The second product in Round 3 is diving gear (DG). Priced at 100k with only 50 units available, DG exhibits extreme volatility with swings easily exceeding hundreds – catching just one wave could yield profits of tens to hundreds of thousands, potentially propelling traders to the top of the leaderboard and causing significant ranking chaos.
This product presents interesting trading opportunities. The product description mentions the influence of dolphin sightings (DS) observations on DG. My analysis suggests:
1. Price Drivers:
⦁ DG prices are affected by multiple factors (production levels, material costs, coral observations, etc.)
⦁ DS is just one of many influences
⦁ Correlation analysis across different timeframes and lags showed no significant DS-DG relationship
2. Exceptional Cases:
⦁ When DS experiences sudden jumps (defined as mid-price changes > threshold between timestamps)
⦁ These jumps temporarily dominate DG’s price movement
⦁ The jump size distribution shows:
⦁ 99% of changes within ±1
⦁ Rare but extreme outliers create trading opportunities
3. Pattern Observation:
⦁ Example at t≈180k: DS spike → gradual DG price increase
⦁ This pattern repeats across all three days’ data
⦁ DG offers few (1-2/day) but high-reward opportunities
⦁ The high unit price compensates for the infrequency of trades
4. Backtesting Limitation:
⦁ Provided backtest data again covers only 10% of timeline
⦁ Crucially excludes these jump events
⦁ Makes meaningful strategy testing impossible
For the manual trading portion:
⦁ Same game as previous round
⦁ Easier selection with known distribution
⦁ Expected profits will decrease as submissions cluster
⦁ Planning to use second-level logic (~9625)
