#计算机科学#Quantitative analysis, strategies and backtests
#计算机科学#Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
algo trading backtesting on BitMEX
#区块链#Professional Backtesting Engine for crypto, stocks and forex
Contains detailed and extensive notes on quantitative trading, leveraging NLP for finance, backtesting, alpha factor research, portfolio management and optimization.
In this project, I had backtested the cross-over trading strategy on Google Stock from Jan 2016 to June 2020. By using historical time-series data, I had tested the Moving Average(MA) cross-over strat...
VectorBT Backtesting
#计算机科学#This repository consists several bots encoding various algorithmic trading strategies. The aim here is for absolute beginners in stock trading to get familiar with the various aspects of the market. A...
#计算机科学#Analyze historical market data using Jupyter Notebooks
A proof-of-concept custom backtester
This is a backtesting demo in Python. Different moving average prices are used to make buy and sell decisions. A Jupyter notebook version is for serial mode. while py version is for multiprocessing. A...
Algorithmic Trading Model Development for BTC/USDT Crypto Market. Crafting models that outperform benchmarks, balancing returns and risk management in the dynamic BTC/USDT market.
Daily Volatility trading strategies on Index Equity Options
#计算机科学#This repo gives an introduction to trading using support vector machines
Explore and leverage the correlation between oil price movements, energy sector, and transportation sector. This repository houses quantitative research findings and trading strategies that exploit th...
Pot 50 & 200 days Simple moving average (SMA). Created class SMApython and used in TestOne
📈 𝗔𝗻 𝗲𝗻𝘀𝗲𝗺𝗯𝗹𝗲 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆 𝗳𝗼𝗿 𝗯𝗮𝗰𝗸𝘁𝗲𝘀𝘁𝗶𝗻𝗴 𝘀𝘁𝗼𝗰𝗸 𝗽𝗿𝗶𝗰𝗲 𝗰𝗼𝗺𝗯𝗶𝗻𝗶𝗻𝗴 𝗕𝗼𝗹𝗹𝗶𝗻𝗴𝗲𝗿 𝗕𝗮𝗻𝗱𝘀 𝗮𝗻𝗱 𝗟𝗦𝗧𝗠 𝗺𝗼𝗱𝗲𝗹𝘀
This is a Backtrader example using ICICIDirect Breeze API
#区块链#Momentum trading strategy for crypto using ML (XGBoost) vs traditional logic — with backtesting, VaR risk analysis & Monte Carlo simulation.