Monte Carlo Freight Volatility Simulator
Probability-based freight rate forecasting
Freight Rate Volatility Simulator
Harness the power of Monte Carlo simulation to model freight rate uncertainty. Generate thousands of scenarios to understand probability distributions, quantify risk exposure, and make data-driven decisions for your shipping strategy.
Simulations Run
1,000
Expected Rate
$2,088.24
Volatility
35%
Time Horizon
12 mo
Expected Price
$2,088.24
Median Price
$1,958.31
Price Range (90% confidence)
Low
High
5th Pctl
$1,106.67
25th Pctl
$1,547.88
Median
$1,958.31
75th Pctl
$2,482.76
95th Pctl
$3,488.05
Monte Carlo simulation is a computational technique that uses random sampling to model complex systems with uncertainty. By running thousands of simulations, we can understand the range of possible outcomes and their probabilities.
In freight markets, Monte Carlo methods help quantify risk by showing not just what might happen, but how likely different scenarios are. This enables better budgeting, hedging decisions, and risk management.
Geometric Brownian Motion (GBM) is the standard model for asset prices, ensuring rates stay positive and exhibit realistic volatility patterns.
- Mean/Median: Expected future price
- Percentiles: Range of likely outcomes
- Volatility: Rate variability measure
- Probability: Likelihood of scenarios
Asia-Europe
35%
Drift: +2%
ModerateAsia-USWC
40%
Drift: +3%
HighAsia-USEC
38%
Drift: +2.5%
HighTrans-Atlantic
25%
Drift: +1.5%
LowerIntra-Asia
30%
Drift: +1%
Moderate- •Run multiple simulations to verify stable results
- •Use 95th percentile for conservative budgeting
- •Compare results across different time horizons
- •Adjust volatility for current market conditions
- •Combine with fundamental market analysis
- ✗Model assumes constant volatility (not realistic)
- ✗Does not capture sudden market shocks
- ✗Ignores mean reversion typical in freight
- ✗Cannot predict structural market changes
- ✗Historical parameters may not persist