Frequently Asked Questions

What is Whale‑E?

Whale‑E, short for Whale Engine, is a backtesting and parameter-optimization tool designed for algorithmic trading strategies on crypto assets. It lets you replay a strategy on historical data under execution conditions close to those of a trading platform while exploring a large number of parameter combinations to identify the settings that matter most for the metrics you choose.

Whale‑E is the crypto-market equivalent of TradingView’s broker emulator. It uses the same strategy calculations and the main backtesting rules that TradingView applies when running strategies. This keeps the results anchored to a widely used reference, making them easier to interpret, verify, and compare.

Is Whale‑E free?

Yes. Whale‑E is free for personal use, and for professional use as long as that use remains internal. It cannot be used to provide services to third parties.

What are hyperparameters, grids, and grid search?

Optimizing a strategy means testing indicator parameters.

• Hyperparameter: a hyperparameter is a numeric parameter you choose to optimize by defining multiple candidate values. It can be an indicator setting (for example a length), a threshold, or another numeric strategy setting.
• Grid: a grid is a fixed strategy configuration where non-numeric choices are locked (for example indicator type, price source, symbol, timeframe). The engine builds one grid per combination of those choices, then explores numeric hyperparameters within each grid.
• Grid search is an exhaustive, deterministic optimization method. For each grid (with fixed non-numeric choices), a full backtest is run for every hyperparameter-value combination, the objective is computed, and the results are ranked. This guarantees that all defined combinations are evaluated, but runtime increases quickly as the search space grows.

What is overfitting?

Overfitting happens when a strategy is tuned too closely to the historical data used during optimization. It can look excellent in backtests and then degrade on new, unseen data. For more details, see Overfitting and historical performance.

Are results reproducible?

Yes. With the same historical data, strategy, and settings, the results and ranking order are identical.

What operating systems does Whale‑E support?

The software is available on Windows x64 (native binary) and on Linux x64 via Docker.

What market data does Whale‑E use for backtesting?

Backtests use OHLCV data sourced from the exchanges supported by the software. This data is then used to run backtests on the symbols and timeframes defined in the strategy.

Data is downloaded automatically on first use and then stored in a local SQLite database so later runs can reuse the cache. If part of the required history is missing, the engine attempts to fetch it before the backtest starts.

The full list of supported exchanges and market types is available in Available exchanges.

Is Whale‑E fast at exploring large parameter grids?

Yes. Computations are parallelized and the CPU cache hierarchy is used efficiently.

Actual throughput depends heavily on both the strategy being tested and the machine it runs on. The number of indicators, expression complexity, grid size, the amount of historical data, and the number of available CPU cores can all significantly affect processing speed and total runtime.

The most practical approach is to download the software and test it on your own hardware. The binary includes a few example strategies. See the Download page to learn how to run a quick test.

Can I use Whale‑E in scripts or pipelines?

Yes. The software can be integrated into scripts, automation tools, and internal pipelines.

It can emit machine-readable JSON output for scripts and external tools. Top results can also be stored in a local SQLite database. This makes it practical to integrate it into automation, analysis, or reporting workflows instead of relying only on console output.

Can I use Whale‑E to provide services to third parties?

No. Internal use is allowed, including in scripts and internal pipelines. However, you may not make the software available to third parties or use it to provide third parties with backtesting, optimization, strategy research, or decision-support services.

This includes SaaS, APIs, managed services, and services delivered with the software. For the full legal terms, see the EULA.

Whale‑E doesn’t include the indicator I need. What should I do?

It does not yet let you build fully custom indicators with structured code.

The [[custom_series]] block already lets you create custom numeric series from a single expression. That expression can combine standard price series, outputs from indicators already defined in the strategy, as well as the variables they expose (for example fast.length, fast.type, fast.symbol, fast.timeframe), and, when needed, conditional logic through the ternary operator.

If the indicator you need cannot be expressed with custom_series, you can request it at support@whale-e.com. If the requested indicator does not already exist as a standard indicator in the Pine Script environment, your request must include a Pine Script version of it. Only indicators that are relevant to a broad user base will be considered for integration.

I exported my strategy to Pine Script, but the results differ. Why?

See the dedicated page: result alignment. It includes the full list of common causes and the complete diagnostic method.

Why do Sharpe and Sortino ratios differ from TradingView?

The Sharpe and Sortino ratios are not designed as a one-to-one copy.

When you use the same symbol, timeframe, date range, and settings, strategy logic stays aligned: the same signals, the same trades, and the same core backtest results.

The difference lies mainly in how they are used here. These ratios are mainly optimization scores used to compare and rank test runs. They are computed from portfolio-equity returns sampled at each close of the backtest’s native timeframe, then annualized so parameter sets, strategies, symbols, and timeframes can be evaluated on a consistent basis. TradingView, for its part, uses its own calculation method, including monthly return sampling, with an approach that is more focused on closed-trade performance.

For a detailed description of the source series, formulas, and annualization, see Metrics.

What developments are planned for Whale‑E?

Planned developments include the following:

• The number of available indicators will increase.
• The [[custom_series]] block will be expanded with more variables and control-flow structures to support more advanced custom indicators.
• Out-of-sample validation will be integrated into grid search so that each tested combination can also be evaluated with methods such as cross-symbol validation or walk-forward testing.
• A graphical interface will complement the command-line interface.

How do I report a bug or get help?

If you run into an issue or need help, email support@whale-e.com with your platform details, logs, and steps to reproduce the problem. The product is not the company’s primary business. Support requests are not handled in real time, and replies may take up to one week.