Algo-Risk Monitor

Algo-Risk Monitor
PythonQuant FinanceStreamlitPlotly

Overview

Algo-Risk Monitor is an automated quantitative analysis suite that blends technical momentum signals with multi-layered risk analytics to turn raw market data into actionable insight. Highlights: - Logarithmic Returns and 21-day Annualized Volatility for risk standardization - RSI/SMA momentum overlays and candlestick dashboards - Parametric (Normal/Hull) and Historical VaR for single tickers and portfolios - Mean-Variance Optimization (MPT), Efficient Frontier search, and Monte Carlo for maximum Sharpe - Geometric Brownian Motion (GBM) scenario engine to simulate forward portfolio values - Interactive Streamlit web app with multi-page navigation and exportable CSV outputs

Supports auto-adjusted OHLCV via yfinance, including all 503 S&P 500 constituents. Built for notebook analysis and real-time web dashboards.

Key Features

  • Automated OHLCV data pipeline (yfinance)
  • Momentum & Trend: RSI, SMA-20/50 crossovers
  • Volatility & VaR: annualized vols, parametric (Hull) and historical VaR
  • Portfolio analytics: expected returns, covariance, efficient frontier
  • Optimization engine: 10,000+ Monte Carlo simulations, max Sharpe & min vol
  • Scenario engine: GBM with percentile bands (500+ paths)
  • Visual outputs: Plotly dashboards, Matplotlib/Seaborn distributions
  • Streamlit web app: interactive multi-page analysis
  • Smart weight input and validation (equal-weight option)
  • Correlation heatmap & performance pages

Technologies Used

PythonPandasNumPySciPyyfinancePlotlyMatplotlibSeabornStreamlitJupyter