portfolio optimization with backtesting
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Updated
Apr 24, 2021 - Jupyter Notebook
portfolio optimization with backtesting
a small script to backtest using a Kalman filter as a trading tool on the EURUSD 5min pair
Back Testing strategies fast in Python
Contains an universal investment strategy backtester. Used by Alpha Rho Technologies LLC
Pot 50 & 200 days Simple moving average (SMA). Created class SMApython and used in TestOne
Backtesting Algo-Trading Strategies, FinTech Analysis & Portfolio Optimization: NVDA, AMD, INTC, MSI vs S&P 500 Benchmark
Backtesting and optimizing a bitcoin/crypto moving average crossover algorithm on Binance data
Bitcoin price analysis and forecast with deep learning
Backtesting and forward testing investment algorithms in the BR Stocks
Machine Learning Bot is a Jupyter Notebook based application prototype to perform algorithmic trading using a Machine Learning algorithm.
Optimization of a trading strategy through Quantconnect.com
Stock Data Analysis
Backgommon is a backtesting and simulation framework for trading strategies, written in pure go. It aims to be fast, flexible and easy to use.
Java-based project related to the stock market, that provides statistical and technical tools to help users back-test and analyze their custom strategies under market dynamics.
This is the repo for a cryptocurrency trading program
A comprehensive system enable discovering profitable strategies in the market of TWSE and TPEx.
This code backtests the performance of SPY vertical bull put spreads from Jan 2022 to May 2022
Using a LSTM Deep Learning model to predict future market opening prices of BTC/USD using timesteps. Comprehensive backtesting illustrating Cumulative returns, average holding time, maximum loss and profit attained by the trading model. Risk management techniques for stop-loss orders and position sizing are also included.
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