Finance
Unverified ML strategy on Indices by shashankvemuri. BotFinder score 18 out of 100.
Python toolkit for quantitative finance: stock analysis, technical indicators, strategy backtesting, portfolio optimization, and financial modeling.
Source: github
BotFinder analysis pending.
Finance
Finance Finance is a Python toolkit for market data, technical indicators, financial analysis, stock screening, strategy research, backtesting, portfolios and statistical models. Calculations use explicit inputs, a small dependency set and tested execution conventions. Models and trading rules are research tools; runnable examples are the starting point. Install Python 3.12 or newer: Core dependencies are NumPy and pandas. Add only the features you need: Use Download normalized, consistently adjusted OHLCV with the data extra: Calculate indicators without any network access: Generate close-time signals and execute them at the next open: Returns and rates are fractions; RSI is 0–100. Warm-up values remain missing. The modest backtester tracks cash, fractional shares, long/short fills, commission, slippage and borrow costs. Read the calculation and execution conventions before interpreting results. Explore | Area | Capabilities | | --- | --- | | data | OHLCV/intraday, Finviz discovery, statements, calendars, analysts, news, transcripts, insiders and universes | | indicators | Moving av
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Open-source maintainer on GitHub.
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