2024-05-14 Cordoba Oro News
2024-05-13
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
Understanding the Overall Trend of The Exchange Rates
The detailed data provided shows very minute fluctuation in the exchange rate of NIO over the indicated period. However, the rate largely remains stable, hovering around the mark of 0.03714 to 0.03720. There isn't a distinctive increasing or decreasing trend indicating a relatively stable period for NIO exchange rate on the specific date of May 13, 2024. It's important to note that the insights are limited to this single day and may not necessarily reflect longer-term trends.
Identifying Seasonality or Recurring Patterns
Given that the data spans over 24 hours of a single day, it's challenging to identify any strong seasonality or recurring patterns. Although, the slight peak in the exchange rate can be noticed around 21:55 to 22:00 interval (reaching 0.03720), but this is very minute and could be influenced by numerous factors. For noticeable seasonality patterns, a dataset covering a longer timeline would likely provide better insights.
Noting Significant Outliers
This dataset doesn't appear to have significant outliers. The fluctuations in the exchange rate are consistent, and the degree of these changes remains relatively small throughout the entire period. From the set, the maximum exchange rate logged is 0.03720, and the minimum is 0.03712, indicating a very narrow range of difference. Thus, there don’t appear to be any instances where the exchange rate differs significantly from the overall observable trend.
Conclusion
The detailed time-series data on NIO exchange rate for May 13, 2024, suggests stable exchange rate conditions. With no discernible wider upward or downward trends and the absence of apparent outliers, the market shows consistent and predictable behaviour on this specific date. However, more prolonged and varied data, possibly covering different days, weeks or months, could provide more extensive insights to better understand longer-term trends, seasonal patterns, and outliers.
