Reading Port Signals: From AIS Data to Trade Forecasts

Learning Objectives

By the end of this module, you will:

Why Port Signals Matter for Prediction Markets

Ports are the physical manifestation of global trade flows. When containers move from ships to trucks, the data tells a story about:

The Critical Advantage: Port authorities publish official monthly throughput data (TEUs handled), but AIS vessel tracking gives you 7-10 day advance notice. When you see 15% more containerships approaching Los Angeles in mid-month compared to the prior month's pace, you can forecast higher TEU volumes before official statistics confirm it.

Key Principle: AIS data is your crystal ball—it shows you cargo in motion before it becomes official statistics.

This early visibility creates asymmetric information advantages in prediction markets. While most traders wait for monthly port reports, you're positioning based on real-time vessel flows.

What Is AIS Data?

Automatic Identification System (AIS) is mandatory satellite-based vessel tracking for ships over 300 gross tons. Every commercial vessel broadcasts:

IMF PortWatch aggregates global AIS data and calculates derived metrics:

  1. Vessel counts: Ships in port, approaching, departed
  2. Queue lengths: Vessels anchored outside port waiting for berth
  3. Dwell times: Average hours from arrival to departure
  4. Port calls: Number of vessel visits over time periods

Free Access: IMF PortWatch provides real-time dashboards for major global ports at portwatch.imf.org. This is the same data professional traders use.

Three Core Metrics for Trading

1. Vessel Count Trends

What It Measures: Number of containerships in port or approaching within 50 nautical miles.

Why It Matters: More vessels = more containers = higher TEU throughput (with lag).

How to Interpret:

Example: Port of Los Angeles — December 2023

IMF PortWatch data on December 10, 2023:

Trade Setup:

Lead Time: Vessel count data on Dec 10 gave you 3+ weeks before official TEU data released in mid-January.

2. Queue Lengths (Vessels at Anchor)

What It Measures: Number of vessels waiting at anchorage outside port, unable to berth.

Why It Matters: Queues indicate:

How to Interpret:

Normal Operations: 2-5 vessels at anchor (typical rotation for most major ports)

Moderate Congestion: 10-20 vessels (1-3 day delays; manageable)

Severe Congestion: 30+ vessels (multi-week delays; supply chain crisis)

Example: Port of Savannah — October 2021

During post-COVID supply chain stress:

Trade Setup:

Pitfall Warning: Don't confuse queue LENGTH with queue CHANGE. A static queue of 20 vessels might be stable congestion. A queue growing from 5 to 20 in one week signals worsening bottleneck.

3. Dwell Time

What It Measures: Average hours a vessel spends in port from arrival to departure.

Why It Matters:

Typical Benchmarks:

How to Calculate: Dwell Time = (Total hours all vessels spent in port) / (Number of vessel departures)

IMF PortWatch auto-calculates this weekly.

Example: Port of Long Beach — June 2024

Signal Interpretation: Rising dwell times WITHOUT rising vessel counts = operational slowdown (labor shortage / equipment breakdown / customs delays).

Trade Setup:

Try this strategy on Ballast → Port of Long Beach Markets

The 7-10 Day Lead Time Window

Why This Timeline?

  1. Vessel transit time: Ships approach port 3-7 days before arrival
  2. Unloading + processing: Containers unload, clear customs, exit port in 2-5 days
  3. Data aggregation lag: Official monthly statistics publish 10-15 days after month-end

Total Lead Time: You see AIS signals 7-10 days before cargo reflects in official TEU counts.

Trading Calendar Example:

November 15: IMF PortWatch shows 20% more containerships approaching Port of Oakland vs Nov 1-15 last year

November 20: You buy YES on "Oakland over 220k TEUs in November?" at $0.55

November 30: Month ends (you're already positioned)

December 12: Oakland publishes official November TEUs: 235,000 (above threshold)

December 12: Market resolves YES → Your shares pay $1 → 82% profit

Key Advantage: Most traders wait until late November to analyze partial data or guess based on economic news. You used real vessel counts on Nov 15 with 15+ days before outcome resolved.

Worked Exercise: Forecasting LA Port Throughput

Scenario: It's December 15, 2024. You're analyzing Port of Los Angeles for a prediction market on December TEU volume.

IMF PortWatch Data (as of Dec 15):

Historical Baseline (December 2023):

Official TEU Volume (December 2023): 920,000 TEUs

Market Setup:

Binary market: "Will LA Port exceed 950,000 TEUs in December 2024?"

Your Analysis Steps:

Step 1: Calculate Vessel Count Change

Current total vessels (in port + approaching): 45 + 22 = 67 Prior year (Dec 15 2023): 38 + 16 = 54 Change: (67 - 54) / 54 = +24.1% more vessels

Step 2: Assess Queue/Congestion

Current queue: 8 vessels (double the prior year's 4) Interpretation: Moderate congestion, but not severe. Queue is processing (dwell time only +7% vs last year).

Step 3: Adjust for Dwell Time

Dwell time increased 7% (30 vs 28 hours) → slight efficiency loss Effective capacity: ~7% fewer ships processed per day

Step 4: Net Throughput Forecast

Vessel count up 24%, but dwell time reduces effective processing by 7% Net increase: +24% - 7% = +17% throughput estimate

Prior year December TEUs: 920,000 Forecast: 920,000 × 1.17 = 1,076,400 TEUs

Step 5: Compare to Market Threshold

Forecast: 1,076,400 TEUs Threshold: 950,000 TEUs Margin: +126,400 TEUs (+13.3% above threshold)

Step 6: Trade Decision

Market implies 48% probability of exceeding 950k Your analysis: Strong 70%+ probability (significant vessel count increase; manageable congestion)

Action: Buy YES shares at $0.48

Expected Value Calculation:

If 70% probability of YES:

Position Sizing: Risk $1,000 → Buy 2,083 YES shares at $0.48

Try this analysis on Ballast → Port of Los Angeles Markets

Case Study 1: Panama Canal Drought (2023-2024)

Background: Panama Canal relies on freshwater from Gatun Lake. Severe drought in 2023 reduced water levels, forcing canal authority to limit daily transits.

AIS Signal Timeline:

August 2023: IMF PortWatch shows vessel queue at Panama Canal anchorage rising

September 2023: Canal authority announces transit restrictions

Trade Setup:

Binary market (created Sept 1): "Will Panama Canal monthly transits fall below 1,000 in September 2023?"

Key Lesson: AIS queue data gave 10+ days advance notice before official announcement. Market was mispricing risk because traders waited for formal statements.

Quotable Framework: "Queues don't lie. When vessels pile up at chokepoints, trade flows are already disrupted—official announcements just confirm what AIS data already revealed."

Try Panama Canal markets on Ballast → Panama Canal Risk Markets

Case Study 2: LA/Long Beach Pre-Tariff Surge (March 2025)

Background: U.S. announces new 25% tariffs on Chinese goods, effective April 1, 2025. Importers rush to front-load shipments before tariffs hit.

AIS Signal Timeline:

February 15, 2025: IMF PortWatch data for LA/Long Beach

Interpretation: Massive surge in inbound containerships. Tariff deadline driving front-loading.

February 20 Analysis:

Prior year (Feb 2024 total TEUs): LA 875k, Long Beach 790k = 1.665M combined

Current vessel count: +41% approaching, +13% in port → weighted average +25% more vessels

Trade Setup:

Scalar market: "LA/Long Beach Combined TEU Index (range 0 to 150 with baseline of 100)"

Market Buckets: | Bucket | Price | |--------|-------| | 100-110 | $0.15 | | 110-120 | $0.45 | | 120-130 | $0.28 | | 130-140 | $0.10 |

Action: Buy 120-130 bucket at $0.28

Outcome (April 10 official data):

Key Lesson: Policy-driven events (tariff deadlines) create predictable surges. AIS vessel counts 6+ weeks before month-end gave clear signal of front-loading volume.

Try pre-tariff surge strategies on Ballast → U.S.-China Tariff Markets

Combining Multiple Signals

Sophisticated traders don't rely on single metrics. Combine signals for higher conviction:

Bullish Throughput Signal (High Probability): ✓ Vessel count up 20%+ YoY ✓ Queue length stable or declining (congestion under control) ✓ Dwell time flat or improving (efficient operations)

Bearish Throughput Signal (Lower Expected Volume): ✓ Vessel count down 15%+ YoY ✓ Queue length rising (but fewer total vessels = less cargo) ✓ Dwell time increasing (slower processing of limited vessels)

Congestion Bottleneck Signal (Mixed): ✓ Vessel count up 25%+ (lots of cargo arriving) ✓ Queue length spiking 3x+ (can't process fast enough) ✓ Dwell time doubling (severe congestion)

Interpretation: Short-term throughput LOWER (cargo stuck at anchor) but medium-term throughput HIGHER (once queue clears and backlog processes).

Trade Strategy:

Common Pitfalls When Reading AIS Data

Pitfall 1: Ignoring Vessel Size

Problem: Counting vessels assumes uniform capacity. A small feeder ship (1000 TEU capacity) ≠ ultra-large container vessel (24000 TEU capacity).

Solution: Weight vessel counts by size class or focus on ports where vessel mix is consistent year-over-year.

Example: Port of Oakland receives mostly Panamax vessels (5000-8000 TEU). If vessel count is up 15%, TEU throughput likely up ~15%. But if Port of LA shifts from 50% Panamax to 70% mega-vessels (18000+ TEU), vessel count could be FLAT while TEUs rise 30%+.

Advanced Technique: IMF PortWatch shows vessel names. Cross-reference vessel IMO numbers with ship databases (Equasis or MarineTraffic) to get deadweight tonnage (DWT) or TEU capacity. Calculate capacity-weighted vessel count.

Pitfall 2: Seasonal Patterns

Problem: December always has more vessels than February (holiday retail imports). Comparing absolute vessel counts without seasonal context misleads.

Solution: Always use year-over-year comparisons for the same month/week.

Example:

Don't conclude December will have 29% higher throughput. December is ALWAYS higher than November. Compare:

Pitfall 3: Destination Port Accuracy

Problem: AIS "destination" field is self-reported by ship crews and often wrong or outdated.

Solution: Use geofence proximity (vessels within 50nm of port) rather than destination field. IMF PortWatch auto-filters by proximity.

Example: A vessel might report "Los Angeles" as destination but reroute to Oakland. If you rely on destination field, you'll miscount. Proximity-based counting (vessel within 50nm of Oakland) captures actual traffic.

Pitfall 4: One-Time Events

Problem: Naval exercises, severe weather, or port labor negotiations create temporary AIS anomalies.

Solution: Check news for one-time disruptions. If typhoon forces 20 vessels to anchor for 48 hours, queue spike is temporary, not structural congestion.

Example: Port of Hong Kong, September 2024

Don't trade: "Hong Kong congestion crisis" based on 2-day weather event.

Try signal filtering on Ballast → Hong Kong Port Markets

Advanced Technique: Port Pair Analysis

Concept: Compare AIS signals between related ports to identify trade flow shifts.

Example: U.S. West Coast vs East Coast

Scenario: Labor negotiations at LA/Long Beach create uncertainty. Importers reroute cargo to Savannah/Charleston.

AIS Signals (March 15 2024):

LA/Long Beach:

Savannah/Charleston:

Trade Setup:

Binary markets:

  1. "Will LA/Long Beach combined exceed 1.7M TEUs in March?" at $0.58 YES
  2. "Will Savannah/Charleston combined exceed 550k TEUs in March?" at $0.42 YES

Pair Trade:

Outcome:

Key Insight: Cargo doesn't disappear—it shifts. AIS shows WHERE it's shifting in real-time.

Building Your AIS Monitoring System

Free Tools:

  1. IMF PortWatch (portwatch.imf.org): Weekly updates for major ports, free dashboards
  2. MarineTraffic (marinetraffic.com): Real-time AIS maps, free tier for basic tracking
  3. VesselFinder (vesselfinder.com): Alternative AIS visualization

Paid Tools (if you scale up):

  1. Windward: Advanced AIS analytics, anomaly detection
  2. Kpler: Commodity flow tracking with AIS + trade data fusion
  3. Bloomberg Terminal: AIS data integrated with financial markets

Your Weekly Routine:

Monday Morning:

  1. Check IMF PortWatch for top 10 ports you trade
  2. Download vessel counts, queue lengths, dwell times (export CSV)
  3. Calculate week-over-week and year-over-year changes
  4. Flag ports with over 15% deviations

Tuesday: 5. Cross-reference flagged ports with prediction markets on Ballast 6. Analyze if market prices reflect AIS signals 7. Identify mispricings (market at $0.50 but AIS suggests 70% probability)

Wednesday-Thursday: 8. Build positions on highest-conviction trades 9. Monitor for new AIS data releases (IMF updates weekly; usually mid-week)

Friday: 10. Review week's trades, update tracking spreadsheet 11. Note which AIS signals were predictive vs noise

Try systematic AIS trading on Ballast → Port Markets Dashboard

Frequently Asked Questions

1. How often does IMF PortWatch update AIS data?

Weekly for aggregated metrics (vessel counts and dwell time). Real-time for individual vessel positions via their map interface. Most useful data for prediction markets is the weekly aggregate update (usually Wednesdays).

2. Can AIS data be manipulated or spoofed?

Rare but possible. Vessels can turn off AIS (illegal for commercial ships over 300 tons but happens in sanctions evasion). For major container ports with dozens of vessels, individual spoofing doesn't affect aggregate counts meaningfully. Focus on large ports with 30+ vessels where single anomalies average out.

3. What if vessel count increases but TEUs don't?

Possible if vessel size mix shifts smaller (more feeder ships / fewer mega-vessels). Or if vessels arrive but don't unload (labor strike / customs issues). Check dwell time—if vessels arrive and leave quickly WITHOUT unloading, you'll see low dwell time + low TEUs. This is rare; most port calls involve cargo exchange.

4. How do I account for empty container repositioning?

AIS tracks vessels, not container status (full vs empty). Ports report TEUs, which includes empties. Historical ratio: ~15-20% of TEUs are empty repositioning. This is fairly stable, so YoY vessel count changes still correlate with loaded TEU changes. If you want precision, research port-specific empty ratios (some ports publish this).

5. What's the best leading indicator: vessel count, queue, or dwell time?

Vessel count is most predictive for normal operations. Queue length signals congestion shifts (but can be noisy). Dwell time is lagging—it reflects what already happened in past 7 days. For 7-10 day forecasts, prioritize vessel count + approaching vessels.

6. Can I use AIS data for bulk cargo (not containers)?

Yes, but bulk carriers (grain / coal / ore) have different dynamics. They often queue longer (days to weeks waiting for berth) and have less time-sensitive schedules. Container vessels prioritize speed due to perishable/retail cargo. AIS works for bulk, but you need bulk-specific baselines.

7. How do I separate coastwise shipping from international?

IMF PortWatch doesn't auto-filter, but you can check vessel "Last Port" and "Next Port" fields. If vessel came from another U.S. port and goes to another U.S. port, it's coastwise (Jones Act trade). For international trade forecasting, filter to vessels with last port = foreign country.

8. What if a port doesn't publish TEU data?

Some smaller ports don't report TEUs publicly. You can't trade prediction markets without verifiable resolution source. Focus on major ports with transparent data: LA, Long Beach, NY/NJ, Savannah, Houston (U.S.); Rotterdam, Singapore, Shanghai, Hong Kong (global).

9. How accurate is AIS-based forecasting?

Historical backtesting shows vessel count changes (YoY) correlate 0.75-0.85 with TEU volume changes for major container ports. That's strong but not perfect. Combine AIS with other signals (freight rates / manufacturing PMI / retail sales data) for higher accuracy.

10. Can I trade on AIS data for chokepoints (Suez / Panama / Malacca)?

Absolutely. Chokepoint AIS data is even more reliable because ALL vessels must pass through defined coordinates. Unlike ports (where vessels might reroute), straits have no alternative. IMF PortWatch tracks Suez / Panama / Bosphorus / Malacca and others.

11. What if market prices move before I can trade after seeing AIS data?

Happens in efficient markets. If you spot a signal at 9 AM and market already adjusted by 10 AM, other traders saw it too. Your edge comes from INTERPRETING signals others miss (e.g. combining vessel count with dwell time for nuanced view) or trading less-watched ports where information diffusion is slower.

12. How do I backtest AIS trading strategies?

IMF PortWatch has historical data back to 2019. Export weekly vessel counts for a port and compare to official monthly TEU data (lagged 4-6 weeks). Calculate correlation and profit/loss from simulated trades. Track hit rate (how often signal direction matched outcome) and return per trade.

Common Pitfalls Summary

1. Overweighting Short-Term Noise: One week of high vessel counts isn't a trend. Look for 2-3 consecutive weeks of elevated levels.

2. Ignoring Seasonal Baselines: Always compare YoY for the same week/month. Never compare December to June.

3. Mistaking Queue Length for Throughput: High queues can mean EITHER "lots of cargo arriving" OR "severe congestion delays." Check dwell time to distinguish.

4. Relying Only on AIS: Combine with freight rate data, economic indicators, and policy news for highest conviction.

5. Trading Illiquid Markets: If a prediction market has less than $5k volume, your trade might move prices and you'll suffer slippage. Stick to liquid markets on major ports.

Ready to Apply What You've Learned?

Turn knowledge into action.

Start Trading on Ballast Markets →

Use prediction markets to apply the concepts from this learning module. Trade real contracts based on port volumes, shipping delays, chokepoint transits, and tariff impacts.

Next Steps

Practice Exercises:

  1. Port Comparison Drill: Go to IMF PortWatch, pull vessel counts for LA, Oakland, and Long Beach for the same week. Calculate YoY changes. Which port shows strongest growth signal?

  2. Queue Analysis: Track Suez Canal queue length daily for 2 weeks. Does it correlate with oil price changes (tankers waiting) or container freight rates (box ships waiting)?

  3. Dwell Time Divergence: Find a port where dwell time increased but vessel count also increased. What's your throughput forecast? (Hint: Throughput = vessel count × efficiency. If vessel count +20% but efficiency -15% then net is ~+2%.)

Continue Learning:

Try on Ballast Markets:

Advanced Resources:

Disclaimer

This content is for educational purposes only and does not constitute financial advice. Prediction markets involve risk. AIS data interpretation requires judgment and may not always accurately predict port throughput. Past correlations do not guarantee future accuracy. Start with small positions and only risk capital you can afford to lose.