2024-05-07 Cayman Islands Dollar News
2024-05-06
Summary of Last Month
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
In order to provide a comprehensive analysis, I analyzed this time-series data in several aspects, namely the macro trends throughout the entire dataset, the periodical changes within smaller time frames, and potential outliers or abrupt fluctuations.
1. Overall Trend of Exchange Rates
First, I observed the general trend by looking at the highest and lowest records within the entire dataset. It appears that the exchange rate started at 1.646 and ended at 1.64194, with a slight overall decrease. However, the fluctuations within this period are evident, and the highest reached as much as 1.6424, while the lowest went down to 1.63784. This slight decrease at the two endpoints doesn't provide a clear picture of the overall trend, so it's crucial to examine more granular patterns.
2. Seasonality and Recurring Patterns
For seasonality, it is common to find patterns within hourly, daily, or monthly data. In this case, due to the limited time interval provided in the data, it's intricate to capture daily or monthly tendencies. However, evidence of hourly seasonality might possibly be recognized, with recurrent patterns of increase and decrease appearing every several hours. A more thorough statistical analysis or visualization like a time-series plotting could provide more accurate cues.
3. Outliers and Abrupt Fluctuations
Finally, it's worth noticing the exchange rate at specific moments. For instance, there was a drop in value to 1.64059 at around 6:25 on May 6, 2024. This might be primarily classified as an outlier in the dataset considering it's significantly deviated from the adjacent data. More precise methods, such as the IQR method or Z score, can be used to detect other outlier numbers in case they exist.
In conclusion, this dataset displays somewhat oscillating fluctuations without a clear upward or downward trend within the period. There seem to be recurring patterns hinting at possible hourly seasonality, and some potential outliers demonstrating momentary drastic changes. However, this analysis is largely descriptive and initial, thus further statistical methodologies and tools would renovate the way we understand this dataset in a much deeper and broader manner.