2024-05-15 Costa Rican Colon News
2024-05-14
Summary of Yesterday
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
1. Understanding the Overall Trend of the Exchange Rates
Based on the provided time series data, the trend in the exchange rate appears to be largely stable. The value of the exchange rate fluctuates slightly, with most values falling within the range of 0.00266 to 0.00267.
This stable trend suggests a balanced supply and demand in the market, with no significant shifts pushing the value of the currency in either direction. Although the rate does vary occasionally, these fluctuations remain very close to the primary rate, indicating brief and minor disturbances rather than any long-term trend changes.
2. Identifying Seasonality or Recurring Patterns
Due to the nature of the data, any seasonality or recurring patterns are not noticeable upon the initial observation. Given that the exchange rates remain largely stable throughout this time period, any recurring patterns or cyclical fluctuations are likely to be minor or subtle.
However, if we could divide the day into segments such as "morning", "afternoon", and "night", we could potentially see certain patterns emerge from those segments. For instance, the exchange rate might slightly fluctuate consistently during opening or closing market hours.
3. Noting Outliers
Considering the stable nature of the exchange rates within this dataset, any value that veers significantly from the range of 0.00266 to 0.00267 could be considered as an outlier.
However, upon initial examination, the data provided does not seem to contain any significant outliers. The lack of outliers indicates few, if any, unexpected or extreme shifts in the exchange rate during the observed timeframe.
For a final analysis with more specifics and detail, a graphical representation of the data would be recommended. This would allow for better visualization of any possible trends or outliers within the data.