stock-trek 0.2.8

Stock Trek time-series analysis python bindings

stock-trek

A lightweight, composable time series and statistical toolkit designed for running crypto bots on stock-trek.com. Rust-native core with optional Python bindings

Overview

stock-trek provides core abstractions and utilities for working with market data, including:

• Order books
• Aligned/Rolling windows
• Ticks
• Statistical and analytical functions

Installation

Add to your Cargo.toml:

[dependencies]
stock-trek = "0.2.8"

Python Bindings

stock-trek also provides Python bindings which can be installed via

pip install stock-trek

Usage

Implement the StockTrekAlgorithm trait and register it with the annotation #[register_algorithm]:

use stock_trek::prelude::*;
use stock_trek::signal::*;

pub struct MyAlgo;

#[register_algorithm]
impl StockTrekAlgorithm for MyAlgo {
    fn create_signal(&self, context: StockTrekContext) -> StockTrekSignal {
        StockTrekSignal::builder()
            .instrument(
                Instrument::builder()
                    .product(crate::signal::InstrumentProduct::Spot)
                    .base("BTC")
                    .quote("USDT"),
            )
            .market_context(
                MarketContext::builder()
                    .market_regime(
                        MarketRegime::builder()
                            .classifications(
                                MarketRegimeClassifications::builder()
                                    .confidence(0.5)
                                    .dominant("")
                                    .top_alternatives(std::collections::HashMap::from([
                                        ("dskfsd".into(), 0.21),
                                        ("irewtnvc".into(), 0.17),
                                        ("cfhwrehk".into(), 0.15),
                                    ]))
                                    .unclassified(0.2),
                            )
                            .cycle(
                                MarketRegimeCycle::builder()
                                    .accumulation(0.3)
                                    .distribution(0.5)
                                    .markdown(0.1)
                                    .markup(0.2)
                                    .neutral(0.8),
                            )
                            .trend(
                                MarketRegimeTrend::builder()
                                    .bearish(0.6)
                                    .bullish(0.2)
                                    .sideways(0.2),
                            )
                            .volatility(
                                MarketRegimeVolatility::builder()
                                    .snapshot(
                                        MarketRegimeVolatilitySnapshot::builder()
                                            .high(0.1)
                                            .low(0.9),
                                    )
                                    .trend(
                                        MarketRegimeVolatilityTrend::builder()
                                            .compression(0.5)
                                            .expansion(0.5),
                                    ),
                            ),
                    )
                    .regime_persistence(
                        RegimePersistence::builder()
                            .regime_persistence_confidence(0.7)
                            .remaining_durations_millis(483648732),
                    ),
            )
            .prediction(
                Prediction::builder()
                    .horizon_confidences_by_millis(HorizonConfidencesByMillis(
                        std::collections::HashMap::from([
                            ("vgfhgkfd".into(), 549357438),
                            ("cdiotkjr".into(), 549357438),
                        ]),
                    ))
                    .optimal_horizon_millis(1000)
                    .percentage_changes(
                        ConfidencePercentageChanges::builder()
                            .p01(-10.2)
                            .p05(-5.1)
                            .p10(-0.4)
                            .p25(3.9)
                            .p50(10.2)
                            .p75(16.5)
                            .p90(19.4)
                            .p95(20.4)
                            .p99(20.8),
                    )
                    .risk(
                        PredictionRisk::builder()
                            .percentage_risks(
                                PredictionRiskPercentageRisks::builder()
                                    .cvar_95(-6.8)
                                    .cvar_99(-7.2)
                                    .max_drawdown_95(25.3)
                                    .max_drawdown_99(31.8)
                                    .var_95(-3.7)
                                    .var_99(-4.5),
                            )
                            .risk_factors(std::collections::HashMap::from([
                                ("dvxvxvvodsgrg".into(), 0.63),
                                ("cnnfgvcxojtnn".into(), 0.41),
                            ])),
                    )
                    .validity_duration_millis(1_000_000),
            )
            .try_into()
            .expect("Expected StockTrekSignal")
    }
}

Stock-Trek verifies code before running it and disallows certain syntax elements. To verify code locally, install it with

cargo install stock-trek

then run the verify command with

stock-trek verify --file ./path/to/my/code/file.rs

Roadmap

Planned features include:

• Technical indicators (EMA, RSI, MACD, etc.)
• Backtesting and simulation utilities

Status

This project is in early development (0.x). APIs may change.

License

MIT