An implementation of trading strategies such as the Stochastic Oscillator with support and resistance using the BackTrader framework for backtesting

A modular and flexible backtesting framework for trading strategies in Python using Backtrader.

This project backtests an SMA crossover strategy in Python, using Backtrader and yfinance, with optimization through grid search to find the best parameters.

Modular backtesting framework for algorithmic trading using Backtrader. Features a 4-phase state machine strategy, JPY pair P&L correction (ERIS logic), and professional reporting. Educational resource for learning systematic trading.

Backtesting, Strategy development and adding indicators using Backtrader

Backtesting strategies using Backtrader.py

Backtesting strategies using Backtrader and AlphaVantage

Backtesting a 30d Returns based strategy with Backtrader and making a report with Quantstats. Done on BTC-USDT historical data.

Aim to create a platform to do: 1. automatically download crypto data from binance 2. organize data using dolphin_db 3. backtest strategies using backtrader 4. trading system 5. portofolio monitor

A comprehensive statistical arbitrage (pairs trading) bot that downloads stock data from Yahoo Finance using yfinance, finds cointegrated pairs via the Engle–Granger test, trades the spread using z-score entry and exit rules, and backtests the strategy with Backtrader.

Backtesting strategy using Python and Backtrader

hypertuning hyper parameter optimization imp backtrader Implement and do backtest strategies about Korean market using Backtrader Framework and Creon API.

Backtest for strategy H using Backtrader

Backtesting a long short strategy in N100 using backtrader module.

Backtesting various trading strategies using the Backtrader module in Python.

Backtesting implementation of a Moving Average Crossover strategy for commodities trading using Backtrader. The script evaluates performance with metrics like Sharpe Ratio, Max Drawdown, and Annual Returns. Easily adaptable to different commodities and datasets for strategy analysis.

Building a long-short strategy using self-made functions and backtest them via backtrader python modules

Backtest Strategies using BackTrader

strategy backtesting platform using backtrader

Performing a backtest of a trading strategy using backtrader

Perform backtesting on different strategies using backtrader Python library

A simple moving average crossover strategy for backtesting using Python and Backtrader.

Full-cycle quantitative strategy research using a time-series momentum signal with Backtrader backtesting and risk analysis.

This project uses a Random Forest model to predict Bitcoin market movements and execute trades using the Backtrader library for backtesting strategies.

Backtesting framework for SMA crossover strategy using Backtrader. Includes parameter optimization (fast/slow SMA), performance analytics (Sharpe, Sortino, Volatility, Winrate), and 3D visualization of strategy metrics

Algorithmic Trading & Backtesting using Exponential Moving Average (EMA) crossover strategy in Python using Backtrader, leveraging historical stock data to generate automated buy/sell signals.

Interactive backtesting framework for trading strategies using Streamlit, Backtrader, and Yahoo Finance. Implements Luca's Strategy with data caching, moving averages, and crossover techniques for actionable insights.

Statistical arbitrage strategy for Hang Seng ETF (2800.HK) using yfinance, XGBoost for signals, and Backtrader backtesting. Built to explore quant trading opportunities.

Synthetic Market Simulator using GANs + Backtrader A generative adversarial network (GAN)-based system to simulate realistic synthetic financial time-series data, followed by backtesting with trading strategies like RSI using Backtrader. This project enables robust evaluation of algorithmic strategies without relying solely on real market data.

This project implements a Mean Reversion Trading Strategy using Backtrader and Yahoo Finance (yfinance) to backtest asset prices. The strategy is based on Bollinger Bands, a common technical indicator used to identify potential overbought and oversold conditions in the market.