results can differ materially.

Evidence labels

Historical simulations and the Forward Record serve different purposes

Available now

Historical strategy simulation

Shows how the signal series would have behaved under the website’s stated assumptions. The complete chart can include periods used during model development as well as later evaluation and production inference.

Starts at public launch

Forward Record

Calculates performance from compact administrator-approved Date, Close, and signal rows beginning on each asset's stated public start date. Earlier approved rows cannot be silently rewritten through the publication workflow.

Model maintenance

Monitoring, retraining, and historical revisions

Model quality is monitored regularly. Individual asset models are periodically retrained when performance and data-quality checks indicate that an update is appropriate.

Asset-specific updates

Each asset can be updated independently. A model may remain deployed for weeks, months, or longer depending on its observed behavior and available data.

Published history

Previously published signal rows are normally preserved when new daily signals are appended. Internal release checks flag unexpected historical changes.

Material revisions

If a correction or data cleanup changes earlier signals, NeuralTrend will identify the affected asset, period, reason, and scope in the public change log.

Technical methodology

Optional details for users who want a deeper explanation

Inputs and model scope

The independent market inputs are daily open, high, low, close, and volume observations. NeuralTrend derives technical and other indicators from those inputs. Each currently supported asset uses its own model.

Chronological evaluation

During model development, observations are ordered by time and divided into training, validation, and testing partitions. The current process uses a combination of fixed chronological holdout and continuous walk-forward testing.

NeuralTrend does not publish the complete feature list, model architecture, optimization search space, label construction, retraining thresholds, or source code. Those elements form part of the proprietary product methodology.

Public disclosure

Model and signal-history change log

Material methodology changes, historical-signal revisions, and data corrections are recorded here. Routine appending of a new daily signal does not require an entry.

Platform-wide Methodology disclosure

Public methodology and signal-history disclosure introduced

NeuralTrend added a public methodology page, clarified the difference between historical simulations and a future immutable live track record, and introduced a public change-log policy. This website release did not rewrite existing market data signal history.

Historical signals changed
No
Affected period
None
Limitations

Use the results as research evidence—not a promise

  • Historical performance does not guarantee future performance.
  • The Forward Record is an approved historical calculation, not real-time brokerage execution.
  • Upstream data providers may revise source data or discontinue assets.
  • NeuralTrend does not remove assets solely because their model performed poorly.