6 repository-uri
Awesome GitHub RepositoriesAlgorithmic Order Executions
Executes orders using time-weighted average price (TWAP) or volume-weighted average price (VWAP) algorithms.
Distinct from Order Execution Engines: Distinct from Order Execution Engines: focuses specifically on algorithmic order types like TWAP and VWAP, not general order execution.
Explore 6 awesome GitHub repositories matching scientific & mathematical computing · Algorithmic Order Executions. Refine with filters or upvote what's useful.
Awesome Algorithmic Order Executions GitHub Repositories
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- timercrack/trader
timercrack/trader
8,281Vezi pe GitHubThis project is a futures algorithmic trading system designed to execute high-performance trading strategies through direct API integrations and low-latency message routing. It features a strategy execution engine that automates order placement and manages trade flows based on predefined logic and API triggers. The system utilizes a native trading API bridge and a low-latency message bus to interface internal logic with external exchange APIs while minimizing execution delays. Monitoring is handled through a web-based trading dashboard for real-time activity tracking and remote management. B
Automates the placement and querying of trade orders by bridging strategy logic to the market.
Calgorithmctpfutures - ricequant/rqalpha
ricequant/rqalpha
6,166Vezi pe GitHubRQAlpha is a Python-native quantitative trading backtesting framework and live trading execution system. It provides an event-driven engine for simulating trading strategies against historical market data, with realistic transaction costs, slippage models, and corporate action handling. The platform supports multi-asset class trading including stocks, futures, options, and REITs, with separate sub-accounts for different asset types and configurable margin requirements. The framework distinguishes itself through a plugin-based extensible architecture that allows users to swap out core componen
Supports TWAP and VWAP algorithmic order types for executing trades in backtesting and live trading.
Pythonbacktestfinancefutures - wondertrader/wondertrader
wondertrader/wondertrader
5,865Vezi pe GitHubExecutes target positions through swappable algorithm units on a dedicated execution monitor separate from strategy engines.
C++algotradingcppcta - shinnytech/tqsdk-python
shinnytech/tqsdk-python
4,789Vezi pe GitHubtqsdk-python este un SDK și framework de tranzacționare cantitativă conceput pentru dezvoltarea de strategii automatizate pentru futures, opțiuni și acțiuni folosind Python. Acesta funcționează ca un motor de tranzacționare algoritmică și API de date financiare de piață, oferind instrumentele necesare pentru a backtest-a strategii, a analiza date istorice și a executa tranzacții live prin mai multe conturi de brokeraj. Proiectul se distinge printr-o bibliotecă specializată de analiză a opțiunilor care calculează Greeks, volatilitatea implicită și suprafețele de volatilitate folosind modelul Black-Scholes. Suportă în continuare tipare complexe de execuție a ordinelor, cum ar fi TWAP, Iceberg și POV, pentru a minimiza impactul asupra pieței în timpul intrării și ieșirii din poziții. SDK-ul acoperă o suprafață largă de capabilități, inclusiv regăsirea datelor de piață în timp real și istorice, gestionarea riscului cantitativ și monitorizarea portofoliului. Încorporează un model de execuție asincron pentru streaming-ul datelor și programarea sarcinilor, alături de instrumente pentru simularea tranzacționării multi-activ și analiza performanței. Biblioteca oferă o interfață grafică bazată pe web pentru monitorizarea strategiei și vizualizarea datelor.
Implements advanced trading patterns like TWAP and Iceberg orders to minimize market impact.
Python - binance/binance-connector-python
binance/binance-connector-python
2,755Vezi pe GitHubBinance Connector Python is a client library that provides programmatic access to the Binance cryptocurrency exchange, enabling automated trading and asset management across spot, margin, futures, and options markets. The library wraps the exchange's REST and WebSocket APIs into a Python interface with type-hinted methods, HMAC and RSA authentication, and a unified request-response pipeline for consistent error handling and rate limiting. The connector supports a broad range of exchange operations beyond core trading, including sub-account management, wallet operations, and algorithmic order
Supports placing algorithmic orders like TWAP and iceberg that execute gradually to minimize market impact.
Pythonbinance-apiconnectorcrypto - trademaster-ntu/trademaster
TradeMaster-NTU/TradeMaster
2,484Vezi pe GitHubTradeMaster is a reinforcement learning trading framework and algorithmic trading simulator designed for designing and testing quantitative trading strategies. The system provides a platform for developing reinforcement learning agents, managing quantitative portfolios, and optimizing trade execution using financial market data. The project features specialized components for multi-modality data preprocessing, a high-fidelity market environment simulation for strategy backtesting, and a quantitative portfolio manager for capital reallocation across multiple assets. It includes a trade executi
Optimizes the timing and volume of trade executions to minimize market impact and costs.
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