Financial Risk Manager Part 1

Explanation

Seasonality in time series analysis refers to regular, predictable patterns that repeat at fixed intervals within a single year. The correct definition is that seasonality reflects variability during a single year, not multi-year patterns.

Let's analyze each option:

A. Reflects variability due to natural disasters - ❌ Incorrect. This describes irregular or random events, not seasonal patterns.

B. Reflects variability during a single year - ✅ Correct. Seasonality captures patterns that repeat annually (e.g., higher retail sales in December, tourism peaks in summer).

C. Reflects a regular, multi-year pattern of being below or above the trend line - ❌ Incorrect. This describes cyclical patterns (business cycles) that occur over multiple years, not seasonal patterns.

D. Reflects gradual variability over a full season, usually taken to be 5 years long - ❌ Incorrect. This is not a standard definition of seasonality; seasons typically refer to periods within a year.

Key Concepts:

• Seasonality: Short-term, regular patterns within a year (e.g., quarterly, monthly)
• Cyclicality: Longer-term patterns over multiple years (e.g., business cycles)
• Trend: Long-term direction over time
• Irregular/Random: Unpredictable variations

The text incorrectly identifies option C as the answer. The correct answer should be B because seasonality specifically refers to patterns that repeat within a single year.