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backtesting.py

kernc / backtesting.py

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calculation of `Buy & Hold Return`

3
zillionare
zillionare commented Apr 30, 2021

this is how Buy & Hold Return is calculated:

        c = data.Close.values
        s.loc['Buy & Hold Return [%]'] = (c[-1] - c[0]) / c[0] * 100  # long-only return

so it's calced use day one and the day last.

Expected Behavior

Buy & Hold Return is used for compare with strategy gain. Therefore, I guess they should started at same time, since the strategy get enough data to w

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bug good first issue Hacktoberfest

enzoampil / fastquant

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AlgoTraders / stock-analysis-engine

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Backtest 1000s of minute-by-minute trading algorithms for training AI with automated pricing data from: IEX, Tradier and FinViz. Datasets and trading performance automatically published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes and docker-compose. >150 million trading history rows generated from +5000 algorithms. Heads up: Yahoo's Finance API was disabled on 2019-01-03 https://developer.yahoo.com/yql/

docker kubernetes redis deep-neural-networks options deep-learning jupyter tensorflow helm s3 keras minio iex helm-charts stocks algorithmic-trading deep-learning-tutorial tradier backtesting iexcloud
  • Updated Sep 5, 2020
  • Jupyter Notebook
Stock.Indicators

DaveSkender / Stock.Indicators

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Star 420

Stock Indicators for .NET is a C# library package that produces financial market technical indicators. Send in historical price quotes and get back desired indicators such as moving averages, Relative Strength Index, Stochastic Oscillator, Parabolic SAR, etc. Nothing more. It can be used in any market analysis software using standard OHLCV price quotes for equities, commodities, forex, cryptocurrencies, and others. We had private trading algorithms, machine learning, and charting systems in mind when originally creating this community library.

package nuget forex cryptocurrency stock-market stock-indicators quantitative-finance technical-analysis algorithmic-trading technical-indicators indicators stock-analysis backtesting stock-trading historical-quotes
  • Updated Mar 20, 2022
  • C#

s-brez / trading-server

Star 390

A multi-asset, multi-strategy, event-driven trade execution and management platform for running many algorithms/bots at many venues simultaneously with unified risk management and reporting. Uses MongoDB for storage and Telegram for user notifications/trade consent.

mongodb telegram trading trading-bot algo-trading forex cryptocurrency derivatives trading-platform technical-analysis futures algorithmic-trading backtest quantitative-trading bitmex backtesting binance portfolio-management trading-execution ftx
  • Updated Mar 9, 2021
  • Python

roq-trading / roq-api

Star 229

The Roq C++20 API used for Live Cryptocurrency Algorithmic and High-Frequency Trading as well as for Back-Testing and Historical Simulation

cryptocurrency exchange market-data trading-platform low-latency trading-strategies trading-algorithms hft algorithmic-trading arbitrage order-book matching-engine fix-protocol order-management tick-data backtesting high-frequency-trading fix-engine market-making ultra-low-latency
  • Updated Mar 20, 2022
  • C++

xFFFFF / Gekko-BacktestTool

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Open

Mysterious error

5
ZongUin
ZongUin commented May 16, 2018

There is this error when I use backtest :

perl backtest.pl Gekko BacktestTool v0.6 Website: https://github.com/xFFFFF/Gekko-BacktestTool

Exchange list: history/binance_0.1.db
config/strategies/MACD.tomltrue[2018-05-16 14:29:20] Brute Force mode enabled
config/strategies/CCI.tomltrue[2018-05-16 14:29:20] Brute Force mode enabled
config/strategies/RSI.tomltrue[2018-05-16 14:29:20
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