Crate nyxs_owl 

NyxsOwl: A comprehensive financial analysis library for Rust

NyxsOwl provides production-ready quantitative finance tools including:

• Technical indicators (40+ indicators with SIMD optimization)
• Advanced forecasting strategies (7 models with adaptive features)
• High-performance backtesting framework
• Real-time market data processing
• Institutional-grade risk management

Quick Start

use nyxs_owl::prelude::*;
use nyxs_owl::common::time_series::sma;
use nyxs_owl::trade_math::momentum::calculate_rsi;
use polars::prelude::*;

let prices = vec![100.0, 102.0, 101.5, 103.0, 104.5];

// Simple technical analysis
let sma_values = sma(&prices, 3);
let price_series = Series::new("price".into(), &prices);
let rsi_series = calculate_rsi(&price_series, 3).unwrap();

println!("SMA: {:?}", sma_values);
println!("RSI length: {}", rsi_series.len());

Modules

async_parallel

Async and parallel processing capabilities for concurrent forecasting

common

Common types, traits, and utilities used throughout NyxsOwl

forecasting

Advanced forecasting models and strategies Forecasting module: Defines common traits, types, and errors for forecasting strategies. It also declares available forecasting model submodules like ARIMA.

memory_optimized

Memory optimization utilities and cache-conscious data structures Memory-Optimized Data Structures for High-Performance Financial Computing

performance_utils

High-performance SIMD-accelerated operations and utilities High-Performance SIMD-Accelerated Mathematical Operations

prelude

Common imports for typical NyxsOwl usage

simple_types

Shared types and error definitions for the simplified API

technical_strategies

Technical analysis strategies and implementations Technical Strategies Module: Technical analysis and trading strategy implementation

trade_math

Core module for technical indicator calculations and trading math Financial mathematics and technical analysis functions