Welcome to FMZ Quant Trading Platform
Programming Languages
Key Security
Live Trading
Strategy Library
Docker
Exchange
Strategy Editor
Backtesting System
Backtesting System Modes
Impact of Backtest Data Granularity on Backtesting
Backtesting System Supports Multiple Programming Languages
Exchanges Supported by Backtesting System
Backtest System Parameter Optimization
Save Backtest Settings
Custom Data Source
Local Backtesting Engine
Backtest Page Shortcuts
Backtest Data Download
Backtest System Sharpe Ratio Algorithm
Strategy Entry Functions
Strategy Framework and API Functions
Template Library
Strategy Parameters
Interactive Controls
Options Trading
C++ Strategy Writing Guide
JavaScript Strategy Writing Guide
Web3
Built-in Libraries
Extended API Interface
MCP Service
Trading Terminal
Data Explorer
Alpha Factor Analysis Tool
General Protocol
Debugging Tool
Remote Editing
Import and Export of Complete Strategies
Multi-language Support
Live Trading and Strategy Grouping
Live Trading Display
Strategy Sharing and Renting
Live Trading Message Push
Common Causes of Live Trading Errors and Abnormal Exits
Exchange-Specific Notes
Functions and Operators
The "{}" below represents placeholders, all expressions are case-insensitive, x represents data time series
abs(x), log(x), sign(x)Literal meaning, respectively absolute value, logarithm, sign function.
The following operators +, -, *, /, >, < also conform to their standard meanings, ==: equality check, ||: logical OR, x ? y : z: ternary conditional operator.
rank(x): Cross-sectional ranking, returns percentile position. Requires specifying candidate universe pool, cannot be calculated for single ticker and will return raw result directly.delay(x, d): Returns the value of series x from d periods ago.sma(x, d): Calculates the simple moving average of series x over d periods.correlation(x, y, d): Calculates the correlation coefficient between time series x and y over the past d periods.covariance(x, y, d): Calculates the covariance between time series x and y over the past d periods.scale(x, a): Normalizes data such thatsum(abs(x))=a(a defaults to 1).delta(x, d): Calculates the current value of time series x minus the value from d periods ago.signedpower(x, a):x^a.decay_linear(x, d): Calculates the d-period weighted moving average of time series x, with weights d,d-1,d-2....1 (normalized).indneutralize(x, g): Industry neutralization based on industry classification g, currently not supported.ts_{O}(x, d): Performs operation O on the past d periods of time series x (O can specifically represent min, max, etc., see below), d will be converted to integer.ts_min(x, d): Minimum value over the past d periods.ts_max(x, d): Maximum value over the past d periods.ts_argmax(x, d): Position ofts_max(x, d).ts_argmin(x, d): Position ofts_min(x, d).ts_rank(x, d): Ranking of time series x over the past d periods (percentile ranking).min(x, d):ts_min(x, d).max(x, d):ts_max(x, d).sum(x, d): Cumulative sum over the past d periods.product(x, d): Cumulative product over the past d periods.stddev(x, d): Standard deviation over the past d periods.