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awesome-quant

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
https://github.com/wilsonfreitas/awesome-quant

Last synced: 10 days ago
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  • Python

    • Trading & Backtesting

      • riskparity.py - fast and scalable design of risk parity portfolios with TensorFlow 2.0
      • FinRL-Library - A Deep Reinforcement Learning Library for Automated Trading in Quantitative Finance. NeurIPS 2020.
      • aat - Async Algorithmic Trading Engine
      • Gunbot Quant - Toolkit for quantitative trading analysis. It integrates an advanced market screener, a multi-strategy, multi-asset backtesting engine. Use with built-in GUI or through CLI.
      • StrateQueue - An open‑source, broker‑agnostic Python library that lets you seamlessly deploy strategies from any major backtesting engine to live (or paper) trading with zero code changes and built‑in safety controls.
      • the0 - Self-hosted execution engine for algorithmic trading bots. Write strategies in Python, TypeScript, Rust, C++, C#, Scala, or Haskell and deploy with one command. Each bot runs in an isolated container with scheduled or streaming execution.
      • PRISM-INSIGHT - AI-powered stock analysis system with 13 specialized agents, automated trading via KIS API, supporting Korean & US markets.
      • Chartscout - Real-time cryptocurrency chart pattern detection with automated alerts across multiple exchanges
      • DayTradingBench - Live autonomous benchmark that evaluates LLM trading performance on DAX and Nasdaq indices using identical strategies and real-time market data. API access available.
      • CoinTester - No-code crypto backtesting platform with 100+ indicators, AI sentiment signals, and 5+ years of historical data across 1,000+ trading pairs.
      • PythonTradingFramework - commit/JustinGuese/python_tradingbot_framework/main) - Python algorithmic trading bot framework for Kubernetes: backtesting, hyperparameter optimization, 150+ technical analysis indicators (RSI, MACD, Bollinger Bands, ADX), portfolio management, PostgreSQL integration, Helm deployment, CronJob scheduling. Minimal overhead, production-ready, Yahoo Finance data.
      • QTradeX-AI-Agents - Example strategies for the QTradeX platfrom.
      • QTradeX-Algo-Trading-SDK - AI-powered SDK featuring algorithmic trading, backtesting, deployment on 100+ exchanges, and multiple optimization engines.
      • antback - A lightweight, event-loop-style backtest engine that allows a function-driven imperative style using efficient stateful helper functions and data containers.

    • Visualization

      • D-Tale - Visualizer for pandas dataframes and xarray datasets.
      • mplfinance - matplotlib utilities for the visualization, and visual analysis, of financial data.
      • finplot - Performant and effortless finance plotting for Python.
      • finvizfinance - Finviz analysis python library.
      • market-analy - Analysis and interactive charting using [market-prices](https://github.com/maread99/market_prices) and bqplot.
      • QuantInvestStrats - Quantitative Investment Strategies (QIS) package implements Python analytics for visualisation of financial data, performance reporting, analysis of quantitative strategies.
      • rallyplot - Fast, GPU-accelerated financial plotting library
      • rallyplot - Fast, GPU-accelerated financial plotting library

  • R

    • Backtesting

      • quantstrat - Transaction-oriented infrastructure for constructing trading systems and simulation. Provides support for multi-asset class and multi-currency portfolios for backtesting and other financial research.

    • Calendars

      • timeDate - Chronological and Calendar Objects
      • bizdays - Business days calculations and utilities

    • Data Sources

      • IBrokers - Provides native R access to Interactive Brokers Trader Workstation API.
      • Quandl - Get Financial Data Directly Into R.
      • Reddit WallstreetBets API - Provides daily top 50 stocks from reddit (subreddit) Wallstreetbets and their sentiments via the API.
      • Rblpapi - An R Interface to 'Bloomberg' is provided via the 'Blp API'.
      • Rbitcoin - Unified markets API interface (bitstamp, kraken, btce, bitmarket).
      • GetTDData - Downloads and aggregates data for Brazilian government issued bonds directly from the website of Tesouro Direto.
      • GetHFData - Downloads and aggregates high frequency trading data for Brazilian instruments directly from Bovespa ftp site.
      • td - Interfaces the 'twelvedata' API for stocks and (digital and standard) currencies.
      • rbcb - R interface to Brazilian Central Bank web services.
      • rb3 - A bunch of downloaders and parsers for data delivered from B3.
      • simfinapi - Makes 'SimFin' data (<https://simfin.com/>) easily accessible in R.
      • tidyfinance - Tidy Finance helper functions to download financial data and process the raw data into a structured Format (tidy data), including
      • Reddit WallstreetBets API - Provides daily top 50 stocks from reddit (subreddit) Wallstreetbets and their sentiments via the API.

    • Factor Analysis

      • FactorAnalytics - The FactorAnalytics package contains fitting and analysis methods for the three main types of factor models used in conjunction with portfolio construction, optimization and risk management, namely fundamental factor models, time series factor models and statistical factor models.
      • Expected Returns - Solutions for enhancing portfolio diversification and replications of seminal papers with R, most of which are discussed in one of the best investment references of the recent decade, Expected Returns: An Investors Guide to Harvesting Market Rewards by Antti Ilmanen.

    • Financial Instruments and Pricing

      • quantmod - Quantitative Financial Modelling Framework.
      • Rmetrics - The premier open source software solution for teaching and training quantitative finance.
      • fAsianOptions - EBM and Asian Option Valuation.
      • fAssets - Analysing and Modelling Financial Assets.
      • fBasics - Markets and Basic Statistics.
      • fBonds - Bonds and Interest Rate Models.
      • fExoticOptions - Exotic Option Valuation.
      • fOptions - Pricing and Evaluating Basic Options.
      • fPortfolio - Portfolio Selection and Optimization.
      • sde - Simulation and Inference for Stochastic Differential Equations.
      • YieldCurve - Modelling and estimation of the yield curve.
      • SmithWilsonYieldCurve - Constructs a yield curve by the Smith-Wilson method from a table of LIBOR and SWAP rates.
      • ycinterextra - Yield curve or zero-coupon prices interpolation and extrapolation.
      • AmericanCallOpt - This package includes pricing function for selected American call options with underlying assets that generate payouts.
      • VarSwapPrice - Pricing a variance swap on an equity index.
      • RND - Risk Neutral Density Extraction Package.
      • LSMonteCarlo - American options pricing with Least Squares Monte Carlo method.
      • OptHedging - Estimation of value and hedging strategy of call and put options.
      • tvm - Time Value of Money Functions.
      • OptionPricing - Option Pricing with Efficient Simulation Algorithms.
      • derivmkts - Functions and R Code to Accompany Derivatives Markets.
      • FinCal - Package for time value of money calculation, time series analysis and computational finance.
      • options.studies - options trading studies functions for use with options.data package and shiny.
      • RQuantLib - RQuantLib connects GNU R with QuantLib.
      • portfolio - Analysing equity portfolios.
      • sparseIndexTracking - Portfolio design to track an index.
      • covFactorModel - Covariance matrix estimation via factor models.
      • riskParityPortfolio - Blazingly fast design of risk parity portfolios.
      • credule - Credit Default Swap Functions.
      • r-quant - R code for quantitative analysis in finance.
      • PortfolioAnalytics - Portfolio Analysis, Including Numerical Methods for Optimizationof Portfolios.
      • fmbasics - Financial Market Building Blocks.
      • R-fixedincome - Fixed income tools for R.

    • Numerical Libraries & Data Structures

      • TSdbi - Provides a common interface to time series databases.
      • zoo - S3 Infrastructure for Regular and Irregular Time Series (Z's Ordered Observations).
      • tis - Functions and S3 classes for time indexes and time indexed series, which are compatible with FAME frequencies.
      • tfplot - Utilities for simple manipulation and quick plotting of time series data.
      • tframe - A kernel of functions for programming time series methods in a way that is relatively independently of the representation of time.
      • xts - eXtensible Time Series: Provide for uniform handling of R's different time-based data classes by extending zoo, maximizing native format information preservation and allowing for user level customization and extension, while simplifying cross-class interoperability.
      • data.table - Extension of data.frame: Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns and a fast file reader (fread). Offers a natural and flexible syntax, for faster development.
      • sparseEigen - Sparse principal component analysis.
      • TSdbi - Provides a common interface to time series databases.

    • Risk Analysis

    • Time Series

      • tseries - Time Series Analysis and Computational Finance.
      • fGarch - Rmetrics - Autoregressive Conditional Heteroskedastic Modelling.
      • timeSeries - Rmetrics - Financial Time Series Objects.
      • rugarch - Univariate GARCH Models.
      • rmgarch - Multivariate GARCH Models.
      • tidypredict - Run predictions inside the database <https://tidypredict.netlify.com/>.
      • tidyquant - Bringing financial analysis to the tidyverse.
      • timetk - A toolkit for working with time series in R.
      • tibbletime - Built on top of the tidyverse, tibbletime is an extension that allows for the creation of time aware tibbles through the setting of a time index.
      • matrixprofile - Time series data mining library built on top of the novel Matrix Profile data structure and algorithms.
      • garchmodels - A parsnip backend for GARCH models.

    • Trading

      • backtest - Exploring Portfolio-Based Conjectures About Financial Instruments.
      • pa - Performance Attribution for Equity Portfolios.
      • QuantTools - Enhanced Quantitative Trading Modelling.
      • TTR - Technical Trading Rules.
      • blotter - Transaction infrastructure for defining instruments, transactions, portfolios and accounts for trading systems and simulation. Provides portfolio support for multi-asset class and multi-currency portfolios. Actively maintained and developed.

    • Data Visualization

      • awesome-sec-filings - A curated list of tools, data sources, libraries, and resources for working with SEC filings (13F, 10-K, 10-Q, 8-K).

      • CONVEXFI - Official GitHub organization for the convex research group at the Hong Kong University of Science and Technology (HKUST).

  • Reproducing Works, Training & Books

    • Data Visualization

      • ML-Quant - Top Quant resources like ArXiv (sanity), SSRN, RePec, Journals, Podcasts, Videos, and Blogs.
      • QuantEcon - Lecture series on economics, finance, econometrics and data science; QuantEcon.py, QuantEcon.jl, notebooks
      • Auto-Differentiation Website - Background and resources on Automatic Differentiation (AD) / Adjoint Algorithmic Differentitation (AAD).
      • Derman Papers - Notebooks that replicate original quantitative finance papers from Emanuel Derman.
      • volatility-trading - A complete set of volatility estimators based on Euan Sinclair's Volatility Trading.
      • quant - Quantitative Finance and Algorithmic Trading exhaust; mostly ipython notebooks based on Quantopian, Zipline, or Pandas.
      • Quantitative-Notebooks - Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy
      • FinanceHub - Resources for Quantitative Finance
      • Python_Option_Pricing - An library to price financial options written in Python. Includes: Black Scholes, Black 76, Implied Volatility, American, European, Asian, Spread Options.
      • python-training - J.P. Morgan's Python training for business analysts and traders.
      • Stock_Analysis_For_Quant - Different Types of Stock Analysis in Excel, Matlab, Power BI, Python, R, and Tableau.
      • MEDIUM_NoteBook - Repository containing notebooks of [cerlymarco](https://github.com/cerlymarco)'s posts on Medium.
      • QuantFinance - Training materials in quantitative finance.
      • IPythonScripts - Tutorials about Quantitative Finance in Python and QuantLib: Pricing, xVAs, Hedging, Portfolio Optimisation, Machine Learning and Deep Learning.
      • Computational-Finance-Course - Materials for the course of Computational Finance.
      • Machine-Learning-for-Asset-Managers - Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos López de Prado.
      • Python-for-Finance-Cookbook - Python for Finance Cookbook, published by Packt.
      • modelos_vol_derivativos - "Modelos de Volatilidade para Derivativos" book's Jupyter notebooks
      • NMOF - Functions, examples and data from the first and the second edition of "Numerical Methods and Optimization in Finance" by M. Gilli, D. Maringer and E. Schumann (2019, ISBN:978-0128150658).
      • py4fi2nd - Jupyter Notebooks and code for Python for Finance (2nd ed., O'Reilly) by Yves Hilpisch.
      • aiif - Jupyter Notebooks and code for the book Artificial Intelligence in Finance (O'Reilly) by Yves Hilpisch.
      • py4at - Jupyter Notebooks and code for the book Python for Algorithmic Trading (O'Reilly) by Yves Hilpisch.
      • dawp - Jupyter Notebooks and code for Derivatives Analytics with Python (Wiley Finance) by Yves Hilpisch.
      • dx - DX Analytics | Financial and Derivatives Analytics with Python.
      • QuantFinanceBook - Quantitative Finance book.
      • rough_bergomi - A Python implementation of the rough Bergomi model.
      • frh-fx - A python implementation of the fast-reversion Heston model of Mechkov for FX purposes.
      • Value Investing Studies - A collection of data analysis studies that examine the performance and characteristics of value investing over long periods of time.
      • Machine Learning Asset Management - Machine Learning in Asset Management (by @firmai).
      • Deep Learning Machine Learning Stock - Deep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders.
      • Technical Analysis and Feature Engineering - Feature Engineering and Feature Importance of Machine Learning in Financial Market.
      • Differential Machine Learning and Axes that matter by Brian Huge and Antoine Savine - Implement, demonstrate, reproduce and extend the results of the Risk articles 'Differential Machine Learning' (2020) and 'PCA with a Difference' (2021) by Huge and Savine, and cover implementation details left out from the papers.
      • systematictradingexamples - Examples of code related to book [Systematic Trading](www.systematictrading.org) and [blog](http://qoppac.blogspot.com)
      • pysystemtrade_examples - Examples using pysystemtrade for Robert Carver's [blog](http://qoppac.blogspot.com).
      • ML_Finance_Codes - Machine Learning in Finance: From Theory to Practice Book
      • Hands-On Machine Learning for Algorithmic Trading - Hands-On Machine Learning for Algorithmic Trading, published by Packt
      • financialnoob-misc - Codes from @financialnoob's posts
      • MesoSim Options Trading Strategy Library - Free and public Options Trading strategy library for MesoSim.
      • Quant-Finance-With-Python-Code - Repo for code examples in Quantitative Finance with Python by Chris Kelliher
      • QuantFinanceTraining - This repository contains codes that were executed during my training in the CQF (Certificate in Quantitative Finance). The codes are organized by class, facilitating navigation and reference.
      • Statistical-Learning-based-Portfolio-Optimization - This R Shiny App utilizes the Hierarchical Equal Risk Contribution (HERC) approach, a modern portfolio optimization method developed by Raffinot (2018).
      • book_irds3 - Code repository for Pricing and Trading Interest Rate Derivatives.
      • Autoencoder-Asset-Pricing-Models - Reimplementation of Autoencoder Asset Pricing Models ([GKX, 2019](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3335536)).
      • Finance - 150+ quantitative finance Python programs to help you gather, manipulate, and analyze stock market data.
      • 101_formulaic_alphas - Implementation of [101 formulaic alphas](https://arxiv.org/ftp/arxiv/papers/1601/1601.00991.pdf) using qstrader.
      • Tidy Finance - An opinionated approach to empirical research in financial economics - a fully transparent, open-source code base in multiple programming languages (Python and R) to enable the reproducible implementation of financial research projects for students and practitioners.
      • RoughVolatilityWorkshop - 2024 QuantMind's Rough Volatility Workshop lectures.
      • AFML - All the answers for exercises from Advances in Financial Machine Learning by Dr Marco Lopez de Parodo.
      • AlgoTradingLib - A catalog of algorithmic trading libraries, frameworks, strategies, and educational materials.
      • KeepRule - Curated library of decision-making principles and investment wisdom from masters like Buffett and Munger, featuring mental models for better investment thinking.

      • Special-Relativity-in-Financial-Modeling - C++20 implementation of special-relativistic geometry applied to OHLCV data: Lorentz factors, spacetime intervals, Christoffel symbols, and geodesic deviation signals from live market data. DOI: 10.5281/zenodo.18639919.
      • Portfolio Optimization Book - Prof. Daniel Palomar's Portfolio Optimization Book. [GitHub](https://github.com/dppalomar/pob)
      • cipher-starter - tier wallet architecture, MEV mitigation, Canadian NI 31-103 compliance, Oracle Cloud Always Free infra, and a 7-day MVP calendar for a Solana signal engine + autonomous trading bot.
      • direct_vola - `Python` `R` - Demo code for direct Black-Scholes implied-volatility calculation from normalized call prices via the inverse-Gaussian quantile representation.
      • Deep Learning Machine Learning Stock - Deep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders.

  • Ruby

    • Data Visualization

      • Jiji - Open Source Forex algorithmic trading framework using OANDA REST API.

  • Rust

    • Data Visualization

      • QuantMath - Financial maths library for risk-neutral pricing and risk
      • Barter - Open-source Rust framework for building event-driven live-trading & backtesting systems
      • LFEST - Simulated perpetual futures exchange to trade your strategy against.
      • TradeAggregation - Aggregate trades into user-defined candles using information driven rules.
      • SlidingFeatures - Chainable tree-like sliding windows for signal processing and technical analysis.
      • RustQuant - Quantitative finance library written in Rust.
      • finalytics - A rust library for financial data analysis.
      • RunMat - Rust runtime for MATLAB-syntax array math with automatic CPU/GPU execution and fused kernels for quant simulations.

  • Scala

    • Data Visualization

      • QuantScale - Scala Quantitative Finance Library.
      • Scala Quant - Scala library for working with stock data from IFTTT recipes or Google Finance.

  • Sentiment Analysis & Alternative Data

    • CoWorker Fin-Agent - `Python` - LLM-powered A-share stock analysis via P2P agent collaboration. Technical analysis (MA60, volume-price patterns, golden eye), deep research reports using proprietary methodology, and market state summaries. Analysis logic stays private via Skill-as-API protocol.
    • StockKit - `TypeScript` - Free AI-powered stock research reports for US, China & HK using Claude Opus and multi-model AI with 20+ technical indicators. [GitHub](https://github.com/kentmswood-ui/stockkit)

  • Technical Indicators

    • fin-primitives - `Rust` - Financial market primitives in Rust: Price/Quantity/Symbol newtypes, BTreeMap order book, OHLCV aggregation, SMA/EMA/RSI indicators, position ledger with PnL, and composable risk monitor.
    • Wickra - `Rust` `Python` `JavaScript` `C++` `C#` `Golang` `Java` `R` - Streaming-first technical-analysis library with a Rust core: 514 indicators updating in O(1) per tick, with bit-exact batch-vs-streaming results.

  • Time Series Analysis

    • OmniOracle - `Python` - Automatic discovery of non-trivial statistical relationships across 500+ time series from FRED, World Bank, EIA, and NOAA using mutual information screening, lagged MI directional testing, and FDR correction.
    • wasserstein-btc - `Python` - Distributional forecasting of crypto log-returns by tangent-space geodesic extrapolation on the 2-Wasserstein manifold (quantile-function coordinates). Walk-forward CRPS evaluation over 6.75 years across 4 assets × 3 horizons; benchmarked against classical baselines (Static / RW-Drift / HS-Bootstrap / GARCH-N / GARCH-t / GJR-GARCH-t) and a named-econometric panel (HAR-RV, CAViaR-SAV, Markov-switching Normal, FIGARCH, AR(1) Stochastic Volatility, bivariate VAR+GARCH). [Live dashboard](https://accursedgalaxy.github.io/wasserstein-btc/).

  • Trading & Backtesting

    • AI Quant Agents - `Python` - Multi-agent LLM trading analysis where 12 AI agents (analysts, debaters, risk manager) debate stock picks in real-time, supporting US equities and China A-shares.
    • TradeSight - `Python` - AI-powered trading intelligence platform with paper trading, strategy optimization tournaments, 15+ technical indicators, and multi-market scanning.
    • Orallexa - `Python` - AI trading operating system with 9 ML models (RF, XGBoost, EMAformer, MOIRAI-2, Chronos-2, DDPM, PPO RL, GNN, LR) ranked by Sharpe ratio, Claude AI synthesis with dual-tier routing (~$0.003/analysis), real-time Next.js dashboard, Alpaca paper trading, and 277 automated tests.
    • FinClaw - `Python` - AI-powered financial intelligence engine with 8 master strategies across US, CN, and HK markets. Multi-agent architecture with +29.1% annual alpha. 227 tests.
    • jquantstats - `Python` - Modern variation of quantstats, with additional features and performance improvements.
    • VARRD - `Python` - AI-powered trading edge discovery platform that validates trading ideas with event studies, statistical tests, and real market data. Web app, MCP server, CLI (`pip install varrd`), and Python SDK.
    • JIT-Optimization-Engine - `Python` - High-performance analytical core using LLVM JIT (Numba) to process large-scale telemetry for quant diagnostics.
    • TradeClaw - `JavaScript` - Open-source AI trading signal platform with RSI/MACD/EMA confluence scoring, real-time signals for 10+ assets, self-hostable with one Docker command.
    • NexusFix - `CPP` - C++23 FIX protocol engine with zero-copy parsing and SIMD acceleration, 3x faster than QuickFIX.
    • income-desk - `Python` - Systematic options trading intelligence for small accounts with desk-based portfolio management, pre-trade validation, and multi-broker consolidation.
    • Vibe-Trading - `Python` - Natural-language multi-agent finance research agent with 29 swarm presets, 70 skills, and 28 auto-discovered tools; 7 backtest engines covering A-shares/US/Crypto/Futures/Forex/Options plus a cross-market CompositeEngine with shared capital pool; 5-source auto-fallback data layer (tushare/okx/yfinance/akshare/ccxt); 17-tool MCP server; includes trade-journal behavioral diagnostics for 同花顺/东财/富途 exports.
    • Lumibot - `Python` - Algorithmic trading framework where the same code runs for backtesting and live trading across stocks, options, crypto, futures, and forex with multiple brokers including Alpaca, Interactive Brokers, Tradier, and Schwab.
    • backtester-mcp - `Python` - Local-first backtesting engine with built-in overfitting checks (PBO, deflated Sharpe, bootstrap CI, walk-forward) and a native MCP server for AI agents. [GitHub](https://github.com/bcosm/backtester-mcp)
    • NexusFix - `CPP` - C++23 FIX protocol engine with zero-copy parsing and SIMD acceleration, 3x faster than QuickFIX.
    • Sextant - `Python` - Local event-driven backtesting engine with no-code strategy builder and FRED vintage, ALFRED, yFinance support.
    • DeepAlpha - `Python` - AI crypto trading bot for Bybit with 70.9% walk-forward validated accuracy on out-of-sample data, LightGBM + XGBoost ensemble with 72 ML features. [GitHub](https://github.com/stefanoviana/deepalpha)
    • aurumq-rl - `Python` - Reinforcement learning stock-selection framework for the China A-share market with multi-source factor input (alpha101 + main-force flow + hot-money seats + northbound + institutional + fundamentals), board-aware price limits, and ONNX CPU inference.
    • flashalpha-fill-simulator - `Python` - Realistic limit-order fill simulator for options credit/debit spreads with post-and-wait limits, stale-quote guards, deterministic same-bar tiebreaks, and a patient-then-cross exit; engine-agnostic and zero runtime dependencies.
    • binance-fix-connector-python - `Python` - Async Python connector for Binance Spot FIX sessions with Order Entry, Market Data, and Drop Copy support.
    • ShowMe - `Python` `Rust` `TypeScript` - Open-source native macOS market cockpit. 12-timeframe consensus scan across 3370 symbols (crypto + equity + ETF + FX + commodity + bond), 23 technical indicators with per-market calibration, real WebSocket streaming. Tauri shell + Python sidecar (FastAPI) + React UI; 110+ exchanges via ccxt.
    • TBV1 - `Python` - Crypto perpetual-futures bot with a 7-tab web dashboard and a 15-indicator consensus engine voting across 12 timeframes (1m → 1d). Paper-mode by default. Includes packaged macOS reference build and Windows distribution.
    • AlgoVault - `TypeScript` - MCP server returning composite crypto trade verdicts (direction, confidence, regime) across 5 perpetual-futures venues, with cross-venue funding-rate arbitrage and an on-chain Merkle-verified track record. Free tier.
    • capitalcom-cli - `Python` - Unofficial CLI and async SDK for the Capital.com broker API: market data, guarded order execution, and real-time streaming.
    • mx-trader-bridge - `Python` - AI auto-trading bridge for East Money's miaoxiang (妙想) China A-share simulation platform; BYOK multi-LLM (OpenAI/DeepSeek/Moonshot/GLM/Qwen) decision brain → automated order placement via miaoxiang API, with daily cron review and weekly AI reflection.
    • DeepAlpha - `Python` - AI crypto trading bot for Bybit with 70.9% walk-forward validated accuracy on out-of-sample data, LightGBM + XGBoost ensemble with 72 ML features. [GitHub](https://github.com/stefanoviana/deepalpha)
    • backtester-mcp - `Python` - Local-first backtesting engine with built-in overfitting checks (PBO, deflated Sharpe, bootstrap CI, walk-forward) and a native MCP server for AI agents. [GitHub](https://github.com/bcosm/backtester-mcp)
    • TBV1 - `Python` - Crypto perpetual-futures bot with a 7-tab web dashboard and a 15-indicator consensus engine voting across 12 timeframes (1m → 1d). Paper-mode by default. Includes packaged macOS reference build and Windows distribution.
Programming Languages
Python 179 Jupyter Notebook 40 R 32 Julia 16 C++ 13 TypeScript 12 Rust 9 HTML 6 JavaScript 4 Go 3
Categories
Python 259 R 77 Reproducing Works, Training & Books 55 Market Data & Data Sources 36 Commercial & Proprietary Services 31 Trading & Backtesting 27 Julia 24 Frameworks 12 Rust 8 JavaScript 8 Java 7 CPP 6 Financial Instruments & Pricing 6 Prediction Markets 6 Matlab 4 Cross-Language Frameworks 3 Portfolio Optimization & Risk Analysis 3 Golang 3 Elixir/Erlang 3 Haskell 3 Numerical Libraries & Data Structures 3 Sentiment Analysis & Alternative Data 2 Technical Indicators 2 CSharp 2 Visualization 2 Related Lists 2 Scala 2 Time Series Analysis 2 Factor Analysis 2 Ruby 1 Excel & Spreadsheet Integration 1
Sub Categories
Data Visualization 92 Trading & Backtesting 88 Data Sources 82 Financial Instruments and Pricing 63 FrameWorks 40 Time Series 22 Risk Analysis 21 Numerical Libraries & Data Structures 17 Excel Integration 10 Visualization 8 Indicators 6 Calendars 5 Factor Analysis 5 Trading 5 Alternatives 2 Sentiment Analysis 2 Quant Research Environment 1 Backtesting 1
Keywords
finance 87 python 80 trading 62 quantitative-finance 61 algorithmic-trading 47 trading-strategies 37 cryptocurrency 32 machine-learning 32 backtesting 31 quant 28 technical-analysis 28 pandas 22 time-series 22 quantitative-trading 21 stock-market 21 trading-bot 20 crypto 18 financial-data 17 trading-algorithms 17 investment 17 algotrading 17 stocks 15 financial-analysis 15 trading-platform 14 stock 14 data-science 14 investing 13 market-data 13 stock-data 13 r 13 fintech 13 derivatives 11 portfolio-optimization 11 algo-trading 11 bitcoin 10 investment-analysis 10 julia 10 forex 10 rust 9 timeseries 9 risk-management 9 options 9 deep-learning 9 python3 9 backtesting-trading-strategies 8 binance 8 yahoo-finance 8 quantitative-analysis 8 ai 8 technical-indicators 8