Figshare
open access
CC BY 4.0
What a Backtest Costs: Throughput, Memory, Scaling and Reproducibility of Four Backtesting Engines on a 64-Core CPU
We measure the wall time and memory of one backtest in Backtrader, NautilusTrader, QuantConnect LEAN and Reamer Research. We also measure how both grow with bar count (50,000 and 500,000 bars), ticker breadth (10 to 100 tickers) and parallel copies (1 to 64). Every engine runs the same
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
2026-10-26T09:37:57Z https://api.figshare.com/v2/oai The request includes illegal arguments, is missing required arguments, includes a repeated argument, or values for arguments have an illegal syntax.
Related documents
- Data Center Benchmarking Methodology#399345
- RECOB: Reliable Benchmarking of Experimental Optimization in Chemistry and Materials Science#1034865
- EPR Count for Runtime Prediction in Distributed Quantum Computing#1160989
- EPR Count for Runtime Prediction in Distributed Quantum Computing#1145018
- StateSync-GKR: Design and Evaluation of a Reusable Sparse GKR Engine#1325745
Record · ID 1449127 · SHA-256 fd03c1ed45632c81
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive