Portfolio Simulation: Complete Guide to Probabilistic Risk Analysis for Indian Investors

Portfolio simulation is a probabilistic method that generates thousands of possible future outcomes for your investments, showing not just what might happen but how likely each outcome is. Unlike traditional tools that show only past performance or single average returns, simulation reveals loss probabilities, worst-case scenarios, and tail risks. Use it to understand if your portfolio matches your risk tolerance, compare strategies (lump sum vs SIP), and stress-test against historical crashes like 2008 or COVID-19.

Loss probability is the percentage of simulation scenarios where your portfolio's final value is less than your total invested capital. For example, a 25% loss probability means that in 1 out of 4 possible futures, you would end with less money than you started. This metric helps you understand the likelihood of nominal losses over your investment horizon. Conservative investors typically target loss probabilities below 10-15%, while aggressive investors may accept 25-35% loss probability in exchange for higher upside potential.

Loss probability tells you the chance of losing money, but not how much you might lose. Expected shortfall (also called Conditional Value at Risk or CVaR) answers: "In the worst 5% of scenarios, what is my average loss?" For example, a portfolio might have 20% loss probability, but if a loss occurs, the expected shortfall could be 30% of your investment. This distinction is crucial — a low loss probability with severe losses when they occur is very different from a higher loss probability with small losses.

Yes. Stock360s Portfolio Simulation supports all Indian mutual funds (via mf_nav table with daily NAV), ETFs (via etf_metrices), and bonds (via combined_bond_master). For newly launched ETFs without full price history, the system synthesizes returns using the underlying index returns plus student-t shocks. Mutual fund simulations use actual historical NAV data. Currently, only Indian assets are supported — US stocks and international ETFs are not available.

No. The AI interpretation (generated by Llama 3.1 on Hugging Face) is purely educational. It translates statistical outputs (loss probability, expected shortfall, diversification efficiency, etc.) into plain English. It does not provide personalized investment recommendations, tax advice, or SEBI-regulated advisory services. Always consult a registered investment advisor before making financial decisions.

Stock360s runs a minimum of 1,000 Monte Carlo simulations for each request. For complex portfolios or higher precision needs, the system may run up to 5,000 simulations. The exact number is determined dynamically based on portfolio complexity and convergence criteria. Each simulation generates a complete wealth path over your chosen horizon (1-10 years) with monthly time steps.

Diversification efficiency measures how much volatility is reduced by holding multiple assets versus holding them individually. The formula is: (1 - portfolio_volatility / weighted_avg_asset_volatility) × 100. Scores above 20% indicate good diversification. Scores above 40% indicate excellent diversification (typical of well-constructed multi-asset portfolios). Scores below 10% suggest poor diversification where assets move together (high correlation), offering little risk reduction benefit.

Hidden leverage doesn't mean you've borrowed money. It means your portfolio behaves as if it had borrowed — amplifying both gains and losses. The system detects hidden leverage when at least two of three conditions are met: factor beta > 1.8 (high market sensitivity), average correlation > 0.6 (assets move together), or volatility ratio > 1.3 (portfolio more volatile than weighted assets). Consider reducing concentrated factor bets or adding uncorrelated assets.

The system analyzes the last 30 days of NIFTY returns and volatility from the india_market_history table. Based on return magnitude and volatility level, it classifies the regime as: Fear/Crash (negative returns, high volatility), Broad Bull (positive returns, normal volatility), High Volatility Chop (flat returns, high volatility), or Normal (trending within 1 standard deviation). This regime then adjusts simulation parameters — Fear/Crash multiplies volatility by 1.5 and reduces drift by 0.15 annualized.

Monte Carlo is forward-looking — it generates thousands of possible future paths based on historical return patterns, volatility, and correlations. It shows a range of outcomes but doesn't guarantee any specific path will occur. Backtest is backward-looking — it replays exactly what happened to your portfolio during specific historical crises (2008, COVID-19, 2022). Backtest shows deterministic results (this is exactly what would have happened), but past performance doesn't guarantee future results. Use both: Monte Carlo for uncertainty, backtest for stress testing.

Yes. Use the Regret Analysis mode to compare any two strategies — lump sum vs SIP, invest now vs delay 6 months, equity-heavy vs balanced portfolio. The simulation runs 1,000+ paths for each strategy, computes median outcomes, loss probabilities, and expected shortfall. It then calculates "regret" — the opportunity cost of choosing the worse strategy — expressed as a percentage and annualized cost. This helps you quantify the trade-off between potential returns and downside protection.

Simulation accuracy depends on how well historical patterns represent future market behavior. No model can predict future returns with certainty. Stock360s uses empirically validated methods: multivariate t-distribution (df=4) for fat tails, regime-aware drift adjustments, and shrunk covariance matrices to reduce estimation error. However, black swan events, structural market changes, and unforeseen crises are not perfectly captured. Use simulations as decision-support tools, not guarantees.

Currently, Stock360s Portfolio Simulation supports only Indian equities (NSE/BSE stocks with .NS suffix), Indian mutual funds, Indian ETFs, and Indian bonds (government and corporate). US stocks, international ETFs, cryptocurrencies, commodities (except gold ETFs), real estate, and private equity are not supported. Support for additional asset classes is under development.

The survival score is a composite metric (0-100) evaluating portfolio resilience. Weights: maximum drawdown (30%), loss probability (25%), expected shortfall (20%), volatility (15%), diversification efficiency (10%). Each metric is normalized and scored, with higher scores indicating better resilience. A score above 70 suggests robust portfolio construction; scores below 40 indicate significant vulnerabilities. The score helps you quickly assess if your portfolio can withstand market stress.

Yes. After running a simulation, your portfolio is automatically saved to your browser's local storage. When you return to the Portfolio Simulator page, it will load your last portfolio automatically. To save multiple portfolios, use the "Export Portfolio" feature (coming soon). Note: local storage is browser-specific — switching browsers or using incognito mode will not retain saved portfolios.