2024-05-14 Chilean Peso 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
1. Understanding the Overall Trend
After going through the time-series data provided, it is apparent that the exchange rates (CLP) have remained constant throughout the entire period indicated in the dataset. This conclusion is drawn because the exchange rate shown in all the timestamps is steady at 0.00148, with no fluctuations or changes noted. This can be considered unusual for exchange rate data, which generally varies over time based on a range of economic factors.
2. Seasonality and Recurring Patterns
Given that the exchange rate remains identical throughout, there is no discernible seasonality or recurring patterns in the data. Typically, such patterns might be depicted as regular fluctuations in the data over specific intervals, which could be linked to various events or conditions that occur regularly over time. However, in this case, there is no variation in the data to analyze for such effects.
3. Outliers in the Dataset
Since the data provided shows a constant exchange rate, there are no identifiable outliers in the dataset. Typically, an outlier would be defined as a data point that varies significantly from the overall pattern or trend in the data. But in this case, with no variations to observe, identifying an outlier is not possible based on the given data.
Conclusion
The given dataset exhibits no variation in the exchange rates for CLP over the time period of the data. While typically exchange rates would be expected to fluctify over time, this dataset shows a constant value, which suggests either a very unusual market condition, or errors in data collection, reporting, or entry. The constant value across all timestamps means that no trend, seasonality, or outliers can be identified from this dataset. Ideally, further investigation would be conducted to confirm the integrity and accuracy of the data.