Statistical arbitrage of cointegrating currencies with pair trading where the signal for the next day is predicted using LSTM
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Updated
Sep 24, 2020 - Python
Statistical arbitrage of cointegrating currencies with pair trading where the signal for the next day is predicted using LSTM
A professional-grade quantitative trading system that implements statistical arbitrage through mean-reversion strategies on cointegrated asset pairs.
pair trading(stat arb), July 2017
Statsmodels: statistical modeling and econometrics in Python
A web app for pairs trading | cointegration | signals | streamlit
Robust backtesting suite for cointegration-based pairs trading on Nifty 50 (2015-2024) with Streamlit dashboard.
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Open-source cointegration & pairs-trading research package: CLI + tests + CI; Engle–Granger/Johansen, OU/ECM diagnostics, and walk-forward backtests with cost/benchmark controls..
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Implement research-grade statistical arbitrage pair trading pipeline with OOS validation
Python library for financial time series analysis and algorithmic trading. VECM-GARCH models, multivariate analysis, and trading strategies. Includes Udemy course materials.
A Python project that finds cointegrated asset pairs and generates Z-score based trading signals. Simulates a portfolio backtest.
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