rust_ti 2.1.4

A fully configurable technical indicators library with over 70 unique indicators written in pure Rust
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🦀 Meet RustTI

Say hello to RusTI, the clawed crusader of candlesticks and the battle-hardened cousin of Ferris! 🦀📈

Forged from rusted metal and born in the depths of the financial abyss, RusTI doesn't just ride sideways markets — he lives for them. With a stack of notebooks, a thousand-yard stare, and more indicators on his screen than legs on his body, RusTI is the ultimate trading bro. He reads charts, calculates MACD in his sleep, and isn’t afraid to pinch your code into shape.

Welcome to RustTI — powered by precision, performance, and one extremely serious crustacean.

RustTI

A highly configurable and high-performance technical indicators library written in pure Rust.

Designed for flexibility, speed, and advanced use cases in quantitative and algorithmic trading.

Looking for the Python version? PyTechnicalIndicators is what you're looking for.

🚀 Getting Started (Tutorial)

The fastest way to get up and running with RustTI.

1. Add RustTI to your project:

cargo add rust_ti

Or, manually in your Cargo.toml:

rust_ti = "2.1.4"

2. Calculate your first indicator:

use rust_ti;

let prices = vec![100.2, 100.46, 100.53, 100.38, 100.19];

let ma = rust_ti::moving_average::single::moving_average(
    &prices,
    rust_ti::MovingAverageType::Simple
);
println!("Simple Moving Average: {}", ma);

Expected output:

Simple Moving Average: 100.352

3. Explore more tutorials

🛠️ How-To Guides

Task-oriented guides for common problems and advanced scenarios.

(Contributions welcome! Submit your favorite how-to guide as a PR.)

📚 Reference

For complete API details, see docs.rs/rust_ti.

Example

A reference of how to call each function can be found

Clone and run:

cargo build
cargo run --example reference

Library Structure

  • Modules based on their analysis areas (moving_average, momentum_indicators, strength_indicators...)
  • bulk & single submodules
    • bulk: Compute indicator over rolling periods, returns a vector.
    • single: Compute indicator for the entire vector, returns a single value.
  • Types used to personalise the technical indicators (MovingAverageType, DeviationModel, Position...)

🧠 Explanation & Design

Why RustTI?

  • Performance: Pure Rust implementation for maximal speed, safety, and zero dependencies.
  • Configurability: Most indicators are highly customizable—tweak calculation methods, periods, or even use medians instead of means.
  • Breadth: Covers a wide range of technical indicators out of the box.
  • Advanced Use: Designed for users who understand technical analysis and want deep control.

Note: Some features may require background in technical analysis. See Investopedia: Technical Analysis for a primer.

📈 Available Indicators

All indicators are grouped and split into modules based on their analysis area.
Each module has bulk (vector output) and single (scalar output) submodules.

Standard Indicators

  • Simple, Smoothed, Exponential Moving Average, Bollinger Bands, MACD, RSI

Basic Indicators

  • Absolute Deviation, Log, Mean, Median, Mode, Std. Deviation, Variance, Max/Min

Candle Indicators

  • Ichimoku Cloud, Moving Constant Bands/Envelopes, Donchian Channels, Keltner, Supertrend

Chart Trends

  • Trend break down, overall trends, peak/valley trends

Correlation Indicators

  • Correlate asset prices

Momentum Indicators

  • Chaikin Oscillator, CCI, MACD, Money Flow Index, On Balance Volume, ROC, RSI, Williams %R

Moving Averages

  • McGinley Dynamic, Moving Average

Other Indicators

  • ROI, True Range, ATR, Internal Bar Strength

Strength Indicators

  • Accumulation/Distribution, PVI, NVI, RVI

Trend Indicators

  • Aroon (Up/Down/Oscillator), Parabolic, DM, Volume-Price Trend, TSI

Volatility Indicators

  • Ulcer Index, Volatility System

📊 Performance Benchmarks

Want to know how fast RustTI runs in real-world scenarios?
We provide detailed, reproducible benchmarks using realistic OHLCV data and a variety of indicators.

Momentum Indicators

Function Time per Operation
relative_strength_index 573.86 µs
stochastic_oscillator 784.13 µs
slow_stochastic 28.866 µs
slowest_stochastic 28.866 µs
williams_percent_r 76.256 µs
money_flow_index 150.69 µs
rate_of_change 5.3984 µs
on_balance_volume 17.405 µs
commodity_channel_index 103.19 µs
mcginley_dynamic_commodity_channel_index 66.044 µs
macd_line 51.482 µs
mcginley_dynamic_macd_line 44.461 µs
chaikin_oscillator 258.33 µs
percentage_price_oscillator 58.060 µs
chande_momentum_oscillator 370.14 µs

Candle Indicators

Function Time per Operation
moving_constant_envelopes 37.572 µs
mcginley_dynamic_envelopes 39.264 µs
moving_constant_bands 119.70 µs
mcginley_dynamic_bands 43.219 µs
ichimoku_cloud 192.93 µs
donchian_channel 28.481 µs
keltner_channel 318.05 µs
supertrend 148.80 µs

Trend Indicators

Function Time per Operation
aroon_up 16.531 µs
aroon_down 16.592 µs
aroon_indicator 66.468 µs
parabolic_time_price_system 43.939 µs
directional_movement_system 88.965 µs
volume_price_trend 6.2801 µs
true_strength_indx 705.25 µs

Strength Indicators

Function Time per Operation
accumulation_distribution 8.2935 µs
positive_volume_index 7.6977 µs
negative_volume_index 7.6167 µs
relative_vigor_index 505.34 µs

Other Indicators

Function Time per Operation
return_on_investment 40.962 µs
true_range 3.4663 µs
average_true_range 122.08 µs
internal_bar_strength 5.3943 µs
positivity_indicator 20.683 µs

Basic Indicators

Function Time per Operation
mean 5.7432 µs
median 333.68 µs
mode 931.09 µs
log 20.335 µs
log_difference 42.223 µs
variance 20.921 µs
standard_deviation 24.095 µs
absolute_deviation(Mean) 26.991 µs
absolute_deviation(Median) 345.14 µs
absoluite_deviation(Mode) 956.83 µs

Chart Trends

Function Time per Operation
peaks 93.094 µs
valleys 92.119 µs
peak_trend 188.14 µs
valley_trend 188.81 µs
overall_trend 10.337 µs
break_down_trends 14.655 ms

Correlation Indicators

Function Time per Operation
correlate_asset_prices 231.14 µs

Moving Average

Function Time per Operation
moving_average(Simple) 17.575 µs
moving_average(Smoothed) 76.601 µs
moving_average(Exponential) 78.505 µs
mcginley_dynamic 39.653 µs

Volatility Indicators

Function Time per Operation
ulcer_index 65.959 µs
volatility_system 137.25 µs

These results are from a Raspberry Pi 5 8GB, your machine will likely be faster!

👉 See all benchmarks and how to run your own

🤝 Contributing

Contributions, bug reports, and feature requests are welcome!

💬 Community & Support

📰 Release Notes

Latest (v2.1.4):

  • Minor document updates

Human friendly changelog →

Full changelog →

📄 License

MIT License. See LICENSE.