MOIL 125 (MOIL) Price Target & Share Price Forecast

Not a guess. A distribution.

1-Year Price Target (median)₹192-33.2%

As of , the MOIL 125 (MOIL) 1-year price target is ₹192-33.2% from the current price of ₹288. The 80% confidence range is ₹115₹322, with a 15.9% probability of finishing above today's price.

MOIL 2027
₹192
-33.2%
MOIL 2029
₹86
-70.0%
MOIL 2031
₹39
-86.6%

Probability-weighted price target and forecast for MOIL 125 (MOIL) 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.

Spot Price · Today
₹0
Based on 2.0 years of daily NSE data ·0.0% annualised volatility
5-yr median forecast
₹0
P(price ↑ in 5y)
0%
1-Year Forecast
2027
₹0
Median (P50)
33.2%
80% range₹115–₹322
P(price ↑)16%
P(price 2×)0%
3-Year Forecast
2029
₹0
Median (P50)
70.0%
80% range₹34–₹213
P(price ↑)4%
P(price 2×)0%
5-Year Forecast
2031
₹0
Median (P50)
86.6%
80% range₹12–₹119
P(price ↑)1%
P(price 2×)0%

MOIL price probability fan

Each band shows where 10,000 simulated paths land. The wider the fan, the more uncertainty.

Probability Fan
MOIL simulated paths · 60 months · 10,000 trials
P10–P90 (80%)P25–P75 (50%)Median (P50)

Probability of key outcomes

What are the odds MOIL hits common targets within the simulated horizon?

0%
P(↑ 1Y)
Above today's price in 1 year
0%
P(↑ 5Y)
Above today's price in 5 years
0%
P(2×)
Doubles within 5 years
0%
P(↓)
Falls below today in 5 years

How the MOIL price target & forecast are calculated

We ran 10,000 simulated price paths for MOIL 125 (MOIL) using Geometric Brownian Motion (GBM) — the same probability framework used in institutional risk-management systems. The simulation uses MOIL's actual 2.0-year historical volatility (40.5%) and mean log return (-32.2%/year), so it reflects real market behaviour, not assumptions.

Each of the 10,000 trials projects a unique MOIL 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 MOIL 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 MOIL could realistically land — so you can plan for the spread of outcomes, not bet on a wish.

MOIL price target & forecast — probability table

HorizonPessimistic (P10)Median (P50)Optimistic (P90)P(↑ from today)P(2× return)
1 year (2027)₹115₹192₹32215.9%0.3%
3 years (2029)₹34₹86₹2134.3%0.4%
5 years (2031)₹12₹39₹1191.2%0.1%

Generated 23/6/2026, 5:46:25 am. Refreshed every 6 hours from 2.0y of NSE history.

MOIL price target & forecast — FAQs

What is the MOIL 125 (MOIL) price target / share price forecast for 2031?

Based on a 10,000-trial Monte Carlo simulation using historical volatility, MOIL's 5-year median (P50) forecast is ₹39. The 80% confidence band is ₹12₹119. The probability of the price being above today's ₹288 in 5 years is 1.2%.

How is Monte Carlo different from analyst price targets?

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.

Can MOIL double in 5 years?

The probability of MOIL reaching 2× the current price (₹575) within 5 years is 0.1%, based on this simulation.

Is this prediction accurate?

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.

How often is this forecast updated?

Every 6 hours, based on the latest NSE close prices and 2.0 years of historical data.

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