The Hallelujah Spot Silver Forecast: 12-Jan - 06 Feb 26

A BIG THANK YOU TO EODHD.COM FOR PROVIDING WITH ACCESS TO THEIR FINANCIAL MARKETS DATA: XAGUSD AND XAUSD !

Above is the probability heat map for Silver. It covers the price range USD70.00 to 90.00. As you can see, the forecast is optimistic. Even 09 and 10 Jan re-balancing of Bloomberg Commodity Index where Silver's current weighting of 9% has been rebalanced to its allocated 4% has not dampened the bullishness. As of US market close on Friday 09 Jan, spot Silver is 79.84. So probability of 90.00 being achieved in current forecast horizon is achievable.  

Below, the is day-by-day quantile forecast table to serve as a guide for your investing:

And here is how the probabiltues for HitAnyDay and CloseAboveOnDay20 are calculated.

SILVER FORECAST PROBABILITY CALCULATIONS

1. Monte Carlo Simulation Setup

We run 1,000 simulations of silver price over 20 business days.

Each simulation:

• Starts from the last observed price
• Uses ARIMA model for expected return
• Uses GARCH model for volatility
• Adds random shocks (Student-t distributed)
• Generates 20 daily prices

Result: 1,000 different possible price paths

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2. "Hit Any Day" Probability

Question: What is the probability silver reaches or exceeds a target price at ANY point during the 20 days?

Steps:

1. For each of 1,000 simulations, check all 20 days
2. If ANY day reaches the target → count as success
3. Divide successes by 1,000 and multiply by 100

Formula: (Number of simulations hitting target at least once / 1,000) × 100

Example: Target = $80

• 914 simulations reached $80 on at least one day
• Probability = 914 ÷ 1,000 = 91.4%

Python code: np.mean(np.any(price_paths >= 80, axis=1)) * 100

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3. "Close Above Day 20" Probability

Question: What is the probability silver closes above a target price specifically on Day 20?

Steps:

1. For each of 1,000 simulations, look ONLY at the Day 20 price
2. If Day 20 price ≥ target → count as success
3. Divide successes by 1,000 and multiply by 100

Formula: (Number of simulations closing above target on Day 20 / 1,000) × 100

Example: Target = $80

• 610 simulations closed above $80 on Day 20
• Probability = 610 ÷ 1,000 = 61.0%

Python code: np.mean(price_paths[:, -1] >= 80) * 100

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4. Key Difference

Hit Any Day:

• Checks all 20 days in each simulation
• Only needs to touch target once
• Higher probability (more opportunities)

Close Above Day 20:

• Checks only the final day (Day 20)
• Must end above target
• Lower probability (single checkpoint)

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5. Concrete Example

Simulation 1: $79 → $81 → $80 → ... → $78

• Hit $80 any day? YES (touched on Day 2)
• Close above $80 on Day 20? NO (ended at $78)

Simulation 2: $79 → $79 → $78 → ... → $82

• Hit $80 any day? YES (reached on Day 20)
• Close above $80 on Day 20? YES (ended at $82)

Simulation 3: $79 → $78 → $77 → ... → $76

• Hit $80 any day? NO (never reached)
• Close above $80 on Day 20? NO (ended at $76)

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6. Why It Matters

Hit Any Day tells you: "Will I get a chance to sell at this price?"

Close Above Day 20 tells you: "Will the price still be high at the end of the period?"

Example: Price can spike to $85 on Day 5 but fall to $75 by Day 20.

• Hit Any Day for $80 = YES
• Close Above Day 20 for $80 = NO

This is why Hit Any Day probabilities are always higher than Close Above Day 20 probabilities.