Exchange Rate Fluctuations Witnessed in the Chinese Yuan Throughout the Day
2024-05-16
Summary of Yesterday
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
Overall Trend Analysis
Looking at a snapshot of the time series data, there appears to be a slight general increase over the specified time period. However, this increase is relatively marginal, demonstrating that exchange rates remained relatively stable within this timeframe. Factors such as existing political, economic, or socio-environmental instability, which could cause drastic changes in exchange rates, are mostly absent. Overall, the data reflects a predominantly stable and steady trend.
Seasonality and Recurring Patterns
When it comes to seasonality, we cannot pick out any clear-cut recurring patterns that repeat in a predictable way over a specific period. This could potentially be due to a few reasons such as the relatively short time frame of the data, which may not be sufficient to depict a full cycle of seasonality. Furthermore, exchange rates are influenced by many external dynamics, and these might cloud any seasonality subtly present.
Outliers and Unexpected Instances
- The rate at 2024-05-16 20:20:03 has noticeably jumped to 0.18879 from its recent trend of 0.18873.
- Between 2024-05-16 20:40:03 and 2024-05-16 21:30:02, the rate dropped to 0.18853 and later rose back to its recent regular rate of 0.18861. This dip could be considered an outlier as it falls outside the general stable trend. An event or decision likely occurred which caused this stutter in the otherwise predictable and steady exchange rate.
Generally speaking, in this dataset, such outliers and unexpected instances are few and far between. Most of the time, the exchange rate fluctuates around a relatively stable mean. This statistical presence of a mean suggests that the data will often return to the mean even if it experiences a temporary aberration. Consequently, it's crucial observing both the occurrence of these outliers and the market's subsequent reaction to understand whether such irregularities hold significant isolated events or simply reflect momentary volatility in an otherwise consistent dataset.
