{"repo":"Heerozh/spectre","free":true,"listed":false,"github":"https://github.com/Heerozh/spectre","clone":"git clone https://github.com/Heerozh/spectre.git","description":"GPU-accelerated Factors analysis library and Backtester","language":"Python","stars":819,"topics":["spectre","algorithmic-trading","quantitative-analysis","factor-analysis","backtesting","backtester"],"license":"GPL-3.0","category":"trading","readme_excerpt":"spectre spectre is a GPU-accelerated Parallel quantitative trading library, focused on performance . Fast GPU Factor Engine, see below Benchmarks Pure python code, based on PyTorch, so it can integrate DL model very smoothly. Compatible with alphalens and pyfolio Python 3.7+, PyTorch 1.3+, Pandas 1.0+ recommended Installation Dependencies: Benchmarks My Machine： - i9-7900X @ 3.30GHz, 20 Cores - DDR4 3800MHz - 3090: GIGABYTE GeForce RTX 3090 GAMING OC 24G - 2080Ti: RTX 2080Ti Founders Running on Quandl 5 years, 3196 Assets, total 3,637,344 bars. spectre (CUDA/3090) spectre (CUDA/2080Ti) spectre (CPU) zipline.pipeline ---------------- ------------------------------- ------------------------------- ---------------------------- ----------------------- SMA(100) 87.9 ms ± 3.35 ms ( 33.9x ) 144 ms ± 974 µs ( 20.7x ) 2.68 s ± 36.1 ms (1.11x) 2.98 s ± 14.4 ms (1x) EMA(50) win=229 166 ms ± 3.25 ms ( 50.5x ) 270 ms ± 1.89 ms ( 31.0x ) 4.37 s ± 46.4 ms (1.74x) 8.38 s ± 56.8 ms (1x) (MACD+RSI+STOCHF).rank.zscore 184 ms ± 7.83 ms ( 77.7x ) 282 ms ± 1.33 ms ( 50.7x ) 6.01 s ± 28.1 (2.38x) 14.3 s ± 277 ms (1x) The CUDA memory used in the spectre benchmark is 1.8G, returned by cuda.max memory allocated(). Benchmarks excluded the initial run (no copy data to VRAM, about saving 300ms). Quick Start DataLoader First of all is data, you can use CsvDirLoader read your csv files. spectre also has built-in Yahoo downloader, symbols=None will download all SP500 components. You can use spectre.data.Arr","default_branch":null,"files":null,"tree":[],"storefront":"/r/Heerozh","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Heerozh/spectre/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}