The short answer is yes. Here is python based stock forecast hosted on a Stremlit server. The problem that you may perceive is the slowness of the application from opening to waking up as it is hosted on a 'free' server.
Simulating the Uncertain: A Monte Carlo Tool for Portfolio Forecasting
Predicting financial outcomes is never linear. Markets shift, volatility spikes, and even the most well-balanced portfolios can drift from expected paths. This app is my attempt to model that uncertainty — an interactive Monte Carlo simulator built with Python and Streamlit that visualizes how portfolios might behave over time.Why Monte Carlo?
Monte Carlo simulations offer a powerful way to understand not just one possible outcome — but thousands. By layering randomized simulations over time, they help investors grasp the range of potential returns, risks, and deviations from baseline expectations.
What the App Does
This Streamlit-based simulator allows users to:
- Input initial price, volatility, time horizon, and number of simulations
- Generate thousands of price paths using statistical modeling
- Visualize results through intuitive charts and summary metrics
- Explore distributions of both absolute prices and percent changes
Key Visuals
Price Distribution
Shows how simulated final prices are distributed after a given time horizon.
Median, min, and max lines help anchor expectations
Useful for gauging downside risk and tail probability
Percent Change Distribution
Highlights performance relative to the initial investment.
See how often gains or losses occur over thousands of iterations
Spot asymmetry or skew in outcomes depending on volatility input
The Interactive app
Press enter or click to view image in full size
Under the Hood
Built with:
Front end: Streamlit
NumPy + Matplotlib for simulation and plotting
Modular architecture: simulator.py for logic, charts_mobile.py for visualization
The app is mobile-optimized and deploys seamlessly via Streamlit Cloud. It’s fast, responsive, and intuitive across devices.
Take a look
🚀Simulator
https://montecarlo-jsim.streamlit.app/
Experiment with parameters, observe outcome shifts, and explore the wide — and often surprising — spectrum of investment futures.
Verified link: 10/8/2025 OK
Conclusions
Financial modeling rarely gives certainty. But with tools like Monte Carlo simulations, we gain context — and context builds confidence. Whether you’re stress testing a strategy or simply curious about volatility’s effect on performance, this app gives you an interactive window into risk.
