Not a guess. A distribution.
Probability-weighted price target and forecast for Punjab & Sind Bank (PSB) across 2027, 2029, and 2031. Built from a 10,000-trial Monte Carlo simulation on 2.0 years of NSE historical data — so you see the full range of where the price could realistically land, weighted by likelihood. No analyst opinions. Just statistics.
Each band shows where 10,000 simulated paths land. The wider the fan, the more uncertainty.
What are the odds PSB hits common targets within the simulated horizon?
We ran 10,000 simulated price paths for Punjab & Sind Bank (PSB) using Geometric Brownian Motion (GBM) — the same probability framework used in institutional risk-management systems. The simulation uses PSB's actual 2.0-year historical volatility (43.6%) and mean log return (-43.9%/year), so it reflects real market behaviour, not assumptions.
Each of the 10,000 trials projects a unique PSB share price path day-by-day for 5 years. The percentile bands (P10/P50/P90) show the full distribution of outcomes — your real price target range, not a single guess.
Why this PSB forecast differs from analyst price targets: Analyst targets are point estimates from subjective valuation models. Monte Carlo price-target forecasts are probability distributions from actual market data. They tell you the range and likelihood of where PSB could realistically land — so you can plan for the spread of outcomes, not bet on a wish.
| Horizon | Pessimistic (P10) | Median (P50) | Optimistic (P90) | P(↑ from today) | P(2× return) |
|---|---|---|---|---|---|
| 1 year | ₹8 | ₹15 | ₹25 | 10.3% | 0.3% |
| 3 years | ₹2 | ₹5 | ₹13 | 1.8% | 0.1% |
| 5 years | ₹0 | ₹2 | ₹6 | 0.4% | 0.1% |
Generated 9/5/2026, 3:24:07 am. Refreshed every 6 hours from 2.0y of NSE history.
Based on a 10,000-trial Monte Carlo simulation using historical volatility, PSB's 5-year median (P50) forecast is ₹2. The 80% confidence band is ₹0–₹6. The probability of the price being above today's ₹25 in 5 years is 0.4%.
Analyst targets are point estimates based on subjective valuation models. Monte Carlo simulations produce a probability distribution from actual historical volatility — showing the full range of where the price could realistically land, weighted by likelihood. No opinions, just statistics.
The probability of PSB reaching 2× the current price (₹50) within 5 years is 0.1%, based on this simulation.
No simulation can predict the future — but Monte Carlo gives you a calibrated range of outcomes weighted by historical probability. It accounts for volatility better than any single price target. Use it as a decision-support tool, not a guarantee.
Every 6 hours, based on the latest NSE close prices and 2.0 years of historical data.