Orca
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Introduction
Documentation Guide for v2.1.0 and above

ORCA: Vectorized backtesting for quants

Orca is a vector based backtesting system and currently supports multiple asset classes including equities, forex, options, futures and cryptocurrencies. Orca also provides data for backtesting at 1M, 5M and 1D timeframes. All additional timeframes can be resampled from this data. Day level data goes back until 2007, 5M data goes back to 2015 and 1M data goes back to 2018.
In addition to the strategy code, you will need some additional parameters such as capital, timeframe that needs to be added through the dropdowns in SharkSigma

Features

Orca consists of multiple features such as:
  • Flow handler: ensures that data flow is correct end to end
  • Indicators: We have a custom indicator library that contains all widely used TA as well as custom indicators. In addition, Orca supports popular indicator libraries (comes prebuilt with Orca) such as ta, pandas-ta
  • Backtesting base: main files that performs backtesting end to end
  • Get data module: gets backtest data needed. Supports equities, forex, options, futures and crypto and timeframes of 1M, 5M and 1D
  • Trade execution module: ensures trades are generated from transactions
  • Performance metrics: creates two types of metrics: one from trades DF and one that is based on capital
  • Data store: ensures that backtesting outputs are stored correctly
  • Tearsheets: creates an institution grade tearsheet with performance metrics
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ORCA: Vectorized backtesting for quants
Features